Patent Publication Number: US-2022228214-A1

Title: Assay for quantitating the extent of methylation of a target site

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. application Ser. No. 14/763,485, filed Jul. 24, 2015, which is a § 371 U.S. National Phase of International Patent Application No. PCT/AU2014/000044, International Filing Date Jan. 24, 2014, which claims priority to Australian Patent Application No. 2013900227, filed Jan. 25, 2013, the entire contents of which, are incorporated herein by reference in their entireties. 
    
    
     REFERENCE TO SEQUENCE LISTING 
     A Sequence Listing submitted as an ASCII text file via EFS-Web is hereby incorporated by reference in accordance with 35 U.S.C. § 1.52(e). The name of the ASCII text file for the Sequence Listing is 54985330_1.TXT, the date of creation of the ASCII text file is Jan. 26, 2022, and the size of the ASCII text file is 7.41 KB. 
     BACKGROUND 
     Field 
     The present specification relates to an assay to quantitate extent of methylation in a DNA sample. Kits and clinical diagnostic assays are also enabled herein including assays to determine clinical phenotypes based on extent of methylation of a DNA target site. 
     Description of Related Art 
     Bibliographic details of the publications referred to by author in this specification are collected alphabetically at the end of the description. 
     Reference to any prior art in this specification is not, and should not be taken as, an acknowledgment or any form of suggestion that this prior art forms part of the common general knowledge in any country. 
     The fragile X mental retardation genetic locus (“FMR genetic locus”) includes the FMR1 gene which is composed of 17 exons, spanning 38 Kb, and encodes fragile X mental retardation protein (FMRP), essential for normal neurodevelopment (Verkerk et al. (1991)  Cell  65(5):905-914; Terracciano et al. (2005)  Am J Med Genet C Semin Med Genet  137C(1):32-37). A CGG repeat segment is located within the 5′ untranslated region (UTR) of the gene. Its normal range is &lt;40 repeats. When expanded, these repeats have been implicated in a number of pathologies, including the fragile X syndrome (FXS), fragile X-associated tremor ataxia syndrome (FXTAS) and fragile X-associated primary ovarian insufficiency (FXPOI; formerly referred to as premature ovarian failure [POF]). FXS is neurodevelopmental in nature with a frequency of 1/2000 males and 1/4000 females, associated with a fragile site at the Xq27.3 locus (Jin and Warren (2000)  Hum. Mol. Genet  9(6):901-908). Furthermore, up to 60% of FXS males have a more severe form of autism termed autism disorder (AD). FXS is the single most common known genetic cause of intellectual impairment and co-morbid autism. 
     This syndrome is usually associated with a CGG expansion to “full mutation” (FM) which comprises &gt;200 repeats, leading to a gross deficit of FMRP and subsequent synaptic abnormalities (Pieretti etal. (1991)  Cell  66(4):817-822; Irwin etal. (2000)  Cereb Cortex  10(10):1038-1044). The FXS clinical phenotype ranges from learning disabilities to severe mental retardation and can be accompanied by a variety of physical and behavioral characteristics. FXTAS is prevalent in ˜30% of premutation individuals (PM), comprising from about 55 to 199 repeats (Nolin et al. (2003)  Am J. Hum Genet  72(2):454-464) and is a progressive neurodegenerative late-onset disorder with a frequency of 1:200 to 1:600 in the general population, manifesting as tremor, imbalance and distinct MRI and histological changes (Hagerman et al. (2001)  Neurology  57(1):127-130; Jacquemont et al. (2005)  J Med Genet  42(2):e14; Loesch et al. (2005) Clin Genet 67(5):412-417). It is often associated with ‘toxicity’ of elevated FMR1 mRNA, which has been linked to the intranuclear inclusions and cell death observed during neurodegeneration (Jin et al. (2003)  Neuron  39(5):739-747). 
     Studies in Australia and the USA indicate that approximately 1 in 100 children have autism spectrum disorder (ASD); ASD is associated with FXS up to 10% of these children. At present, there is no laboratory test available to diagnose ASD. The use of intervention programs at the earliest stages has been shown to result in better outcomes for these children and early diagnosis is a clear unmet need. 
     It is apparent that DNA methylation and other epigenetic modifications play a role in the regulation of gene expression in higher organisms. The importance of epigenetic modification has been highlighted by its involvement in several human diseases. Methylation, for example, of cytosine at the 5′ position is the only known methylation modification of mammalian genomic DNA. In particular, methylation of CpG islands within regulatory regions of the genome appears to be highly tissue specific. It is now apparent that methylation of cytosines distal to the islands is also important. These regions are called “shores” or “island shores” (Irizarry et al,  Nature Genetics  41(2):178-186, 2009). 
     Despite the availability of a range of methylation assays (see, for example, Rein et al. (1998)  Nucleic Acids Res.  26:2255), accurate quantitation of the extent of methylation is an important aspect of determining an epigenetic profile characteristic of a disease condition. 
     The current gold standard assay used for molecular diagnosis of FXS is methylation sensitive southern blot. Whilst this approach is time consuming and low throughput, it provides information on the CGG size up to FM and methylation status of several methylation sensitive restriction sites within the FMR1 CpG island. One major limitation associated with this and other alternative approaches currently used for the molecular diagnosis of FXS is that the test results cannot be used to provide accurate prognostic information in both male and female carriers of the expanded alleles on the type and severity of the disease. Alternative PCR based diagnostic assays targeting only the CGG expansion size have not been prognostically informative. 
     Another form of an assay is a methylation sensitive PCR (MS-PCR) which has been used for the diagnosis of FXS in males and Prader-Willi syndrome (PWS)/Angelman syndrome (AS) and is based on the difference in methylation status of a few CpG sites of the targeted region. A complicating factor is methylation mosaicism which is rare in PWS (Wey et al. (2005)  Eur J Hum Genet  13(3):273-277) but is much more common (approximately 27%) in AS (Buiting et al. (2003)  Am J Hum Genet  72(3):571-577) and in FXS (approximately 40%) [Nolin et al. (1994)  Am J Med Genet.  51(4):509-512]. The level of mosaicism representing the proportion of “diseased” cells, has also been related to the disease severity in X-linked disorders involving imprinting genes. Since MS-PCR is not highly sensitive or quantitative, a certain proportion of the methylation mosaic individuals, AS, PWS, FXS and modified X-chromosome disorders are not detected or accurate level of mosaicism is not determined using current techniques for the molecular diagnosis of these disorders and thus disease severity cannot be accurately predicted. 
     High resolution melt curve analysis has been used for PWS and AS (Wang et al. (2009)  J. Mol. Diagn.  11(5):446-449; White et al. (2007)  Clin Chem  53(11):1960-1962) and FXS (Dahl et al. (2007)  Clin Chem.  53(4):790-793) . However, this method does not accurately quantitate the extent of methylation. 
     Coffee et al. (2009)  Am. J. Hum. Genet.  85:503-514 proposed a methylation assay of the FMR1 locus to assess the incidence of FXS. The assay employed methylation-sensitive PCR targeting the FMR1 CpG island. Whilst the assay provided some information, the usefulness of assay is limited to males. CpG island methylation data do not correlate with the type or severity of any of the FXS clinical features. 
     Elias et al. (2011)  Genet. Testing and Mol. Biomarkers  15(56):387-393 also proposed a gene methylation assay based on multiplex-specific real-time PCR. However, insofar as it was applied to the FMR1 gene, it was only suitable for molecular diagnosis in males and did not accurately quantitate the extent of methylation. 
     A poster presented by Hamilton et al. (2012) European Human Genetics Conference, June 23-26, Nurnberg, Germany evaluated a melt assay to determine the methylation status of the FMR1 promoter. The assay achieved qualitative results in line with other assays and, in FM females, the assay did not provide a quantitative threshold that could separate affected from non-affected subjects; and the qualitative results obtained using this method were not quantitatively correlated with any parameter of disease type and severity, which is a major limitation for use of these tests in female expansion carriers. 
     An accurate quantitative assay has been successfully used to determine methylation of a region of the FMR1 genetic locus in males and females (Godler et al. (2010)  Hum Mole Genet  19:1618-1632; Godler et al. (2011)  J Mol Diag  13:528-536; Godler et al. (2012)  Clin Chem  58:590-598; International Patent Application No. PCT/AU2010/00169 [WO 2010/094061]). However, this assay requires the use of MALDI-TOF MS which requires expensive equipment and a level of expertise outside the resources of many diagnostic laboratories. There is a pressing need to develop a low cost, high throughput, quantitative methylation test that does not require specialized equipment and training, and can be used by most diagnostic laboratories with existing technical platforms to provide at least comparable results to the MALDI-TOF MS reference method. 
     SUMMARY 
     A present disclosure teaches an assay to quantitate the extent of methylation at a target site within a DNA sample. The assay enables high throughput screening of DNA samples. The assay enables the detection of methylation changes which can be used to correlate with clinical phenotypes and, hence, has significant diagnostic and prognostic value. This is useful especially when screening children too young to undergo certain procedures such as, in the case of neurological disorders, neuropsychological testing. An algorithm can be used to interface output data from the assay with percentage of methylation and ultimately with clinical phenotype. 
     The present disclosure is, therefore, instructional for a method referred to herein as “methylation specific-quantitative melt analysis” (MS-QMA) for quantitating the extent of methylation of a target region comprising one or more CpG sites within a DNA sample. The method comprises subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides followed by amplifying and melting a portion of the DNA sample comprising the target region. The amplification uses selected forwarded and reverse primers to amplify and incorporate a label in real-time which is capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength. The melting reaction of the amplified DNA releases the label in real-time. The assay is conducted in the presence of a first control DNA sample set of known DNA concentration and a second control DNA sample set of known percentage methylated and non-methylated DNA. The first control DNA sample set is used to generate a standard curve of DNA concentration versus cycle threshold (Ct) to determine the dynamic linear range of the amplification and the stable amplified product melting range where the signal strength is independent of the DNA dilution which indicates that the product has reached the maximum PCR amplification. The second control DNA is used to generate a standard curve of signal strength versus percentage of methylation. DNA samples to be tested which fall within the dynamic linear range of amplification and the stable amplified product melting range are used to determine the percentage of methylation based on the standard curve generated by the second control DNA sample set. The melting temperature for the second control DNA sample set is selected at the signal providing a measurable difference between the non-methylated and methylated control samples. In an embodiment, this is the temperature giving a maximum difference between non-methylation and methylated DNA. 
     The percentage of methylation can, therefore, be determined for a given DNA sample. It will be understood that the terms “percentage of methylation” and “methylation ratio” or “MR” are used herein interchangeably. The percentage methylation is calculated by multiplying the methylation ratio by 100, i.e. MR×100=% methylation. 
     In an embodiment, the DNA sample is serially diluted after bisulfite conversion and if multiple dilutions of the same DNA sample are selected, the mean of the determined percentage methylation is calculated. In an embodiment, the DNA sample is serially diluted four times after bisulfite treatment. Conveniently, the amplification reaction is a real-time polymerase chain reaction (RT-PCT) and the label incorporated into the amplified DNA is an intercalating fluorescent dye which binds double stranded DNA and fluorescences at a signal strength measured in aligned fluorescence units (AFU) and which does not provide a fluorescence signal in single stranded DNA. 
     Generally, the melt reaction is high resolution melt (HRM) conducted at a defined temperature which, in an embodiment, is the temperature providing the greatest difference between the non-methylated and methylated controls. This can be regarded as the lowest temperature where all double stranded DNA from non-methylated DNA in the second control DNA set is melted. 
     Conveniently, the DNA sample to be tested is one of a multiplicity of DNA samples and the multiplicity of DNA samples and the first and second control samples are located in a multi-compartmental container, such as a microtiter tray. The DNA sample may be derived from any source and includes cells contained in body fluid or a dried body fluid sample from a human subject. In an embodiment, the DNA sample is derived from cells in venous blood or a dried blood spot. In another embodiment, the DNA sample is derived from cells from sputum or other respiratory fluid, blood, saliva tissue fluid, a tissue sample, lymph fluid, semen, urine, fecal material or skin material. Reference to “blood” includes whole blood or a fraction thereof, a dried blood spot, and venous or arterial blood. 
     Taught herein is the correlation between extent of methylation of an artificially treated target site and a clinical phenotype including presence or absence of an adverse clinical condition, the stage of progression of the clinical condition, the severity of the clinical condition and the amelioration of the clinical condition after or during treatment. By “artificially treated” includes bisulfite treatment to convert non-methylated cytosines to uracils. The clinical phenotype further extends to rejection of transplanted tissue in a subject and monitoring for fetal cells in a maternal subject. 
     The DNA target site may be located in a genetic locus associated with neurological development, cognitive impairment, tumor suppression, tumor growth, sex determination, aneuploidy, immune response progression, trinucleotide disorders, imprinting disorders, X-linked disorders, modified X-chromosome disorders and X-chromosome inactivation skewing related disorders. In an embodiment, the assay is capable of quantitating skewed X-chromosome inactivation. The DNA target site may also be selected to monitor transplant tissues and organs and in prenatal diagnosis. The DNA target site may also be used to monitor treatment. 
     Included herein is a DNA target site selected from a site defined by an intron, exon, intron-exon boundary, promoter region or a region 5′ of the promoter region, a CpG island or group of CpG islands and a site downstream of the 3′ end region of a genetic locus, differentially methylated loci and CpG island shores. In an embodiment, the DNA target site is within the FMR1 genetic locus. 
     In an embodiment, the target DNA is fragile X-related epigenetic element 2 (FREE2). Reference to “FREE2” includes FREE2 (A) [SEQ ID NO:1], FREE2 (B) [SEQ ID NO:2], FREE2 (C) [SEQ ID NO:3], FREE2 (D) [SEQ ID NO:4] and FREE2 (E) [SEQ ID NO:5]. In another embodiment the target DNA is fragile X-related epigenetic element 3 (FREE3) [SEQ ID NO:6]. In any embodiment, the defined temperature for providing the greatest difference between methylated and non-methylated DNA is 78° C.±10° C. 
     In relation to the targeting FREE2 (A), forward and reverse primers are those defined by SEQ ID NOs:7 and 8, respectively. FREE2 (B) can be targeted by forward and reverse primers defined by SEQ ID NOs:9 and 10, respectively. FREE2 (C) can be targeted by forward and reverse primers defined by SEQ ID NOs:11 and 12, respectively. FREE3 can be targeted by forward and reverse primers defined by SEQ ID NOs:13 and 14, respectively. 
     In another embodiment, the DNA target site is the SNRPN gene promoter. Reference to “SNRPN” includes SNRPN-M [SEQ ID NO:19] and SNRPN-P [SEQ ID NO:20]. In one embodiment, the defined temperature for providing the greatest difference between methylated and non-methylated DNA is 80.08° C.±10° C. 
     In relation to the targeting SNRPN-M, forward and reverse primers are those defined by SEQ ID NOs:15 and 16, respectively. SNRPN-P can be targeted by forward and reverse primers defined by SEQ ID NOs:17 and 18, respectively. 
     The assay enabled herein includes using the DNA target site to distinguish one cell type from another cell type based on extent of methylation in a target site in the genome of one cell type which differs from another cell type. Furthermore, the assay can be used to identify an epigenetic-based disorder in a subject such as a developmental or neurological disorder, Prader-Willi syndrome/Angelman Syndrome, Alzheimer&#39;s disease, autism, bipolar disorder, diabetes, male sexual orientation, obesity, schizophrenia and a cancer selected from bladder, breast, cervical, colorectal, esophageal, hepatocellular, lung, mesothelioma, ovarian, prostate and testicular cancer and leukemia. 
     Conditions contemplated herein include pathoneurological conditions such as pathoneurodevelopmental and pathoneurodegenerative conditions as well as non-neurological conditions. Conditions and disorders contemplated herein include polyglutamine (polyQ) diseases such as Huntington&#39;s disease (HD), dentatorubropallid-oluysiantrophy (DRPLA), spinobulbar muscular atrophy or Kennedy disease (SBMA), spinocerebella ataxia Type 1 (SCA1), spinocerebella ataxia Type 2 (SCA2), spinocerebella ataxia Type 3 or Machado-Joseph disease (SCA3), spinocerebella ataxia Type 6 (SCA6), spinocerebella ataxia Type 7 (SCAT), spinocerebella ataxia Type 17 (SCA17) and non-polyQ diseases such as Fragile X syndrome (FXS), Fragile X-associated tremor or ataxia (FXTAS), Fragile XE mental retardation (FRAXE), myotonic dystrophy (DM), spinocerebella ataxia (SCAB) and spinocerebella ataxias Type 12 (SCA12). Other conditions contemplated herein include trinucleotide expansion related disorders including but not limited to Fragile X-associated primary ovary insufficiency (FXPOI), Friedrich&#39;s ataxia (FRDA). Fragile type, folic acid type, rare 12 (FRA12A), autism (including co-morbid autism), mental retardation (MR), Klinefelter&#39;s syndrome, RNA toxicity disease, Turner&#39;s syndrome, a modified X-chromosome and cognitive impairment are also contemplated herein. Further contemplated herein are learning and behavioral problems. Other conditions include skewed X-chromosome inactivation disorders. 
     The assay is also useful for diagnosing the epigenetic cause of cognitive impairment and autism-related disorders (including ASD and AD), especially in young children. 
     The assay is quantitative and, hence, the extent of methylation can be correlated to a disease condition or clinical phenotype, its stage or level of progression or severity and the effectiveness or otherwise of treatment. The instant disclosure further enables an algorithm to transform raw output data into a percentage of methylation or methylation ratio as well as the probability that a particular subject has or does not have a clinical condition. It will be understood that the terms “percentage of methylation” and “methylation ratio” or “MR” are used herein interchangeably. The percentage methylation is calculated by multiplying the methylation ratio by 100, i.e. MR×100=% methylation. 
     In an embodiment, contemplated herein is the use of an algorithm to resolve data from a real-time standard curve and a melt standard curve in the manufacture of a diagnostic assay to quantitate the extent of methylation at a target site within a DNA sample. In an embodiment, an algorithm is used to determine DNA concentration and quality post conversion of DNA from the DNA samples to be tested from the real-time amplification standard curve. In a further embodiment, the algorithm assists in correlating the extent of methylation with a clinical phenotype. 
     Kits for conducting the assay are also enabled by the instant disclosure. 
     Nucleotide sequences are referred to by a sequence identifier number (SEQ ID NO). The SEQ ID NOs correspond numerically to the sequence identifiers &lt;400&gt;1 (SEQ ID NO:1), &lt;400&gt;2 (SEQ ID NO:2), etc. A summary of the sequence identifiers is provided in Table 1. A sequence listing is provided after the claims. 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Summary of sequence identifiers 
               
            
           
           
               
               
               
            
               
                   
                 SEQUENCE ID 
                   
               
               
                   
                 NO: 
                 DESCRIPTION 
               
               
                   
                   
               
            
           
           
               
               
               
            
               
                   
                 1 
                 Nucleotide sequence of FREE2 (A) 
               
               
                   
                 2 
                 Nucleotide sequence of FREE2 (B) 
               
               
                   
                 3 
                 Nucleotide sequence of FREE2 (C) 
               
               
                   
                 4 
                 Nucleotide sequence of FREE2 (D) 
               
               
                   
                 5 
                 Nucleotide sequence of FREE2 (E) 
               
               
                   
                 6 
                 Nucleotide sequence of FREE3  
               
               
                   
                 7 
                 Nucleotide sequence of forward 
               
               
                   
                   
                 FREE2 (A) primer for MS-QMA 
               
               
                   
                 8 
                 Nucleotide sequence of reverse 
               
               
                   
                   
                 FREE2 (A) primer for MS-QMA 
               
               
                   
                 9 
                 Nucleotide sequence of forward 
               
               
                   
                   
                 FREE2 (B) primer for MS-QMA 
               
               
                   
                 10 
                 Nucleotide sequence of reverse 
               
               
                   
                   
                 FREE2 (B) primer for MS-QMA 
               
               
                   
                 11 
                 Nucleotide sequence of forward 
               
               
                   
                   
                 FREE2 (C) primer for MS-QMA 
               
               
                   
                 12 
                 Nucleotide sequence of reverse 
               
               
                   
                   
                 FREE2 (C) primer for MS-QMA 
               
               
                   
                 13 
                 Nucleotide sequence of forward 
               
               
                   
                   
                 FREE3 primer for MS-QMA 
               
               
                   
                 14 
                 Nucleotide sequence of reverse 
               
               
                   
                   
                 FREE3 primer for MS-QMA 
               
               
                   
                 15 
                 Nucleotide sequence of SNRPN-M 
               
               
                   
                   
                 forward primer for PWS/AS PCR 
               
               
                   
                 16 
                 Nucleotide sequence of SNRPN-M 
               
               
                   
                   
                 reverse for PWS/AS PCR 
               
               
                   
                 17 
                 Nucleotide sequence of SNRPN-P 
               
               
                   
                   
                 forward primer for PWS/AS PCR 
               
               
                   
                 18 
                 Nucleotide sequence of SNRPN-P 
               
               
                   
                   
                 reverse primer for PWS/AS PCR 
               
               
                   
                 19 
                 Nucleotide sequence of SNRPN-M 
               
               
                   
                   
                 target sequence to detect AS 
               
               
                   
                 20 
                 Nucleotide sequence of SNRPN-P 
               
               
                   
                   
                 target sequence to detect PWS 
               
               
                   
                   
               
            
           
         
       
     
     Abbreviations used herein are defined in Table 2. 
     
