Abstract:
Alzheimer&#39;s disease, the most common cause of dementia in older individuals, is a debilitating neurodegenerative disease for which there is currently no cure. In the past, AD could only be definitively diagnosed by brain biopsy or upon autopsy after a patient died. These methods, which demonstrate the presence of the characteristic plaque and tangle lesions in the brain, are still considered the gold standard for the pathological diagnoses of AD. However, in the clinical setting brain biopsy is rarely performed and diagnosis depends on a battery of neurological, psychometric and biochemical tests, including the measurement of biochemical markers such as the ApoE and tau proteins or the beta-amyloid peptide in cerebrospinal fluid and blood. The present invention discloses and describes panels of makers that are differentially expressed in the disease state relative to their expression in the normal state and, in particular, identifies and describes panels of makers associated with neurocognitive disorders. Such biomarker panel might have considerable value in triaging patients with early memory disorders to yet more specific but more invasive and costly approaches such as molecular markers in CSF and on PET imaging in clinical trials and possibly in clinical practice.

Description:
FIELD OF THE INVENTION 
       [0001]    The present invention relates to panels of markers that are differentially expressed in neurocognitive disorders, such as 
         [0002]    Alzheimer&#39;s disease, relative to the normal state. Further, the present invention provides methods of progression, prognosis and diagnosis of neurocognitive disorders using the panels of markers. Still further, the present invention provides methods for the identification of agents for the prevention and treatment of neurocognitive disorders using the panels of markers. 
       BACKGROUND OF THE INVENTION 
       [0003]    Dementia is one of the major public health problems of the elderly, and in our ageing populations the increasing numbers of patients with dementia is imposing a major financial burden on health systems around the world. More than half of the patients with dementia have Alzheimer&#39;s disease (AD). The prevalence and incidence of AD have been shown to increase exponentially. The prevalence for AD in Europe is 0.3% for ages 60-69 years, 3.2% for ages 70-79 years, and 10.8% for ages 80-89 years. The survival time after the onset of AD is approximately from 5 to 12 years. 
         [0004]    AD is the most common neurodegenerative disorder of the aging population; usually affecting people over the age of 65 years and resulting in a relentlessly progressive decline in cognition and function. Currently there is no cure. It destroys neurons in parts of the brain, chiefly the hippocampus, which is a region involved in coding memories. Alzheimer&#39;s disease gives rise to an irreversible progressive loss of cognitive functions and of functional autonomy. 
         [0005]    The earliest signs of AD may be mistaken for simple forgetfulness, but in those who are eventually diagnosed with the disease, these initial signs inexorably progress to more severe symptoms of mental deterioration. While the time it takes for AD to develop will vary from person to person, advanced signs include severe memory impairment, confusion, language disturbances, personality and behaviour changes, and impaired judgement. Patients with AD may become non-communicative and hostile. As the disease ends its course in profound dementia, patients are unable to care for themselves and often require institutionalisation or professional care in the home setting. While some patients may live for many years after being diagnosed with AD, the average life expectancy after diagnosis is eight years. 
         [0006]    In the past, AD could only be definitively diagnosed by brain biopsy or upon autopsy after a patient died. These methods, which demonstrate the presence of the characteristic plaque and tangle lesions in the brain, are still considered the gold standard for the pathological diagnoses of AD. However, in the clinical setting brain biopsy is rarely performed and diagnosis depends on a battery of neurological, psychometric and biochemical tests, including the measurement of biochemical markers such as the ApoE and tau proteins or the beta-amyloid peptide in cerebrospinal fluid and blood. 
         [0007]    Biomarkers may possibly possess the key in the next step for diagnosing AD and other dementias. A marker that fulfils the requirements for the diagnostic test for AD would have several advantages. An ideal marker would be one that identifies AD cases at a very early stage of the disease, before there is degeneration observed in the brain imaging and neuropathological tests. A biomarker could be the first indicator for starting treatment as early as possible, and also very valuable in screening the effectiveness of new therapies, particularly those that are focused on preventing the development of neuropathological changes. A marker would also be useful in the follow-up of the development of the disease. 
         [0008]    Markers related to pathological characteristics of AD such as plaques and tangles (Aβ and tau respectively) have been the most extensively studied. The most promising has been from studies of cerebrospinal fluid (CSF) concentration of the polypeptide fragments Aβ (1-40), Aβ (1-42) and tau or the combination of both proteins in AD. Many studies have reported a decrease in Aβ (1-42) in CSF, while the total Aβ protein or Aβ (1-40) concentration remain unchanged. 
         [0009]    Recognising that CSF samples are less desirable, there have been several efforts to identify protein markers in blood and blood products, such as serum and plasma. A group of such blood proteins that are differentially expressed in the AD state relative to their expression in the normal state are described in WO2006/035237. Whilst these proteins are proving useful in the development of new diagnostic and prognostic tests there remains a need for the discovery and validation of further panels of markers that may perform with superior sensitivity and/or specificity in the diagnosis and prognostic monitoring of patients with Alzheimer&#39;s disease and related dementias. 
       SUMMARY OF THE INVENTION 
       [0010]    Accordingly, in a first aspect, the present invention provides for a biomarker panel consisting essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG) Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT). 
         [0011]    In one embodiment, the panel further comprises markers regulated on activation, normal T cell expressed and secreted (RANTES) and Apolipoprotein C-III (ApoC3). 
         [0012]    The panel may further comprise markers plasminogen activator inhibitor type 1 (PAI-1), C-reactive protein (CRP), Cathepsin D (CTSD) and apolipoprotein E (ApoE) and optionally, the panel may further comprise one or more of markers selected from the group consisting of alpha-2-macroglobulin (A2M), serum amyloid P component (SAP), advanced glycosylation end product-specific receptor (sRAGE), Neuron specific enolase (NSE), complement factor H (CFH), amyloid beta (A4) precursor protein (AB40 or Aβ40), Ceruloplasmin, neural cell adhesion molecule (NCAM), ApoA1, Abeta 42, BDNF, Beta-2-microglobulin (B2M), and VCAM-1. 
         [0013]    In a further embodiment, the biomarker panel may further comprises ApoE ε4 allele presence (ApoE genotype). 
         [0014]    In a second aspect, the present invention provides for a method for determining the progression and/or the prognosis of a neurocognitive disorder in a subject, the method comprising detecting markers of a biomarker panel as defined herein in a tissue sample and/or body fluid sample obtained from said subject. 
         [0015]    In one embodiment of this second aspect the method comprises:
       a) providing a tissue sample or body fluid sample obtained from said subject having a neurocognitive disorder or symptoms thereof at a test time point;   b) determining the amount or concentration of said markers of the biomarker panel as defined herein;   c) comparing the amount or concentration of said markers of the biomarker panel in the sample at the test time point with reference values;       
 
         [0019]    wherein the test time point corresponds to time when the progression and/or prognostic method is carried out; and wherein the amount or concentration of said proteins in said sample is indicative of the progression and/or prognosis of the neurocognitive disorder in said subject. 
         [0020]    Preferably, the amount or concentration of said markers in said sample is indicative of the progression and/or prognosis of the neurocognitive disease and/or the nature or degree of the neurocognitive disorder is determined. 
         [0021]    The neurocognitive disorder may be mild cognitive impairment (MCI), Alzheimer&#39;s disease (AD), vascular dementia, dementia with lewy bodies, fronto-temporal dementia or any combinations thereof. 
         [0022]    Preferably, the neurocognitive disorder is MCI or AD and the progression and/prognosis of the neurocognitive disease is the progression and/or prognosis of MCI or AD or the progression of the neurocognitive disorder is the conversion from MCI to AD. 
         [0023]    More preferably, the conversion is determined over 12 months or less. 
         [0024]    In a third aspect according to the invention there is provided method of diagnosing or assessing a neurocognitive disorder in a subject comprising detecting markers of a biomarker panel as defined herein in a tissue sample and/or body fluid sample obtained from said subject. 
         [0025]    In one embodiment of this third aspect the method comprises:
       a) providing a tissue sample or body fluid sample obtained from said subject having a neurocognitive disorder or symptoms thereof at a test time point;   b) determining the amount or concentration of said markers of the biomarker panel as defined herein;   c) comparing the amount or concentration of said markers of the biomarker panel in the sample with reference values;       
 
         [0029]    wherein the test time point corresponds to time when the method of diagnosing is carried out; and wherein the amount or concentration of said markers in said sample is indicative of the presence or absence of the neurocognitive disorder in said subject. 
         [0030]    Preferably, the amount or concentration of said markers in said sample is indicative of the neurocognitive disorder and/or the nature or degree of the neurocognitive disorder is determined. 
         [0031]    The neurocognitive disorder may be mild cognitive impairment (MCI), Alzheimer&#39;s disease (AD), vascular dementia, dementia with lewy bodies, fronto-temporal dementia or any combinations thereof. 
         [0032]    Preferably, the neurocognitive disorder is MCI or AD. 
         [0033]    In one embodiment of this method, a change in the amount or concentration of said proteins in said sample is indicative of the progression to AD in a subject having MCI, wherein the progression from MCI to AD occurs over a period of 12 months or less. 
         [0034]    In another embodiment, a change in the amount or concentration of said markers in said sample is indicative of the presence or extent of brain atrophy in said subject. 
         [0035]    In yet another embodiment, the amount or concentration of said markers of the biomarker panel in the sample taken from a subject with a neurocognitive disorder are used to predict the most appropriate and effective therapy to alleviate the neurocognitive disorder and to monitor the success of that therapy. 
         [0036]    In another embodiment, the markers of said biomarker panel are detected by a) using one or more binding agents to each said markers, or b) by detecting in the sample autoantibodies specific to each of said markers, or c) by mass spectrometry, or any combinations of a), b) and c). Preferably, the sample is immobilised on a solid support. 
         [0037]    In yet another embodiment, the markers of the biomarker panel are detected using 2D gel electrophoresis. 
         [0038]    In a fourth aspect, the present invention provides for a method of screening an agent for treating a neurocognitive disorder, the method comprising:
       (a) providing a tissue sample or body fluid sample obtained from, or representative of, a subject having a neurocognitive disorder or symptoms thereof, wherein the subject and/or the sample has been treated with the agent being screened,   (b) determining the amount or concentration in the sample from, or representative of, the treated subject and/or sample of markers of a biomarker panel as defined herein; and   (c) determining whether the agent affects the amount or concentration of the markers of the biomarker panel in the treated subject and/or sample.       
 
         [0042]    In one embodiment of this fourth aspect the amount or concentration of the markers of the biomarker panel in a subject treated with the agent compared to a subject not treated with the agent is indicative that the agent may be useful in treating a neurocognitive disorder. 
         [0043]    In another embodiment, the method further comprises, prior to step (a), the step of determining the concentration or amount of the markers of the biomarker panel in one or more control samples from healthy individuals, patients having a neurocognitive disorder of differing severity or progression and patients having a neurocognitive disorder not treated with the agent. 
         [0044]    In yet another embodiment, the agent is selected if prevents or slows the change over time of the amount or concentration of the markers of the biomarker panel relative to controls. 
         [0045]    In a further embodiment the amount or concentration of said markers of the biomarker panel is determined in samples obtained from, or representative of:
       (a) normal subjects and subjects having neurocognitive disorder symptoms; and/or,   (b) subjects with neurocognitive disorder symptoms which have not been treated with the agent and subjects with neurocognitive disorder symptoms which have been treated with the agent.       
 
         [0048]    Preferably the subjects having neurocognitive disorder or symptoms thereof are human subjects with the neurocognitive disorder or a non-human animal model of the neurocognitive disorder. More preferably the neurocognitive disorder is AD. 
         [0049]    In some embodiments the subjects are mutant amyloid precursor protein (APP) transgenic mice, presenilin-1 (PS-1) transgenic mice, double transgenic APP/PS-1 transgenic mice and/or glycogen synthase kinase transgenic mice, and the normal subjects are wild-type mice. 
         [0050]    In the embodiments of the methods according to the invention the tissue or body fluid samples are preferably urine, blood, plasma, serum, saliva or cerebro-spinal fluid samples. 
         [0051]    In a fifth aspect, the present invention provides for a kit comprising reagents for the detection of markers of a biomarker panel in a tissue sample or body fluid sample, wherein said biomarker panel is as defined herein. 
         [0052]    In one embodiment the kit further comprises one or more binding agents which specifically bind to the markers of the biomarker panels. 
         [0053]    Preferably, the one or more binding agent are primary antibodies, wherein each primary antibody specifically binds to a different markers of the biomarker panel and more preferably, the kit further comprises one or more secondary antibodies which specifically bind to the primary antibodies. 
         [0054]    Optionally, the secondary antibodies are labeled. 
         [0055]    In another embodiment the kit further comprises control samples of the markers on the biomarker panel. 
     