       
         
           
               
             
               
                 TABLE 2 
               
             
            
               
                   
               
               
                 Abbreviations 
               
            
           
           
               
               
               
            
               
                   
                 Abbreviation 
                 Definition 
               
               
                   
                   
               
               
                   
                 AD 
                 Autism disorder  
               
               
                   
                 AFU 
                 Aligned fluorescence unit  
               
               
                   
                 AS 
                 Angelman syndrome  
               
               
                   
                 ASD 
                 Autism spectrum disorder  
               
               
                   
                 FM 
                 Full mutation  
               
               
                   
                 FREE 
                 Fragile X epigenetic element 
               
               
                   
                   
                 (e.g. FREE2, FREE3) 
               
               
                   
                 FREE2 
                 FREE2 (A), FREE2 (B), FREE2 (C), 
               
               
                   
                   
                 FREE2 (D) and FREE2 (E) 
               
               
                   
                 FSIQ 
                 Full scale IQ  
               
               
                   
                 FXPOI 
                 Fragile X-associated primary 
               
               
                   
                   
                 ovary insufficiency 
               
               
                   
                 FXS 
                 Fragile X syndrome  
               
               
                   
                 FXTAS 
                 Fragile X-associated tremor 
               
               
                   
                   
                 ataxia syndrome 
               
               
                   
                 GZ 
                 Grey zone  
               
               
                   
                 HRM 
                 High resolution melt  
               
               
                   
                 MR 
                 Methylation ratio  
               
               
                   
                 MS-QMA 
                 Methylation specific-quantitative  
               
               
                   
                   
                 methylation assay 
               
               
                   
                 MS-QMA 
                 Methylation specific-quantitative  
               
               
                   
                 MR 
                 methylation assay methylation ratio 
               
               
                   
                 PCR 
                 Polymerase chain reaction  
               
               
                   
                 PIQ 
                 Performance IQ  
               
               
                   
                 PM 
                 Permutation  
               
               
                   
                 POI 
                 Performance organization index  
               
               
                   
                 PWS 
                 Prader-Willi syndrome  
               
               
                   
                 RT-PCT 
                 Real time-polymerase chain reaction  
               
               
                   
                 SCA 
                 X-chromosome aneuploidy  
               
               
                   
                 UFM 
                 Unmethylated FM  
               
               
                   
                 VIQ 
                 Verbal IQ 
               
               
                   
                   
               
            
           
         
       
     
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
       Some figures contain color representations or entities. Color photographs are available from the Patentee upon request or from an appropriate Patent Office. A fee may be imposed if obtained from a Patent Office. 
         FIG. 1  is a schematic representation of an overview of Methylation Specific Quantitative Melt Analysis (MS-QMA) of the Fragile X Related Epigenetic Element 2 (FREE2). (A) The protocol is based on a single bisulfite. (B) Converted DNA (1 conversion per sample) serially diluted 4 times. (C) Real-time PCR standard curve method. (D) High Resolution Melt (HRM) analysis using FREE2 specific primers. (E) RT-PCR Analysis determining DNA concentration from the dynamic linear range. This system utilizes a custom designed computer algorithm to simultaneously perform steps. (F) HRM analysis of RT-PCR standard curve DNA: determining of the unknown are within the DNA quality control range. DNA concentration and quality post conversion for all dilutions from the unknown samples from real-time PCR standard curve (pink diamonds). (G) The unknown sample dilutions (blue star in the pink box) within the concentration and quality control ranges (depicted by pink diamonds in the pink box), are automatically plotted against the HRM methylation standard curve (green box). The sample dilutions outside the quality control range (depicted by yellow diamonds in the pink box) are not utilized in HRM analysis, and are discarded. (H) The HRM methylation standard curve is also automatically obtained from 100% methylated and completely unmethylated control samples spiked at different ratios. The AFU for the methylation standard curve and unknowns is analyzed at the melting temperature where there is the greatest difference in fluorescence between 100% methylated and completely unmethylated controls which corresponds to the lowest temperature point where all double stranded DNA (DS DNA) from the unmethylated strands has completely melted. AFU for the unknowns is then converted to methylation ratio (MR) from the HRM standard curve (in the green box). The percentage of methylation can be obtained by multiplying the MR by 100. 
         FIG. 2( i )  is a graphical representation showing the relationship between Full Scale IQ (FIQ) and FREE2 methylation assessed using MS-QMA in blood of 19 FM females and 23 PM females; and MS-QMA methylation reference ranges in 63 FM, 82 PM, and 115 control (CGG&lt;40) females, where formal cognitive testing was not performed. Note: blue dot-line at 0.41 methylation ratio represents the cut off methylation threshold for low functioning FM females (IQ&lt;70) and the upper limit for the PM group. Values above 0.41 methylation ratio threshold (red broken line) identify 40% of all FM females. The green broken line at 0.37 methylation ratio represents the cut off methylation threshold above the maximum value of the control group. Values above 0.37 methylation ratio threshold identify 65% of all FM females. 
         FIG. 2 ( ii ) is a graphical representation of a comparison between groups of FREE2 MS-QMA methylation ratio (MR) in venous blood based on Wechsler IQ scores and CGG expansion size in 138 females. (A) The median MS-QMA MR was significantly increased in FM females with scores &lt;70 for full scale IQ (FSIQ) compared to FM females with scores &gt;70, PM females and controls. This was also the case for verbal IQ (VIQ) (B) and performance IQ (PIQ) (C). The broken line represents the optimal threshold value (cut-off point) for each IQ measure determined using area under the ROC curve (AUC) and Youden Index as summary measures of diagnostic accuracy described in Table 5. 
       Red broken line represents threshold determined to provide optimal separation for FM females based on verbal IQ (VIQ) of 70. The purple broken line represents the upper limit of the borderline range where for VIQ there is overlap between FM females with VIQ&gt; and &lt;70. Blue broken line represents threshold determined to provide optimal separation for FM females based on full scale IQ (FSIQ) and performance IQ (PIQ) of 70, and is equivalent to the maximum value of the female control sample. Note: FM FSIQ&lt;70 compared to controls ***-P&lt;0.001; **-P&lt;0.01; *-P&lt;0.05; FM IQ&lt;70 compared to PM IQ &gt;70 ♦♦♦- P&lt;0.001; ♦♦-P&lt;0.01; ♦-P&lt;0.05; and FM IQ&lt;70 compared to FM IQ&gt;70 ###-P&lt;0.001; ##-P&lt;0.01; #-P&lt;0.05. 
         FIG. 3( i )  is a graphical representation of FREE2 (A) methylation assessed using MALDI-TOF MS and MS-QMA in: (A) DNA from venous blood; and (B) newborn and adult dried blood spots (DBS) of FXS affected FM, PM, rare non-methylated FM (UFM) not affected with FXS (IQ&gt;70) and healthy control (HC - CGG&lt;40) males and females. (A) DNA from venous blood values identify 33% of all FM females with 70% of these with IQ&lt;70 and 86 of these with IQ&lt;80 (as indicated in  FIG. 2( i ) ). 36 AFU represents the cut off methylation threshold with maximum specificity and sensitivity for FM genotype, independent of the cognitive status. (B) DBS values at 42 AFU identify 68% of all FM females with no overlap with PM and healthy control groups in females. 39 AFU represents the cut off methylation threshold with maximum specificity and sensitivity for FM genotype, independent of the cognitive status. In DBS values identify 96% of all FM females with only 4% control and 28% PM false positives. Note that in both venous blood DNA and DBS values thresholds identify 100% of FM males with FXS, with no overlap with PM, healthy control and UFM males (IQ&gt;70) not affected with FXS. 
         FIG. 3 ( ii ) is a graphical representation of the distribution of MS-QMA methylation ratio (MR) in a larger cohort of controls and FMR1 expansion males and females. (A) MR in venous blood DNA from 20 male controls, 28 PM, 3 ‘high functioning’ UFM males (identified through cascade testing with FSIQ, VIQ and PIQ&gt;70 and determined to be unmethylated on Southern blot analysis), 52 FM males (identified through investigation of developmental delay/ASD), 4 FM methylation mosaics and 17 PM/FM size mosaics. (B) MR in venous blood DNA from 88 female controls, 105 PM and 95 FM females (identified through investigation of developmental delay/ASD). Note: Formal IQ testing was performed only on the UFM group. The red broken line is the threshold identified in  FIG. 2 ( ii ) which separates FM females with VIQ&gt; or &lt;70. The purple broken line represents the upper limit of the borderline range where for VIQ there is overlap between FM females with VIQ&gt; and &lt;70 in  FIG. 2 . The green broken line is the threshold that separates FM males from UFMs, PM and control males. Each brace connected to the broken line indicates the range of methylation values and the proportion of FM identified above this threshold. Compared to controls ***-P&lt;0.001; **-P&lt;0.01; *-P&lt;0.05; compared to PM IQ&gt;70 ♦♦♦- P&lt;0.001; ♦♦-P&lt;0.01; ♦-P&lt;0.05. 
         FIG. 4  is a graphical representation of MS-QMA and MALDI-TOF MS analysis of different FMR1 intron 1 FREE2 units in the same newborn blood spots (NBS): comparisons of control and FM groups. (A) MS-QMA CpG2-12 methylation ratio (MR) in spots from 87 male controls (CGG&lt;40) and 13 FM males; (B) MS-QMA CpG2-12 MR in spots from 95 female controls (CGG&lt;40) and 15 FM females. (C) MALDI-TOF MS CpG 10-12 methylation output ratio (MOR) and (D) MALDI-TOF MS CpG 6-12 MR in spots from 95 female controls (CGG&lt;40) and 15 FM females. Note: Only spots stored at room temperature for 10 years or less were included, since storage within this period was found to have no significant impact on the MS-QMA and MALDI-TOF MS outputs. Compared to controls ***-P&lt;0.001. The green broken line is the threshold from  FIG. 3  that separated FM males from UFMs, PM and control males. The red broken line is the threshold from  FIG. 2 ( ii ) which separated FM females of VIQ&gt; or &lt;70. The purple broken line is the threshold which separated FM female newborn blood spot cohort into two equal portions. The blue broken line is the CpG6-12 threshold above maximum value of blood spot female controls. Each brace connected to the broken line gives the range of values above the specific threshold and the proportion of FM identified above this threshold. 
         FIG. 5  is a graphical representation of MS-QMA melt profiles from venous blood DNA of FXS cryptic male #1 -IQ 30/ASD-41 and 450 CGG repeat alleles and cryptic male #2-IQ 30/ASD-25 and 1300 CGG repeat alleles, both 70% methylated by MALDI-TOF MS; one control male—0% methylated by MALDI-TOF MS and one FXS male—100% methylated by MALDI-TOF MS. 
         FIG. 6  is a graphical representation of FREE2 MS-QMA repeated methylation measures for 7 FXS males in blood spots taken at birth and in dried blood spots made at time of consent. MS-QMA methylation reference range in newborn blood spots of male controls (CGG&lt;40). Open boxes/triangles represent newborn blood spots kept at room temperature for less than 2 years. Grey boxes/triangles represent newborn blood spots kept at room temperature for 11 years. 
         FIG. 7  is a graphical representation showing a comparison of FMR1 MS-QMA Aligned Fluorescent Unit (AFU) with a serial dilution (2-4N) and with only a single dilution (1N) of the DNA samples with the relationship between Verbal IQ (VIQ). One AFU (red point) was obtained from 4 times diluted DNA samples (1N). Rectangular boxes: 21 control (CGG&lt;40) females without formal cognitive testing scores. Circles: 18 FM females with VIQ. 
         FIG. 8( i )  is a graphical representation of MS-QMA methylation ratio (MR) and SRY copy number in 100 saliva DNA samples from control males and females and individuals with clinical features of Klinefelter syndrome. The sample consisted of 13 46,XY control males (&lt;40 CGGs); 27 46,XX control females (&lt;40 CGGs); 36 47,XXY Klinefelter syndrome males (confirmed by microarray analysis); 12 47,XXY treated as Klinefelter syndrome males (confirmed by androgen receptor methylation analysis and androgen receptor CAG repeat length heterozygocity; no karyotype available); 5 mosaics for 46,XY/47,XXY (confirmed by microarray analysis); and 4 46,XX males with an SRY translocation (confirmed by microarray analysis); (A) The MR values determined using MS-QMA; (B) The SRY/Beta-globin copy number ratios were determined using real-time PCR relative standard curve method. 
         FIG. 8 ( ii ) is a graphical representation of MS-QMA methylation ratio (MR) and SRY copy number in blood DNA samples from control males and females and individuals with clinical features of Klinefelter syndrome. The sample consisted of 19 46,XY control males (&lt;40 CGGs); 48 46,XX control females (&lt;40 CGGs); 4 47,XXY Klinefelter syndrome males (confirmed by microarray analysis); 1 48,XXYY/47,XXY mosaic male (confirmed by microarray analysis); 2 48,XXXY males (confirmed by microarray analysis); and 4 49,XXXXY males (confirmed by microarray analysis). (A) The MR values determined using MS-QMA; (B) The SRY/Beta-globin copy number ratios determined using real-time PCR relative standard curve method. Note: Comparison to 46,XX controls **-P&lt;0.01, *** P&lt;0.001. 
         FIG. 8 ( iii ) in a graphical representation of MS-QMA methylation ratio (MR) and SRY copy number in blood DNA samples from control males and females and individuals with Turners Syndrome. The sample consisted of 19 46,XY control males (&lt;40 CGGs); 48 46,XX control females (&lt;40 CGGs); 10 45,X Turners syndrome females (confirmed by microarray analysis). 
         FIG. 8 ( iv ) is a graphical representation of MS -QMA methylation ratio (MR) and SRY copy number in blood DNA samples from control males and females and individuals with Triple X Syndrome. The sample consisted of 19 46,XY control males (&lt;40 CGGs); 48 46,XX control females (&lt;40 CGGs); 8 47,XXX females (confirmed by microarray analysis). Note: Comparison to 46,XX controls ** -P&lt;0.01, ***P&lt;0.001. 
         FIG. 8( v )  is a graphical representation of MS-QMA methylation ratio (MR) and SRY copy number in blood DNA samples from control males and females and individuals with Jacob&#39;s Syndrome. The sample consisted of 19 46,XY control males (&lt;40 CGGs); 48 46,XX control females (&lt;40 CGGs); 4 47,XYY males (confirmed by microarray analysis). Note: Comparison to 46,XY controls ###P&lt;0.001. 
         FIG. 9  is a graphical representation of FREE2 methylation comparisons between 50 FM males and 95 females with MS-QMA and MALDI-TOF MS CpG-10/12 methylation output ratio. MS-QMA targets seven CpG sites within FMR1 intron 1 including CpG10-12; while MALDI-TOF MS CpG10-12 MOR is specific only for methylation of CpG10-12. Note: all comparisons between FM males and FM females showed P&lt;0.001; *** comparisons for MS-QMA values; ### comparison for MALDI-TOF MS between FM groups. The bell shaped curve represents the expected normal distribution for the FM females methylation values if the X-inactivation at the locus were random, with mean methylation ratio of 0.75, the higher tail of distribution at 1 and the lower tail of distribution at 0.5. 
         FIG. 10  is a graphical representation of FREE2 methylation assessed using MALDI-TOF MS CpG10-12 and MS-QMA in FMR1 expansion carriers, sex chromosome aneuploidies and healthy control (CGG&lt;40) males and females. (A) 433 DNA from venous blood (B) 239 newborn and adult dried blood spots (DBS) and (C) 97 Saliva DNA. Note: Linear regression analysis results corresponding to these plots are presented in Table 8. Red broken line represents threshold determined to provide optimal separation for FM females based on VIQ of 70. Blue broken line represents threshold determined to provide optimal separation for FM females based on FSIQ and PIQ of 70, and is equivalent to the maximum value of the female control sample. Dried blood spots stored for &lt;10 years were not included. 
         FIG. 11  shows the use of the SNRRP promoter in MS-QMA High Resolution Melt (HRM) Profiles and the HRM standard curve of 12 separate DNA spiking experiments of DNA from Prader-Willi (PWS) and Angelman (AS) syndromes. (A) representative derivative melt curves and (B) Aligned Melt Curves of AS DNA 0% methylated, where both (A) and (B) were spiked at different ratios with 100% methylated PWS DNA; (C) methylation specific standard curve representing the relationship between the mean aligned fluorescence at 80.08° C. of 12 separate DNA spiking experiments determined using MS-QMA (X axis) and the expected methylation ratio in AS DNA spiked with methylated PWS DNA; the error bars represent two standard deviations between runs for each point. (D) AFU for the unknowns was converted to methylation ratio (MR) from the HRM standard curve (C); with the healthy control methylation range between 0.43 and 0.5 MR; PWS at ˜0.9 -1 MR; and AS between 0 and 0.15 MR. Based on these ranges the expected AS mosaic range was between 0.16 and 0.42 MR and the expected PWS mosaic range was between 0.51 and 0.98 MR. Note: The AFU for the methylation standard curve and unknown samples (HC, PWS and AS) was analyzed at the melting temperature of 80.08° C. 
         FIG. 12  is a graphical representation of the relationship between FREE2 CpG2-12 methylation ratio analysed using MS-QMA and age in female venous blood DNA. There was no significant relationship found using linear regression analysis between methylation ratio (y axis) and age (x axis) in (A) control, (B) PM and (C) FM females. We also used Davies test (Davies, 1987 Biometrika 74, 33-43) to test if there was a change in the slope in the relationship between MS-QMA-MR and age for three difference females groups. The break points were identified at 35.8 and 54.4 year of age respectively for controls and PM females, however they were both not significant (p-value=0.36 and 0.14 respectively). For FM females the break-point occurred at age 5.98 (95% CI=0.06-11.9), but the slopes before and after this breakpoint were not significant (p-value=0.23 and 0.62 respectively). 
         FIG. 13  Matrixes for sensitivity, specificity, positive and negative predictive values for MS-QMA MR in male and female dried blood spots collected at birth and female venous blood collected between 6 and 35 years of age. (A) NBS males and (B) NBS that had a FM allele were considered positive. In venous blood of FM females age between 6 and 35 years (C) and (D) VIQ&lt;70 was condition positive and VIQ&gt;70 was condition negative. For (C) test positive was MR&gt;0.39 and test negative wasMR&lt;0.39; while for (D) positive was MR&gt;0.41 and test negative was MR&lt;0.39. For (D) all MR within the 2% borderline range of 0.39 to 0.41, were not included in the analyses. Note: In venous blood of FM females sensitivity and specificity were calculated based on the Youden index optimal cutoff value of 0.39 for VIQ. 
     
    
    
     DETAILED DESCRIPTION 
     Throughout this specification, unless the context requires otherwise, the word “comprise” or variations such as “comprises” or “comprising”, will be understood to imply the inclusion of a stated element or integer or method step or group of elements or integers or method steps but not the exclusion of any element or integer or method step or group of elements or integers or method steps. 
     As used in the subject specification, the singular forms “a”, “an” and “the” include singular and plural aspects unless the context clearly dictates otherwise. Thus, for example, reference to “a methylation marker” includes a single methylation marker, as well as two or more different methylation markers; reference to “an algorithm” includes a single algorithm, as well as two or more algorithms; reference to “the invention” includes a single or multiple aspects taught by the disclosure. Aspects disclosed herein are encompassed by the term “invention”. All aspects of the invention are enabled within the width of the claims. 
     The present disclosure teaches a methylation specific-quantitative melt analysis (MS-QMA) protocol to quantitate the extent of methylation at a target site on DNA. The MS-QMA comprises bisulfite conversion of non-methylated cytosine residues to uracil nucleotides followed by generation of a real-time amplification standard curve method using forward and reverse primers to amplify the target site and then melt analysis 
     The amplification and melting steps involve the incorporation of a label in real-time which emits an identifiable signal when part of double stranded DNA and wherein the signal decreases during the melt process as single stranded DNA is generated. DNA samples to be tested are analyzed based on the temperature which provides a useful separation between methylated and non-methylated standards. In an embodiment, an algorithm is used to determine DNA concentration and quality post conversion of DNA from the DNA samples to be tested from the real-time amplification standard curve. The DNA concentrations and quality control ranges are then plotted against a melt standard curve. The signal strength of the label in the unknown samples is then converted to percentage methylation from the melt standard curve. 
     Accordingly, enabled herein is a method for quantitating the extent of methylation of a target site within a DNA sample, the method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) amplifying and melting a portion of the DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA; and then   (iii) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (iv) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (v) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and   (vi) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set.       