    
     DETAILED DESCRIPTION 
     Definitions 
       [0056]    The term “neurocognitive disorders” is used herein as a synonym of “neurocognitive diseases” and includes, but is not limited to, Alzheimer&#39;s Disease (AD) which is the main representative example of all related dementias and neurocognitive disorders. References to AD may therefore be equally taken as references to Mild Cognitive Impairment (MCI) (a recognised precursor to AD) and other late onset dementias including vascular dementia, dementia with lewy bodies and fronto-temporal dementia, alone and as a mixed dementia with 
         [0057]    Alzheimer&#39;s disease, unless it is explicitly specified the progression between MCI and AD. It may also refer to a specific diagnosis given to a subject or it may also include symptoms of that neurocognitive disorders where a specific diagnosis has not been yet formalised by a medical practitioner according to the present clinical assessment measures. Currently, the disease status is assessed by duration of disease from inception to present (longer duration equals more severe disease) and clinical assessment measures. These assessment measures include clinical tests for memory and other cognitions, clinical tests for function (abilities of daily living) and clinical assessments of global severity. Trials of potential therapies in AD and other dementias and neurocognitive disorders are currently evaluated against these measures. The FDA and other regulatory authorities require as part of these assessments measures of both cognition and global function. The Global Dementia Scale is one such measure of global function. It is assessed by assessment of severity including cognition and function against a standardised set of severity criteria. 
         [0058]    The term “biomarkers panel” is used herein interchangeably with the term “marker panel” and includes all biologically relevant forms of the protein identified, including post-translational modifications. For example, the protein in the biomarkers panel can be present in a glycosylated, phosphorylated, multimeric, fragmented or precursor form. It further includes deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) products resulting from the gene codifying such proteins, such as cDNA, mRNA and fragments thereof. 
         [0059]    The term “relevant tissue” means any tissue involved in brain function, in particular tissue which is affected in AD. 
         [0060]    The terms “tissue or body fluid sample” or “representative of a tissue or body fluid sample” mean any tissue or body fluid in which the detection of the markers can be carried out and includes, for example, blood, serum, plasma, CSF, a primary cell culture or a biopsy from the relevant tissue. 
         [0061]    The term “subjects” includes human and non-human animal subjects. 
         [0062]    The term “differential expression”, as used herein, refers to both qualitative and quantitative differences in markers&#39; transcription and/or expression and indicates that a marker may be present at different levels in samples from normal and diseased subjects. The term further refers to at least one recognisable difference of marker expression in a tissue or body fluid sample. It may be a quantitatively measurable, semi-quantitatively estimable or a qualitatively detectable difference of marker expression in tissue or body fluid sample. 
         [0063]    The term “differentially expressed marker”(or DEM) refers to a marker which may be strongly expressed in tissues or body fluids in the normal state and less strongly expressed or not expressed at all in tissues in AD. Conversely, it may be strongly expressed in tissues in AD and less strongly expressed or not expressed at all in normal samples. Further, expression may be regarded as differential if the marker undergoes any recognisable change between the samples under comparison. 
         [0064]    The term differentially expressed markers (DEMs) includes “fingerprint proteins”, “target proteins” or “pathway proteins”. 
         [0065]    “Fingerprint protein”, as used herein, means a DEM, the expression of which can be used, alone or together with other DEMs, to monitor or assess the condition of a patient suspected of suffering from AD. Since these proteins will normally be used in combination, especially a combination of four or more, they are conveniently termed “fingerprint proteins”, without prejudice to the possibility that on occasions they may be used singly or along with only one or two other proteins for this purpose. Such a fingerprint protein or proteins can be used, for example, to diagnose a particular type of AD and hence to indicate a specific treatment for it. 
         [0066]    “Target protein”, as used herein, means a DEP, the level or activity of which can be modulated by treatment to alleviate AD or other dementias and neurocognitive disorders. Modulation of the level or activity of the target protein in a patient may be achieved, for example, by administering the target protein, another protein or gene which interacts with it or an agent which counteracts or reduces it, for example an antibody to the protein, competitive inhibitor of the protein or an agent which acts in the process of transcription or translation of the corresponding gene. 
         [0067]    “Pathway protein”, as used herein, means proteins that can interact with at least one other protein or with a gene involved in the regulation of brain function. The term is for the protein with which the DEP interacts, not to the DEP itself, although a pathway protein can be another DEP. 
         [0068]    It is further contemplated herein that a “fingerprint protein” may also be a “target protein” or a “pathway protein” and vice versa. 
         [0069]    The term “detectable”, as used herein, refers to a marker transcription and/or expression pattern, which are detectable using techniques described herein. 
         [0070]    The term “control” refers to a tissue sample or a bodily fluid sample taken from a human or non-human subject not diagnosed or not presenting any symptoms of a neurocognitive disorder or disease. 
         [0071]    The term “isolated” means throughout this specification, that the marker, antibody or polynucleotide, as the case may be, exists in a physical milieu distinct from that in which it may occur in nature. 
         [0072]    The term “treat”, “treating”, “treatment”, “prevent”, “preventing” “prevention” or “alleviation” includes therapeutic treatments, prophylactic treatments and applications in which one reduces the risk that a subject will develop a disorder or other risk factors. Treatment does not require the complete curing of a disorder and encompasses the reduction of one or more symptoms or underlying risk factors. Treatment may also include slowing down the progression of the disease and may comprise the administration of one or more drugs or foodstuffs, and/or other factors such as diet or exercise. 
         [0073]    The term “diagnosis”, as used herein, includes the provision of any information concerning the existence or presence, non-existence or absence or probability of the disorder in a patient. It further includes the provision of information concerning the type or classification of the disorder or of symptoms which are or may be experienced in connection with it. This may include, for example, diagnosis of the severity of the disorder. It encompasses prognosis of the medical course of the disorder, for example its duration, severity and the course of progression from MCI to AD or other dementias. 
         [0074]    The term “efficacy” indicates the capacity for beneficial change of a given intervention (e.g. a drug, medical device, surgical procedure, etc.). If efficacy is established, that intervention is likely to be at least as good as other available interventions, to which it will have been compared. The term “efficacy” and “effectiveness” are used herein interchangeably. 
         [0075]    The term “comprising” indicates that the subject includes all the elements listed, but may, optionally, also include additional, unnamed elements (i.e. open). 
         [0076]    The term “and/or” where used herein is to be taken as specific disclosure of each of the two specified features or components with or without the other. For example “A and/or B” is to be taken as specific disclosure of each of (i) A, (ii) B and (iii) A and B, just as if each is set out individually herein. 
         [0077]    Unless the context dictates otherwise, the definitions of the features/terms set out above are not limited to any particular aspect or embodiment of the invention and apply equally to all aspects and embodiments which are described herein. 
       Biomarker Panels and Methods of Using Thereof 
       [0078]    The present invention relates to biomarkers panels of markers that are differentially expressed in neurocognitive disorders, such as MCI and AD, relative to each other and/or their expression in the normal state. These panels allow for the improved detection and assessment of neurocognitive disorders. 
         [0079]    The biomarker panel according to the invention consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT). 
         [0080]    The biomarker panel may further comprise markers regulated on activation, normal T cell expressed and secreted (RANTES) and Apolipoprotein C-III (ApoC3). 
         [0081]    The biomarker panel may also further comprises markers plasminogen activator inhibitor type 1 (PAI-1), C-reactive protein (CRP), Cathepsin D (CTSD) and apolipoprotein E (ApoE). 
         [0082]    In addition, the biomarker panel may further comprise one or more of markers selected from the group consisting of alpha-2-macroglobulin (A2M), serum amyloid P component (SAP), advanced glycosylation end product-specific receptor (sRAGE), Neuron specific enolase (NSE), complement factor H (CFH), amyloid beta (A4) precursor protein (AB40 or Aβ40), Ceruloplasmin, neural cell adhesion molecule (NCAM), ApoA1, Abeta 42, BDNF, Beta-2-microglobulin (B2M), and VCAM-1. 
         [0083]    In one embodiment the biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT), optionally in combination with ApoE ε4 allele presence (ApoE genotype). The ApoE ε4 allele presence includes both the genetic presence of the ε4 allele, detectable as a genetic marker, as well as the protein presence of the specific ApoE E4 (S112R and H158R). 
         [0084]    In another embodiment the biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT), wherein the biomarker panel further comprises regulated on activation, normal T cell expressed and/or secreted (RANTES) and Apolipoprotein C-III (ApoC3), optionally in combination with ApoE ε4 allele presence (ApoE genotype). 
         [0085]    In yet another embodiment the biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT), regulated on activation, normal T cell expressed and secreted (RANTES) and Apolipoprotein C-III (ApoC3), wherein the biomarker panel further comprises one or more of markers selected from the group of plasminogen activator inhibitor type 1 (PAI-1), C-reactive protein (CRP), Cathepsin D (CTSD) and apolipoprotein E (ApoE), optionally in combination with ApoE ε4 allele presence (ApoE genotype). 
         [0086]    In a further embodiment the biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT), regulated on activation, normal T cell expressed secreted (RANTES), Apolipoprotein C-III (ApoC3), plasminogen activator inhibitor type 1 (PAI-1), C-reactive protein (CRP), Cathepsin D (CTSD) and apolipoprotein E (ApoE), wherein the biomarker panel further comprises one or more of markers selected from the group of alpha-2-macroglobulin (A2M), serum amyloid P component (SAP), advanced glycosylation end product-specific receptor (sRAGE), Neuron specific enolase (NSE), complement factor H (CFH), amyloid beta (A4) precursor protein (AB40 or Aβ40), Ceruloplasmin, neural cell adhesion molecule (NCAM), ApoA1, Abeta 42, BDNF, Beta-2-microglobulin (B2M), and VCAM-1, optionally in combination with ApoE ε4 allele presence (ApoE genotype). 
         [0087]    The proteins in the biomarker panel according to the invention are indicated in Table 1A below. 
         [0000]    
       
         
               
             
               
               
               
               
               
             
           
               
                 TABLE 1A 
               
             
             
               
                   
               
               
                 Overview of proteins investigated in the current study 
               
             
          
           
               
                   
                   
                   
                 Reported 
                   
               
               
                 Protein Name 
                 Method 
                 Study design 
                 findings 
                 References 
               
               
                   
               
               
                 Alpha-2- 
                 2-DGE; LC-MS/MS 
                 AD v Control 
                 ↑ AD 
                 Hye et al. 2006 
               
               
                 macroglobulin 
               
               
                 (A2M) 
               
               
                 Serum amyloid 
                 2-DGE; LC-MS/MS 
                 AD v Control 
                 ↑ AD 
                 Hye et al. 2006 
               
               
                 P component 
               
               
                 (SAP) 
               
               
                 Complement 
                 2-DGE; LC-MS/MS 
                 AD v Control 
                 ↑ AD 
                 Hye et al. 2006; 
               
               
                 factor H (CFH) 
                   
                   
                   
                 Cutler et al. 2008 
               
               
                 Complement C4 
                 2-DGE; LC-MS/MS 
                 AD v Control 
                 ↓ AD 
                 Hye et al. 2006 
               
               
                 (CC4) 
               
               
                 Apolipoprotein 
                 2-DGE; LC-MS/MS 
                 PiB PET association 
                 ↑ Aβ brain 
                 Thambisetty et al. 2010 
               
               
                 E (ApoE) 
                 and ELISA 
                   
                 region 
               
               
                 Clusterin 
                 2-DGE; LC-MS/MS 
                 Low v high brain 
                 ↑ High atrophy 
                 Thambisetty et al. 2011 
               
               
                   
                 and ELISA 
                 atrophy 
               
               
                 Apolipoprotein 
                 2-DGE; LC-MS/MS 
                 SCD v FCD 
                 ↑ FCD 
                 Thambisetty et al. 2011 
               
               
                 (ApoA1) 
               
               
                 Transthyretin 
                 2-DGE; LC-MS/MS 
                 SCD v FCD 
                 ↓ FCD 
                 Velayudhan et al. 2012 
               
               
                 (TTR) 
                 and ELISA 
               
               
                 Ceruloplasmin 
                 2-DGE; LC-MS/MS 
                 AD v Control 
                 ↓ AD 
                 Hye et al. 2006 
               
               
                 Amyloid beta 
                 ELISA 
                 AD v Control 
                 ↑ AD 
                 Mehta et al. 2001, 
               
               
                 (A4) precursor 
                   
                   
                   
                 Mayeux et al. 2003 
               
               
                 protein (AB 40) 
               
               
                 (Aβ40) 
               
               
                 Amyloid beta 
                 ELISA 
                 AD v Control 
                 ↓ AD 
                 Hampel et al. 2010, 
               
               
                 protein 1-42 
                   
                   
                   
                 Blennow et al. 2001 
               
               
                 fragment 
               
               
                 (Abeta 42) 
               
               
                 Alpha-1- 
                 ELISA 
                 AD v Control 
                 ↓ AD 
                 Roher et al. 2010 
               
               
                 Acid 
               
               
                 Glycoprotein 
               
               
                 (A1AcidG) 
               
               
                 Alpha1 
                 ELISA 
                 AD v Control 
                 ↑ AD 
                 Nielsen et al. 2007; 
               
               
                 antitrypsin 
                   
                   
                   
                 Sun et al. 2003 
               
               
                 (A1AT) 
               
               
                 Apolipoprotein 
                 Luminex 
                 ε4 carrier v non- 
                 ↓ AD 
                 Song et al. 2012 
               
               
                 C-III (Apo C3) 
                   
                 carrier 
               
               
                 Brain Derived 
                 ELISA 
                 MRI association 
                 ↑ Age related 
                 Driscoll et al. 2011 
               
               
                 neurotrophic 
                   
                   
                 white atrophy 
               
               
                 factor (BDNF) 
                 ELISA 
                 AD v Control 
                 ↓ AD 
                 Aisa et al. 2010 
               
               
                   
                 ELISA 
                 AD v Control 
                 ↓ AD 
                 Laske et. 2006 
               
               
                 Beta-2- 
                 Luminex 
                   
                 ↑ AD 
                 Wilson et al. 2012 
               
               
                 microglobulin 
               
               
                 Cathepsin D 
                 Western blot 
                 AD v Control 
                 ↓ AD 
                 Urbanelli et al. 2008 
               
               
                 C-reactive 
                 Nephalometric 
                 SCD v FCD 
                 ↑ FCD 
                 Locascio et al. 2008 
               
               
                 protein (CRP) 
                 detection 
               
               
                 Cystatin C 
                 Immunoturbidimetric 
                 AD v Control 
                 ↓ AD 
                 Zhong et al. 2013; 
               
               
                   
                 assay 
               
               
                   
                 ELISA 
                 AD v Control 
                 No change 
                 Sundelöf et al. 2010 
               
               
                 Intracellular 
                 IHC 
                 AD v Control 
                 ↑ AD 
                 Frohman et al. 1991 
               
               
                 adhesion 
               
               
                 molecule 1 
               
               
                 (ICAM-1) 
               
               
                 Neural cell 
                 ELISA 
                 AD v Control 
                 ↓ AD 
                 Aisa et al. 2010 
               
               
                 adhesion 
               
               
                 molecule 
               
               
                 (NCAM) 
               
               
                 Neuron specific 
                 Electrochemiluminescence 
                 AD v Control 
                 No change 
                 Chaves et al. 2010; 
               
               
                 enolase (NSE) 
                 assay 
               
               
                   
                 Immunoradiometric 
                 AD v Control 
                 ↑ AD 
                 Blennow et al. 1994 
               
               
                   
                 assay 
               
               
                 Plasminogen 
                 ELISA 
                 AD v Control 
                 ↑ AD 
                 Sutton et al. 1994; 
               
               
                 activator 
                   
                   
                   
                 Akenami et al. 1997 
               
               
                 inhibitor 1 
               
               
                 (PAI-1) 
               
               
                 Pigment 
                 2-DGE; LC-MS/MS 
                 AD v Control 
                 ↑ AD 
                 Castano et al. 2006 
               
               
                 epithelium 
               
               
                 derived factor 
               
               
                 (PEDF) 
               
               
                 Regulated on 
                 Q-RT-PCR 
                 AD v Control 
                 ↓ AD 
                 Kester et a., 2011 
               
               
                 activation, 
                   
                   
                 ↑ AD 
                 Tripathy et al. 2011; 
               
               
                 normal T cell 
                   
                   
                   
                 Reynolds et al. 2007 
               
               
                 expressed and 
               
               
                 secreted 
               
               
                 (RANTES) 
               
               
                 Vascular cell 
                 ELISA 
                 AD v Control 
                 ↑ AD 
                 Zuliani et al. 2008 
               
               
                 adhesion 
               
               
                 molecule 1 
               
               
                 (VCAM-1) 
               
               
                 Advanced 
                 ELISA 
                 AD v Control 
                 ↓AD 
                 Emanuele et al. 2005 
               
               
                 glycosylation 
                 ELISA 
                 AD vs. MCI 
                 ↓MCI 
                 Chidoni et al. 2008 
               
               
                 end product- 
               
               
                 specific 
               
               
                 receptorsRAGE 
               
               
                   
               
               
                 Abbreviations: 
               
               
                 PiB PET association, Philadelphia Compound B Positron Emission Tomography; 
               
               
                 2-DGE, two-dimensional gel electrophoresis; 
               
               
                 LC-MS/MS, liquid chromatography tandem mass spectrometry; 
               
               
                 ELISA, Enzyme-linked immunosorbent assay; 
               
               
                 Q-RT-PCR, quantitative Reverse transcription polymerase chain reaction; 
               
               
                 IHC, Immunohistochemistry; 
               
               
                 SCD, slow cognitive decline; 
               
               
                 FCD, fast cognitive decline. 
               
             
          
         
       
     
         [0088]    Reference sequences for these proteins are provided in SEQ ID NOS: 1 to 27 according to Table 1B. 
         [0000]    
       
         
               
             
               
               
             
               
               
             
           
               
                 TABLE 1B 
               
             
             
               
                   
               
               
                 Sequence correlation table 
               
             
          
           
               
                 Protein 
                 SEQ ID NO: 
               
               
                   
               
             
          
           
               
                 Transthyretin (TTR) 
                 1 
               
               
                 Clusterin 
                 2 
               
               
                 Cystatin C (CST3) 
                 3 
               
               
                 Alpha-1-Acid glycoprotein (A1AcidG) 
                 4 
               
               
                 Intercellular adhesion molecule 1 (ICAM 1) 
                 5 
               
               
                 Complement C4 (CC4) 
                 6 
               
               
                 Pigment epithelium derived factor (PEDF) 
                 7 
               
               
                 Alpha1 antitrypsin (A1AT) 
                 8 
               
               
                 RANTES 
                 9 
               
               
                 Apolipoprotein C-III (ApoC3) 
                 10 
               
               
                 Plasminogen activator inhibitor type 1 (PAI-1) 
                 11 
               
               
                 C-reactive protein (CRP) 
                 12 
               
               
                 Cathepsin D (CTSD) 
                 13 
               
               
                 Apolipoprotein E (ApoE) 
                 14 
               
               
                 Alpha-2-macroglobulin (A2M) 
                 15 
               
               
                 Serum amyloid P component (SAP) 
                 16 
               
               
                 Neuron specific enolase (NSE) 
                 17 
               
               
                 Complement factor H (CFH) 
                 18 
               
               
                 Amyloid beta (A4) precursor protein (AB40 or Aβ40) 
                 19 
               
               
                 Ceruloplasmin 
                 20 
               
               
                 Neural cell adhesion molecule (NCAM) 
                 21 
               
               
                 ApoA1 
                 22 
               
               
                 BDNF 
                 23 
               
               
                 Beta-2-microglobulin (B2M) 
                 24 
               
               
                 VCAM-1 
                 25 
               
               
                 Advanced glycosylation end product-specific receptor 
                 26 
               
               
                 (sRAGE) 
               
               
                 Abeta42 
                 27 
               
               
                   
               
               
                 In any individual subject, the sequence of a protein in the biomarker panel may be the reference sequence or an allele or natural variation of the reference sequence. 
               
             
          
         
       
     
         [0089]    An allele or natural variation may have 80% or more, 90% or more, 95% or more or 98% or more sequence identity with a reference sequence over its full length. Sequence identity may be commonly defined with reference to the algorithm GAP (Genetics Computer Group, Madison, Wis.). GAP uses the Needleman and Wunsch algorithm to align two complete sequences that maximizes the number of matches and minimizes the number of gaps. Generally, default parameters are used, with a gap creation penalty=12 and gap extension penalty=4. Use of GAP may be preferred but other algorithms may be used, e.g. BLAST 63 , FASTA 64 , or the Smith-Waterman algorithm, or the TBLASTN program 63 , generally employing default parameters. 
         [0090]    An allele or natural variation may differ from the reference sequence by the addition, deletion, substitution and/or insertion of one or more amino acids. For example, an allele or natural variation may differ from the reference sequence described herein (e.g SEQ ID Nos: 1 to 27) by addition, deletion or substitution of 1 or more amino acids, for example, up to 2, up to 5 amino acids, up to 10 amino acids, or up to 20 amino acids. A natural variation as defined herein also include post-translational modifications such as phosphorylation and glycosylation. 
         [0091]    The expression of some markers in the panels described herein may be increased in subjects with a neurocognitive disorder as compared to control subjects or may be uniquely present in subjects with a neurocognitive disorder as compared to control subjects. The expression of other markers in the panels described herein may be decreased in subjects with neurocognitive disorder as compared to control subjects or may be uniquely absent in subjects with a neurocognitive disorder as compared to control subjects. Table 1 indicates whether the expression of the proteins disclosed therein is increased or decreased in disease versus control subjects. 
         [0092]    Biomarker panels as described herein may be employed for monitoring progression of neurocognitive disorders such as mild cognitive impairment and AD, the predisposition to neurocognitive disorders such as AD, for the diagnosis of neurocognitive disorders such as AD, and for monitoring the efficacy of an agent during, for example, clinical trials and for monitoring patients undergoing clinical evaluation for the treatment of neurocognitive disorders such as AD. Biomarker panels as described herein can be used to precisely define the nature or degree of the neurocognitive disorder to aid in the identification and/or selection of treatments for the disorder. 
         [0093]    AD, for example, is characterised by a progressive, insidious onset, two or more deficits in cognitive function, and the absence of any other illnesses that could account for the dementia. 
         [0094]    In addition to memory loss, there may be disorientation, poor attention span, and language impairment. There is likely to be a decline in the activity of daily living, and possibly also impaired perception and personality changes. Behavioural symptoms include delusions, aggression, agitation, anger, wandering, hallucinations, and sleep disturbance. 
         [0095]    A simple test assessing orientation, registration, calculations and attention, recall, language, and visual-spatial function may be used for an initial diagnosis. 
         [0096]    Structural imaging by standard CT or MRI may also be used. Typically a non-contrast head CT scan suffices, but MRI is preferred for those who have hypertension or diabetes, who are at risk for cerebral vascular disease. 
         [0097]    AD may be confirmed histologically by autopsy or brain biopsy showing neurofibrillary tangles and senile plaques. 
         [0098]    Identifying individuals at risk from AD or other neurocognitive disorder may involve diagnosis of mild cognitive impairment (MCI). (MCI) may be a transitional state between normal aging and dementia. There are different types of MCI. There may be cognitive impairment in multiple areas of cognitive function, in addition to memory. In some cases, memory is normal but some other domain of cognitive function is abnormal. 
         [0099]    Amnestic MCI appears to be a risk state for the development of AD. Amnestic impairment is defined by subjective memory complaints. These patients have poor memory performance for their age and education on formal testing when compared to age-matched peers. General cognitive functions and the ability to perform the activities of daily living should be entirely normal. The amnestic type of MCI is associated with hippocampal atrophy, neurofibrillary tangles in the medial temporal lobes, and elevated levels of Tau in the cerebrospinal fluid (CSF). 
         [0100]    In particular, the present invention provides for a method for determining the progression and/or the prognosis of a neurocognitive disorder in a subject comprising detecting markers of a biomarker panel as defined herein in a tissue sample and/or body fluid sample obtained from said subject. 
         [0101]    Preferably the method is an in vitro method. 
         [0102]    In details, the method may comprises:
       a) providing a tissue sample or body fluid sample obtained from said subject having a neurocognitive disorder or symptoms thereof at a test time point;   b) determining the amount or concentration of said markers of the biomarker panel;   c) comparing the amount or concentration of said markers of the biomarker panel in the sample at the test time point with reference values;
 
wherein the test time point corresponds to time when the progression and/or prognostic method is carried out; and wherein the amount or concentration of said proteins in said sample is indicative of the progression and/or prognosis of the neurocognitive disorder in said subject and wherein the biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT), optionally in combination with ApoE ε4 allele presence (ApoE genotype).
       
 
         [0106]    The reference values may have been obtained from a large screening of patients, like the one carried out for the present study, by reference to a known or previously determined correlation between such a determination and clinical information in control patients. For example, the reference values may be determined by comparison to the concentration, amount or level of expression of the said markers in a control subject, for example a healthy person (i.e. without dementia) of similar age and gender as the subject. Alternatively, the reference values are value which can be found in literature such as the ApoE ε4 allele presence whereby the presence or absence of the mutations at position 112 and 158 represent the reference to be compared to. In addition, the reference values may have been obtained from the same subject at one or more time points which precede in time the test time point. Such earlier sample may be taken one week or more, one month or more, three months or more, most preferably six months or more before the date of the test time point. In some embodiments, multiple earlier samples may be compared in a longitudinal manner and the slope of change in marker expression may be calculated as a correlate of cognitive decline. 
         [0107]    The neurocognitive disorder may be selected from the group consisting of mild cognitive impairment (MCI), Alzheimer&#39;s disease (AD), vascular dementia, dementia with lewy bodies, fronto-temporal dementia or combinations thereof. 
         [0108]    Preferably the neurocognitive disorder is MCI or AD and the progression and/prognosis of the neurocognitive disease is the progression and/or prognosis of MCI or AD. 
         [0109]    In a preferred embodiment, the method comprises:
       a) providing a tissue sample or body fluid sample obtained from said subject having a neurocognitive disorder or symptoms thereof at a test time point;   b) determining the amount or concentration of said markers of the biomarker panel;   c) comparing the amount or concentration of said markers of the biomarker panel in the sample at the test time point with reference values;
 
wherein the test time point corresponds to time when the progression and/or prognostic method is carried out; and wherein the amount or concentration of said proteins in said sample is indicative of conversion of MCI to AD in said subject and wherein the biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT), optionally in combination with ApoE ε4 allele presence (ApoE genotype).
       
 
         [0113]    Preferably, the conversion is determined over 12 months or less. 
         [0114]    More preferably, the biomarker panel also comprises regulated on activation, normal T cell expressed and secreted (RANTES) and Apolipoprotein C-III (ApoC3). 
         [0115]    The reference values derived in the present studies for the conversion of MCI to AD are the following: transthyretin 222 μg/ml; Clusterin 402 μg/ml; Cystatin C 3.21 μg/ml; Alpha-1-Acid glycoprotein 768.3 μg/ml; Intercellular adhesion molecule 1 99.72 ng/ml; Complement C4 78.5 μg/ml; pigment epithelium derived factor 10.7 μg/ml; Alpha1 antitrypsin 9.5 μg/ml; RANTES 33.8 ng/ml; and Apolipoprotein C-III 105.5 μg/ml. 
         [0116]    In particular, MCI to AD conversion may be expected when the concentration of at least some of these markers is as following: transthyretin less (&lt;) than 222 μg/ml; Clusterin more (&gt;) than 402 μg/ml; Cystatin C less (&lt;) than 3.21 μg/ml; Alpha-1-Acid glycoprotein more (&gt;) than 768.3 μg/ml; Intercellular adhesion molecule 1 less (&lt;) than 99.72 ng/ml; Complement C4 more (&gt;) than 78.5 μg/ml; pigment epithelium derived factor more (&gt;) than 10.7 μg/ml; Alpha1 antitrypsin less (&lt;) than 9.5 μg/ml; RANTES less (&lt;) than 33.8 ng/ml; and Apolipoprotein C-III less (&lt;) than 105.5 μg/ml. 
         [0117]    In addition, it may be that not all of the markers in the biomarker panels are differentially expressed within an individual subject. The number and identity of the differentially expressed markers seen in any individual test will vary between different subjects and between samples taken from an individual subject over time. Within each subset panel, a minimum number of differentially expressed proteins may be required to provide a secure determination. For example, three or more proteins in the panel, preferably four or more, and more preferably five or more, six or more, seven or more or eight or more proteins in the panel may be differentially expressed in an individual subject. 
         [0118]    In one preferred embodiment, the method for determining the progression and/or the prognosis of a neurocognitive disorder in a subject comprises detecting markers of a biomarker panel in a tissue sample and/or body fluid sample obtained from said subject, wherein the method comprises:
       a) providing a tissue sample or body fluid sample obtained from said subject having a neurocognitive disorder or symptoms thereof at a test time point;   b) determining the amount or concentration of said markers of the biomarker panel;   c) comparing the amount or concentration of said markers of the biomarker panel in the sample at the test time point with reference values;
 
wherein the test time point corresponds to time when the progression and/or prognostic method is carried out; and wherein the amount or concentration of said proteins in said sample is indicative of the progression and/or prognosis of the neurocognitive disorder in said subject and wherein the biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF), Alpha1 antitrypsin (A1AT), regulated on activation, normal T cell expressed and secreted (RANTES) and Apolipoprotein C-III (ApoC3) in combination with ApoE ε4 allele presence (ApoE genotype); wherein the progression and/or prognosis of the neurocognitive disorder is the conversion from MCI to AD; and wherein the method is an in vitro method.
       