     Reference to Roman numerical paragraphs is not to imply that two or more steps may precede each other or be performed simultaneously. It will be understood that the terms “percentage of methylation” and “methylation ratio” or “MR” are used herein interchangeably. The percentage methylation is calculated by multiplying the methylation ratio by 100, i.e. MR×100=% methylation. 
     Accordingly, enabled herein is a method for quantitating the extent of methylation of a target site within a DNA sample, the method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) amplifying and melting a portion of the DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA; and then   (iii) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (iv) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (v) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and   (vi) determining the methylation ratio for the DNA from the level of signal strength using the standard curve resolved from the second control DNA sample set.       

     Generally, the amplification reaction is a real-time polymerase chain reaction (RT-PCR) and the melting reaction is a high resolution melt (HRM). Amplification data and thermal melt data may be monitored by any of a number of means but is conveniently monitored by an increase in fluorescence or emitted light during amplification or a decrease in fluorescence or emitted light during denaturation. The degree of, or change in, fluorescence is correlational or proportional to the degree of change in the physical conformation of the DNA. 
     Conveniently, the output data from the amplification and melt reactions are processed via an algorithm that determines DNA concentration and quality post-conversions from the real-time PCR amplification curve and which plots a sample to be tested within the concentration and quality control range against the HRM standard curve. 
     A method of measuring the degree of denaturation/unfolding of the target DNA is through monitoring of the fluorescence of dyes or molecules added to the reaction along with control and test DNA samples. A fluorescence dye or molecule refers to any fluorescent molecule or compound (i.e. a fluorophore) which can bind to a target DNA either once the target DNA is unfolded or denatured or before the target DNA undergoes conformational change by, e.g. denaturing and which emits fluorescent energy or light after it is excited by, e.g. light of a specified wavelength. 
     One dye type suitable for use herein is one that intercalates within strands of nucleic acids. The example of such a dye is ethidium bromide. An example of use of ethidium bromide for binding assays includes, e.g. monitoring for a decrease in fluorescence emission from ethidium bromide due to binding of test DNA. See, e.g. Lee et al. (1993)  J Med Chem  36(7):863-870. The use of nucleic acid intercalating gents in measurement of denaturation is well known to those in the art. See, e.g. Haughland (1996)  Handbook of Fluorescent Probes and Research Chemicals,  Molecular Probes, Inc. Eugene, Oreg. 
     Dyes that bind to nucleic acids by mechanisms other than intercalation can also be employed in the subject assay. For example, dyes that bind the minor groove of double stranded DNA can be used to monitor the molecular unfolding/denaturation of the target molecule due to temperature. Examples of suitable minor groove binding dyes are the SYBR Green family of dyes sold by Molecular Probes Inc. (Eugene, Oreg., USA). See, e.g. Haughland (1996) supra. SYBR Green dyes will bind to any double stranded DNA molecule. When a SYBR Green dye binds to double stranded DNA, the intensity of the fluorescent emissions increases. As more double stranded DNA are denatured due to increasing temperature, the SYBR Green dye signal will decrease. Another suitable dye is LCGreen Plus sold by Idaho Technology, Inc. (Salt Lake City, Utah, USA). 
     In an embodiment, the stable amplified product melting range is selected such that the product has reached the maximum PCR amplification. Furthermore, in an embodiment the melting temperature is selected to provide the greatest difference between non-methylated and control samples. 
     Hence, taught herein is a method for quantitating the extent of methylation of a target site within a DNA sample, the method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) amplifying and melting a portion of the DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA; and then   (iii) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (iv) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (v) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a maximum difference between the non-methylated and methylated control samples; and   (vi) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set.       

     In an embodiment, the DNA sample to be tested is serially diluted after bisulfite conversion. If multiple dilutions are analyzed, then the mean of the determined percentage methylation is calculated. In one embodiment, the DNA sample is serially diluted four times after bisulfite treatment. It will be understood that the terms “percentage of methylation” and “methylation ratio” or “MR” are used herein interchangeably. The percentage methylation is calculated by multiplying the methylation ratio by 100, i.e. MR×100=% methylation. 
     Taught herein is a method for quantitating the extent of methylation of a target site within a DNA sample, the method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) serially diluting the DNA sample after bisulfite conversion;   (iii) amplifying and melting a portion of the DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA; and then   (iv) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (v) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (vi) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference such as the maximum difference between the non-methylated and methylated control samples; and then   (vii) determining the percentage of methylation for the DNA sample by reducing the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set, wherein if multiple dilutions of the same DNA sample set are selected, the mean of the determined percentage methylation is calculated;   wherein an algorithm is used to determine whether a sample set of DNA falls within the dynamic linear range and the stable amplified product melt range and to correlate signal strength with percentage of methylation.       

     In an embodiment, an algorithm is used to interface with the method. Hence enabled herein is a method for quantitating the extent of methylation of a target site within a DNA sample, the method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) optionally serially diluting the DNA sample after bisulfite conversion;   (iii) amplifying and melting a portion of the DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA; and then   (iv) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (v) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (vi) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and then   (vii) determining the percentage of methylation for the DNA sample by determining the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set, wherein if multiple dilutions of the same DNA sample set are selected, the mean of the determined percentage methylation is calculated;   wherein an algorithm is used to determine whether a sample set of DNA falls within the dynamic linear range and the stable amplified product melt range and to correlate signal strength with percentage of methylation.       

     In an embodiment, the extent of methylation of a target DNA site on a genome is correlated to a clinical phenotype. 
     Hence, a method for quantitating the extent of methylation of a target site within a DNA sample, the level of which is associated with a clinical phenotype, the method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) serially diluting the DNA sample after bisulfite conversion;   (iii) subjecting the bisulfite treated DNA sample comprising the target site to real-time PCR and high resolution in melt with selected forwarded and reverse primers incorporating a fluorescence label in real-time and releasing the fluorescence label from double stranded DNA as determined by the AFU as part of the melting, the PCR and melt occurring in the presence of a first control DNA of known concentration providing an identifiable fluorescence signal in double stranded DNA as determined by and a second control DNA of known percentage of methylated and non-methylation DNA;   (iv) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (v) deriving a standard curve of signal strength measured in AFU released as part of melt versus the known percentage of methylation from the second control DNA sample set, the melting temperature for the second control DNA set selected at the signal providing the greatest difference between the non-methylated and methylated control samples;   (vi) determining the signal strength in AFU in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (vii) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength in AFU using the standard curve resolved from the second control DNA sample set, wherein the percentage of methylation correlates with a particular clinical phenotype.       

     Examples of clinical phenotype include neurological disorders, imprinting disorders, modified X-chromosome disorders, cancers, transplant rejection and pregnancies. 
     Examples of neurological disorders includes fragile X syndrome (FXS), fragile X-associated tremor ataxia syndrome (FXTAS), autism, mental retardation, cognitive impairment, Klinefelter&#39;s syndrome, Turner&#39;s syndrome, Prada-Willi syndrome syndrome/Angelman syndrome and fragile X-associated primary ovarian insufficiency (FXPOI) and other disorders associated with aneuploidy and/or modified X-chromosome, including Triple X Syndrome and Jacob&#39;s Syndrome. In an embodiment, the condition is associated with skewed X-chromosome inactivation. 
     In an embodiment, the neurological condition is cognitive and behavioral impairment, a neurodevelopmental and/or neurodegenerative disorder, attention deficit disorder, mood disorder, schizophrenia, bipolar disorder, memory lapse, and/or poor memory retention. 
     Conditions contemplated herein include pathoneurological conditions such as pathoneurodevelopmental and pathoneurodegenerative conditions as well as non-neurological conditions. Conditions and disorders contemplated herein include polyglutamine (polyQ) diseases such as Huntington&#39;s disease (HD), dentatorubropallid-oluysiantrophy (DRPLA), spinobulbar muscular atrophy or Kennedy disease (SBMA), spinocerebella ataxia Type 1 (SCA1), spinocerebella ataxia Type 2 (SCA2), spinocerebella ataxia Type 3 or Machado-Joseph disease (SCA3), spinocerebella ataxia Type 6 (SCA6), spinocerebella ataxia Type 7 (SCAT), spinocerebella ataxia Type 17 (SCA17) and non-polyQ diseases such as Fragile X syndrome (FXS), Fragile X-associated tremor or ataxia (FXTAS), Fragile XE mental retardation (FRAXE), myotonic dystrophy (DM), spinocerebella ataxia (SCAB) and spinocerebella ataxias Type 12 (SCA12). Other conditions contemplated herein include trinucleotide expansion related disorders including but not limited to Fragile X-associated primary ovary insufficiency (FXPOI) and Friedrich&#39;s ataxia (FRDA). Fragile type, folic acid type, rare 12 (FRA12A), autism (including co-morbid autism), mental retardation (MR), Klinefelter&#39;s syndrome, RNA toxicity disease, Turner&#39;s syndrome, a modified X-chromosome disorder including skewed X-chromosome inactivation, and cognitive impairment and also contemplated. Further contemplated herein are learning and behavioral problems. 
     A methylation map of a target DNA site can thus be constructed in accordance with the MS-QMA assay in the genome of various cells. Any cell type may be assayed. These cells include cultured or uncultured chorionic villi sample (CVS) cells, lymphoblasts, blood cells including whole blood, blood fraction, venous blood, arterial blood and dried blood, buccal cells, an amniocyte and EBV transformed lymphoblast cell lines from male and female subjects with either no clinical phenotype or from a spectrum clinical phenotypes. 
     In an embodiment, the DNA target site is selected from fragile X-related epigenetic elements FREE1, FREE2 and FREES. Reference herein to “FREE2” includes FREE2 (A), FREE2 (B), FREE2 (C), FREE2 (D) and/or FREE2 (E). Reference can be made to International Patent Publication No. WO 2012/174610, the contents of which are incorporated herein by citation. It is proposed that these regions are responsible neurological phenotypes including autism, cognitive impairment, FXS and mental retardation phenotype including fragile X mental retardation-like conditions and FMR conditions. 
     In another embodiment, the DNA target site is selected from the SNRPN genetic locus including its promoter region. It is proposed that this region is responsible for neurological phenotypes including Prada-Willi syndrome (PWS)/Angelman syndrome (AS). 
     Hence, in an embodiment, the instant disclosure correlates a change in extent of methylation of a genetic locus or region with a clinical manifestation. The quantitated extent of methylation provides an indicator as to the presence or absence of a condition severity or stage of progression of the condition and/or its amelioration during treatment. 
     The present assay also demonstrates that the quantitative methylation pattern of the DNA target site is significantly associated with symptoms of a pathological condition compared to healthy controls with normal size alleles. Thus, assessment of the methylation pattern of the contemplated DNA target site is proposed to be a useful biomarker for the rapid and wide spread screening of infants, neonates and other age groups for neurodegenerative, neurodevelopmental or other disorders characterized by changes in methylation pattern. 
     A “normal” or “control” in the present assay may be a control genome from a healthy individual performed at the same time or the methylation pattern may be compared to a statistically validated standard. A healthy individual includes a subject with no symptoms of a pathological condition. A healthy individual also includes a subject with a (CGG) n  where  n  is &lt;40, with no clinically apparent neurological phenotype. 
     As used herein, the terms “subject”, “patient”, “individual”, “target” and the like refer to any organism or cell of the organism on which the MS-QMA assay of the present invention is performed whether for experimental, diagnostic, prophylactic, and/or therapeutic purposes. Typical subjects include both male and female humans but the present assay extends to experimental animals such as non-human primates, (e.g., mammals, mice, rats, rabbits, pigs and guinea pigs/hamsters). The “subject” may also be referred to as a population since the present assay is useful in population studies including epidemiological prevalence studies or assays of ethnic population. In an embodiment, the subject is a human. The test may be tailored to human females or human males or pre-natal humans or a DNA from a cell of a human zygote. 
     The terms “fragile X mental retardation-like condition” and “FMR condition” refer to a neurological disease, disorder and/or condition characterized by one or more of the following symptoms: (1) behavioral symptoms, including but not limited to hyperactivity, stereotypy, anxiety, seizure, impaired social behavior, and/or cognitive delay; (2) defective synaptic morphology, such as an abnormal number, length, and/or width of dendritic spines; and/or (3) defective synaptic function, such as enhanced long-term depression (LTD); and/or reduced long-term potentiation (LTP); and/or impaired cognitive ability. The pathological condition is a disease, disorder, and/or condition caused by and/or associated with one or more of the following: (1) a mutation in FMR1 or FMR4 or ASFMR1; (2) defective FMR1/FMR4/ASFMR1 expression; (3) increased and/or decreased levels of FMRP; (4) defective FMRP function; (5) increased and/or decreased expression of genes or genetic functions regulated by FMR1, FMRP, FMR4 transcript or ASFMR1 transcript; (6) the increased methylation of FMR locus at CpG or CpNpG sites in the region upstream of FMR1 promoter and/or the region downstream of the (CGG) n  portion of the FMR1 promoter but not including the (CGG) n  portion; (7) an increased and/or decreased function of the FMR locus via miRNAs and/or members of the miRNA pathway; (8) an increased and/or decreased ability of FMRP to interact with its known target RNAs, such as RNAs encoding Racl, microtubule-associated protein IB, activity-regulated cytoskeleton-associated protein, and/or alpha-calcium/calmodulin-dependent protein kinase II; and/or (9) symptoms of FXS, FXTAS, POF, mental retardation, autism and/or autism spectrum disorders. Those of ordinary skill in the art will appreciate that the teachings of the present disclosure are applicable to any neurodevelopmental or neurodegenerative disorders linked, associated or otherwise influenced by the function of the FMR genetic locus or genes therein such as FMR1, FMR4 and ASFMR1. Non-neurological disorders are also contemplated herein including FXPOI. 
     The term “genomic DNA” includes all DNA in a cell, group of cells, or in an organelle of a cell and includes exogenous DNA such a transgenes introduced into a cell. 
     The present disclosure further contemplates a method for identifying in a genome of a mammalian cell including a human cell, a pathological condition associated with methylation within the FMR locus, the method comprising extracting genomic DNA from the cell and subjecting the DNA to a method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) serially diluting the DNA sample after bisulfite conversion;   (iii) amplifying and melting a portion of the bisulfite treated DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA;   (iv) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (v) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (vi) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and   (vii) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set; the amplification reaction using primers selective of a region of the FMR genetic locus comprising CpG and/or CpNpG sites, the CpG and CpNpG sites located in a region selected from:
           (i) fragile X-related epigenetic element 2 (A) [FREE2 (A)] comprising the nucleotide sequence set forth in SEQ ID NO:1 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:1 or which hybridizes to SEQ ID NO:1 or its complementary form under medium stringency conditions;   (ii) fragile X-related epigenetic element 2 (B) [FREE2 (B)] comprising the nucleotide sequence set forth in SEQ ID NO:2 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:2 or which hybridizes to SEQ ID NO:2 or its complementary form under medium stringency conditions;   (iii) fragile X-related epigenetic element 2 (C) [FREE2 (C)] comprising the nucleotide sequence set forth in SEQ ID NO:3 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:3 or which hybridizes to SEQ ID NO:3 or its complementary form under medium stringency conditions;   (iv) fragile X-related epigenetic element 2 (D) [FREE2 (D)] comprising the nucleotide sequence set forth in SEQ ID NO:4 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:4 or which hybridizes to SEQ ID NO:4 or its complementary form under medium stringency conditions;   (v) fragile X-related epigenetic element 2 (E) [FREE2 (E)] comprising the nucleotide sequence set forth in SEQ ID NO:5 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:5 or which hybridizes to SEQ ID NO:5 or its complementary form under medium stringency conditions; and   (vi) fragile X-related epigenetic element 3 (FREE3) comprising the nucleotide sequence set forth in SEQ ID NO:6 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:6 or which hybridizes to SEQ ID NO:6 or its complementary form under medium stringency conditions.   
               

     Insofar as the melt reaction relates to FREE2 or FREE3 or other FMR locus regions, the temperature melting giving maximum difference between methylated and non-methylated DNA is 78° C.±10° C. This includes 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87 and 88° C. or a fraction in between. 
     The present disclosure further contemplates a method for identifying in a genome of a mammalian cell including a human cell, a pathological condition associated with methylation within the SNRPN locus, the method comprising extracting genomic DNA from the cell and subjecting the DNA to a method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) serially diluting the DNA sample after bisulfite conversion;   (iii) amplifying and melting a portion of the bisulfite treated DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA;   (iv) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (v) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (vi) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and   (vii) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set; the amplification reaction using primers selective of a region of the SNRPN genetic locus comprising CpG and/or CpNpG sites, the CpG and CpNpG sites located in a region selected from:
           (i) SNRPN genetic locus (SNRPN-M) comprising the nucleotide sequence set forth in SEQ ID NO:19 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:19 or which hybridizes to SEQ ID NO:19 or its complementary form under medium stringency conditions; and   (ii) SNRPN genetic locus (SNRPN-P) comprising the nucleotide sequence set forth in SEQ ID NO:20 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:20 or which hybridizes to SEQ ID NO:20 or its complementary form under medium stringency conditions.   
               