 
         [0122]    More preferably the subject is human; even more preferably the sample is blood, plasma or serum. 
         [0123]    The most preferred embodiment is an vitro method for determining the progression and/or the prognosis of MCI to AD in a human subject which comprises determining at testing point in a blood sample obtained from said human subject, the concentration of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF), Alpha1 antitrypsin (A1AT), regulated on activation, normal T cell expressed and secreted (RANTES) and Apolipoprotein C-III (ApoC3) in combination with ApoE ε4 allele presence (ApoE genotype); and wherein when at least three or more of the markers have their concentrations as following: transthyretin less (&lt;) than 222 μg/ml; Clusterin more (&gt;) than 402 μg/ml; Cystatin C less (&lt;) than 3.21 μg/ml; Alpha-1-Acid glycoprotein more (&gt;) than 768.3 μg/ml; Intercellular adhesion molecule 1 less (&lt;) than 99.72 ng/ml; Complement C4 more (&gt;) than 78.5 μg/ml; pigment epithelium derived factor more (&gt;) than 10.7 μg/ml; Alpha1 antitrypsin less (&lt;) than 9.5 μg/ml; RANTES less (&lt;) than 33.8 ng/ml; and Apolipoprotein C-III less (&lt;) than 105.5 μg/ml, then the human subject will convert from MCI to AD within 12 months from testing point. 
         [0124]    The markers of the biomarker panel as described herein may also be present as fragments. Preferred fragments are less than 50, less than 100, less than 150 less than 200, less than 250, less than 300, less than 350, less than 400, less than 500, less than 600, less than 700, less than 800, less than 900, less than 1000, less than 1100, less than 1200, less than 1300, less than 1400, less than 1500, less than 1600, less than 1700, less than 1800, less than 1900 or less than 2000 amino acids in length. 
         [0125]    The amount or concentration of the markers in the sample is indicative of the progression and/or prognosis of the neurocognitive disease. 
         [0126]    Alternatively, the nature or degree of the neurocognitive disorder may be determined. 
         [0127]    The present invention further comprises a method of diagnosing or assessing a neurocognitive disorder in a subject comprising detecting markers of a biomarker panel as defined herein in a tissue sample and/or body fluid sample obtained from said subject. 
         [0128]    In particular the method comprises:
       a) providing a tissue sample or body fluid sample obtained from said subject having a neurocognitive disorder or symptoms thereof at a test time point;   b) determining the amount or concentration of said markers of the biomarker panel;   c) comparing the amount or concentration of said markers of the biomarker panel in the sample with reference values;
 
wherein the test time point corresponds to time when the method of diagnosing is carried out; and wherein the amount or concentration of said markers in said sample is indicative of the presence or absence of the neurocognitive disorder in said subject; wherein the biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT), optionally in combination with ApoE ε4 allele presence (ApoE genotype).
       
 
         [0132]    Preferably, the biomarker panel further comprises regulated on activation, normal T cell expressed and/or secreted (RANTES) and Apolipoprotein C-III (ApoC3), optionally in combination with ApoE ε4 allele presence (ApoE genotype). 
         [0133]    Alternatively, the biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT), regulated on activation, normal T cell expressed and secreted (RANTES) and Apolipoprotein C-III (ApoC3), and further comprises one or more of markers selected from the group of plasminogen activator inhibitor type 1 (PAI-1), C-reactive protein (CRP), Cathepsin D (CTSD) and apolipoprotein E (ApoE), optionally in combination with ApoE ε4 allele presence (ApoE genotype). 
         [0134]    In a further embodiment the biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT), regulated on activation, normal T cell expressed secreted (RANTES), Apolipoprotein C-III (ApoC3), plasminogen activator inhibitor type 1 (PAI-1), C-reactive protein (CRP), Cathepsin D (CTSD) and apolipoprotein E (ApoE), and further comprises one or more of markers selected from the group of alpha-2-macroglobulin (A2M), serum amyloid P component (SAP), advanced glycosylation end product-specific receptor (sRAGE), Neuron specific enolase (NSE), complement factor H (CFH), amyloid beta (A4) precursor protein (AB40 or Aβ40), Ceruloplasmin, neural cell adhesion molecule (NCAM), ApoA1, Abeta 42, BDNF, Beta-2-microglobulin (B2M), and VCAM-1, optionally in combination with ApoE ε4 allele presence (ApoE genotype). 
         [0135]    In one embodiment of this method, the amount or concentration of said markers in said sample is indicative of the neurocognitive disorder and/or the nature or degree of the neurocognitive disorder is determined. 
         [0136]    The neurocognitive disorder may be selected from the group consisting of mild cognitive impairment (MCI), Alzheimer&#39;s disease (AD), vascular dementia, dementia with lewy bodies, fronto-temporal dementia or combinations thereof. 
         [0137]    Preferably the neurocognitive disorder is MCI or AD. More preferably a change in the amount or concentration of said proteins in said sample is indicative of the progression to AD in a subject having MCI, wherein the progression from MCI to AD occurs over a period of 12 months or less. 
         [0138]    The methods described herein allows the type or sub-type of neurocognitive disorder in a subject to be correlated to different types to prophylactic or therapeutic treatment available in the art, thereby enhancing the likely response of the subject to the therapy. 
         [0139]    In particular, the amount or concentration of said markers of the biomarker panel in the sample taken from a subject with a neurocognitive disorder are used to predict the most appropriate and effective therapy to alleviate the neurocognitive disorder and to monitor the success of that therapy. 
         [0140]    The sample used in the methods of the invention can be a tissue sample or body fluid sample such as urine, blood, plasma, serum, saliva or cerebro-spinal fluid sample. Preferably the sample is a blood, serum or plasma sample. Use of body fluids such as those listed is preferred because they can be more readily obtained from a subject. This has clear advantages in terms of cost, ease, speed and subject wellbeing. Blood, blood products such as serum and plasma, and urine are particularly preferred. 
         [0141]    Following assessment or diagnosis by the methods described herein, a subject may undergo further tests, for example cognitive tests and/or brain imaging, such as positron emission tomography (PET) scans. 
         [0142]    The progression of the disorder over time may be tracked using methods of the invention to determine the severity of the disorder (e.g. global dementia severity). 
         [0143]    The biomarker panel according to the invention may be used in combination with or as a replacement for other clinical assessments of cognitive decline in patients undergoing treatment as part of a clinical trial or in standard clinical management. 
         [0144]    In one embodiment, the biomarkers panels may be useful as a surrogate for a clinical assessment, such as Mini Mental State Examination (MMSE) and AD Assessment Scale—Cognitive subscale (ADAS-cog). 
         [0145]    In some embodiments, the biomarker panel may comprise one or more of the prognostic biomarkers Clusterin, RANTES, NSE, TTR, VCAM-1 and SAP; or NCAM, sRAGE and ICAM and the amount of said prognostic biomarkers in the sample may be indicative of MMSE performance of the subject and/or the severity, progression or prognosis of AD in the subject. The biomarkers panel may for example be used in combination with or as a replacement for MMSE in patients undergoing treatment as part of a clinical trial or in standard clinical management. 
         [0146]    In some other embodiments, the biomarker panel may comprise one or more of the prognostic biomarkers APOA1, A1AT, ApoC3, BDNF, AB40, PAI-1 and NSE and the amount of said prognostic biomarkers in the sample is indicative of the ADAS-Cog performance of the subject and/or the severity, progression or prognosis of AD in the subject. The biomarker panel may, for example, be used in combination with or as a replacement for ADAS-Cog in patients undergoing treatment as part of a clinical trial or in standard clinical management. 
         [0147]    Alternatively, a change in the amount or concentration of said markers in said sample is indicative of the presence or extent of brain atrophy in said subject. 
         [0148]    The amount or concentration in sample of the atrophy biomarkers may be indicative of the presence or extent of brain atrophy in the subject. Such biomarkers panel may be used, for example, in combination with or as a replacement for brain imaging in patients undergoing treatment as part of a clinical trial or in standard clinical management. 
         [0149]    Individual markers of the biomarkers panels may be useful in determining the presence or extent of atrophy in specific brain regions in the subject. 
         [0150]    For example (see Table 4 below) in a subject having MCI:
       Individual markers Clusterin and/or RANTES may be useful in assessing ventricular volume. The amount or concentration in the sample of these markers is indicative of the ventricular volume of the subject;   Individual markers Clusterin and/or NSE may be useful in assessing mean hippocampal volume (LHV). The amount or concentration in sample of these markers is indicative of the left hippocampal volume (LHV) of the subject;   Individual marker Clusterin may be useful in assessing right entorhinal cortex volume (REC). The amount or concentration in the sample of this marker is indicative of the right entorhinal cortex volume (REC) in the subject.   Individual marker transthyretin may be useful in assessing left entorhinal cortical volume (LEC). The amount or concentration in sample of these markers is indicative of the left entorhinal cortical volume (LEC) of the subject.   Individual markers Clusterin and/or transthyretin may be useful in assessing entorhinal cortical thicknesses (ECT). The amount or concentration in sample of these markers is indicative of the entorhinal cortical thicknesses (ECT) in both right and left hemispheres of the subject. Individual marker Clusterin and/or NSE and/or RANTES may be useful in assessing whole brain volume. The amount or concentration in sample of said atrophy biomarkers being indicative of whole brain volume in both right and left hemispheres of the subject.       
 
         [0156]    For example (see Table 4 below) in a subject having AD:
       Individual markers A1AT and/or NSE may be useful in assessing ventricular volume. The amount or concentration in the sample of these markers is indicative of the ventricular volume of the subject;   Individual markers BDNF and/or ApoC3 and/or ApoA1 and/or ApoE may be useful in assessing mean hippocampal volume. The amount or concentration in sample of these markers is indicative of the mean hippocampal volume of the subject;   Individual marker ApoC3 and/or ApoE may be useful in assessing mean entorhinal volume. The amount or concentration in sample of these markers is indicative of the mean entorhinal volume of the subject.   Individual markers ApoC3 and/or ApoA1 and/or ApoE and/or transthyretin may be useful in assessing mean entorhinal cortical thicknesses (ECT). The amount or concentration in sample of these markers is indicative of the entorhinal cortical thicknesses (ECT) of the subject.   Individual marker ApoE and/or ApoA1 and/or Aβ40 may be useful in assessing whole brain volume. The amount or concentration in sample of said atrophy biomarkers being indicative of whole brain volume in both right and left hemispheres of the subject.       
 
         [0162]    The biomarker panels described herein comprise markers which expression is modulated, i.e. quantitatively increased or decreased, in normal versus disease states. The degree to which expression differs in normal versus disease states need only be large enough to be visualised via standard characterisation techniques. Methods for the detection and quantification of the differentially expressed markers of a biomarker panel are well known in the art and any suitable method may be employed. 
         [0163]    In one embodiment, the marker of a biomarker panel may be detected using a binding agent, such as an antibody, specific to that marker, for example in an ELISA assay or Western blotting. 
         [0164]    Methods relating to the production of antibodies capable of specifically recognising one or more epitopes of the individual markers in the biomarker panels described herein are known in the art. Such antibodies may include, but are not limited to, polyclonal antibodies, monoclonal antibodies (mAbs), humanised or chimeric antibodies, single chain antibodies, Fab fragments, F(ab′) 2  fragments, fragments produced by a Fab expression library, anti-idiotypic (anti-Id) antibodies, and epitope-binding fragments of any of the above. Such antibodies may be utilised as part of AD treatment methods, and/or may be used as part of diagnostic techniques whereby patients may be tested for the amount, concentration or expression of the individual markers in the biomarker panels. 
         [0165]    For the production of antibodies, various host animals may be immunised by injection with a differentially expressed or pathway protein, or a portion thereof. Such host animals may include, but are not limited to, rabbits, mice and rats, to name but a few. Various adjuvants may be used to increase the immunological response, depending on the host species, including active substances such as lysolecithin, Pluronic polyols, polyanions, peptides, oil emulsions, keyhole limpet hemocyamin, dinitrophenol, and potentially useful human adjuvant such as BCG bacille Calmette-Fuerin) and  Corynebacterium parvum.    
         [0166]    Polyclonal antibodies are heterogeneous populations of antibody molecules derived from the sera of animals immunised with an antigen, such as target proteins, or an antigenic functional derivative thereof. For the production of polyclonal antibodies, host animals such as those described above, may be immunised by injection with differentially expressed or pathway protein supplemented with adjuvants as also described above. 
         [0167]    Monoclonal antibodies, which are homogeneous populations of antibodies to a particular antigen, may be obtained by any technique, which provides for the production of antibody molecules by continuous cell lines in culture. These include, but are not limited to, the hybridoma technique of Kohler and Milstein (1975, Nature 256; 495-497; and U.S. Pat. No: 4,376,110), the human β-cell hybridoma technique (Kosbor, et al., 1983, Immunology Today 4: 72; Cole, et al., 1983, Proc. Natl. Acad. Sci. USA 80; 2026-2030), and the EBV-hybridoma technique (Cole, et al., 1985, Monoclonal Antibodies and Cancer Therapy, Alan R. Liss Inc., pp. 77-96). Such antibodies may be of any immunoglobulin class including IgG, IgM, IgE, IgA, IgD and any subclass thereof. The hybridoma producing the mAb of this invention may be cultivated in vitro or in vivo. Production of high titers of mAbs in vivo makes this the presently preferred method of production. 
         [0168]    In addition, techniques developed for the production of ‘chimeric antibodies’ (Morrison, et al., 1984, Proc. Natl. Acad. Sci. 81: 6851-6855; Neuberger, et al., 1984, Nature 312: 604-608; Takeda, et al., 1985, Nature 314: 452-454) by splicing the genes from a mouse antibody molecule of appropriate antigen specificity together with genes from a human antibody molecule of appropriate biological activity can be used. A chimeric antibody is a molecule in which different portions are derived from different animal species, such as those having a variable region derived from a murine mAb and a human immunoglobulin constant region. 
         [0169]    Alternatively, techniques described for the production of single chain antibodies (U.S. Pat. No: 4,946,778; Bird, 1988, Science 242: 423-426; Huston, et al., 1988, Proc. Natl. Acad. Sci. USA 85: 5879-5883; and Ward, et al., 1989, Nature 334: 544-546) can be adapted to produce differentially expressed or pathway protein-single chain antibodies. Single chain antibodies are formed by linking the heavy and light chain fragments of the Fv region via an amino acid bridge, resulting in a single chain polypeptide. 
         [0170]    Antibody fragments, which recognise specific epitopes, may be generated by known techniques. For example, such fragments include, but are not limited to, the F(ab′) 2  fragments which can be produced by pepsin digestion of the antibody molecule and the Fab fragments which can be generated by reducing the disulfide bridges of the F(ab′) 2  fragments. Alternative, Fab expression libraries may be constructed (Huse, et al., 1989, Science 246: 1275-1281) to allow rapid and easy identification of monoclonal Fab fragments with the desired specificity. 
         [0171]    In some embodiments of the methods described herein, the sample may be immobilised on a solid support for analysis. An antibody sandwich technique may be employed in which binding agents, such as antibodies, specific for the individual markers in the biomarkers panel are immobilized on a solid support such as a planar surface or a microparticle bead and markers in the panel are captured by the immobilised binding agents, such as immobilized antibodies. The captured markers are then detected using a second binding agent, such as a secondary antibody, that may be directly labeled with a signal generating agent (enzyme, fluorescent tag, radiolabel etc.) or may be detected using further amplification (labeled secondary antibody, streptavidin/biotin systems with enzyme, fluorophore, radiolabel etc.). Other methods may include, but are not limited to, one-dimensional or two-dimensional (2D) gel electrophoresis of samples. Such methods are followed by transfer to a solid surface using techniques such as Western blotting and subsequent detection using antibodies specific for the AD biomarkers. 
         [0172]    In other embodiments, autoantibodies to the biomarkers may be detected using the Western blotting approach described above using samples from a healthy subject, a patient or representative of AD, and then detecting the presence of auto-antibodies specific for the marker that are present in the sample, but not in healthy subjects. 
         [0173]    An example of a non-antibody binding agent is an aptamer. Examples of aptamers include nucleic acid aptamers and peptide aptamers. 
         [0174]    Alternatively, the markers may be detected by, amongst others, silver staining of 2D gel electrophoresis or mass spectrometry techniques including LS/MS/MS, MALDI-TOF, SELDI-TOF and TMT-SRM. 
         [0175]    Other such standard characterisation techniques by which expression differences may be visualised are well known to those skilled in the art. These include successive chromatographic separations of fractions and comparisons of the peaks, capillary electrophoresis, separations using micro-channel networks, including on a micro-chip, SELDI analysis and qPST analysis. 
         [0176]    Chromatographic separations can be carried out by high performance liquid chromatography as described in literature, the chromatogram being obtained in the form of a plot of absorbance of light at 280 nm against time of separation. The material giving incompletely resolved peaks is then re-chromatographed and so on. 
         [0177]    Capillary electrophoresis is a technique described in many publications, for example in the literature “Total CE Solutions” supplied by Beckman with their P/ACE 5000 system. The technique depends on applying an electric potential across the sample contained in a small capillary tube. The tube has a charged surface, such as negatively charged silicate glass. Oppositely charged ions (in this instance, positive ions) are attracted to the surface and then migrate to the appropriate electrode of the same polarity as the surface (in this instance, the cathode). In this electro-osmotic flow (EOF) of the sample, the positive ions move fastest, followed by uncharged material and negatively charged ions. Thus, proteins are separated essentially according to charge on them. 
         [0178]    Micro-channel networks function similarly to capillaries and can be formed by photoablation of a polymeric material. In this technique, a 
         [0179]    UV laser is used to generate high energy light pulses that are fired in bursts onto polymers having suitable UV absorption characteristics, for example polyethylene terephthalate or polycarbonate. The incident photons break chemical bonds with a confined space, leading to a rise in internal pressure, mini-explosions and ejection of the ablated material, leaving behind voids which form micro-channels. The micro-channel material achieves a separation based on EOF, as for capillary electrophoresis. It is adaptable to micro-chip form, each chip having its own sample injector, separation column and electrochemical detector: see J. S. Rossier et al., 1999, Electrophoresis 20: pages 727-731. 
         [0180]    Surface enhanced laser desorption ionisation time of flight mass spectrometry (SELDI-TOF-MS) combined with ProteinChip technology can also provide a rapid and sensitive means of profiling markers and is used as an alternative to 2D gel electrophoresis in a complementary fashion. The ProteinChip system consists of aluminium chips to which protein samples can be selectively bound on the surface chemistry of the chip (eg. anionic, cationic, hydrophobic, hydrophilic etc). Bound markers are then co-crystallised with a molar excess of small energy-absorbing molecules. The chip is then analysed by short intense pulses of N2 320 nm UV laser with protein separation and detection being by time of flight mass spectrometry. Spectral profiles of each group within an experiment are compared and any peaks of interest can be further analysed using techniques as described below to establish the identity of the markers. 
         [0181]    Isotopic or isobaric Tandem Mass Tags® (TMT® Thermo Scientific, Rockford, USA) technology may also be used to detect markers such as proteins of a biomarker panel described herein. Briefly, the proteins in the samples for comparison are optionally digested, labeled with a stable isotope tag and quantified by mass spectrometry. In this way, expression of equivalent proteins in the different samples can be compared directly by comparing the intensities of their respective isotopic peaks or of reporter ions released from the TMT® reagents during fragmentation in a tandem mass spectrometry experiment. 
         [0182]    Detection of markers of biomarker panels described herein may be preceded by a depletion step to remove the most abundant proteins from the sample. The large majority of the protein composition of serum/plasma consists of just a few proteins. For example, albumin, which is present at a concentration of 35-50 mg/ml, represents approximately 54% of the total protein content with IgG adding other 16%. In contrast, proteins changing in response to disease, for example as a result of tissue leakage, may circulate at 10 ng/ml. This vast dynamic range of protein concentrations represents a major analytical challenge and to overcome the problem, a multiple affinity depletion column may be used to remove the most highly abundant proteins (e.g. the 5, 6, 7, 8, 9 or 10 most highly abundant proteins). 
         [0183]    This enables the detection of changes in lower abundance ranges because more starting material can be used and there is less interference from the highly abundant molecules. Such a depletion strategy can be applied before any detection method. 
         [0184]    The method may further comprise determining an effective therapy for treating neurocognitive disorder. For example, the amount or concentration of the markers in the biomarker panels may be indicative of the subject being responsive or non-responsive to a particular therapy or treatment. 
         [0185]    In one embodiment of the invention, the biomarker panel may be useful in a method whereby the amounts or concentrations of the individual markers in the biomarker panel in a tissue sample or body fluid sample of a subject with a neurocognitive disorder are used to predict the most appropriate and effective therapy to alleviate the neurocognitive disorder. 
         [0186]    In another embodiment, such method may be further include the use of an agent to treat the neurocognitive disorder wherein the agent will reduce, delay or arrest the disease-associated change in marker levels of the biomarker panel in the neurocognitive disorder towards that found in the normal state in order to prevent the development or progression of the neurocognitive disorder. Preferably, the expression of the marker is restored to that of the normal state. Monitoring the expression of the markers of the biomarker panels described herein may be indicative of the progress and/or efficacy of the treatment. 
         [0187]    The biomarker panel may also be used in method of screening an agent to determine its usefulness in treating a neurocognitive disorder, such as AD, the method comprising:
       (a) providing a tissue sample or body fluid sample obtained from, or representative of, a subject having a neurocognitive disorder or symptoms thereof, wherein the subject and/or the sample has been treated with the agent being screened,   (b) determining the amount or concentration in the sample from, or representative of, the treated subject and/or sample of markers of a biomarker panel as defined herein; and   (c) determining whether the agent affects the amount or concentration of the markers of the biomarker panel in the treated subject and/or sample.       
 
         [0191]    Preferably, the biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT), optionally further comprising one or more markers selected from the group of normal T cell expressed and secreted (RANTES), Apolipoprotein C-III (ApoC3), activator inhibitor type 1 (PAI-1), C-reactive protein (CRP), Cathepsin D (CTSD), apolipoprotein E (ApoE), alpha-2-macroglobulin (A2M), serum amyloid P component (SAP), advanced glycosylation end product-specific receptor (sRAGE), Neuron specific enolase (NSE), complement factor H (CFH), amyloid beta (A4) precursor protein (AB40 or Aβ40), Ceruloplasmin, neural cell adhesion molecule (NCAM), ApoA1, Abeta 42, BDNF, Beta-2-microglobulin (B2M), and VCAM-1. 
         [0192]    More preferably, the panel further comprises ApoE ε4 allele presence (ApoE genotype). 
         [0193]    The biomarker panels described herein may be used to test agents for the ability to prevent or ameliorate neurocognitive disorders, such as AD, or one or more symptoms thereof. 
         [0194]    Such agents may be tested in human subjects in clinical trials. Any agent which restores the expression of the proteins in a biomarker panel described herein towards levels found in healthy individuals may be of potential use in treating a neurocognitive disorder, such as AD, i.e. reducing AD symptoms or slowing the progression of AD 
         [0195]    During clinical trials, for example, the amount or concentration of a marker of a biomarker panel as described herein can be determined in the presence or absence of the agent being tested. The efficacy of the agent can be followed by comparing the expression data obtained to the corresponding known expression patterns in a normal state. Agents exhibiting efficacy are those which alter the amount or concentration of the markers in the biomarker panel to more closely resemble that of the normal state, or which stabilise expression of the biomarker panel i.e. prevent progression of the disease. 
         [0196]    The detection of the markers in the biomarker panel in the neurocognitive disorder relative to their expression in a normal state can also be used for monitoring the efficacy of potential agents for the treatment of a neurocognitive disorder, such as AD, during clinical trials. During clinical trials, for example, the level and/or activity of the markers in the biomarker panel can be determined in relevant cells and/or tissues and/or body fluids in the presence or absence of the agent being tested. The efficacy of the agent can be followed by comparing the markers levels and/or activity data obtained to the corresponding known levels/activities for the cells and/or tissues and/or body fluids in a normal state. Agents exhibiting efficacy are those which alter the amount or concentration of the biomarker panel of the cell and/or tissue sample and/or body fluid from a subject to more closely resemble that of the normal state or which stabilise the pattern i.e. prevent progression of the disease. 
         [0197]    With regard to intervention, any treatments that restore or partially restore the expression of markers in a biomarker panel described herein to healthy levels should be considered as candidates for therapeutic intervention in neurocognitive disorders such as AD. Dosages of test agents may be determined by deriving dose-response curves. 
         [0198]    Similarly, any treatments that can prevent the development of neurocognitive disorders such as AD or prevent progression to levels of more advanced AD should be considered as candidates for the AD therapeutic intervention. 
         [0199]    In addition, animal models of neurocognitive disorders such as AD, and those described herein, may be used to identify agents capable of treating AD symptoms. Such animal models may be used in the identification of drugs, pharmaceuticals, therapies and interventions which may be effective in treating such disorders. The response of the animals to the exposure may be monitored by assessing the expression of the markers and comparing it to that of wild-type mice. 
         [0200]    The amount or concentration of the markers of the biomarker panel described herein may be utilised in conjunction with animal model systems to assess the ability of an agent to ameliorate symptoms of neurocognitive disorder, or prevent the progression of neurocognitive disorder. For example, the amount or concentration of the markers of the biomarker panel described herein may form part of a fingerprint profile, which may then be used in such an assessment. Fingerprint profiles may be characterised for disease states within the animal model systems. Subsequently, these known fingerprint profiles may be compared to ascertain the effect a test agent has to modify such fingerprint profiles, and to cause the profile to more closely resemble that of a more desirable fingerprint. For example, administration of an agent may cause the fingerprint profile of an AD model system to more closely resemble the control system, or may prevent further changes in fingerprint profile. Administration of an agent may, alternatively, cause the fingerprint profile of a control system to begin to mimic an AD state, which may, for example, be used in further characterising the agent of interest, or may be used in the generation of additional animal models. 
         [0201]    The amount or concentration of the markers of the biomarker panels described herein, in a subject treated with the agent compared to a subject not treated with the agent, is indicative that the agent may be useful in treating a neurocognitive disorder. 
         [0202]    The divergence of the concentration or amount of the markers in the biomarker panel over time in subjects having symptoms of a neurocognitive disorder and normal subjects may be determined. 
         [0203]    The screening method described herein may further comprise prior to step (a), the step of determining the concentration or amount of the markers of the biomarker panels in one or more control samples from healthy individuals, patients having a neurocognitive disorder of differing severity or progression, or symptoms thereof, and patients having a neurocognitive disorder or symptoms thereof not treated with agent. 
         [0204]    The step of selecting or rejecting the agent according to the extent to which it changes the concentration or amount of the markers of the biomarker panel in the treated subject having symptoms of a neurocognitive disorder relative to controls. Suitable controls include similarly aged people without the neurocognitive disorder. 
         [0205]    An agent may be selected if it prevents or slows the change over time in the concentration or amount of the markers of the biomarker panels relative to controls. 
         [0206]    Preferably, the agent is selected if it converts the amount or concentration of a marker of the biomarker panels towards that of a normal subject. More preferably, the agent is selected if it converts amount or concentration of a marker of the biomarker panels to that of the normal subject. 
         [0207]    Samples taken over time may be taken at intervals of weeks, months or years. For example, samples may be taken at monthly, two-monthly, three-monthly, four-monthly, six-monthly, eight-monthly or twelve-monthly intervals. 
         [0208]    A change in concentration or amount over time may be an increase or decrease in concentration or amount, compared to the initial level of concentration or amount in samples from the subject and/or compared to the level of concentration or amount in samples from normal subjects. The agent may be selected if it slows or stops the change of concentration or amount over time. 
         [0209]    In the screening methods described above, subjects comprise: 
         [0000]    (a) normal subjects and subjects having symptoms of a neurocognitive disorder, such as AD; and/or,
 
(b) subjects having symptoms of a neurocognitive disorder which have not been treated with the agent and subjects having a neurocognitive disorder which have been treated with the agent.
 
         [0210]    In another embodiment, subjects may include:
       (a) normal subjects who have and have not been treated with the agent; and one or both of   (b) subjects having mild cognitive impairment (MCI) who have and have not been treated with the agent; and   (c) subjects having symptoms of a neurocognitive disorder, such as AD, who have and have not been treated with the agent.       
 