     Insofar as the melt reaction relates to SNRPN, the temperature melting giving maximum difference between methylated and non-methylated DNA is 80° C.±10° C. This includes 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89 and 90° C. or a fraction in between. In one embodiment the temperature melting giving maximum difference between methylated and non-methylated DNA is 80.08° C. 
     Any real-time amplification, methodology may be employed. Amplification methodologies contemplated herein include the polymerase chain reaction (PCR) such as disclosed in U.S. Pat. Nos. 4,683,202 and 4,683,195; the ligase chain reaction (LCR) such as disclosed in European Patent Application No. EP-A-320 308 and gap filling LCR (GLCR) or variations thereof such as disclosed in International Patent Publication No. WO 90/01069, European Patent Application EP-A-439 182, British Patent No. GB 2,225,112A and International Patent Publication No. WO 93/00447. Other amplification techniques include Qβ replicase such as described in the literature; Stand Displacement Amplification (SDA) such as described in European Patent Application Nos. EP-A-497 272 and EP-A-500 224; Self-Sustained Sequence Replication (3SR) such as described in Fahy et al. (1991)  PCR Methods Appl.  1(1):25-33) and Nucleic Acid Sequence-Based Amplification (NASBA) such as described in the literature. 
     A PCR amplification process is useful in the practice of the present assay. 
     A “nucleic acid” as used herein, is a covalently linked sequence of nucleotides in which the 3′ position of the phosphorylated pentose of one nucleotide is joined by a phosphodiester group to the 5′ position of the pentose of the next nucleotide and in which the nucleotide residues are linked in specific sequence; i.e. a linear order of nucleotides. A “polynucleotide” as used herein, is a nucleic acid containing a sequence that is greater than about 100 nucleotides in length. An “oligonucleotide” as used herein, is a short polynucleotide or a portion of a polynucleotide. An oligonucleotide typically contains a sequence of about two to about one hundred bases. The word “oligo” is sometimes used in place of the word “oligonucleotide”. The term “oligo” also includes a particularly useful primer length in the practice of the present invention of up to about 10 nucleotides. 
     As used herein, the term “primer” refers to an oligonucleotide or polynucleotide that is capable of hybridizing to another nucleic acid of interest under particular stringency conditions. A primer may occur naturally as in a purified restriction digest or be produced synthetically, by recombinant means or by PCR amplification. The terms “probe” and “primers” may be used interchangeably, although to the extent that an oligonucleotide is used in a PCR or other amplification reaction, the term is generally “primer”. The ability to hybridize is dependent in part on the degree of complementarity between the nucleotide sequence of the primer and complementary sequence on the target DNA. 
     The terms “complementary” or “complementarity” are used in reference to nucleic acids (i.e. a sequence of nucleotides) related by the well-known base-pairing rules that A pairs with T or U and C pairs with G. For example, the sequence 5′-A-G-T-3′ is complementary to the sequence 3′-T-C-A-5′ in DNA and 3′-U-C-A-5′ in RNA. Complementarity can be “partial” in which only some of the nucleotide bases are matched according to the base pairing rules. On the other hand, there may be “complete” or “total” complementarity between the nucleic acid strands when all of the bases are matched according to base-pairing rules. The degree of complementarity between nucleic acid strands has significant effects on the efficiency and strength of hybridization between nucleic acid strands as known well in the art. This is of particular importance in detection methods that depend upon binding between nucleic acids, such as those of the invention. The term “substantially complementary” is used to describe any primer that can hybridize to either or both strands of the target nucleic acid sequence under conditions of low stringency as described below or, preferably, in polymerase reaction buffer heated to 95° C. and then cooled to room temperature. As used herein, when the primer is referred to as partially or totally complementary to the target nucleic acid, that refers to the 3′-terminal region of the probe (i.e. within about 10 nucleotides of the 3′-terminal nucleotide position). 
     Reference herein to a stringency in relation to hybridization includes and encompasses from at least about 0 to at least about 15% v/v formamide and from at least about 1 M to at least about 2 M salt for hybridization, and at least about 1 M to at least about 2 M salt for washing conditions. Generally, low stringency is at from about 25-30° C. to about 42° C. The temperature may be altered and higher temperatures used to replace formamide and/or to give alternative stringency conditions. Alternative stringency conditions may be applied where necessary, such as medium stringency, which includes and encompasses from at least about 16% v/v to at least about 30% v/v formamide and from at least about 0.5 M to at least about 0.9 M salt for hybridization, and at least about 0.5 M to at least about 0.9 M salt for washing conditions, or high stringency, which includes and encompasses from at least about 31% v/v to at least about 50% v/v formamide and from at least about 0.01 M to at least about 0.15 M salt for hybridization, and at least about 0.01 M to at least about 0.15 M salt for washing conditions. In general, washing is carried out T m =69.3+0.41 (G+C) % (Marmur and Doty, (1962)  J. Mol. Biol.  5:109). However, the T., of a duplex DNA decreases by 1° C. with every increase of 1% in the number of mismatch base pairs (Bonner and Laskey (1974)  Eur. J. Biochem.  46:83). Formamide is optional in these hybridization conditions. Accordingly, particularly preferred levels of stringency are defined as follows: low stringency is 6× SSC buffer, 0.1% w/v SDS at 25-42° C.; a moderate stringency is 2× SSC buffer, 0.1% w/v SDS at a temperature in the range 20° C. to 65° C.; high stringency is 0.1× SSC buffer, 0.1% w/v SDS at a temperature of at least 65° C. Reference to at least “80% identity” includes 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 and 100%. 
     As indicated above, the cells may be a lymphoblast, a CVS cell, a blood cell, an amniocyte or an EBV transformed lymphoblast cell line. In addition, the methylation profile may be determined or one or both alleles of a genetic locus such as the FMR or the SNRPN genetic locus and in selected cells where mosaicism has occurred. In particular, the extent of methylation can determine homozygosity, heterozygosity and mosaicism in male and female subjects. Reference to “mosaicism” includes the situation wherein two alleles of the same locus have different methylation profiles. 
     The present disclosure also contemplates kits for determining the methylation or at one or more sites within the genome of a eukaryotic cell or group of cells. The kits may comprise many different forms but in one embodiment, the kits comprise reagents for the bisulfite methylation assay, an amplification reaction and a melt reaction. The kits may further comprise a DNA reference/standard, software algorithms to determine the level of DNA methylation after bisulfite treatment. 
     A further embodiment enabled herein is a kit for the use in the above methods comprising primers to amplify the FREE2 and/or FREE3, the kit used in the method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) serially diluting the DNA sample after bisulfite conversion;   (iii) amplifying and melting a portion of the bisulfite treated DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA;   (iv) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (v) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (vi) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and   (vii) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set.       

     By “FREE2” means any or all of FREE2 (A), FREE2 (B), FREE2 (C), FREE2 (D) and/or FREE2 (E). In an embodiment, the FREE2 (A) region is screened for extent of methylation. 
     In an embodiment, the present invention provides a use of primers which amplify a DNA sample selected from:
         (i) fragile X-related epigenetic element 2 (A) [FREE2 (A)] comprising the nucleotide sequence set forth in SEQ ID NO:1 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:1 or which hybridizes to SEQ ID NO:1 or its complementary form under medium stringency conditions;   (ii) fragile X-related epigenetic element 2 (B) [FREE2 (B)] comprising the nucleotide sequence set forth in SEQ ID NO:2 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:2 or which hybridizes to SEQ ID NO:2 or its complementary form under medium stringency conditions;   (iii) fragile X-related epigenetic element 2 (C) [FREE2 (C)] comprising the nucleotide sequence set forth in SEQ ID NO:3 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:3 or which hybridizes to SEQ ID NO:3 or its complementary form under medium stringency conditions;   (iv) fragile X-related epigenetic element 2 (D) [FREE2 (D)] comprising the nucleotide sequence set forth in SEQ ID NO:4 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:4 or which hybridizes to SEQ ID NO:4 or its complementary form under medium stringency conditions;   (v) fragile X-related epigenetic element 2 (E) [FREE2 (E)] comprising the nucleotide sequence set forth in SEQ ID NO:5 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:5 or which hybridizes to SEQ ID NO:5 or its complementary form under medium stringency conditions; and   (vi) fragile X-related epigenetic element 3 (FREE3) comprising the nucleotide sequence set forth in SEQ ID NO:6 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:6 or which hybridizes to SEQ ID NO:6 or its complementary form under medium stringency conditions,       

     in the manufacture of a diagnostic kit or device to detect methylation of the FMR locus-associated with a pathological condition wherein the extent of methylation is determined by the method comprising:
         subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) serially diluting the DNA sample after bisulfite conversion;   (iii) amplifying and melting a portion of the bisulfite treated DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA;   (iv) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (v) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (vi) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and   (vii) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set;   and then correlating the extent of methylation with the pathological condition.       

     In a related embodiment, taught herein is a set of primers which amplify a DNA sample selected from:
         (i) fragile X-related epigenetic element 2 (A) [FREE2 (A)] comprising the nucleotide sequence set forth in SEQ ID NO:1 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:1 or which hybridizes to SEQ ID NO:1 or its complementary form under medium stringency conditions;   (ii) fragile X-related epigenetic element 2 (B) [FREE2 (B)] comprising the nucleotide sequence set forth in SEQ ID NO:2 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:2 or which hybridizes to SEQ ID NO:2 or its complementary form under medium stringency conditions;   (iii) fragile X-related epigenetic element 2 (C) [FREE2 (C)] comprising the nucleotide sequence set forth in SEQ ID NO:3 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:3 or which hybridizes to SEQ ID NO:3 or its complementary form under medium stringency conditions;   (iv) fragile X-related epigenetic element 2 (D) [FREE2 (D)] comprising the nucleotide sequence set forth in SEQ ID NO:4 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:4 or which hybridizes to SEQ ID NO:4 or its complementary form under medium stringency conditions;   (v) fragile X-related epigenetic element 2 (E) [FREE2 (E)] comprising the nucleotide sequence set forth in SEQ ID NO:5 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:5 or which hybridizes to SEQ ID NO:5 or its complementary form under medium stringency conditions; and   (vi) fragile X-related epigenetic element 3 (FREE3) comprising the nucleotide sequence set forth in SEQ ID NO:6 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:6 or which hybridizes to SEQ ID NO:6 or its complementary form under medium stringency conditions.       

     In relation to the targeting FREE2 (A), forward and reverse primers are those defined by SEQ ID NOs:7 and 8, respectively. FREE2 (B) can be targeted by forward and reverse primers defined by SEQ ID NOs:9 and 10, respectively. FREE2 (C) can be targeted by forward and reverse primers defined by SQ ID NOs:11 and 12, respectively. FREES can be targeted by forward and reverse primers defined by SEQ ID NOs:13 and 14, respectively. 
     In relation to an embodiment of the present disclosure a kit is provided for the use in the above methods comprising primers identified by SEQ ID NOs:7 and 8 (FREE2 (A)), SEQ ID NOs:9 and 10 (FREE2 (B)), SEQ ID :NOs:11 and 12 (FREE2 (C)) and SEQ ID NOs:13 and 14 (FREE2 (E)). 
     A further embodiment enabled herein is a kit for the use in the above methods comprising primers to amplify SNRPN, the kit used in the method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) serially diluting the DNA sample after bisulfite conversion;   (iii) amplifying and melting a portion of the bisulfite treated DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA;   (iv) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (v) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (vi) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and   (vii) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set.       

     In an embodiment, the present invention provides a use of primers which amplify a DNA sample comprising the nucleotide sequence selected from:
         (i) SNRPN genetic locus (SNRPN-M) comprising the nucleotide sequence set forth in SEQ ID NO:19 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:19 or which hybridizes to SEQ ID NO:19 or its complementary form under medium stringency conditions; and   (ii) SNRPN genetic locus (SNRPN-P) comprising the nucleotide sequence set forth in SEQ ID NO:20 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:20 or which hybridizes to SEQ ID NO:20 or its complementary form under medium stringency conditions,   in the manufacture of a diagnostic kit or device to detect methylation of the SNRPN locus-associated with a pathological condition wherein the extent of methylation is determined by the method comprising:
           (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) serially diluting the DNA sample after bisulfite conversion;   (iii) amplifying and melting a portion of the bisulfite treated DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA;   (iv) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (v) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (vi) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and   (vii) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set;   and then correlating the extent of methylation with the pathological condition.   
               

     In a related embodiment, taught herein is a set of primers which amplify a DNA sample comprising the nucleotide sequence set forth comprising the nucleotide sequence selected from:
         (i) SNRPN genetic locus (SNRPN-M) comprising the nucleotide sequence set forth in SEQ ID NO:19 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:19 or which hybridizes to SEQ ID NO:19 or its complementary form under medium stringency conditions; and   (ii) SNRPN genetic locus (SNRPN-P) comprising the nucleotide sequence set forth in SEQ ID NO:20 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:20 or which hybridizes to SEQ ID NO:20 or its complementary form under medium stringency conditions.       

     In relation to the targeting SNRPN-M, forward and reverse primers are those defined by SEQ ID NOs:15 and 16, respectively. SNRPN-P can be targeted by forward and reverse primers defined by SEQ ID NOs:17 and 18, respectively. 
     In relation to an embodiment of the present disclosure a kit is provided for the use in the above methods comprising primers identified by SEQ ID NOs:15 and 16 (SNRPN-M) and SEQ ID NOs:17 and 18 (SNRPN-P). 
     The kit may also comprise instructions for use. 
     Conveniently, the kit comprises a multi-compartmental microtiter tray. Furthermore, buffers, nucleotides and/or enzymes may be combined into a single compartment or multiple compartment. 
     As stated above, instructions optionally present in such kits instruct the user on how to use the components of the kit to perform the various methods of the present assay. It is contemplated that these instructions include a description of the use of an algorithm to determine the extent of methylation of a target site. 
     The present disclosure further contemplates kits which contain a primer for a nucleic acid target of interest with the primer being complementary to a predetermined nucleic acid target. In another embodiment, the kit contains multiple primers or probes, each of which contains a different base at an interrogation position or which is designed to interrogate different target DNA sequences. In a contemplated embodiment, multiple probes are provided for a set of nucleic acid target sequences that give rise to analytical results which are distinguishable for the various probes. The multiple probes may be in microarray format for ease of use. Kits may further comprise vessels containing labels and vessels containing reagents for attaching the labels. Microtiter trays are useful and these may comprise from two to 100,000 wells or from about six to about 10,000 wells or from about six to about 1,000 wells. 
     Another important application is in the high throughput screening of agents to determine the degree of which demethylation or hypermethylation of whole genomes or specific genomic loci. This may be important, for example, in de-differentiating cells. 
     The present invention further enables a method for screening for an agent which modulates methylation of a target site with a DNA sample, the method comprising screening for a change relative to a control in the extent of methylation modification within the target site in the presences or absence of an agent to be tested, wherein an agent is selected if it induces a change in the extent of methylation, the method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) serially diluting the DNA sample after bisulfite conversion;   (iii) amplifying and melting a portion of the bisulfite treated DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA;   (iv) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (v) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (vi) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and   (vii) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set.       

     By “FREE2” means any or all of FREE2 (A), FREE2 (B), FREE2 (C), FREE2 (D) and/or FREE2 (E). In an embodiment, the FREE2 (A) region is assayed. 
     In an embodiment, the target site is within the FMR genetic locus in a mammalian cell including a human cell, and includes:
         (i) fragile X-related epigenetic element 2 (A) [FREE2 (A)] comprising the nucleotide sequence set forth in SEQ ID NO:1 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:1 or which hybridizes to SEQ ID NO:1 or its complementary form under medium stringency conditions;   (ii) fragile X-related epigenetic element 2 (B) [FREE2 (B)] comprising the nucleotide sequence set forth in SEQ ID NO:2 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:2 or which hybridizes to SEQ ID NO:2 or its complementary form under medium stringency conditions;   (iii) fragile X-related epigenetic element 2 (C) [FREE2 (C)] comprising the nucleotide sequence set forth in SEQ ID NO:3 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:3 or which hybridizes to SEQ ID NO:3 or its complementary form under medium stringency conditions;   (iv) fragile X-related epigenetic element 2 (D) [FREE2 (D)] comprising the nucleotide sequence set forth in SEQ ID NO:4 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:4 or which hybridizes to SEQ ID NO:4 or its complementary form under medium stringency conditions;   (v) fragile X-related epigenetic element 2 (E) [FREE2 (E)] comprising the nucleotide sequence set forth in SEQ ID NO:5 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:5 or which hybridizes to SEQ ID NO:5 or its complementary form under medium stringency conditions; and   (vi) fragile X-related epigenetic element 3 (FREE3) comprising the nucleotide sequence set forth in SEQ ID NO:6 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:6 or which hybridizes to SEQ ID NO:6 or its complementary form under medium stringency conditions.       

     In another embodiment, the target site is within the SNRPN genetic locus in a mammalian cell including a human cell, and includes:
         (i) SNRPN genetic locus (SNRPN-M) comprising the nucleotide sequence set forth in SEQ ID NO:19 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:19 or which hybridizes to SEQ ID NO:19 or its complementary form under medium stringency conditions; and   (ii) SNRPN genetic locus (SNRPN-P) comprising the nucleotide sequence set forth in SEQ ID NO:20 or a homolog thereof or portion or part thereof defined by having at least 80% nucleotide sequence identity to SEQ ID NO:20 or which hybridizes to SEQ ID NO:20 or its complementary form under medium stringency conditions.       

     In cases where the gene is methylated and silenced in affected individuals or tissues, compounds are screened in high throughput fashion in stable cell lines or individuals to identify drugs that result in demethylation and reactivation of the affected gene. Alternatively, a normal active copy of the affected gene is transfected as a transgene into cells to correct the defect. Such transgenes are introduced with modulating sequences that protect the transgene from methylation and keep it non-methylated and transcriptionally active. 
     In cases where the gene is non-methylated and transcriptionally active or transcriptionally over-active in affected individuals or tissues, compounds are screened in high throughput fashion in stable cell lines to identify drugs that result in methylation and silencing of the affected gene. Alternatively, a transgene encoding a double stranded RNA homologous to the affected sequences or homologs thereof, are transfected as a transgene into cells to methylate the gene, silence it and thereby correct the defect. Such double stranded RNA-encoding transgenes are introduced with modulating sequences which protect it from methylation, keep it transcriptionally active and producing double stranded RNA. 
     The present invention further enables a method for monitoring the treatment of a clinical condition associated with extent of methylation, the method comprising monitoring for a change relative to a control or a pre- and post-treatment sample in the extent of methylation within a DNA target site, the method comprising:
         (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) serially diluting the DNA sample after bisulfite conversion;   (iii) amplifying and melting a portion of the bisulfite treated DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA;   (iv) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (v) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (vi) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and   (vii) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set.       

     By monitoring includes diagnosis, prognosis, pharmacoresponsiveness, pharmacosensitivity, level of disease progression or remission, improving or declining health of a subject and the like. 
     Disease conditions associated with abnormal methylation include but are not limited to FXS, FXTAS, FXPOI, autism, cognitive and behavioral impairment, reduced ovarian function, memory lapse, poor memory retention, a neurodevelopmental and/or neurodegenerative disorder, attention deficit disorder, mood disorder, schizophrenia, bipolar disorder, mental retardation, Klinefelter&#39;s syndrome, Turner&#39;s syndrome, aneuploidy and a modified X-chromosome. Reference to a “modified” X-chromosome includes skewed X-inactivation, inversions, deletions, duplications, hybrids and any modification leading to X-chromosome inactivation. Imprinting conditions include Prada-Willi syndrome (PWS)/Angelman syndrome (AS). 
     Conditions contemplated herein include pathoneurological conditions such as pathoneurodevelopmental and pathoneurodegenerative conditions as well as non-neurological conditions. Conditions and disorders contemplated herein include polyglutamine (polyQ) diseases such as Huntington&#39;s disease (HD), dentatorubropallid-oluysiantrophy (DRPLA), spinobulbar muscular atrophy or Kennedy disease (SBMA), spinocerebella ataxia Type 1 (SCA1), spinocerebella ataxia Type 2 (SCA2), spinocerebella ataxia Type 3 or Machado-Joseph disease (SCA3), spinocerebella ataxia Type 6 (SCA6), spinocerebella ataxia Type 7 (SCAT), spinocerebella ataxia Type 17 (SCA17) and non-polyQ diseases such as Fragile X syndrome (FXS), Fragile X-associated tremor or ataxia (FXTAS), Fragile XE mental retardation (FRAXE), myotonic dystrophy (DM), spinocerebella ataxia (SCAB) and spinocerebella ataxias Type 12 (SCA12). Other conditions contemplated herein include trinucleotide expansion related disorders including but not limited to Fragile X-associated primary ovary insufficiency (FXPOI) and Friedrich&#39;s ataxia (FRDA). Fragile type, folic acid type, rare 12 (FRA12A), autism (including co-morbid autism), mental retardation (MR), Klinefelter&#39;s syndrome, RNA toxicity disease, Turner&#39;s syndrome, a modified X-chromosome disorder and cognitive impairment are also contemplated. Further contemplated herein are learning and behavioral problems. 
     The present disclosure further contemplates a computer program and hardware which monitors the changing state, if any, of extent of methylation over time or in response to therapeutic and/or behavioral modification or for high throughput routine screening of populations. Such a computer program has important utility in monitoring disease progression, response to intervention and may guide modification of therapy or treatment. The computer program is also useful in understanding the association between increasing methylation and disease progression. The computer program is useful in routine maternal, paternal, pre-natal and post-natal testing. 
     The computer program executes an algorithm which determines DNA concentration and quality post-conversion for all dilutions from unknown DNA samples from a real-time amplification curve. Hence, the computer program executes an algorithm which determines the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the table product melt range and reads the percentage of methylation from the level of signal strength using the standard curve resolved from the control DNA sample site of known percentage methylation and non-methylation. A program may include a learning algorithm where the relationship between the expected methylation levels, the variation and signal from the DNA standard, may be embedded in the software. 
     Thus, in another aspect, enabled herein is a computer program product for assessing extent of methylation of a target DNA site, the product comprising executes an algorithm which determines the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the table product melt range and reads the percentage of methylation from the level of signal strength using the standard curve resolved from the control DNA sample site of known percentage methylation and non-methylation. 
     The computer program further comprising: means to converting index value to a code; and means to store the code in a computer readable medium and compare code to a melt standard curve. 
     In a related aspect, the invention extends to a computer program for assessing an association between extent of methylation and a clinical phenotype, wherein the computer program comprises executes an algorithm which determines the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the table product melt range and reads the percentage of methylation from the level of signal strength using the standard curve resolved from the control DNA sample site of known percentage methylation and non-methylation and a machine-readable data storage medium comprising a data storage material encoded with machine-readable data, wherein the machine-readable data comprise index values associated with the features of change in methylation, together with one or more of:
         (a) general phenotype or clinical manifestations in subjects;   (b) behavioral assessment criteria; and/or   (c) cognitive ability; and   means to store the code in a computer readable medium and compare code to a knowledge database to determine whether the code corresponds to a pathological condition.       