         [0214]    The subjects having symptoms of a neurocognitive disorder, such as AD, may be human subjects with a neurocognitive disorder. 
         [0215]    As described above, the neurocognitive disorders may include Mild Cognitive Impairment (MCI), a recognised precursor to AD, and dementias, such as AD and other late onset dementias including vascular dementia, dementia with lewy bodies and frontotemporal dementia, alone and as a mixed dementia with Alzheimer&#39;s disease. 
         [0216]    Alzheimer&#39;s disease may be AD at any stage or severity, including pre-Alzheimer&#39;s stages, such as mild cognitive impairment (MCI) as well as advanced AD. 
         [0217]    In one embodiment, the subjects having symptoms of a neurocognitive disorder, such as AD, may be non-human animal models of the neurocognitive disorder. Suitable non-human animal models of AD are well known in the art and include mutant amyloid precursor protein (APP) transgenic mice, presenilin-1 (PS-1) transgenic mice, double transgenic APP/PS-1 transgenic mice and mice overexpressing glycogen synthase kinase (GSK) (see Lucas et al (2001) EMBO J. 20, p 27-39). In this embodiment, the normal subjects are wild-type mice. 
         [0218]    The tissue or body fluid samples which may be used in the screening methods described herein are, for example, brain tissue, blood, plasma, serum, saliva or cerebro-spinal fluid samples. 
         [0219]    Within the present invention are also encompassed methods of making a pharmaceutical composition which comprises having identified an agent using the screening method described herein, the further step of manufacturing, isolating or obtaining the agent and formulating it with an acceptable carrier to provide the pharmaceutical composition. 
         [0220]    It is possible that AD symptoms may be brought about, at least in part, by an abnormal level of target protein, or by the presence of a target protein exhibiting an abnormal activity. As such, the reduction in the level and/or activity of such target protein would bring about the amelioration AD symptoms. Techniques for the reduction of target protein gene expression levels or target protein activity levels are discussed herein. 
         [0221]    Alternatively, it is possible that symptoms of neurocognitive disorders such as AD, may be brought about, at least in part, by the absence or reduction of the level of target protein expression, or a reduction in the level of a target protein&#39;s activity. As such, an increase in the level of target protein gene expression and/or the activity of such proteins would bring about the amelioration of AD symptoms. 
         [0222]    The effects of an increase or reduction in target protein gene expression levels or target protein activity levels may be determined or monitored using a panel of biomarkers as described herein. 
         [0223]    A variety of techniques may be utilised to inhibit the expression, synthesis, or activity of such target genes and/or proteins. 
         [0224]    For example, agents which exhibit inhibitory activity, may be used in accordance with the invention to prevent mild cognitive impairment or AD symptoms. Such molecules may include, but are not limited to, peptides (such as, for example, peptides representing soluble extracellular portions of target protein transmembrane receptors), phosphopeptides, small organic or inorganic molecules, or antibodies (including, for example, polyclonal, monoclonal, humanised, anti-idiotypic, chimeric or single chain antibodies, and Fab, F(ab′) 2  and Fab expression library fragments, and epitope-binding fragments thereof). 
         [0225]    Antibodies that are both specific for target protein and interfere with its activity may be used to inhibit target protein function. Where desirable, antibodies specific for mutant target protein, which interferes with the activity of such mutant target product, may also be used. 
         [0226]    In instances where the target gene protein is intracellular and whole antibodies are used, internalising antibodies may be preferred. However, lipofectin or liposomes may be used to deliver the antibody or a fragment of the Fab region, which binds to the target protein epitope into cells. Where fragments of the antibody are used, the smallest inhibitory fragment, which binds to the target protein&#39;s binding domain, is preferred. For example, peptides having an amino acid sequence corresponding to the domain of the variable region of the antibody that binds to the target protein may be used. Such peptides may be synthesised chemically or produced via recombinant DNA technology using methods well known in the art (e.g. see Creighton, 1983, supra; and Sambrook et al, 1989, supra). 
         [0227]    Alternatively, single chain neutralising antibodies, which bind to intracellular target protein epitopes, may also be administered. Such single chain antibodies may be administered, for example, by expressing nucleotide sequences encoding single-chain antibodies within the target cell populating by utilising, for example, techniques such as those described in Marasco et al (Marasco, W. et al, 1993, Proc. Natl. Acad. Sci. USA, 90: 7889-7893). 
         [0228]    In instances where the target protein is extracellular, or is a transmembrane protein, any of the administration techniques described herein, which are appropriate for peptide administration may be utilised to effectively administer inhibitory target protein antibodies to their site of action. 
         [0229]    Furthermore, antisense, siRNA and ribozyme molecules, which inhibit expression of the target protein gene, may also be used in accordance with the invention to inhibit the aberrant target protein gene activity; triple helix molecules may be utilised in inhibiting the aberrant target protein gene activity. Antisense, ribozyme and triple helix molecules may be designed to reduce or inhibit either wild type, or if appropriate, mutant target protein gene activity. Techniques for the production and use of such molecules are well known to those of skill in the art. 
         [0230]    Antisense RNA and DNA molecules act to directly block the translation of mRNA by hybridising to targeted mRNA and preventing protein translation. With respect to antisense DNA, oligodeoxy-ribonucleotides derived from the translation initiation site, e.g. between the −10 and +10 regions of the target gene nucleotide sequence of interest, are preferred. 
         [0231]    Ribozymes are enzymatic RNA molecules capable of catalysing the specific cleavage of RNA. (For a review, see Rossi, J., 1994, Current Biology 4: 469-471). The mechanism of ribozyme action involves sequence specific hybridisation of the ribozyme molecule to complementary target RNA, followed by an endonucleolytic cleavage. The composition of ribozyme molecules must include one or more sequences complementary to the target protein mRNA, and must include the well-known catalytic sequence responsible for mRNA cleavage. For this sequence, see U.S. Pat. No. 5,093,246. As such, within the scope of the invention are engineered hammerhead motif ribozyme molecules that specifically and efficiently catalyse endonucleolytic cleavage of RNA sequences encoding target proteins. 
         [0232]    Specific ribozyme cleavage sites within any potential RNA target are initially identified by scanning the molecule of interest for ribozyme cleavage sites which include the following sequences, GUA, GUU and GUC. Once identified, short TNA sequences of between 15 and 20 ribonucleotides corresponding to the region of the target protein gene, containing the cleavage site may be evaluated for predicted structural features, such as secondary structure, that may render the oligonucleotide sequence unsuitable. The suitability of candidate sequences may also be evaluated by testing their accessibility to hybridise with complementary oligonucleotides, using ribonuclease protection assays. 
         [0233]    RNA interference (RNAi) is a process of sequence-specific, post-transcriptional gene silencing in animals and plants, initiated by double-stranded RNA (dsRNA) that is homologous in sequence to the silenced gene. RNAi is mediated by short double-stranded RNA molecules (small interfering RNAs or siRNAs). siRNAs may be introduced into a cell as short RNA oligonucleotides of 10-15 bp, or as longer dsRNAs which are subsequently cleaved to produce siRNAs. The RNA may be introduced into the cell as RNA, or may be transcribed from a DNA or RNA vector. 
         [0234]    siRNA molecules may be synthesized using standard solid or solution phase synthesis techniques which are known in the art. Alternatively, siRNA molecules or longer dsRNA molecules may be made recombinantly by transcription of a nucleic acid sequence, preferably contained within a vector as described below. 
         [0235]    Another alternative is the expression of a short hairpin RNA molecule (shRNA) in the cell. shRNAs are more stable than synthetic siRNAs. A shRNA consists of short inverted repeats separated by a small loop sequence. One inverted repeat is complimentary to the gene target. The shRNA is then processed into a siRNA which degrades the target gene mRNA and suppresses expression. shRNAs can produced within a cell by transfecting the cell with a DNA construct encoding the shRNA sequence under control of a RNA polymerase III promoter, such as the human H1 or 7SK promoter. Alternatively, the shRNA may be synthesised exogenously and introduced directly into the cell. Preferably, the shRNA sequence is between 40 and 100 bases in length, more preferably between 40 and 70 bases in length. The stem of the hairpin is preferably between 19 and 30 base pairs in length. The stem may contain G-U pairings to stabilise the hairpin structure. 
         [0236]    Nucleic acid molecules to be used in triplex helix formation for the inhibition of transcription should be single stranded and composed of deoxynucleotides. The base composition of these oligonucleotides must be designed to promote triple helix formation via Hoogsteen base pairing rules, which generally require sizeable stretches of either purines or pyrimidines to be present on one strand of a duplex. Nucleotide sequences may be pyrimidine-based, which will result in TAT and CGC +  triplets across the three associated strands of the resulting triple helix. The pyrimidine-rich molecules provide base complementary to a purine-rich region of a single strand of the duplex in a parallel orientation to that strand. In addition, nucleic acid molecules may be chosen that are purine-rich, for example, containing a stretch of G residues. These molecules will form a triple helix with a DNA duplex that is rich in GC pairs, in which the majority of the purine residues are located on a single strand of the targeted duplex, resulting in GGC triplets across the three strands in the triplex. 
         [0237]    Alternatively, the potential sequences that can be targeted for triple helix formation may be increased by creating a so-called “switchback” nucleic acid molecule. Switchback molecules are synthesised in an alternating 5′-3′, 3′-5′ manner, such that they base pair with first one strand of a duplex and then the other, eliminating the necessity for a sizeable stretch of either purines or pyrimidines to be present on one strand of a duplex. 
         [0238]    Anti-sense RNA and DNA, siRNAs, ribozyme and triple helix molecules of the invention may be prepared by any method known in the art for the synthesis of DNA and RNA molecules. They include techniques for chemically synthesising oligodeoxyribonucleotides and oligo-ribonucleotides well known in the art such as, for example, solid phase phosphoramidite chemical synthesis. Alternatively, RNA molecules may be generated by in vitro and in vivo transcription of DNA sequences encoding the antisense RNA molecule. Such DNA sequences may be incorporated into a wide variety of vectors, which incorporate suitable RNA polymerase promoters such as the T7 or SP6 polymerase promoters. Alternatively, antisense cDNA constructs that synthesise antisense RNA constitutively inducible, depending on the promoter used, can be introduced stably into cell lines. 
         [0239]    Target proteins that cause neurocognitive disorders such as AD, may be underexpressed in disorder situations. Alternatively, the activity of target protein may be diminished, leading to the development of symptoms. Described herein are methods whereby the level of target protein may be increased to levels wherein AD symptoms are prevented or ameliorated. The level of target protein activity may be increased, for example, by either increasing the level of target protein present or by increasing the level of active target protein which is present. 
         [0240]    For example, a target protein, at a level sufficient to ameliorate AD symptoms may be administered to a patient exhibiting such symptoms. One of skill in the art will readily know how to determine the concentration of effective, non-toxic doses of the normal target protein, utilising techniques such as those described herein. 
         [0241]    Further, patients may be treated by gene replacement therapy. One or more copies of a normal target protein gene or a portion of the gene that directs the production of a normal target protein with target protein gene function, may be inserted into cells, using vectors which include, but are not limited to, adenovirus, adeno-associated virus, and retrovirus vectors, in addition to other particles that introduce DNA into cells, such as liposomes. Additionally, techniques such as those described above may be utilised for the introduction of normal target protein gene sequences into human cells. 
         [0242]    Cells, preferably autologous cells, containing normal target protein gene sequences may then be introduced or reintroduced into the patient at positions which allow for the prevention or amelioration of AD symptoms. Such cell replacement techniques may be preferred, for example, when the target protein is a secreted, extracellular protein. 
         [0243]    The effects of administering an antibody or nucleic acid suppressor may be determined or monitored using a panel of biomarkers as described herein. 
       Pharmaceutical Preparations and Methods of Administration 
       [0244]    Agents that affect target protein expression, synthesis and/or activity can be administered to a patient at therapeutically effective doses to prevent or to treat or to ameliorate neurocognitive disorders such as AD. A therapeutically effective dose refers to that amount of the compound sufficient to result in amelioration of symptoms, or alternatively, to that amount of a nucleic acid molecule sufficient to express a concentration of protein which results in the amelioration of such symptoms. 
         [0245]    The effects of an agent, whether it is a nucleic acid molecule, an antibody, a small molecule compound or a cell may be determined or monitored using a panel of biomarkers as described herein. 
         [0246]    Toxicity and therapeutic efficacy of such agents can be determined by standard pharmaceutical procedures in cell cultures or experimental animals, e.g. for determining by ED 50  (the dose therapeutically effective in 50% of the population) and by determining the ED 50  of any side-effects (toxicity—TD50). The dose ratio between toxic and therapeutic effects is the therapeutic index and it can be expressed as the ratio TD 50 /ED 50 . Agents, which exhibit large therapeutic indices, are preferred, whilst for those that exhibit toxic side effects, care should be taken to design a delivery system that targets such agents to the site of affected tissue in order to minimise potential damage to uninfected cells and, thereby, reduce side effects. 
         [0247]    The data obtained from the animal studies can be used in formulating a range of dosage for use in humans. The dosage of such agents lies preferably within a range of circulating concentrations that include the ED 50  with little or no toxicity. The dosage may vary within this range depending upon the dosage form employed and the route of administration utilised. 
         [0248]    Pharmaceutical compositions for use in accordance with the present invention may be formulated in conventional manner using one or more physiologically acceptable carriers or excipients. 
         [0249]    Thus, the agents may be formulated for administration by inhalation or insufflation (either through the mouth or the nose) or oral, buccal, parenteral and rectal administration. 
         [0250]    For oral administration, the pharmaceutical compositions may take the form of, for example, tablets or capsules prepared by conventional means with pharmaceutically acceptable excipients such as binding agents (e.g. pre-gelatinised maize starch, polyvinylpyrrolidone or hydroxypropyl methyl-cellulose); fillers (e.g. lactose, microcrystalline cellulose or calcium hydrogen phosphate); lubricants (e.g. magnesium, stearate, talc or silica); disintegrants (e.g. potato starch or sodium starch glycollate); or wetting agents (e.g. sodium lauryl sulphate). The tablets may be coated by methods well known in the art. Liquid preparations for oral administration may take the form of, for example, solutions, syrups or suspensions, or they may be presented as a dry product for constitution with water or other suitable vehicle before use. Such liquid preparations may be prepared by conventional means with pharmaceutically acceptable additives such as suspending agents (e.g. sorbitol syrup, cellulose derivatives or hydrogenated edible fats); emulsifying agents (e.g. lecithin or acacia); and preservatives (e.g. methyl or propyl-p-hydroxybenzoates or sorbic acid). The preparations may also contain buffer salts, flavours, colours and sweeteners as appropriate. 
         [0251]    Preparations for oral administration may be suitably formulated to give controlled release of the active agent. For buccal administration the compositions may take the form of tablets or lozenges formulated in conventional manner. 
         [0252]    For administration by inhalation, the agents for use according to the present invention are conveniently delivered in the form of an aerosol spray presentation from pressurised packs or a nebuliser, with the use of a suitable propellant, e.g. dichlorodifluoromethane, trichlorofluoromethane, dichloro-tetrafluoroethane, carbon dioxide or other suitable gas. In the case of a pressurised aerosol the dosage unit may be determined by providing a valve to deliver a metered amount. Capsules and cartridges of, e.g. gelatin, for use in an inhaler or insufflator may be formulated containing a powder mix of the compound and a suitable powder base such as lactose or starch. 
         [0253]    The agents may be formulated for parenteral administration by injection, e.g. by bolus injection or continuous infusion. Formulations for injection may be presented in unit dosage form, e.g. in ampoules or in multi-dose containers, with an added preservative. 
         [0254]    The compositions may take such forms as suspensions, solutions or emulsions in oily or aqueous vehicles, and may contain formulatory agents such as suspending, stablising and/or dispersing agents. Alternatively, the active ingredient may be in powder form for constitution with a suitable vehicle, e.g. sterile pyrogen-free water, before use. 
         [0255]    The agents may also be formulated in rectal compositions such as suppositories or retention enemas, e.g. containing conventional suppository bases such as cocoa butter or other glycerides. 
         [0256]    In addition to the formulations described previously, the agents may also be formulated as a depot preparation. Such long acting formulations may be administered by implantation, for example, subcutaneously or intramuscularly) or by intramuscular injection. Thus, for example, the compounds may be formulated with suitable polymeric or hydrophobic materials (for example, as an emulsion in an acceptable oil) or ion exchange resins, or as sparingly soluble derivatives, for example, as a sparingly soluble salt. 
         [0257]    The compositions may, if desired, be presented in a pack or dispenser device, which may contain one or more unit dosage forms containing the active ingredient. The pack may, for example, comprise metal or plastic foil, such as blister pack. The pack or dispenser device may be accompanied by instructions for administration. 
       Kits for the Detection of the Biomarkers Panel 
       [0258]    The present invention also provides for a kit comprising reagents for the detection of markers of a biomarker panel as described herein in a tissue sample or body fluid sample. The biomarker panel consists essentially of markers transthyretin (TTR), Clusterin, Cystatin C (CST3), Alpha-1-Acid glycoprotein (A1AcidG), Intercellular adhesion molecule 1 (ICAM1), Complement C4 (CC4), pigment epithelium derived factor (PEDF) and Alpha1 antitrypsin (A1AT) and optionally one or more markers selected from the group of regulated on activation, normal T cell expressed and secreted (RANTES), Apolipoprotein C-III (ApoC3), plasminogen activator inhibitor type 1 (PAI-1), C-reactive protein (CRP), Cathepsin D (CTSD), apolipoprotein E (ApoE), alpha-2-macroglobulin (A2M), serum amyloid P component (SAP), advanced glycosylation end product-specific receptor (sRAGE), Neuron specific enolase (NSE), complement factor H (CFH), amyloid beta (A4) precursor protein (AB40 or Aβ40), Ceruloplasmin, neural cell adhesion molecule (NCAM), ApoA1, Abeta 42, BDNF, Beta-2-microglobulin (B2M) and VCAM-1. 
         [0259]    Preferably, the panel further comprises ApoE ε4 allele presence (ApoE genotype). 
         [0260]    In one embodiment, the kit further comprises one or more binding agents which specifically bind to the markers of the biomarker panels. 
         [0261]    In one particular embodiment, the one or more binding agents are primary antibodies, each antibody binding specifically to a different individual marker in the biomarker panel. Preferably, the kit may further comprise one or more secondary antibodies which specifically bind to the primary antibodies. The secondary antibodies may optionally be labeled, for example fluorescent labeled or tagged. 
         [0262]    The binding agent may be an aptamer, an oligonucleotide or a chemical compound. 
         [0263]    Alternatively, a kit may comprise one or more peptides representing the selected markers and a suitable grade of a proteolytic enzyme for use in a mass spectrometry method. The peptides may be synthetic peptides and may comprise one or more heavy isotopes of carbon, nitrogen, oxygen and/or hydrogen. The binding agents, e.g. the antibodies, may be immobilised on an assay plate, beads, microspheres or particles. Optionally, beads, microspheres or particles may be dyed, tagged or labeled. 
         [0264]    The kit may further comprise a control sample of the markers of the biomarker panel. 
         [0265]    A kit may further comprise one or more detection reagents for detecting the presence of the tagged secondary antibodies. 
         [0266]    The reagents in the kit may be sealed in a suitable container which protects its contents from the external environment. Such a kit may include instructions for use. 
         [0267]    The methods described herein may be performed, for example, by utilising pre-packaged diagnostic kits comprising a biomarker panel as described herein and/or reagents which specifically bind to the individual markers of the biomarker panel, such as binding agents, e.g. antibodies, which may be conveniently used, e.g. in clinical settings, to diagnose patients exhibiting AD symptoms. 
         [0268]    All documents, publications and sequence database entries mentioned in this specification are incorporated herein by reference in their entirety for all purposes. 
         [0269]    Certain aspects and embodiments of the invention will now be illustrated by way of example and with reference to the figures and tables described above. 
       EXAMPLES 
       [0270]    Alzheimer&#39;s disease (AD) is exemplified herein as a representative example of all related dementias and neurocognitive disorders. 
         [0271]    Detecting AD at the earliest possible stage is vital to enable trials of disease modification agents and considerable efforts are being invested in the identification and replication of biomarkers for this purpose. 
         [0272]    Such biomarkers currently include measures of tau and amyloid beta (Aβ) in cerebrospinal fluid (CSF), measures of atrophy using magnetic resonance imaging (MRI) and measures of Aβ pathological load using positron emission tomography (PET). All these approaches are promising although molecular imaging is currently a costly procedure available in relatively few centres and lumbar puncture is moderately invasive. Furthermore repeated measures are problematical in both cases. 
         [0273]    Blood (plasma) on the other hand is a more accessible bio-fluid suitable for repeated sampling. Using a case-control study design with a gel based approach (2-DGE &amp; LC-MS/MS) two proteins (complement factor H (CFH) and alpha-2-macroglobulin) were observed as potential markers of AD 1 , both of which were subsequently replicated by independent groups 2-3 . In the present study changes in three other proteins, namely serum amyloid P (SAP), complement C4 (CC4), and ceruloplasmin were observed, all of which have been implicated in AD pathogenesis 4-6 . However, case-control studies are problematical when there is a long prodromal disease phase as there is in AD. In such instances a large proportion of apparently normal controls already harbour the disease processes and hence may already have a peripheral biomarker disease signature. In order to overcome the limitations of case-control design, proteins associated with surrogates of disease severity (hippocampal atrophy and clinical progression) were sought and Clusterin was identified as a marker associated with both these surrogate measures&#39;. Building on this ‘endophenotype’ discovery approach transthyretin (TTR) and Apolipoprotein A1 (ApoA1) were found to be associated with faster declining AD subjects and increased plasma Apolipoprotein E (ApoE) levels related to increased Aβ burden in the brain 8-9 . 
         [0274]    These observations led to a set of that might act as biomarkers relevant to AD. However such findings require replication, in large studies, ideally using samples drawn from more than one cohort source and using a platform that enables multiplexing. 
         [0275]    Hence, firstly multiplex panels of biomarkers implicated in the disease needed to be identified; secondly validation of a set of blood-based biomarkers in a large multicentre cohort with specified a priori outcome variables of the disease endophenotype measure of atrophy on MRI and of clinical severity needed to be established and thirdly determination of the accuracy of a multiplexed panel of disease relevant biomarkers in predicting conversion of mild cognitive impairment to dementia in a defined time period needed to be found. 
         [0276]    Furthermore, as disease case compared to normal control designs are limited because of occult disease in controls, such replication studies should have as outcomes, endophenotypes of disease or clinically meaningful outcomes such as prediction of disease progression. 
       Methods 
     Subjects and Clinical Classification 
       [0277]    Plasma samples from AD, MCI and elderly non-demented controls were selected from three independent studies. AddNeuroMed (ANM), a multi-center European study 10 ; Kings Health Partners-Dementia Case Register (KHP-DCR), a UK clinic and population based study and Genetics AD Association (GenADA) a multisite case-control longitudinal study based in Canada. The diagnosis of probable AD was made according to Diagnostic and Statistical Manual for Mental Diagnosis (DSM-IV) and National Institute of Neurological, Communicative Disorders and Stroke-Alzheimer&#39;s disease and Related Disorders Association (NINCDS-ADRDA) criteria. Mild cognitive impairment (MCI) was defined according to Petersen criteria 11 . Standardized clinical assessment included the Mini-Mental State Examination (MMSE) and Alzheimer&#39;s disease Assessment Scale-cognitive subscale (ADAS-cog) (ANM and KHP-DCR studies only) for cognition and for global levels of severity the Clinical Dementia Rating (CDR) (ANM and KHP-DCR studies only). Institutional review boards approved the study procedures and subjects provided written informed consent or proxy consent was obtained. 
         [0278]    Plasma samples from 1153 subjects were examined—476 with AD, 225 with MCI and 452 elderly controls with no dementia (Table 2). APOE genotype was determined from venous blood using standard methods 12 . 
         [0000]    
       