     The present invention further provides a web-based system where data on extent of methylation within a target genomic site (optionally together with clinical phenotype) are provided by a client server to a central processor which analyzes and compares to a control and optionally considers other information such as patient age, sex, weight and other medical conditions and then provides a report, such as, for example, a risk factor for disease severity or progression or status or response to treatment. 
     Hence, knowledge-based computer software and hardware also form part of the present disclosure. 
     In an embodiment, the assay of the present disclosure is used in existing or newly developed knowledge-based architecture or platforms associated with pathology services. For example, results from the assays are transmitted via a communications network (e.g. the internet) to a processing system in which an algorithm is stored and used to generate a predicted posterior probability value which translates to the index of disease probability which is then forwarded to an end user in the form of a diagnostic or predictive report. 
     The assay may, therefore, be in the form of a kit or computer-based system which comprises the reagents necessary to detect the extent of methylation modification within a genetic locus and includes computer hardware and/or software to facilitate determination and transmission of reports to a clinician. 
     Enabled herein is an assay which permits integration into existing or newly developed pathology architecture or platform systems. For example, a method contemplated herein allows a user to determine the status of a subject with respect to a methylation-associated pathology, the method including:
         (a) receiving data in the form of extent of methylation at a selected genomic site; wherein the extent of methylation or other epigenetic modification provides a correlation to the presence, state, classification or progression of the pathology; the extent of methylation determined by the method comprising:
           (i) subjecting the DNA sample to bisulfite treatment to convert non-methylated cytosine nucleotides in the DNA to uracil nucleotides;   (ii) amplifying and melting a portion of the DNA sample comprising the target site with selected forwarded and reverse primers incorporating a label in real-time capable of providing an identifiable signal in double stranded DNA as determined by units of signal strength as part of the amplification and releasing the label in real-time from double stranded DNA as determined by units of signal strength as part of melting, the amplification and melting occurring together with a first control sample set of known DNA concentration and a second control DNA sample set of known percentage of methylated and non-methylation DNA;   (iii) deriving a standard curve of DNA concentration versus cycle threshold (Ct) from the first control DNA sample set to determine the dynamic linear range of the amplification; and determining the stable amplified product melting range on the same set of control DNA samples where the signal strength is independent of the DNA dilution which indicates that the product has reached a defined state of PCR amplification;   (iv) determining the signal strength in the DNA sample to be tested which falls within the dynamic linear range of amplification and the stable amplified product melt range;   (v) deriving a standard curve of signal strength released as part of melt versus the known percentage of methylation from the second control DNA set sample, the melting temperature for the second control DNA set selected at the signal providing a selected difference between the non-methylated and methylated control samples; and   (vi) determining the percentage of methylation for the DNA sample by reading the percentage of methylation from the level of signal strength using the standard curve resolved from the second control DNA sample set; and then transferring the data from the user via a communications network;   
           (b) processing the subject data via multivariate or univariate analysis to provide a disease index value;   (c) determining the status of the subject in accordance with the results of the disease index value in comparison with predetermined values; and   (d) transferring an indication of the status of the subject to the user via the communications network. Reference to the multivariate or univariate analysis includes an algorithm which performs the multivariate or univariate analysis function.       

     Conveniently, the method generally further includes:
         (a) having the user determine the data using a remote end station; and   (b) transferring the data from the end station to the base station via the communications network.       

     The base station can include first and second processing systems, in which case the method can include:
         (a) transferring the data to the first processing system;   (b) transferring the data to the second processing system; and   (c) causing the first processing system to perform the multivariate analysis function to generate the disease index value.       

     The method may also include:
         (a) transferring the results of the multivariate or univariate analysis function to the first processing system; and   (b) causing the first processing system to determine the status of the subject.       

     In this case, the method also includes at least one of:
         (a) transferring the data between the communications network and the first processing system through a first firewall; and   (b) transferring the data between the first and the second processing systems through a second firewall.       

     The second processing system may be coupled to a database adapted to store predetermined data and/or the multivariate analysis and/or univariate analysis function, the method including:
         (a) querying the database to obtain at least selected predetermined data or access to the multivariate or univariate analysis function from the database; and   (b) comparing the selected predetermined data to the subject data or generating a predicted probability index.       

     The second processing system can be coupled to a database, the method including storing the data in the database. 
     The aspect provides a diagnostic rule based on the application of statistical and machine learning algorithms. Such an algorithm uses the relationships between methylation profile and disease status observed in training data (with known disease status) to infer relationships which are then used to predict the status of patients with unknown status. Practitioners skilled in the art of data analysis recognize that many different forms of inferring relationships in the training data may be used without materially changing the outcome disclosure herein. 
     The present disclosure contemplates, therefore, the use of a knowledge base of training data comprising extent of methylation within a genetic locus from a subject with a clinical phenotype to generate an algorithm which, upon input of a second knowledge base of data comprising levels of the same biomarkers from a patient with an unknown pathology, provides an index of probability that predicts the nature of unknown pathology or response to treatment. 
     The term “training data” includes knowledge of the extent of methylation relative to a control. A “control” includes a comparison to levels in a healthy subject devoid of a pathology or is cured of the condition or may be a statistically determined level based on trials. 
     Whilst the assay enabled herein comprises the various steps, in an embodiment, the assay consists essentially of the steps. In another embodiment, the assays consists of the steps. 
     EXAMPLES 
     Aspects disclosed herein are now further described by the following non-limiting Examples. 
     Materials and Methods 
     Data Source 
     A retrospective cohort study of extent of methylation is conducted on venous blood DNA and newborn blood spots and correlated with clinical assessment. 
     An additional patient cohort comprised of 258 male and 427 female samples collected from birth to 82 years of age collected as part of previous studies (Godler et al. (2012) supra; Inaba et al. (2013)  Genet Med  15:290-298; Loesch et al. (2012)  Glin Genet  82:88-92; Tassone et al. (2000)  Am J Med Genet  97:195-203). Of these, formal cognitive assessments were performed on 23 PM female, 21 FM females and 3 ‘high functioning’ unmethylated FM (UFM) males (with Full Scale IQ - FSIQ between 71 and 81) determined using the Wechsler intelligence test appropriate for chronological age as described in previous publications (Godler et al. (2012) supra; Loesch et al. (2012) supra; Tassone et al. (2000)  American Journal of Medical Genetics  94:232-236). 
     A further patient cohort comprised of 433 DNA from venous blood, 209 newborn and adult blood spots and 100 saliva DNA samples, with the participants&#39; age range between birth and 82 years. Of these, 100 samples were from individuals with a sex chromosome aneuploidy, 194 were from FM carriers (pure and size/methylation mosaic), 140 were from PM carriers, and 308 were from controls. EpiTYPER system analysis of all of the samples included in this study has been performed as part of previous studies (Godler et al. (2013) supra; Inaba et al. (2013) supra). EpiTYPER is a tool for the determination of DNA methylation that uses base specific cleavage and matrix-assisted later desorption/ionization time-of flight mass spectrometry. This cohort was used to analyze the sex chromosome in aneuploidy samples, the ability of MS-QMA to detect skewed X-chromosome inactivation, and the comparison between MS-QMA and the EpiTYPER system in this large cohort which includes sex chromosome aneuploidy 
     Neuropsychological Assessments 
     For the individuals whose archival clinical data and DNA samples were available, the phenotype was assessed using the Autism Diagnostic Observation Schedule-Generic (ADOS-G) [Loesch et al. (2007)  Neuro Sci Biobeta Rev  31:315-326] and Wechsler intelligence test appropriate for chronological age: WPPSI-III for ages less than 6 (Wechsler (2002)  Wechsler Protocol and Primary School of Intelligence,  The Psychological Corporation, San Antonio, Texas, USA), WISC-III for ages between 6 and 16 years and WAIS-III for ages greater than 16 years (Wechsler (1997) Orlando, the Psychological Corporation). The cognitive status of these individuals has been described in Wechsler (1991)  Wechsler Intelligence School for Children,  3 rd  Ed. (WISC-III), The Psychological Corporation, San Antonio, Tex., USA elsewhere (Godler et al. (2012) supra; Chanchaiya et al. (2010)  Hum Genet  128:539-548; Loesch et al. (2007) supra; Dissanayake et al. (2009)  J Child Psychol Psychiatry  50:290-299) and this information is used for the specificity and sensitivity assessments, determination of predictive value and correlation analysis between molecular and clinical measures. 
     Newborn Guthrie Spot Samples: 
     The newborn blood spots were assayed. The methylation results for 50 FM males and females in whole blood (greater than 4 years of age) are compared to the results in blood spots taken at birth. The newborn blood spot MS-QMA results are also compared to neuropsychological assessments in these individuals. FREE2 methylation results determined using MALDI-TOF MS are available (Godler et al. (2011) supra; Godler (2012) supra; Godler et al. (2013)  Hum Mol Genet,  In Press). 
     The MS-QMA protocol developed in accordance with the present invention was based on a combined real-time PCR standard curve method and High Resolution Melt (HRM) analysis performed on bisulfite converted DNA as described in  FIG. 1 . The input was either one 3mm dried blood spot, or DNA extracted from 0.3 to 1 ml of venous blood, with DNA or blood spot lysate extracted and CGG repeat sized as previously described (Inaba et al. (2013) supra; Loesch et al. (2009)  Am J Med Genet A  149A:2306-2310; Khaniani et al. (2008) supra; Tassone et al. (2008) supra; Christie et al. (2013)  Am J Med Genet A  161A:301-311). For 19 FM females, the FMR1 activation ratio had been previously determined using methylation sensitive Southern blot as described in (de Vries et al. (1996)  Am J Hum Genet  58:1025-1032). FMRP immunoreactivity in venous blood smears was previously assessed in 18 of these FM females and was expressed as the percentage of lymphocytes staining positive for the protein (Loesch et al. (2002)  Am J Med Genet  107:136-142; Tassone et al. (1999)  Am J Med Genet  84:250-261). FREE2 methylation was also assessed in the same samples using the Sequenom EpiTYPER system, as previously described (Godler et al. (2010) supra). 
     For the detection of skewed X-chromosome inactivation, 3 to 10 ml venous blood were collected in EDTA-treated tubes went through a DNA extracted using NucleoSpin (Registered Trade Mark) Tissue genomic DNA extraction kit, as per manufacturer&#39;s instructions (MACHEREY-NAGEL GmbH &amp; Co. KG, Duren, Germany); 2 ml saliva were collected using the Oragene (Registered Trade mark) DNA Self-Collection Kit (DNA Genotek Inc., Ottawa, Canada) and isolated as per manufacturer&#39;s instructions. Wallac dried blood spot puncher (Perkin Elmer, Mass., USA) was used to obtain one or two three-millimeter punches from each spot disk into 96-well plates. These were then incubated in 55 μl of salt lysis buffer as previously described (Inaba et al. (2012) supra) for cell lysis, degradation of proteins and release of the DNA into the solution, and stored at −20° C. until analysis. 
     MS-QMA Conditions: 
     Table 3 provides the real-time PCR/HRM conditions and primer sequences for the FREE2 (A) region. 
     
       
         
           
               
             
               
                 TABLE 3 
               
             
            
               
                   
               
               
                 MS-QMA conditions 
               
            
           
           
               
               
               
               
               
            
               
                 Real-time 
                   
                 Distance 
                 Primer sequence 
                   
               
               
                 PCR/High 
                   
                 3′ of 
                   
                   
               
               
                 resolution melting 
                 Size 
                 CGG 
                   
                 SEQ 
               
               
                 condition 
                 (b) 
                 (b): 
                   
                 ID NO: 
               
               
                   
               
               
                 (I) 95° C. for 10 min. 
                 161 
                 117 
                 Fw: 5′- 
                 7 
               
               
                 (II) 40 cycles of: 
                   
                   
                 AAGGTATTTGGTTTTAGGGTAGGTTTT -3′ 
                 8 
               
               
                 95° C. for 30 s, 65° C. 
                   
                   
                 Rv: 5′- AAATCCAATCCTTCCCTCCCA -3′ 
                   
               
               
                 for 1 min. 
                   
                   
                   
                   
               
               
                 (III) 95° C. for 30 sec, 
                   
                   
                   
                   
               
               
                 65° C. for 1 min, 95° C. 
                   
                   
                   
                   
               
               
                 for 30 sec, 65° C. for 
                   
                   
                   
                   
               
               
                 15 sec. 
               
               
                   
               
            
           
         
       
     