         
               
             
               
               
               
             
               
               
               
               
               
               
             
               
               
               
               
               
               
             
           
               
                 TABLE 2 
               
             
             
               
                   
               
               
                 Subject demographics 
               
             
          
           
               
                   
                 MCI 
                   
               
             
          
           
               
                   
                 Control 
                 MCI nc   
                 MCI c   
                 AD 
                 Significance 
               
               
                   
                   
               
             
          
           
               
                 N 
                 452 
                 173 
                 52 
                 476 
                   
               
               
                 Age (yrs) 
                 75.6 
                 76.3 
                 76.2 
                 77.0 
                 P = 0.012# 
               
               
                   
                 (±6.3, 53-93) 
                 (±5.7, 65-90) 
                 (±6.9, 56-89) 
                  (±6.4, 58-96) 
               
               
                 Sex (%, Female) 
                 55.6% 
                 50.1% 
                 49.1% 
                 49.4% 
                 P = 0.277 
               
               
                 APOE genotype 
                   28% 
                   35% 
                   55% 
                   59% 
                 P &lt; 0.001# 
               
               
                 (%, e4+) 
               
               
                 MMSE 
                 29.0 
                 26.9 
                 26.3 
                 20.8 
                 P &lt; 0.001* 
               
               
                   
                 (±1.2, 22-30) 
                 (±2.9, 0-30)  
                 (±2.1, 18-30) 
                 (±5.4, 0-30) 
               
               
                 CDR 
                 0.18 
                 1.82 
                 2.41 
                 4.04 
                 P &lt; 0.001* 
               
               
                 (Sum of 
                 (±0.4, 0-3)  
                 (±0.9, 0-4.5)  
                 (±0.9, 0.5-5)  
                 (±3.2, 0-20) 
               
               
                 Boxes) 
               
               
                   
               
               
                 Abbreviations: 
               
               
                 AD, Alzheimer&#39;s disease; 
               
               
                 APOE, Apolipoprotein E; 
               
               
                 CDR, Clinical dementia rating; 
               
               
                 GDS, Global Deterioration Scale; 
               
               
                 MCI nc , mild cognitive impairment non-converter; 
               
               
                 MCI c , mild cognitive impairment converter; 
               
               
                 MMSE, mini mental state examination. 
               
               
                 Mean (±S.D, Range), ANOVA was performed and if significant a Tukey&#39;s post-hoc comparison was carried out. 
               
               
                 *Significance across all 3 groups, 
               
               
                 #Control compared to AD. 
               
             
          
         
       
     
       Cognitive Decline 
       [0279]    Cognitive decline, as determined by the slope of change in cognition, was calculated for a subset of AD subjects (n=342) who had a minimum of three separate MMSE assessments. Linear mixed effect models were generated using the package ‘nlme’ in R. Covariates including age at baseline, gender, apolipoprotein E(APOE) ε4 allele presence (ApoE genotype), and years of education were investigated for their effect on the rate of decline. Age at baseline and years of education had a significant effect on the rate (p-value&lt;0.05) and thus were included as fixed effects in the final model. The slope coefficient obtained from the final model for each sample was then used as a rate of cognitive change, defined as the change in MMSE score per year. 
       Magnetic Resonance Imaging (MRI) 
       [0280]    High resolution sagittal 3D T1-weighted MPRAGE volume (voxel size 1.1×1.1×1.2 mm 3 ) and axial proton density/T2-weighted fast spin echo images were acquired on 1.5 T MRI scanners for 476 of the subjects (179 CTL, 123 MCI and 174 AD) as previously reported 13 . The MPRAGE volume was acquired using a custom pulse sequence specifically designed for the ADNI study to ensure compatibility across scanners 14 . Full brain and skull coverage was required for all MR images according to previously published quality control criteria 13, 15 . Image analysis was carried out using the Freesurfer image analysis pipeline (version 5.1.0) to produce regional cortical thickness and subcortical volumetric measures as previously described 16-17 . This segmentation approach has been previously used for analysis in imaging-proteomic studies 18  and AD biomarker discovery 19 . All volumetric measures from each subject were normalized by the subject&#39;s intracranial volume while cortical thickness measures were used in their raw form 19 . Measures of hippocampal volume, entorhinal cortex volume and ventricular volume were chosen as key MRI endophenotypes of Alzheimer&#39;s disease. For evaluation of hippocampal atrophy the MRI data was stratified into high and low atrophy for the MCI group based on their median volumetric measures. 
       Immunoassay—Luminex Measurement 
       [0281]    Multi-analyte profile (xMAP) technology was used to quantify the candidate proteins (Table 6) and the Luminex 200 (Austin, Tex.) instrument using 7 Milliplex panels. In more detail: 
       Milliplex Assays 
       [0282]    Seven MILLIPLEX® MAP multiplex panels (96 well plate format; Millipore EMD) were utilised: Human Neurodegenerative Panel 1 (7-plex) Cat. # HNDG1-36K, Panel 2 (6 plex) Cat.# HNDG2-36K, Panel 3-(10-plex) HNDG3-36K, Panel 4 (5-plex) HNDG4-36K, Human Kidney Toxicity Panel 2 (3-plex) Cat. # HKTX2-38K, Human Neurological disorders Mag Panel 1 (12plex) and Panel 2 (4-plex). 
       Immunoassay Protocol 
       [0283]    The Luminex xMAP technology (Austin, Tex.) uses a solid phase approach to analyze multiple proteins. In brief, the xMAP technology is a flow cytometric-based platform that uses microspheres inserted with a ratio of two different fluorescent dyes. In theory, up to 100 differently coloured beads can be generated with a theoretical multiplex capacity of up to 100 assays per well of a 96-well plate. The capture antibody is covalently coupled to the bead, and immunoassays are run under standard sandwich immunoassay formats. 
         [0284]    The plasma samples were first diluted as recommended in the protocol for each Milliplex assay. Each assay well was first rinsed with 100 μL wash buffer (1× L-WB) prior to samples loading. 25 μL of Assay Buffer was added to either 25 μL controls, or samples followed by 25 μL beads to bring the total volume in each well to 75 μL. The assay plates were incubated for 2 hours at room temperature or overnight with agitation on an orbital shaker. The beads in the plate were washed 3 times with 100 μL wash buffer and incubated for 1 hour with 25 μL biotinylated detection antibody. 25 μL fluorescently labeled reporter (streptavidin-PE) molecule was added to the detection antibody for a further 30 minutes. Finally the assay plate was washed 3 times with 100 μL wash buffer and the beads suspended in 100 μL sheath fluid. All plasma samples were assayed in duplicate and a pooled plasma (Mastermix) sample was included as a positive control in addition to high and low QC per plate. 
       Data Quality Check and Pre-Processing 
       [0285]    Fluorescence in each well was measured using Luminex 200 (Austin, Tex.) instrument and the results were analysed with the Xponent 3.1 (Luminex) software. Median fluorescent intensity (MFI) values were exported and the characteristics of the individual samples were confirmed by calculating the mean, standard deviation (SD) and coefficient of variation (CV %) from the MFI readouts. All processed data points were then imported into Sigma Plot (Systat, ver. 12). 
         [0286]    Using a 5-parameter logistic curve fitting method the concentrations of the unknown plasma samples and the master mix were calculated. Any individuals samples that recorded a CV&gt;15% for either duplicate was eliminated; if both duplicates were out of range then both data points were excluded. 
         [0287]    Individual analytes were then assessed for quality by applying ranked according to their performance in the assay (31 plates; 1148 plasma samples) and defined using a scoring system based on 4 criteria as follows: 
         [0288]    Criteria 1. Standard curve rank: 1=Good quality-within linear section on standard curve and within quality checks (QC) range. 2= 
         [0289]    Moderate quality, spread across the linear section on standard curve, clustered either higher or lower than QC and 3=poor quality, not on linear section at all, below low QC or higher than top QC. 
         [0290]    Criteria 2. Intra-assay CV (%) for QC1 and QC2, CV&lt;30% accepted (point for each QC value). 
         [0291]    Criteria 3. Inter-assay CV (%) for our in-house pooled sample (master mix), CV&lt;30% accepted. 
         [0292]    Criteria 4. Missing data defined as samples that could not be reliably intrapolated from the standard curve. 1) MFI values outside the quantifiable range, 2) Technical failure resulting in no MFI value being generated. 
       Data Pre-Processing 
       [0293]    Prior to statistical analysis, we examined the performance of each assay using a number of quality checks (QC). Median fluorescent intensity (MFI) was measured using Xponent 3.1 (Luminex Corporation) and exported into Sigma plot (Systat Software; version 12) for estimation of protein concentrations using a 5-parameter logistic fit. Briefly, all analytes that passed QC checks based on the 4 criteria (Standard curve linearity, intra-assay coefficient of variation, inter-assay CV for reference sample and percentage of missing data) were taken forward for further analysis. 
       Statistical Analysis 
       [0294]    Univariate statistical analysis was performed in SPSS 20 (IBM). All raw MFI measures were log transformed to achieve normal distribution. Covariates including age, gender, plasma storage duration (days) and centre were investigated. The inventors found that the majority of proteins were significantly affected by covariates and therefore values were adjusted using a generalized linear regression model (GLM). Partial correlation (adjusting for APOE genotype) analysis was performed to observe any association with either structural MRI brain imaging or cognition assessments. Correlations were performed separately within groups due to the discrete nature of the clinical scores across all groups. The proteins were also analysed individually for their association with disease phenotypes and disease status (AD vs. CTL) via ANCOVA (adjusting for APOE genotype). Multiple linear regressions were used to test for combinations of proteins required for prediction of hippocampal volume. 
       Classification Analysis 
       [0295]    For class prediction and attribute selection, WEKA (University of Waikato) was employed. Naive Bayes Simple algorithm was used with default settings unless stated otherwise. Datasets were randomly split into 75% train and 25% test. Attribute selection was performed using the Classifier Subset Evaluator with best first search method on the training data. Five iterations of attribute selection were performed and attributes ranked by times observed in each of the iterations. Proteins seen &gt;3 or more times were taken forward as predictor variables (Table 3). Any class imbalance was overcome by applying the Synthetic Minority Oversampling Technique (SMOTE) in WEKA. 
         [0000]    
       