     Methylation Specific Quantitative Melt Analysis (MS-QMA) 
     Bisulfite Conversion and Sample Preparation 
     For newborn blood spots, one or two three-millimeter punches from each spot disk were collected into 96-well plates using the Wallac DBS Puncher (Perkin Elmer, Mass., USA) and stored at room temperature until analysis. Each punch or set of punches was incubated in 55 μl of salt lysis buffer as previously described (Inaba et al. (2013) supra). The supernatant was then transferred to a fresh 96-well plate. The extracts were then treated with sodium bisulfite using EZ-96 DNA Methylation-Gold (Trade Mark) (Zymo Research, Irvine, Calif.). 
     Real-Time PCR Standard Curve Method and High Resolution Melt Analysis (HRM) 
     The 96 converted samples (with 3 controls and 93 unknown samples per plate) were serially diluted 4 times post-conversion ( FIG. 1 ). The four 96 well plates were then transferred into a 384 well format for real-time PCR analysis utilizing MeltDoctor (Trade Mark) high-resolution melt reagents in 10 ul reactions as per manufacturer&#39;s instructions (Life technologies, Foster City, Calif.). For Real-time PCR, a unique primer set was used that targets specific CpG sites within the FREE2 region that were previously shown to be most significantly associated with cognitive impairment in FM females (Godler et al. (2012) supra). The annealing temperature for the thermal cycling protocol was 65° C. for 40 cycles. The ViiA (Trade Mark) 7 Real-Time PCR System (Life technologies, Foster City, Calif.) was then used to initially measure the rate of dye incorporation into double stranded DNA in order to quantify DNA concentration of the unknown samples using the relative standard curve method ( FIG. 1 ). The dynamic linear range (usually between 0.05-10 ng/μl) was determined from the standard curve using a series of doubling dilutions of a converted DNA standard from a control lymphoblast cell line during each run. To progress to the next stage of the analysis the unknown samples had to be within this dynamic linear range ( FIG. 1  in wells on the 384 plate in pink). The high resolution melt step followed the real-time PCR without additional sample handling/sample transfer. In the temperature range of 74° C. and 82° C. the products from methylated FREE2 sequence separated into single strands at higher temperatures than those from unmethylated FREE2. The HRM Software Module for ViiA (Trade Mark) 7 System was then used to plot the rate of PCR product separation to single strands at different temperatures with the difference in fluorescence first converted to Aligned Fluorescence Units (AFU) at the temperature that provided the greatest separation between methylated and unmethylated sequences, and then converted to the methylation ratio (MR) from the methylation curve, as described in  FIG. 1 . It will be understood that the terms “percentage of methylation” and “methylation ratio” or “MR” are used herein interchangeably. The percentage methylation is calculated by multiplying the methylation ratio by 100, i.e. MR×100=% methylation. 
     Data Analysis 
     Testing for normality distribution of the methylation ratio was conducted using Shaprico-Wilk test at significant level p=0.05. Depending on results of this test for the inter-group comparisons, either two-sample t-test for the means was used, if the data were normally distributed, or nonparametric Mann-Whitney test for median was used, if the data were not normally distributed. Individuals were also classified with FSIQ, VIQ and PIQ&gt;70 as negative and FSIQ, VIQ and PIQ&lt;70 as positive for FM females. Males were classified individuals with FM alleles recruited through the developmental delay/ASD referrals for FXS testing as positive, and all other male samples as negative. The receiver operating characteristic (ROC) curve was then used to evaluate ability of MS-QMA MR to classify the positive and negative classes. Area under the ROC curve (AUC) computed using predicted probabilities from logistic regression was used as the summary measure of diagnostic accuracy and Youden Index (Youden (1950)  Cancer  3:32-35) was used to determine the optimal threshold (cut-off point) for MS-QMA analysis. 
     The relationship between MS-QMA MR and each outcome variable including cognitive scores and other molecular measures were assessed using simple linear regression analysis. All analyses were conducted using RMS, DiagnosisMed and the publicly available R statistical computing package (Godler et al. (2012) supra; R Foundation for Statistical Computing (2007) http:/www.r-project.org/(Accessed February 2009)). 
     CGG Sizing, Methylation Using Southern Blot and SRY Real-Time PCR 
     For venous blood and saliva DNA, the processing of DNA samples and assessment of CGG repeat size (with precision of +/− one repeat) was conducted using a fully validated PCR amplification assay (Loesch et al. (2009) supra; Khaniani et al. (2008) supra). CGG repeat sizing and methylation of the FMR1 CpG island restriction sites of all samples greater than 55 repeats was also performed using a methylation sensitive Southern Blot procedure with appropriate normal and abnormal controls, as previously described (Tassone et al. (2008) supra). FREE2 methylation analysis using the Sequenom EpiTYPER system for each sample was performed in quadruplicate, giving four separate methylation output ratios (MOR), which were averaged to take account for technical variation resulting from bisulfite conversion, PCR and mass cleave reactions, as previously described (Godler et al. (2010) supra; Khaniani et al. (2008) supra; Tassone et al. (2008) supra). For newborn and dried blood spots, the CGG sizing was performed using the standard PCR amplification assay (Loesch et al. (2009) supra; Khaniani et al. (2008) supra) and triple primed PCR, as previously described. Of the 209 newborn and adult dried blood spots, 160 had CGG sizing performed as part of the previous study (Christie et al. (2013) supra). For sex chromosome aneuploidy samples and control males and females, the SRY copy number was determined using the real-time PCR relative standard curve method, normalized to β-globin, as described (Inaba et al. (2012) supra). 
     Example 1 
     Methylation Specific-Quantitative Melt Analysis (MS-QMA) Protocol 
     Bisulfite Conversion and Sample Preparation: 
     The protocol is based on combined real-time PCR standard curve method and High Resolution Melt (HRM) Analysis of bisulfite converted DNA and is referred to as methylation specific-quantitative melt analysis (MS-QMA). The required input is either a 3 mm dried blood spot or DNA extracted from 0.3 to 1 ml of venous blood. 
     For newborn blood spots, one or two three-millimeter punches from each spot disk are collected into 96-well plates using the Wallac DBS Puncher (Perkin Elmer, Mass., USA) and stored at room temperature until analysis. Each punch or set of punches is incubated in 55 μl of salt hybridization buffer for 15 minutes at 98° C. in a heat block for cell lysis, degradation of proteins and release of the DNA into the solution. After boiling, the samples are centrifuged and the supernatant transferred to a fresh 96-well plate. This extract is then treated with sodium bisulfite as previously described for venous blood DNA (Inaba et al. (2012) supra). 
     Bisulfite conversion is performed as per manufacturer&#39;s instructions (Zymo Research, Irvine, Calif.) using 96 well format Z-96 DNA Methylation-Gold (Trade Mark) MagPrep kit (less than 3 hours). The Z-96 DNA Methylation-Gold (Trade Mark) MagPrep kit integrates DNA denaturation and bisulfite conversion processes into one-step coupled to a magnetic bead based clean-up for high-throughput methylation analysis using liquid handling robotics. EZ-96 DNA Methylation-Gold (Trade Mark) [Zymo Research, Irvine, Calif.] is an alternative conversion kit that does not utilize magnetic beads, but may be also used. 
     Real-Time PCR Standard Curve Method: 
     The 96 converted samples (which include 3 controls and 93 unknown samples per plate) are serially diluted 4 times post conversion ( FIG. 1 ). The four 96 well plates are then transferred into a 384 well format for real-time PCR analysis utilizing MeltDoctor (Trade Mark) high-resolution melt reagents in 10 μl reactions as per manufacturer&#39;s instructions (Life technologies, Foster City, Calif.). For real-time PCR, unique primer sets which target specific CpG sites within the FREE2 (A) region are used (SEQ ID NOs:7 and 8) which have been shown to be significantly associated with cognitive impairment in FM females (Godler (2012) supra). The annealing temperature for the thermal cycling protocol is 65° C. for 40 cycles. The ViiA (Trade Mark) 7 real-time PCR System (Life technologies, Foster City, Calif.) is used to initially measure the rate of dye incorporation into double stranded DNA to quantify DNA concentration of the unknown samples. This is done using a standard curve of serially diluted converted DNA of known concentrations ( FIG. 1 ). For the data not to be discarded from the methylation analysis steps following real-time PCR, Ct values for the unknown sample dilutions have to be within the dynamic linear range ( FIG. 1 ) in wells on the 384 plate), usually between 0.05-10 ng/μl. The dynamic linear range is generally performed on a series of doubling dilutions of a converted DNA standard from a control lymphoblast cell line. 
     High Resolution Melt Analysis (HRM): 
     Products from methylated FREE2 (A) sequence separate into single strands at higher temperatures than those from non-methylated FREE2 (A), between 74° C. and 82° C. As strands separate the MeltDoctor (Trade Mark), dye is released and is detected by the system. The HRM Software Module for ViiA (Trade Mark) 7 System is then used to plot the rate of PCR product separation to single strands at different temperatures. HRM step follows real-time PCR in a closed well format (no additional sample handling/ sample transfer). This difference in fluorescence is quantified using a computer algorithm. Aligned Fluorescence Units (AFU) are extracted by the algorithm at the temperature that provides the greatest separation between methylated and non-methylated sequences of control methylated and non-methylated standards (the HRM methylation standard curve in  FIG. 1( i ) ). This point equates to the lowest temperature at which all double stranded DNA that originated from the non-methylated strands has completely melted emitting no new fluorescence, while the double stranded DNA from the methylated strands is actively emitting fluorescence due to strand separation and dye release. AFU&#39;s of the real-time PCR standard curve are then used to determine the quality control range ( FIG. 1 ). The AFU values for the unknown samples with high DNA quality post conversion need to be within the range of dilutions of the dynamic linear range that provide AFU output that does not change between dilutions. 
     The data analysis algorithm extrapolates methylation % for bisulfite dilutions from the HRM methylation standard curve for the unknown samples when: (i) the DNA concentration post conversion is within the real-time PCR dynamic linear range; and (ii) they are within the AFU quality control range. The HRM methylation standard curve is essential for conversion of AFU to methylation %, and is co-run on each 384 well plate with unknowns. This curve is plotted from AFU values over expected methylation of spiked lymphoblast DNA samples from a control male with completely non-methylated FREE2 (A) and a FXS male with 100% methylated FREE2 (A). The AFU values for the unknown samples are plotted against an HRM methylation standard curve ( FIG. 1 ), where AFU is converted to methylation percentage. 
     For an example of data analysis, the following filter conditions are used: (1) apply DNA concentration threshold (e.g. if DNA concl is &lt;0.5 ng/μl, then remove AF1 from the data set; (2) remove outlier (up to 2 AFs) [e.g. if absolute value (mean of AF1-4)-AF2) is &gt;6.2] (this value is obtained from two time standard deviation of the linear dynamic range controls), then remove AF2 from the data set; and (3) N≥2 (e.g. if 2N:AF3 and AF4 [AF1 and AF2 are removed from the data sets]). See  FIG. 1 . 
     Example 2 
     Development and Technical Validation of the FREE2 MS-QMA Assay 
     To assess the intra run variation and the ability of the assay to predict the expected methylation ratio (MR) 16 different spiking experiments were performed. A temperature of 78° C. was identified as the lowest temperature at which all unmethylated alleles are completely melted, at which point no further fluorescence is emitted. At this temperature, the 100% methylated alleles are actively melting, and emitting fluorescence. A reliable method with the lowest inter and intra run variation (two standard deviations) and the lowest detection limit (LOD of 0.02 MR) used the AFUs from the aligned fluorescence curves at 78° C. This produced a correlation coefficient of 0.998 for the High Resolution Melt (HRM) standard curve representing the relationship between AFU at 78° C. and the expected methylation ratio in the spiked samples. 
     MS-QMA analysis was performed in  FIG. 2 ( ii ) in 138 females previously examined for the relationship between FREE2 methylation and cognitive impairment using the MALDI-TOF MS based EpiTYPER system (Godler et al. (2012) supra) [ FIG. 3( i )  and Table 4) and 288 females ( FIG. 3 ( ii )) for the majority of whom no formal cognitive assessment performed ( FIG. 3 ( ii )). It was found that assay sensitivity and specificity for FM females with IQ&lt;70 in the sub-group of 138 participants varied depending on the type of IQ measure. The optimal threshold of 0.39 MR that provided sensitivity of ˜95% and specificity 100% was for detection of FM females with VIQ&lt;70 (Table 5A). The threshold of 0.37 MR provided the highest sensitivity and specificity of ˜92% and 100%, respectively for both the FSIQ and PIQ assessments in FM females. 
     Notably, there was also some overlap between controls and PM and low functioning FM females at the lower threshold of 0.37 for FSIQ and PIQ ( FIG. 3 ( ii )) suggesting that the VIQ threshold of 0.39 should be used instead. At 0.39 MR there were no female controls (CGG&lt;40) with MR values above this threshold. When applied to a group 288 females ( FIG. 3 ( ii )), approximately 50% of all FM females had an MR above 0.39 MR. In contrast, only one PM female had MR above the 0.39 threshold, and only two PM females had MR of 0.39. This equates to 0% of controls and ˜3% of PM females at or slightly above the VIQ&lt;70 threshold. These 3% of PM females and 19% of FM females had MS-QMA output within a borderline range of 0.39 to 0.41 MR ( FIGS. 2 ( ii ) and  3 ( ii )) suggesting that, CGG sizing should be used on all samples in this range to resolve any potential overlap between allele classes. 
     It is also important to note that in this borderline range (0.39 to 0.41 MR) there was overlap between VIQ&lt;70 and &gt;70 for a proportion of FM females. However, for all PM and FM samples above and below this borderline range MS-QMA VIQ&lt;70 sensitivity, specificity, positive and negative predictive values were 100% ( FIG. 2 ( ii ) and  FIG. 13 ). Each FM female within the borderline range (0.39 to 0.41 MR) had 86% probability for VIQ&gt;70 (high functioning). Furthermore all PM females within this range had 100% probability for VIQ&gt;70, suggesting that in relation to verbal cognitive impairment the MS-QMA results should be reported as risk or probabilities depending where the MR values fall. 
     Intergroup comparison of MS-QMA in venous blood DNA from 124 males showed that the median MR was significantly higher for FM males (identified through investigation of developmental delay/ASD), FM methylation mosaics and PM/FM size mosaics than for male controls, PM males and ‘high functioning’ UFM males with FSIQ, VIQ and PIQ&gt;70 ( FIG. 3 ( ii )). A threshold of 0.1 MR provided sensitivity and specificity approaching 100% for FM males and FM methylation mosaics, while for PM/FM size mosaics the sensitivity was 88% and specificity was 100% at this threshold (Table 5). 
     EXAMPLE 3 
     Follow-up Testing of Identified Cryptic FM Individuals Using Reference Methods 
     To confirm the cryptic FM status, the samples identified as positive using MS-QMA are re-tested using CGG sizing PCR, methylation-sensitive Southern blot and MALDI-TOF MS FREE2 analysis as described in earlier publications (Godler et al. (2010) supra; Godler et al. (2012) supra). Briefly, processing of ‘positive’ DNA samples and the assessment of the size of CGG repeat from the extracted DNA (with precision of +/− one repeat) are conducted using a fully validated PCR amplification assay (Khaniani et al. (2008)  Mol Cytogenet  1:5). CGG repeat sizing and methylation of the FMR1 CpG island restriction sites of all positive samples are also performed using a methylation sensitive Southern Blot procedure with appropriate normal and abnormal controls, as previously described (Godler et al. (2010) supra; Tassone et al. (2008)  J Mol Diagn  10:43-49). Briefly, EcoRI and NruI digestion is performed on 7 to 9 μg of DNA. The FMR1 alleles are detected using the StB 12.3 probe, labeled with Dig-11-dUTP by PCR (PCR Dig Synthesis kit; Roche Diagnostics). Southern blot methylation for the expanded FMR1 alleles are determined as previously described (Godler et al. (2010) supra) with alleles classified as either non-methylated, partially methylated or fully methylated. Alleles at CGG sizes greater than 150 repeats that are methylated by Southern blot are classified as FM; alleles between 55 and 200 repeats that are non-methylated by Southern blot are classified as PM. FREE2 (A) methylation analysis using MALDI-TOF MS are assessed in the same samples using the Sequenom EpiTYPER system, as previously described (Godler et al. (2010) supra). FREE2 (A) methylation analysis for each sample are performed in duplicate, giving two separate methylation output ratios (MOR), averaged to take account of technical variation resulting from bisulfite conversion, PCR and mass cleave reactions. 
     Example 4 
     Advantages of FREE2 (A) MS-QMA in FXS Diagnostics 
     Standard laboratory testing for FXS falls into the following categories. The first category applies to diagnostic testing of individuals with intellectual disability or ASD of unknown etiology, where a positive result leads to testing of other family members, in whom the risk of carrier status is high. The second category applies to prenatal testing in known carrier pregnancies. The third category is the population screening of newborns. Earlier treatment intervention, identification of probands pointing to high risk relatives and provision of reproductive counseling are strong arguments in favor of newborn screening. 
     One major impediment is the limited suitability of current test methods which are a combination sizing of small and large CGG repeat expansions by PCR and Southern blot testing, respectively (Tassone et al. (2008) supra). Several PCR based approaches have been developed to amplify PM and small FM alleles, however, they do not provide information on the gene&#39;s methylation status (Tassone et al. (2008) supra; Filipovic-Sadic et al.  Clin Chem  56(3):399-408; Hantash et al.  Genet Med  12(3):162-173; Dodds et al. (2009)  Anal Chem ). These short-comings necessitate further testing using methylation sensitive Southern blot. However, the use of Southern blot for any type of large scale testing is primarily restricted by low throughput, cost and DNA quality and quantity limitations. 
     A PCR based test has been developed that determines CGG length up to FM size and examines methylation of two HpaII sites on either side of the CGG expansion (Chen et al. (2011)  Genet Med  13:528-538). Whilst it has been suggested that use of this test avoids reflexing to methylation sensitive Southern blot because it provides methylation analysis as well as CGG size, the CpG sites examined by this method are different from those examined by methylation sensitive Southern blot and provide different results particularly in PM females compared to the reference method. Importantly, methylation of these HpaII sites has not been as yet related to any clinical phenotype in FMR1 expansion carrier females, thus reflexing to methylation sensitive Southern blot is still required for carrier females. 
     Furthermore, all of the above PCR tests detect GZ and PM carriers who are highly prevalent in the general population (for males 1 in ˜30 for GZ and 1 in ˜700 for PM carriers; for females 1 in ˜15 GZ and 1 in ˜250 for PM carriers) [Sherman (2000)  Am J Med Genet  97:189-194; Bretherick et al. (2005)  Hum Genet  117:376-382]. These small expansions do not cause FXS but PM carriers have a high risk of transmitting them in an expanded form. Furthermore, both PM and GZ alleles have been associated with elevated FMR1 mRNA (Kenneson et al. (2001)  Hum Mol Genet  10:1449-1454; Loesch et al. (2007)  J Med Genet  44:200-204) and related to increased risk of developing FXPOI, while PM alleles have been also linked to FXTAS (Bretherick et al. (2005) supra; Hagerman et al. (2001) supra; Greco et al. (2002)  Brain  125:1760-1772; Allingham-Hawkins et al. (1999)  Am J Med Genet  83:322-325; Sullivan et al. (2005)  Hum Reprod  20:402-412; Bodega et al. (2006)  Hum Reprod  21:952-957). Thus, a test that detects GZ and PM alleles may inadvertently turn a screen for FXS into a predictive assay for a late onset disorder. 
     This is addressed by the MALDI-TOF mass spectrometry test for FREE2 (A) methylated markers. The method is advantageous over most other MS-PCR based assays (Boyd et al. ((2006)  Anal Biochem  354:266-273; Zhou et al. (2006)  Clin Chem  52:1492-1500) and enzyme based MS-MLPA methods (Nygren et al. (2008)  J Mol Diagn  10:496-501) developed to examine methylation of the ‘classical’ FMR1 CpG island, as MALDI-TOF MS can be used to rapidly examine large stretches of DNA for methylation. In contrast, most PCR, or MS-MLPA and enzyme based MS-MLPA methods are restricted to a few sites that are less biologically significant and/or more heavily affected by skewed X-inactivation (Boyd et al. ((2006) supra; Nygren et al. (2008) supra). This point is clearly evident from another high-throughput MS-PCR assay recently developed by another group, with proposed applications in population screening (Coffee et al. (2009) supra), where although this assay has 100% specificity and 100% sensitivity for detecting FMR1 methylation in males, in females it cannot not reliably detect excess FMR1 methylation, and its levels do not correlate with intellectual disability (Coffee et al. (2009) supra). In contrast, FREE2 (A) analysis using MALD-TOF MS is suitable for both males and female samples, and most importantly, as demonstrated (Godler et al. (2010) supra; Godler et al. (2010) supra; Inaba et al. (2012) supra), it reflects the level of neurodevelopmental changes in carriers of expanded FMR1 alleles. Whilst FREE2 (A) MALD-TOF MS analysis showed high sensitivity and specificity for FXS, it could not differentiate between GZ and PM alleles and controls - a technical drawback that could also be a major advantage of the MALDI-TOF MS over the existing methodologies particularly in newborn screening applications. 
     The main limitation of MALDI-TOF MS method is that it requires expensive, specialized equipment, which is not commonly used in diagnostic laboratories and uses a multi-step process with relatively high reagent costs. The MS-QMA methodology described herein, however, is more suitable for widespread and high throughput use since it does not require expensive equipment or specialized training. 
     The MS-QMA protocol requires virtually no initial sample processing such as measurement of DNA concentration and purity using spectrophotometry or capillary electrophoresis for fragmentation/quality. Either one 3mm dried blood spot or DNA extracted from 0.3 to 1 ml of venous blood is the required input. Other advantages of MS-QMA is that it has higher inter-run reproducibility (&lt;5% variation) with the lower limit of detection of 5% methylation than MALDI-TOF MS. This is evidenced from  FIG. 1  HRM methylation standard curve (inside the green box) where male control DNA has been spiked at different ratios with 100% methylated FXS male DNA. The HRM methylation standard curve represents the relationship between the mean aligned fluorescence (AFU) at 78° C. of six separate DNA spiking experiments determined using MS-QMA (X axis) and the expected methylation ratio in male control DNA spiked with methylated FXS male DNA (Y axis). The error bars represent one standard deviation between runs for each point, with the coefficient of correlation approaching 1 demonstrating that AFU is highly predictive of expected % methylation of the FREE2 (A) region. 
     Furthermore, MS-QMA requires ˜1000 fold less DNA quantity than Southern blot, ˜100 fold less DNA than the MS-PCR established for FXS testing in males (Zhou et al. (2006) supra), and ˜10 fold less DNA than MALDI-TOF MS. It is less sensitive to DNA quality issues than Southern blot (as it was used to identify FM/FXS samples that failed when analyzed via Southern blot). The MS-QMA analysis is far more rapid than Southern blot (&lt;2 days vs. 1 to 2 weeks for Southern). To maximize productivity the process is further automated by coupling the real-time PCR machine to the Applied Biosystems (Registered Trade Mark) Twister (Registered Trade Mark) II Robot, which can automatically load up to six 384 plates in 12 hours. This increases MS-QMA throughput to ˜500 samples per 24 hours. 
     In addition, FREE2 (A) analysis using both MS-QMA and MALDI-TOF MS identify cryptic FXS individuals (mosaics with normal and FM size expansions) missed using standard FXS testing. This could become a major advantage of FREE2 (A) analysis over the current FXS testing protocol, once the prevalence estimates are determined for these individuals in the ASD and cognitive impairment populations and provides a strong argument for inclusion of FREE2 (A) methylation analysis as a first line test for all ASD and developmental delay cases of unknown cause referred for molecular testing worldwide. 
     Furthermore, FREE2 (A) methylation analysis has been conducted using both MALDI-TOF MS (Inaba et al. (2012) supra) and MS-QMA ( FIG. 3( i ) ) and are both robust for analysis of methylation from both freshly prepared and archival newborn dried blood spots. MS-QMA test has the potential to become the most suitable method for widespread testing due to its specificity for the individuals that are affected with FXS, and thus it would identify the individuals that would benefit from early intervention. 
     Example 5 
     Sensitivity and Specificity of the MS-QMA Test for the Type and Severity of Specific Cognitive Impairment Using DNA from Blood 
     Sensitivity and specificity are determined for MS-QMA ( FIG. 2( i ) ) and MALDI-TOF MS ( FIG. 3( i ) ) FREE2 (A) methylation analysis in FMR1 expansion carriers and controls. The sensitivity is considered to be a measure of the probability of correctly identifying the presence of specific cognitive and behavioral deficits as determined using neuropsychological assessments, and the specificity - a measure of the probability of correctly identifying a person as not being affected by cognitive and behavioral deficits. The individuals are considered as affected with: (i) ASD if the ADOS-G score is &gt;17; (ii) cognitive impairment if IQ test score is &lt;70; or cognitive indexes or cognitive sub-scores are &lt;7.5. Comparisons between the median methylation for blood DNA between PM and FM groups and healthy controls are also conducted using the nonparametric Mann-Whitney two-sample test. ANOVA or nonparametric Kruskal-Wallis rank test are also used to compare the differences in the levels of methylation determined using MALDI-TOF MS and MS-QMA, with the neuropsychological measures between the FM (n=111), PM (n=186) and age matched control (n=90) groups. 
     
       
         
           
               
             
               
                 TABLE 4 
               
             
            
               
                   
               
               
                 Comparison of FREE2 MS-QMA median methylation ratios for FM females re-classified as 
               
               
                 negative for FSIQ, VIQ and PIQ values &gt;70 and as positive for FSIQ, VIQ and PIQ values &lt; 
               
               
                 70, with the comparisons conducted using the non-parametric Mann-Whitney two-sample test. 
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                   
                 n 1   
                 n 2   
                 med 1   
                 med 2   
                 IQR 1   
                 IQR 2   
                 P-value 
               
               
                   
               
               
                 FSIQ 
                 7 
                 13 
                 0.45 
                 0.38 
                  0.11 
                 0.04 
                  0.0068** 
               
               
                 PIQ 
                 8 
                 11 
                 0.43 
                 0.38 
                 0.1 
                 0.04 
                  0.0101* 
               
               
                 VIQ 
                 6 
                 13 
                 0.47 
                 0.38 
                  0.07 
                 0.03 
                  0.0024** 
               
               
                   
               
               
                 Note: 
               
               
                 *P values &lt;0.05 are highlighted in bold; 
               
               
                 **P values &lt;0.01 are highlighted in bold; 
               
               
                 sample size (n); 
               
               
                 median (med); 
               
               
                 interquartile range (IQR);. 
               
               
                 n 1  represents numbers of positive (IQ &lt; 70), and n 2  represents number of negative (IQ &gt; 70). 
               
            
           
         
       
     
     Example 6 
     Relationship Between FREE2 (A) MS-QMA Results and the Severity of Cognitive and Behavioral Impairments 
     Nonparametric regression is used to determine whether there is a non-linear relationship between each predictor of methylation levels (determined using MALDI-TOF MS and MS-QMA) in PM and FM carriers, and cognitive/behavioral outcome measures in the subgroup of 111 FM and the combined sample of 297 carriers. Parametric regression and correlation analysis is then used to conduct analysis between a pair of these variables. In the multivariate analysis stepwise regression using Bayesian information criteria and penalized regression method is used to select the best methylation analysis approach that best predicts the outcome. All final models are validated internally using cross-validation and bootstrap. Finally, ANOVA or nonparametric Kruskal-Wallis rank test is used to compare the differences in the levels of methylation, determined using MALDI-TOF MS and MS-QMA, and the neuropsychological measures between FM ASD +  and ASD −  groups. 
     Furthermore, nonparametric regression is used to determine whether there is a non-linear relationship between each predictor of FREE2 (A) methylation levels in PM and FM groups in blood, and cognitive/behavioural outcome for the FMR1 expansion carriers as detailed in (Godler et al. (2012) supra). 
     The level of FREE2 methylation in venous blood DNA determined using MS-QMA correlated significantly with Wechsler Adult Intelligence Scale (Godler et al. (2010)  Genet Med  12:595) FSIQ, VIQ and PIQ and most WAIS subtest scores (Table 6). The epigenotype-phenotype correlations were most evident for the relationships of MS-QMA MR with VIQ, and the Arithmetic and Information subtests (p&lt;0.01). However, in PM females these subscale and subtest scores did not show significant correlations. In these samples MS-QMA MR was also significantly correlated with FREE2 CpG sites examined using the EpiTYPER system (Table 7), with p&lt;0.0001 for all of these sites. Of the other molecular parameters available through the previous studies for these samples (Godler et al. (2010) supra; Godler et al. (2011) supra), FREE2 MS-QMA also showed significant correlation (p=0.018) with FMR1 activation ratio determined using methylation sensitive Southern blot, which represents the methylation status of the FMR1 CpG island on normal size alleles in these females. Correlation with FMRP levels was of borderline significance (p=0.058), with no significant correlation observed with CGG size in the FM range of these females (Table 7). 
     
       
         
           
               
             
               
                 TABLE 5 
               
             
            
               
                   
               
               
                 Sensitivity and specificity for MS-QMA MR in venous blood DNA: (A) FM females with FSIQ, 
               
               
                 VIQ and PIQ &lt; 70 determined using the ROC analysis in a sample of 94 controls, 23 PM, and 
               
               
                 21 FM females. Sensitivity and specificity were calculated based using the Youden index 
               
               
                 optimal cut off value which for FSIQ and PIQ was 0.37, and for VIQ was 0.39; (B) 52 FM 
               
               
                 males indentified through investigation of developmental delay/ASD, 4 FM methylation 
               
               
                 mosaics and 17 PM/FM size mosaics in a sample of 124 males including 20 male controls, 
               
               
                 28 PM and 3 ‘high functioning’ FM males with FSIQ, VIQ and PIQ &gt; 70; determined to be 
               
               
                 unmethylated using methylation sensitive Southern blot identified through cascade testing. 
               
            
           
           
               
               
               
               
               
               
               
            
               
                   
                   
                   
                   
                 **Optimal cut 
                   
                   
               
               
                   
                   
                   
                   
                 off value 
                   
                   
               
               
                   
                   
                   
                   
                 (Youden index) 
                   
                   
               
               
                   
                   
                   
                   
                 for MS-QMA 
                   
                   
               
               
                 Variable 
                 AUC* 
                 SE 
                 95% Cl 
                 MR 
                 Sensitivity+ 
                 Specificity+ 
               
               
                   
               
            
           
           
               
            
               
                 (A) Females 
               
            
           
           
               
               
               
               
               
               
               
            
               
                 FSIQ 
                 0.983 
                 0.013 
                 0.946-0.998 
                 0.37 
                 1.000 
                 0.911 
               
               
                 VIQ 
                 0.993 
                 0.007 
                 0.958-0.999 
                 0.39 
                 1.000 
                 0.943 
               
               
                 PIQ 
                 0.983 
                 0.011 
                 0.946-0.998 
                 0.37 
                 1.000 
                 0.918 
               
            
           
           
               
            
               
                 (B) Males 
               
            
           
           
               
               
               
               
               
               
               
            
               
                 FM males 
                 1.000 
                 0.000 
                 0.965-1.000 
                 0.10 
                 1.000 
                 1.000 
               
               
                 with ASD 
                   
                   
                   
                   
                   
                   
               
               
                 FM 
                 1.000 
                 0.000 
                 0.935-1.000 
                 0.10 
                 1.000 
                 1.000 
               
               
                 methylation 
                   
                   
                   
                   
                   
                   
               
               
                 mosaics 
                   
                   
                   
                   
                   
                   
               
               
                 PM/FM size 
                 0.959 
                 0.033 
                 0.876-0.991 
                 0.10 
                  0.8824 
                 1.000 
               
               
                 mosaics 
               
               
                   
               
               
                 *AUC indicates Area under the curve; 
               
               
                 **Specificity and methylation cut off value were calculated at 100% sensitivity; 
               
               
                 +Sensitivity and specificity were calculated base on the Youden index optimal cut-off value. 
               
            
           
         
       
     
     
       
         
           
               
             
               
                 TABLE 6 
               
             
            
               
                   
               
               
                 Relationships between FREE2 MS-QMA MR (predictor) with outcome  
               
               
                 variables WAIS FSIQ, subscales and subtests using simple linear regression 
               
            
           
           
               
               
               
               
               
            
               
                   
                 N 
                 Estimated coeff. 
                 SE 
                 P 
               
               
                   
               
            
           
           
               
               
               
               
               
            
               
                 Full Scale IQ (FSIQ) 
                 20 
                 −236.7 
                 64.99 
                 
                   0.002** 
                 
               
               
                 Verbal IQ (VIQ) 
                 19 
                 −239.0 
                 64.64 
                 
                   0.002** 
                 
               
               
                 Performance IQ (IQ) 
                 19 
                 −184.5 
                 66.59 
                 
                   0.013* 
                 
               
               
                 Verbal Comprehension Index 
                 15 
                 −197.9 
                 72.95 
                 
                   0.018* 
                 
               
               
                 (VCI) 
                   
                   
                   
                   
               
               
                 Perceptual Organization Index 
                 15 
                 −161.5 
                 80.34 
                 0.066 
               
               
                 (POI) 
                   
                   
                   
                   
               
               
                 Working Memory Index (WMI) 
                 9 
                 −201.5 
                 72.57 
                 
                   0.027* 
                 
               
               
                 Processing Speed Index (PSI) 
                 15 
                 −115.0 
                 52.42 
                 
                   0.047* 
                 
               
               
                 Picture Completion 
                 17 
                 −40.43 
                 14.19 
                 
                   0.012* 
                 
               
               
                 Vocabulary 
                 16 
                 −44.63 
                 15.75 
                 
                   0.013* 
                 
               
               
                 Coding 
                 15 
                 −28.87 
                 11.91 
                 
                   0.031* 
                 
               
               
                 Similarities 
                 17 
                 −27.76 
                 13.72 
                 0.061 
               
               
                 Block Design 
                 17 
                 −26.33 
                 13.83 
                 0.076 
               
               
                 Arithmetic 
                 17 
                 −41.15 
                 10.13 
                 
                   0.001** 
                 
               
               
                 Matrix Reasoning 
                 9 
                 −22.22 
                 18.34 
                 0.265 
               
               
                 Digit Span 
                 16 
                 −23.48 
                 12.61 
                 0.084 
               
               
                 Information 
                 17 
                 −42.85 
                 12.19 
                 
                   0.003** 
                 
               
               
                 Picture Arrangement 
                 15 
                 −31.67 
                 12.11 
                 
                   0.021* 
                 
               
               
                 Comprehension 
                 17 
                 −42.24 
                 17.54 
                 
                   0.029* 
                 
               
               
                 Symbol Search 
                 15 
                 −19.21 
                 10.34 
                 0.086 
               
               
                 Letter Number Sequencing 
                 9 
                 −41.42 
                 14.49 
                 
                   0.024* 
                 
               
               
                 Object Assembly 
                 17 
                 −21.27 
                 13.90 
                 0.147 
               
               
                   
               
               
                 Note: 
               
               
                 *P values &lt; 0.05 are highlighted in bold; 
               
               
                 **P values &lt; 0.01 are highlighted in bold; 
               
               
                 sample size (n). 
               
            
           
         
       
     
     
       
         
           
               
             
               
                 TABLE 7 
               
             
            
               
                   
               
               
                 Relationships between FREE2 MS-QMA MR (outcome variable) with 
               
               
                 each molecular variable (predictor) using simple linear regression 
               
            
           
           
               
               
               
               
               
               
               
            
               
                   
                   
                 Estimate 
                   
                   
                 #Standardized 
                   
               
               
                   
                 N 
                 coeff. 
                 SE 
                 P 
                 coeff 
                 #R-square 
               
               
                   
               
               
                 cpg1   
                 18 
                 0.5488 
                 0.1095 
                  &lt;0.0001** 
                 0.7815 
                 0.5865 
               
               
                 cpg2   
                 18 
                 0.6234 
                 0.1239 
                  &lt;0.0001** 
                 0.7828 
                 0.5885 
               
               
                 cpg67  
                 18 
                 0.5504 
                 0.0801 
                  &lt;0.0001** 
                 0.8641 
                 0.7308 
               
               
                 cpg89  
                 18 
                 0.6399 
                 0.0902 
                  &lt;0.0001** 
                 0.8712 
                 0.7439 
               
               
                 cpg1012 
                 18 
                 0.6090 
                 0.0671 
                  &lt;0.0001** 
                 0.9150 
                 0.8373 
               
               
                 FMR1  
                 19 
                 −0.2216  
                 0.0845 
                 0.018* 
                 −0.5364  
                 0.2877 
               
               
                 activation 
                   
                   
                   
                   
                   
                   
               
               
                 ratio 
                   
                   
                   
                   
                   
                   
               
               
                 FMRP % 
                 18 
                 −0.0018  
                 0.0009 
                 0.058  
                 −0.4546  
                 0.2067 
               
               
                 positive 
                   
                   
                   
                   
                   
                   
               
               
                 CGG 
                 20 
                  0.00002 
                 0.0001 
                 0.844  
                 0.0469 
                 0.0022 
               
               
                   
               
               
                 #Standardized coefficient and R-square approaching 1 indicate that a variable has a stronger relationship with outcome variable MS-QMA MR. 
               
               
                 Note: 
               
               
                 *P values &lt;0.05 are highlighted in bold; 
               
               
                 **P values &lt;0.01 are highlighted in bold; sample size (n). 
               
            
           
         
       
     
     Example 7 
     Positive and Negative Predictive Values of this Test in Newborn DNA Samples from FXS Affected Children 
     The positive predictive values are determined through a retrospective analysis of 50 FM newborn bloodspots using FREE2 (A) MALDI-TOF MS and MS-QMA systems. The positive predictive values for FREE2 (A) methylation analysis are calculated as the probability of methylation to provide a positive test result as determined using: (i) methylation analysis in venous blood DNA at greater than 4 years of age; (ii) neuropsychological assessments in affected subjects greater than 4 years of age. The positive methylation thresholds for each clinical measure are determined using the receiver operating characteristic curve (ROC) analysis and the ability of the MALDI-TOF MS and MS-QMA methylation value to classify the affected and not affected classes for each clinical measure will be determined as described in (Godler et al. (2012) supra). 
     The negative predictive values for FREE2 (A) methylation analysis are calculated, as the probability that methylation analysis in newborn blood spot DNA from 300 de-identified controls, with normal FMR1 gene as determined using standard diagnostic protocols, to provide a negative test result. The negative test result is defined by the negative methylation thresholds in venous blood DNA of the combined sample of FMR1 expansion carriers and controls determined using ROC analysis. 
     In newborn blood spots at the threshold of 0.1 for males and 0.39 for females the sensitivity, specificity, positive and negative predictive value for presence of a FM allele approached 100% ( FIG. 4  and  FIG. 13 ). For male newborn blood spots the exception was an FM spot which had an MR value identical to those UFM ‘high functioning’ individuals. This was not an artifact as it was shown to be unmethylated using EpiTYPER system analysis of FREE2 (Inaba et al. (2013) supra). 
     Unexpectedly in newborn blood spots MS-QMA identified more than 90% of all FM females above the 0.39 threshold, while in earlier study (Inaba et al. (2013) supra) MALDI-TOF MS analysis of CpG10-12 identified only 50% above the affected threshold (which for CpG10-12 was 0.435). In an attempt to explain the blood spot discrepancy was performed MALDI-TOF MS analysis on the same newborn blood spots for FREE2 CpG10-12 and CpG6-12 ( FIGS. 4C  and D). Consistent with the previous study (Inaba et al. (2013) supra), MALDI-TOF MS analysis of CpG10-12 identified only 50% above the affected threshold. However, inclusion of additional CpG sites for MALDI-TOF MS analysis (present in the MS-QMA amplicon) increased the MOR of both control and FM groups, and altered the proportion of FM females above the affected threshold ( FIG. 4D ). This suggests that difference in the number and the way the CpG sites were analysis is the most likely the reason why in NBS MS-QMA identified more than 90% of all FM females above the 0.39 threshold while in this and earlier studies (Inaba et al. (2013) supra) MALDI-TOF MS analysis of CpG10-12 identified only 50% above the affected threshold. Furthermore, although the EpiTYPER approach targets CpG 3, 4 and 5 within FREE2, these cluster as one fragment which is too big in size (Dalton) to be captured within the mass spectrum. For this reason CpGs 3 to 5 cannot be analyzed by the EpiTYPER approach, but are analyzed by the MS-QMA approach, and in this sense MS-QMA appears to be a superior strategy. 
     Example 8 
     Application of Methylation Specific-Quantitative Melt Analysis 
     The epigenetic marker for FXS, FREE2 (A) methylation analysis, is inversely correlated with FMRP expression in males and females with expanded FMR1 alleles (Godler et al. (2010) supra; Godler et al. (2011) supra). Data also show that FREE2 (A) MALDI-TOF MS methylation analysis is superior to methylation-sensitive Southern blot (used in current FXS diagnostics) and FMRP immunostaining in blood as a predictor of cognitive impairment in female carriers of expanded FMR1 alleles as assessed using Wechsler Adult Intelligence Scale (WAIS) IQ tests, with specificity and sensitivity approaching 100% (Godler et al. (2012) supra). 
     The MS-QMA protocol described herein also examines the FREE regions. However its reagent cost is a third of that for the reference method MALDI-TOF MS, and it is also high-throughput and methylation-specific. MS-QMA involves bisulfite conversion followed by a real-time PCR relative standard curve method utilizing unique primer set that targets specific CpG sites within the FREE2 (A) region (Godler et al. (2012) supra) which is then followed by the high resolution melt (HRM) analysis. The real-time PCR output is used as an internal DNA quality/concentration control. The HRM analysis provides methylation output, defined by AFU&#39;s are determined from melt profiles. AFU is generated by a computer algorithm to obtain specific temperature/s that provide the greatest separation between methylated and non-methylated sequences of control methylation standards. This AFU measure shows high inter- and intra-run reproducibility (&lt;5% variation). 
       FIG. 5  data show that MS-QMA is a robust tool for detection of FXS cryptic mosaic individuals missed using standard FXS testing. These cryptic mosaics with ASD have both a normal size allele and a FM methylated allele, where the smaller alleles are generated through somatic instability. The melt profiles of the individuals contain two peaks, one peak at the same temperature as male healthy controls, and the other higher peak at the same temperature as FM only FXS affected individuals. 
     In  FIG. 2( i )  quantitation using MS-QMA provided the same methylation values as the reference method, MALDI-TOF MS. However, one of the advantages of MS-QMA is that, unlike MALDI-TOF MS, it is both qualitative and quantitative. This contributes to twice as high detection limit for methylated FM alleles (only 5%) in the background of non-methylated control alleles of for MS-QMA. Therefore, MS-QMA has the potential to identify more FXS cryptic mosaic individuals than MALDI-TOF MS. Using MS-QMA the test can accurately differentiate all carriers of harmful methylated FM alleles from healthy controls and PM carriers in a cohort studies. In the group of 17 FM females MS-QMA, AFU correlated most significantly with Full Scale IQ (FSIQ) and Verbal IQ (VIQ) (P&lt;0.01) ( FIG. 2 ), but also with Performance IQ (PIQ) (P=0.03). AFU also showed significant correlation with most cognitive sub-score measures, with the strongest magnitude of correlation with Arithmetic (P=0.0098) and Information (P=0.0059) sub-scores. For FM females there were differences in assay sensitivity and specificity assessments and optimal AFU threshold depending on the IQ measure. The optimal threshold of 39 AFU provided highest sensitivity and specificity approaching 100%, for detection of FM with VIQ&lt;70. In an independent cohort of 60 FM females with no formal cognitive assessment, it was found that 33% of all FM females were above 39 AFU ( FIG. 3( i ) ). If this threshold was lowered to 36 AFU it provided maximum specificity and sensitivity for FM genotype, independent of the cognitive status. Values above this lower threshold identified 58% of all FM females with only 3% control and PM female false positives in venous blood DNA. If applied in newborn screening, these false positives can be further resolved through by second stage testing follow-up involving CGG sizing. 
     The output of MS-QMA in DNA from venous blood to the previously published and validated MALDI-TOF MS method (Godler et al. (2012) supra) in the larger cohort of males and females for venous blood DNA and newborn and adult dried blood spots (DBS) ( FIG. 3( i ) ). In both venous blood DNA and DBS, FM males and females showed methylation significantly higher than in their respective PM and control groups as assessed by both MALDI-TOF MS and MS-QMA (P&lt;0.0001). As expected, the only FM group that showed overlap with PM and control groups were FM females. Interestingly, in DBS the threshold of 39 AFU determined to be optimal for identification of the FM group with verbal cognitive impairment ( FIG. 2( i ) ) identified 96% of all FM females examined which is ˜3 fold increase to that in venous blood FM subgroup ( FIG. 3( i ) ). 
     In venous blood DNA the combined comparison of all allele classes for males (n=76) and females (n=223) showed correlation coefficient of 0.99 and 0.78, respectively, with P&lt;0.0001. In DBS the combined comparison of all allele classes for males (n=50) and females (n=54) showed correlation coefficient of 0.98 and 0.5, respectively, with P&lt;0.0001. In the FM only males, venous blood DNA subgroup (n=39) showed correlation coefficient of 0.75; p&lt;0.0001; and for DBS (n=22) correlation coefficient of 0.85; p&lt;0.0001. In the FM only females, venous blood DNA subgroup (n=78) showed correlation coefficient of 0.77; p&lt;0.0001; and for DBS (n=25) correlation coefficient of 0.37; p=0.07 (not significant possibly due to small sample size). It is also important to note that in the rare FM male not affected with FXS (IQ&gt;70) and non-methylated as determined by Southern blot (UFM) (red triangles in  FIG. 3( i ) ), were also completely non-methylated by MALDI-TOF MS and MS-QMA in both venous blood DNA and DBS. This suggests that MS-QMA FREE2 (A) methylation output in blood reflects that in brain, and is consistent with two reference methods—MALDI-TOF MS and methylation sensitive Southern blot analysis. 
     The present invention provides a novel method (MS-QMA) which is much more efficacious and cost-effective than Sequenom EpiTYPER approach for methylation analysis of the FREE2 region if utilized in FXS diagnostics and population screening. In females the FMR1 activation ratio determined using the Southern blot was significantly correlated with FREE2 methylation assessed using MS-QMA and the EpiTYPER system (Godler et al. (2011) supra). In males, two PM/FM mosaics and three ‘high functioning’ FM males (IQ&gt;70) unmethylated in the FMR1 CpG island by Southern blot (Godler et al. (2010) supra), were below the 0.1 MR threshold within FREE2 as determined using MS-QMA and the EpiTYPER system ( FIG. 4A ). Therefore, the ability of MS-QMA to differentiate the ‘high functioning’ FM males from the typical FXS males, is likely to be of prognostic value when used for early detection of FXS in males. 
     A somewhat surprising finding was that in newborn blood spots at 0.39 threshold MS-QMA identified not only most FM males, but also almost all FM females, with sensitivity, specificity, positive and negative predictive value for presence of a FM allele between 92 and 100%. For this reason, this indicates that the MS-QMA test has applications for early detection of all FXS FM in females as well as males, particularly if used within the 1 st  year of life. 
     However, at the age range from 6 to 35 years at the same threshold, in venous blood MS-QMA identified only 50% of all FM females. This FM group had VIQ&lt;70, with the test showing sensitivity of 100% and specificity ˜95%. Rather than a technical issue or bias of ascertainment, the likely explanation for this is that age range of the participants was different between venous blood and blood spot cohorts. While in the venous blood for FM, PM and control females there was no significant relationship between age and MS-QMA output ( FIG. 12 ). This indicates that the MS-QMA output has prognostic value. 
     Example 9 
     Timing of Methylation Analysis 
     Data suggest that methylation assessment of the FREE2 (A) biomarkers using MS-QMA can be done at any time of life and that this produces similar result as at birth in both males and females ( FIG. 6 ). Specifically, it was found that for MS-QMA FREE2 (A) analysis: (i) there was no significant relationship between the age and AFU in males (n=76) and females (n=223) in  FIG. 2( i ) , comprising controls, PM and FM individuals with age range birth and 80 years (3); (ii) methylation values for both NBS and venous blood for FM male and females ( FIGS. 2( i ) and 3( i ) ) were significantly higher than methylation values for control and PM and healthy controls, and the positive, cognitive impairment threshold of 39 AFU; and the 39 AFU threshold separated FM individuals from PM and control groups as effectively in 500ng of DNA from venous blood as in cell extract from one 3 mm punch per sample from dried blood spots of adults and newborns; (iii) in five FM individuals the methylation values were almost identical for the repeated methylation measures taken at birth (NBS material) and at 15, 32, 35 and and 38 years of age (dried blood spot material), and was significantly higher than that for NB S material of male and female controls ( FIG. 6 ). Other FREE2 regions (e.g. FREE2 (B), FREE2 (C), FREE2 (D) and FREE2 (E)) as well as FREES may also be assayed. 
     It is also important to note that one female control NBS kept at room temperature for greater than 11 years, showed AFU greater than 39 threshold by ˜2 units, and two had AFU of 39. However, for NBS kept at room temperature for 3 years or less, all AFU are below this threshold. This suggests that there is small increase in AFU for NBS with age possibly due to increased DNA fragmentation/poor DNA quality. This, however, is not a significant limitation when comparing MS-QMA results between birth and time of consent, as most FM participants are children under 10 years of age. Methylation of FREE2 (A) region is highly conserved between tissues and cell types (Godler et al. (2010) supra), including post-mortem brains of FXS males with co-morbid autism. Hence, data suggest that the biomarker MS-QMA test has superior prognostic and diagnostic value in FMR1 expansion carriers too young to undergo formal neuropsychological testing. 
     Example 10 
     MS-QMA Analysis of Saliva and Venous Blood DNA for Detection of Sex Chromosome Aneuploidies 
     As shown herein, the threshold of 0.37 MR was the maximum value of the female healthy control range as well as the optimal for detection of FM females with performance IQ (PIQ) and full scale IQ (FSIQ) impairment (&lt;70). Using saliva DNA, 3 out of 57 sex chromosome aneuploidy samples showed MS-QMA MR above the 0.37 and 0.39 MR thresholds. These were XXY samples with apparently skewed X inactivation ( FIG. 8( i ) ). It is also of interest that the saliva DNA of the FXS affected males had MS-QMA MR values well above these thresholds, while for the PM/FM mosaic group one male showed an MR of 0.37. 
     For venous blood DNA, only samples with three or more copies of X-chromosome showed MS-QMA MR above 0.37 and 0.39 MR thresholds ( FIG. 8 ( ii )). The 47,XXX and 49,XXXXY groups showed MS-QMA MR significantly above those of female controls. As shown in  FIGS. 8 ( iii )- 8 ( v ), MS-QMA methylation was able to distinguish control males and females from individuals with Turners Syndrome (45,X), Triple X Syndrome and Jacob&#39;s Syndrome (47,XYY). 
     As expected, saliva and venous blood DNA samples with a Y chromosome according to previous laboratory testing also showed ˜1 copy of SRY, while samples with two or more copies of a Y chromosome showed SRY copy number between 1.5 and 2 ( FIGS. 8( i )  and  8 ( ii )). The only exception was one 45,X sample that consistently showed SRY/β-globin ratio above the positive threshold of 0.1. Because the Y chromosome was not detected using microarray analysis in this sample, this result may be either a false positive or a true positive where real-time PCR may be a more sensitive approach for detection of low level mosaicism. 
     Example 11 
     Detection of Skewed X-Inactivation and the Comparison with the EpiTYPER System 
     The relationship between X-inactivation and FREE2 MS-QMA MR is investigated in a larger sample than was previously analyzed with the EpiTYPER system. Despite the differences in assay design, the distribution of the MR values in venous blood DNA for both assays was almost identical in FM females. It showed clear skewing towards the unmethylated state from the distributions expected if the X-inactivation were random at this locus ( FIG. 9 ; bell shaped curve). For both assays, methylation in FM males was significantly elevated compared to that in FM females. The only difference between the two assays was in FM males where for the EpiTYPER system the methylation ratio was skewed towards 1, while the FREE2 MS-QMA MR was normally distributed in the same samples, with the top and bottom tails of distribution at ˜1 and 0.5. 
     Example 12 
     MS-QMA and the EpiTYPER System Analysis in Venous Blood and Saliva DNA, and Dried Blood Spots 
     When examining specific subgroups, in control males there was no significant correlation between methods regardless of the sample type, primarily because all of the male control samples were below the detection limit of the EpiTYPER system MR of 0.1. In female controls the two methods were significantly correlated in venous blood and saliva (p&lt;0.05), but not in dried blood spots ( FIG. 10  and Table 8). As expected, the highest correlation was observed in venous blood DNA and dried blood spots of FM males and females (P&lt;0.0001) possibly due to the greatest spread in methylation values. This significant relationship was consistent in the venous blood DNA of the PM/FM mosaic group, but was absent in female PM carriers. In saliva DNA of Klinefelter syndrome (47,XXY) individuals, the methylation ratio between the MS-QMA analysis and EpiTYPER reference method were also significantly correlated (p&lt;0.05). 
     Furthermore, the specific comparisons between MS-QMA and the EpiTYPER system in the control females ( FIG. 10 ) using dried blood spots of poor DNA quality, showed that MS-QMA did not identify false positives, and by this outperformed the EpiTYPER system. Specifically there were two outliers above the MALD-TOF MS threshold of 0.435 MOR, including one female control (Tassone et al. (2008) supra), these same samples had MR below 0.39 for the MS-QMA analysis. This suggests that MS-QMA would be more appropriate to avoid false positives in screening applications associated with low quantity and poor quality DNA. 
     
       
         
           
               
             
               
                 TABLE 8 
               
             
            
               
                   
               
               
                 Linear regression analysis between predictor FREE2 methylation assessed using MALDI-TOF 
               
               
                 MS and outcome MS-QMA) in venous blood DNA, Newborn and Dried Blood Spots (NBS and DBS) 
               
               
                 and saliva DNA. Note: blood spots stored for more than 10 years were not included in these analyses. 
               
            
           
           
               
               
               
               
            
               
                   
                 Venous Blood DNA 
                 NBS/DBS 
                 Saliva DNA 
               
            
           
           
               
               
               
               
               
               
               
               
               
               
            
               
                   
                 n 
                 Coef ± SE 
                 R 2   
                 n 
                 Coef ± SE 
                 R 2   
                 n 
                 Coef ± SE 
                 R 2   
               
               
                   
               
               
                 ALL 
                 433 
                   1.042 ± 0.013*** 
                 0.94 
                 239 
                   1.011 ± 0.020*** 
                 0.92 
                 97 
                   0.976 ± 0.046*** 
                 0.82 
               
               
                 samples 
                 132 
                   1.048 ± 0.014*** 
                 0.98 
                 124 
                   1.073 ± 0.016*** 
                 0.97 
                   
                   
                   
               
               
                 Males 
                 301 
                   0.982 ± 0.032*** 
                 0.75 
                 115 
                   0.650 ± 0.064*** 
                 0.48 
                   
                   
                   
               
               
                 Females 
                   
                   
                   
                   
                   
                   
                   
                   
                   
               
               
                 ♂ controls 
                  17 
                 0.125 ± 0.340 
                 0.01 
                  89 
                 −0.088 ± 0.236  
                 0.02 
                 13 
                 −0.500 ± 1.158  
                 0.02 
               
               
                 ♀ controls 
                  86 
                  0.256 ± 0.115* 
                 0.06 
                  83 
                 0.299 ± 0.100 
                 0.10 
                 26 
                  0.440 ± 0.208* 
                 0.16 
               
               
                 ♂ FM 
                  49 
                   0.559 ± 0.069*** 
                 0.58 
                  24 
                   0.941 ± 0.121*** 
                 0.73 
                 . . . 
                 . . . 
                 . . . 
               
               
                 ♀ FM 
                  95 
                   1.040 ± 0.073*** 
                 0.69 
                  24 
                  0.759 ± 0.260** 
                 0.28 
                 . . . 
                 . . . 
                 . . . 
               
               
                 ♂ PM/FM 
                  16 
                   0.998 ± 0.069*** 
                 0.94 
                 . . . 
                 . . . 
                 . . . 
                 . . . 
                 . . . 
                 . . . 
               
               
                 ♀ PM 
                 102 
                 0.185 ± 0.097 
                 0.04 
                 . . . 
                 . . . 
                 . . . 
                 . . . 
                 . . . 
                 . . . 
               
               
                 47, XXY 
                 . . . 
                 . . . 
                 . . . 
                 . . . 
                 . . . 
                 . . . 
                 47 
                  0.330 ± 0.130* 
                 0.12 
               
               
                   
               
               
                 N represents sample size; 
               
               
                 Coef. represents regression coefficient; 
               
               
                 SE represents standard errors; 
               
               
                 Note: 
               
               
                 Regression results are presented for groups with n &gt; 10; 
               
               
                 *P &lt;0.05; 
               
               
                 **P &lt;0.01; 
               
               
                 ***P &lt;0.001. 
               
            
           
         
       
     
     Example 13 
     Application of MS-QMA on Sample from Imprinting Disorders 
     Mammals inherit two complete sets of chromosomes, one from the father and one from the mother, and most autosomal genes are expressed from both maternal and paternal alleles. Imprinted genes show expression from only one member of the gene pair (allele) and gene expression is determined by the parent. Examples of imprinting disorders includes Beckwith-Wiedemann syndrome, Silver-Russell syndrome, Prader-Willi syndrome and Angelman syndrome. A methylation specific PCR test is available for the detection of Prader-Willi syndrome (PWS) and Angelman syndrome (AS) [Kubota et al. (1997) Nat Genet 16(1):16-17]. It is anticipated that the number of positive confirmed patients with these disorders will increase with the use of the MS-QMA assay, which gives a greater sensitivity and specificity. 
     Prader-Willi syndrome (PWS) and Angelman syndrome (AS) are two different neurological disorders caused by opposite defects in imprinting of the same chromosomal region 15q11-q13. The estimated frequencies in the general population of both PWS and AS are between 1 in 10,000 and 1 in 20,000. Ninety nine percent of all PWS cases are associated with detectable hypermethylation of the SNRPN gene promoter within the chromosomal region, while approximately 80% of AS cases have detectable hypomethylation of the same SNRPN locus. The hypermethylation in PWS is usually caused by absence of a paternally contributed allele that is unmethylated; while hypomethylation of AS is usually associated with absence of maternally contributed allele that is hypermethylated at the locus. In healthy control individuals not affected with AS or PWS, SNRPN gene promoter methylation is usually ˜50%, as they have one copy of paternally contributed and one copy of maternally contributed allele. 
     Primers were designed for the MS-QMA for the detection of PWS/AS using a similar region of the SNRPN gene used in the current diagnostic PCR assay (Kubota et al. (1997) supra). These are SEQ ID NOs:15 through 18 for targets SEQ ID NO:19 (SNRPN-M for AS) [Chr 15:25200039-252000212] and SEQ ID NO:20 (SNRPN-P for PWS) [Chr 15:25200068-252000167]. 
       FIG. 11  shows the results of MS-QMA spiking experiments of PWS and AS blood DNA samples mimicking mosaicism; as well as venous blood DNA of PWS, AS and healthy control individuals. From the figure it is evident that MS-QMA provides quantitative methylation assessment of SNRPN gene promoter, and can be used to differentiate pure PWS and AS, as well as PWS and AS artificially spiked mosaics from healthy controls. 
     Example 14 
     Serial Dilution After Bisulphite Conversions for MS-QMA 
     Serial dilutions after bisulphite conversions are required for maximum efficacy for MS-QMA and the linkage with clinical prognosis. Without serial dilution ( FIG. 7 ), not all samples may fall into the dynamic range of DNA control 1. This is demonstrated by the red dots in  FIG. 7  which correspond to only one dilution and these samples do not correlate to the clinical prognosis. These samples are inconsistent with both the clinical prognosis and the expected level of methylation. A filter process is used to ensure the greatest correlation with clinical prognosis and quantitation of the methylated DNA. An example of this filter is as follows: if the DNA concentration is not in the dynamic range and greater than two standard deviations from the mean, the data generated from this sample (which includes methylation data) are not use for further analysis. The mean is re-calculated for the remaining samples without the outlier and this mean value is used to determine the quantitative methylation result. 
     The MS-QMA methylation assay has significant potential for use in newborn FXS screening as there has been no test available that is suitably sensitive in males and females, is high throughput and low cost. The benefits of identifying most male and female probands early are improved clinical management, identification of other carriers through cascade testing and the provision of this information for reproductive planning. As part of the ls t  NBS screen, the 0.39 threshold should be used followed by second line testing that would involve CGG sizing, and this would confirm that all positives carry a FM alleles. This may present a better alternative to using CGG sizing as a first line test in newborns or very young children, because detection of PM alleles that have been associated with late onset disorders (Godler et al. (2010) supra; Hagerman and Hagerman,  Nat Clin Pract Neurol  3:107-112), would raise the ethical issue of pre-symptomatic testing for currently untreatable and non-preventable disorders with incomplete penetrance (Bailey et al. (2009) J Pediatr Psychol 34:648-661). Furthermore, detection of the relatively common GZ and PM alleles which do not cause FXS at population wide level, would require large scale genetic counselling follow-up, which have significant add-on cost-benefit implications. 
     In the diagnostic context, MS-QMA can be easily combined with several PCR based approaches recently developed to reliably amplify PM and small FM alleles (Tassone et al. (2008) supra; Filipovic-Sadic et al. supra; Hantash et al. supra; . MS-QMA methylation values could be used to accurately separate most high end unmethylated PM from low end methylated FM alleles, and may in the future provide prognostic information from quantitative methylation data in both males and females. This could remove the need for the cumbersome Southern blot and identify all categories of expanded alleles. 
     Example 15 
     Correlation with Cognitive Sub-Scores in FM Females 
     In a sub-group of 20 FM females for whom a set of IQ subscales was available, subtest-scores and indices available, it was found that MS-QMA MR strongly correlated with subtest scores representing different aspects of VIQ. Arithmetic subtest scores (Working Memory Index) which largely rely on working memory and attention, and the Information subtest scores (Verbal Comprehension Index) which examine general knowledge stood out as the subtest scores most strongly correlated with MS-QMA MR (p&lt;0.01). 
     It is also of interest to note, that most FM and all PM females that were within the MS-QMA borderline range 0.39 to 0.41, were high functioning (VIQ&gt;70). This, however, does not rule out other forms of FXS related impairment that may be identified using more subtle measures of cognitive function, such as the sub-scores and indexes of IQ, or measures of behavioral impairment such as ADOS-G. 
     Hence, described herein for venous blood DNA, in the PM and FM females for the age range examined in this study, MS-QMA has high sensitivity if the aim is not to identify all FM females, but to identify only those likely to have a low verbal IQ (&lt;70). However, in newborn blood spots, MS-QMA is likely to have another application if used within the 1 st  year of life, which is identification of more than 90% of all FM males and females. This is superior to the comparator EpiTYPER system that target the same sites as MS-QMA, but cannot analyze some of these because their fragments are too large for MALDI-TOF MS based assessment (Tost and Gut (2012) DNA methylation analysis by maldi mass spectrometry: Wiley-VCH Verlag GmbH &amp; Co. KGaA:3-34). Other advantages of MS-QMA analysis are: (i) flexibility for both quantitative (as in the case of standard HRM) and qualitative (as in the case of the EpiTYPER System) assessment; (ii) automated detection of DNA concentration in the samples post conversion; (iii) incorporation of inbuilt PCR amplification quality control measures and associated automated data cleaning; and (iv) reduced time to obtain the methylation ratio—6 to 9.5 hours for MS-QMA including the bisulfite conversion compared with 48 to 72 hours for the EpiTYPER system. Furthermore, MS-QMA is an automated method that does not require specialized proprietary equipment and extensive training. It uses standard HRM reagents and standard real-time PCR machines that cost up to one third of that of MALDI-TOF MS and pyrosequencing based chemistries and equipment, and for these reasons the likelihood may be high for its widespread uptake into practice as a screening tool for both research and diagnostic applications. 
     In this study, it is demonstrated that FREE2 MS-QMA can identify most sex chromosome aneuploidies and detect both locus-specific skewing towards the hypomethylated state, as is apparent in FM females, and skewed X inactivation towards the hypermethylated state for the whole X-chromosome, as with sex chromosome aneuploidies with three of more X-chromosomes. The performance of MS-QMA was assessed using the same sample set for detection of these abnormalities. It was found that similar to the EpiTYPER system, when combined with the SRY analysis at the MR threshold of 0.1, MS-QMA identified sex chromosome aneuploidies with specificity and sensitivity approaching 100%. However, without the SRY analysis and at the VIQ threshold of 0.39 MR, MS-QMA could not detect the vast majority of sex chromosome aneuploidies using either venous blood or saliva DNA. 
     In the FMR1 locus specific context, as with EpiTYPER system results, the MS-QMA MR control range was lower than the expected value of 0.5, with ˜0.4 being the maximum control value. The test also showed clear skewing towards the unmethylated state from the distributions expected if the X-inactivation were random in FM females at this locus. Specifically, if the X-inactivation were random, one would expect the higher tail of the MR distribution to be at 1, representing all cells having the normal size allele on the inactive X and the methylated FM allele on the active X. The lower tail of the distribution would then be 0.5 MR with all cells having the FM alleles on the inactive X and normal cell alleles on the active X. In contrast, the upper tail for both the MS-QMA and EpiTYPER system results was at ˜0.7 MR with the lower tail at ˜0. 2MR, demonstrating skewing towards the unmethylated state. Because in FM males more than half of the samples showed MR values between 0.7 and 1 MR using either method , the lack of any FM female results with MR values above 0.7 cannot be considered to be a result of technical bias associated with the MS-QMA assay. 
     It is also interesting to note that for FM males with 100% methylation at the FMR1 CpG island (shown on Southern blot), both MS-QMA and the EpiTYPER system find methylation of FMR1 intron 1 between 60% and 100%. This suggests that methylation mosaicism between different CpG sites in FM males maybe more common than previously thought, and this may relate to the wide spectrum of clinical phenotype (other than severe cognitive impairment) found in FM males. 
     There are a number of published HRM based methods developed for quantitative methylation analysis developed for locus specific (Snell et al. (2008)  Breast Cancer Res / 0:R12; Kristensen et al. (2008)  Nucleic Acids Res  36:e42; Candiloro et al. (2011) Epigenetics 6:500-507; Malentacchi et al. (2009)  Nucleic Acids Res  37:e86) or genome wide (Newman et al. (2012)  Epigenetics  7:92-105) applications, each with advantages and limitations for their specific applications. However, one common feature between all of these is use of methylation standards generated from unmethylated samples spiked at different ratios with artificially methylated DNA. An important distinction between these methods and MS-QMA is that MS-QMA uses a real-time PCR based internal filter process on serially diluted bisulfite conversions to ‘clean’ the data prior to a methylation value being derived. This filter process is essential for the applications described in this study, particularly for the intermediate methylation range this was not performed in previously described quantitative HRM methods, which were primarily developed for assessments in the low methylation range in cancer diagnostics Snell et al. (2008) supra; Kristensen et al. (2008) supra; Candiloro et al. (2011) supra; Malentacchi et al. (2009) supra). The lack of a filtering/quality control process post-conversion could also be also the reason why quantitative HRM has had limited utility with poor quality DNA samples (Pichler et al. (2009)  JMD  11;140-147). For poor DNA quality samples these methods have been largely restricted to formalin fixed paraffin embedded tissue samples (Balic et al. (2009)  JMD  11:102-108); none have been described for quantitative methylation analysis using crude extracts from adult and newborn blood spots or saliva DNA of poor quality as described here. 
     Comparison of quantitative HRM to pyrosequencing has been made in assessment of methylation of APC and CDKN2A genes (Migheli et al. (2013)  PLoS One  8:e52501). As with the previous application of HRM in FXS testing (Elias et al. (2011) supra), mixtures of methylated and unmethylated DNA were used as standards. While the derived methylation results for both APC and CDKN2A in the clinical test samples was highly consistent with the pyrosequencing results at low methylation levels (˜0 to 30%), HRM based quantification overestimated methylation by as much as 20% in the 30 to 60% methylation range, as compared to pyrosequencing. 
     To overcome this technical limitation of quantitative HRM for detection of FXS females, inter- and intra-run methylation ratio variation has to be ˜5% in the methylation range between 30 and 60%. This is achieved using a quality control filter process involving quantitative real-time PCR analysis of serial dilutions after bisulphite conversion. 
     Hence, demonstrated herein is the immediate applications of MS-QMA for detection of sex chromosome aneuploidies and X-inactivation at the FMR1 locus. However, the method has potential for any application where quantitative detection of even small changes in the genomic position and the amount of locus specific methylation that of diagnostic or prognostic significance due to mosaicism in the methylation state within and between different cell types (Godler et al. (2013) supra). These may include monogenic disorders such as Rett Syndrome (Signorini et al (2013).  PLoS One  8:e56599), trinucleotide disorders such as Friedreich ataxia and myotonic dystrophy, imprinting disorders such as Angelman, Prader-Willi and Beckwith-Weidemann Syndromes, disorders related to more general skewed X-inactivation, as well as somatic genetic disorders such as cancer. 
     Those skilled in the art will appreciate that the disclosure described herein is susceptible to variations and modifications other than those specifically described. It is to be understood that the disclosure contemplates all such variations and modifications. The disclosure also enables all of the steps, features, compositions and compounds referred to or indicated in this specification, individually or collectively, and any and all combinations of any two or more of the steps or features or compositions or compounds. 
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