         
               
             
               
               
               
               
             
           
               
                 TABLE 3 
               
             
             
               
                   
               
               
                 Proteins observed in the feature selection 
               
             
          
           
               
                   
                 No. Times 
                   
                 No. Times 
               
               
                   
                 observed in 
                   
                 observed in 
               
               
                   
                 feature 
                   
                 feature 
               
               
                 Protein 
                 selection 
                 Protein 
                 selection 
               
               
                   
               
               
                 
                   Transthyretin 
                 
                 5 
                 CathepsinD 
                 1 
               
               
                 
                   Clusterin 
                 
                 4 
                 ApoE 
                 1 
               
               
                 
                   Cystatin C 
                 
                 4 
                 SAP 
                 0 
               
               
                 
                   A1AcidG 
                 
                 4 
                 Ceruloplasmin 
                 0 
               
               
                 
                   ICAM1 
                 
                 4 
                 NCAM 
                 0 
               
               
                 
                   CC4 
                 
                 4 
                 NSE 
                 0 
               
               
                 
                   PEDF 
                 
                 4 
                 VCAM1 
                 0 
               
               
                 
                   A1AT 
                 
                 4 
                 A2M 
                 0 
               
               
                 
                   APOE genotype 
                 
                 3 
                 B2M 
                 0 
               
               
                 
                   RANTES 
                 
                 3 
                 BDNF 
                 0 
               
               
                 
                   ApoC3 
                 
                 3 
                 CFH 
                 0 
               
               
                 PAI-1 
                 2 
                 ApoA1 
                 0 
               
               
                 CRP 
                 2 
                 Ab40 
                 0 
               
               
                   
               
               
                 Proteins are ranked according to the number of times a protein was observed in the feature selection; 
               
               
                 proteins highlighted in bold were taken forward as the predictors for MCI conversion. 
               
             
          
         
       
     
       Cut-Off Point Analysis 
       [0296]    Untransformed protein concentrations on the full dataset (n=169 MCI-converter MCI c  and MCI-nonconverter (MCI nc )) were binarised at different cut-off points using the upper and lower quartile ranges and the percentile rank. A minimum of three cut-off concentrations were tested per protein. Logistic regression analysis was performed on individual cut-off concentrations and selected based on their accuracy of predicting conversion. 
       Results 
     Study Participants 
       [0297]    The demographic and clinical characteristics of participants from the three cohorts are presented in Table 2. The AD group were marginally, but significantly older than controls (AD: mean 77 yrs, Controls: 75 yrs, p=0.012). The frequency of the APOEε4 allele was higher in MCI and AD groups than controls. 
       Plasma Proteins and Disease Pathology 
       [0298]    Preliminary analysis showed that only two proteins were found to be significantly different between AD and controls (ApoE: F=6.5, p&lt;0.001; CFH: F=6.1, p&lt;0.001). However, using partial correlation, and after adjusting for APOE, the inventors identified a number of plasma proteins that were significantly associated with atrophy using MRI measures of one or more of the brain regions hippocampus, entorhinal cortex, ventricles and whole brain volume in the disease groups (Table 4; sections a and b). Controlling for multiple testing, only Clusterin (MCI group: p&lt;0.001) and ApoE (AD group: p=0.0014) remained significant. 
         [0000]    
       
         
               
             
               
               
               
               
               
             
               
               
               
               
               
             
           
               
                 TABLE 4 
               
             
             
               
                   
               
               
                 Proteins identified as significantly associated with 
               
               
                 structural brain MRI measures in the (a) MCI group and (b) AD group 
               
             
          
           
               
                   
                   
                 Correlation 
                 Significance 
                   
               
               
                   
                 Protein 
                 coefficient* 
                 (2-tailed) 
                 df 
               
               
                   
                   
               
             
          
           
               
                 (a) 
                   
                   
                   
                   
               
               
                 MCI Brain Regions 
               
               
                 Ventricular volume 
                 Clusterin 
                 0.23 
                 0.01 
                 115 
               
               
                   
                 RANTES 
                 −0.19 
                 0.03 
                 116 
               
               
                 Mean hippocampal 
                 Clusterin 
                 −0.38 
                 0.00 
                 115 
               
               
                 volume 
                 NSE 
                 0.22 
                 0.02 
                 116 
               
               
                 Right Entorhinal 
                 Clusterin 
                 −0.22 
                 0.02 
                 115 
               
               
                 thickness 
               
               
                 Left Entorhinal 
                 Transthyretin 
                 −0.20 
                 0.04 
                 109 
               
               
                 thickness 
               
               
                 Whole Brain 
                 Clusterin 
                 −0.25 
                 0.01 
                 118 
               
               
                 Volume 
                 NSE 
                 0.21 
                 0.02 
                 119 
               
               
                   
                 RANTES 
                 0.19 
                 0.04 
                 119 
               
               
                 (b) 
               
               
                 AD Brain Regions 
               
               
                 Ventricular volume 
                 A1AT 
                 0.24 
                 0.01 
                 119 
               
               
                   
                 NSE 
                 0.16 
                 0.03 
                 169 
               
               
                 Mean hippocampal 
                 BDNF 
                 −0.21 
                 0.02 
                 123 
               
               
                 volume 
                 ApoC3 
                 −0.18 
                 0.02 
                 168 
               
               
                   
                 ApoA1 
                 −0.15 
                 0.04 
                 169 
               
               
                   
                 ApoE 
                 −0.15 
                 0.05 
                 169 
               
               
                 Mean Entorhinal 
                 ApoC3 
                 −0.204 
                 0.01 
                 168 
               
               
                 volume 
                 ApoE 
                 −0.177 
                 0.02 
                 169 
               
               
                 Mean Entorhinal 
                 ApoC3 
                 −0.217 
                 0.00 
                 168 
               
               
                 Thickness 
                 ApoA1 
                 −0.209 
                 0.01 
                 169 
               
               
                   
                 ApoE 
                 −0.198 
                 0.01 
                 169 
               
               
                   
                 Transthyretin 
                 −0.154 
                 0.05 
                 158 
               
               
                 Whole Brain Volume 
                 ApoE 
                 −0.19 
                 0.02 
                 145 
               
               
                   
                 ApoA1 
                 −0.19 
                 0.02 
                 145 
               
               
                   
                 Aβ40 
                 0.17 
                 0.04 
                 141 
               
               
                   
               
               
                 MRI: magnetic resonance imaging; 
               
               
                 *Pearson&#39;s correlation coefficient. 
               
             
          
         
       
     
         [0299]    The inventors then set out to identify a set of proteins that together would predict disease pathology in a pre-disease group of MCI as represented by the surrogate of hippocampal atrophy. Using multiple linear regression analysis, six proteins (Clusterin, RANTES, NSE, TTR, VCAM-1 and SAP) were identified as able to predict 19.5% (p=0.006) of hippocampal volume in the MCI group. A different combination of proteins associated with atrophy in the AD group was observed. Using linear regression analysis, 7 proteins (APOA1, A1AT, ApoC3, BDNF, Aβ40, PAI-1 and NSE) in the AD group were identified as able to predict 11.9% (p=0.039) of hippocampal volume. 
         [0300]    Surprisingly, an association of clusterin with greater atrophy, and a trend to a decrease in RANTES, NSE and TTR levels in the MCI group was found. Unexpectedly, in the AD group A1AT, NSE, ApoC3, ApoA1, ApoE, BDNF plasma levels were increased alongside greater atrophy. 
       Plasma Proteins Clinical Cognition and Cognitive Decline 
       [0301]    The relationship between these proteins and disease severity as measured by cognition at the time of sampling and by rate of change in cognition was examined. In the MCI group at the time of sampling, both ApoE and CRP negatively correlated with MMSE (ApoE: r=−0.150, p=0.001; CRP: r=−0.186, p=0.007). 
         [0302]    In the AD group at the time of sampling ApoE, CFH, NCAM, AB40, A1AcidG and clusterin were all negatively correlated with MMSE (ApoE: r=−0.150, p=0.001; CFH: r=−0.104, p=0.026; NCAM: r=−0.114, p=0.014; AB40: r=−0.161, p=0.001; A1AcidG: r=−0.135, p=0.004; clusterin: r=−0.135, p=0.004). 
         [0303]    Furthermore, the association of the proteins with longitudinal prospective MMSE changed in the AD group. Three novel proteins, NCAM, sRAGE and ICAM were significantly associated with the MMSE cognitive slope. NCAM and sRAGE were both negatively correlated with the rate of decline in cognition as measured by change in MMSE (NCAM: r=−0.129, p=0.0018; sRAGE: r=−0.125, p=0.029) whereas ICAM was positively correlated (ICAM: r=0.108, p=0.047). 
       Protein Biomarkers to Predict Disease Conversion of MCI to AD 
       [0304]    A number of proteins, previously identified as putative markers of AD, correlated with disease pathology, whether measured by MRI or by severity of cognitive impairment not only in disease but in the pre-disease state of MCI. These proteins were believed reflecting pathological load and hence thought to be markers predictive of conversion from pre-disease states such as MCI to clinical dementia. To confirm this, a machine learning approach was used (Naive Bayes Simple) with feature selection on a training dataset and subsequently on the relevant test set. A total of 220 samples were analysed (N=220; MCI nc =169 and MCI c =51). The average time of conversion of MCI to AD was 375 days (SD=23 days). Ten proteins (TTR, Clusterin, Cystatin C, A1AcidG, ICAM1, CC4, PEDF, A1AT, RANTES, ApoC3) plus APOE genotype were observed to have the greatest predictive power (Table 3). The 
         [0305]    Receiving Operating Characteristics Area Under the Curve, also known as ROC AUCs, from the test set were 0.78 (protein only) and 0.84 (protein+APOE genotype) (Table 5). In order to test the accuracy, three different sensitivity cut-off points at 30%, 50% and 85% were investigated. The optimal accuracy was observed at the 85% sensitivity with the test achieving an accuracy of 87% with a specificity of 88% (in bold in Table 5). 
         [0000]    
       
         
               
             
               
               
               
               
               
               
               
               
             
           
               
                 TABLE 5 
               
             
             
               
                   
               
               
                 Characteristics of the ROC curve for the full dataset 
               
             
          
           
               
                   
                 Sensi-  
                   
                   
                   
                   
                   
                   
               
               
                 Class- 
                 tivity 
                   
                   
                   
                   
                   
                   
               
               
                 ification  
                 cut- 
                 SN  
                 SP  
                 PPV  
                 NPV  
                 ACC  
                   
               
               
                 model 
                 off % 
                 % 
                 % 
                 % 
                 % 
                 % 
                 ROC 
               
               
                   
               
               
                 Protein + 
                 30 
                 30.8 
                 92.9    
                 57.1 
                 81.3 
                 87.2 
                 0.84 
               
               
                 APOE 
                   
                   
                   
                   
                   
                   
                   
               
               
                 Protein  
                 30 
                 30.8 
                 92.9    
                 57.1 
                 81.3 
                 87.2 
                 0.78 
               
               
                 only 
                   
                   
                   
                   
                   
                   
                   
               
               
                 Protein + 
                 50 
                 53.9 
                 88.1    
                 58.3 
                 86.1 
                 80.0 
                 0.84 
               
               
                 APOE 
                   
                   
                   
                   
                   
                   
                   
               
               
                 Protein  
                 50 
                 43.8 
                 84.6% 
                 53.9 
                 78.6 
                 72.7 
                 0.78 
               
               
                 only 
                   
                   
                   
                   
                   
                   
                   
               
               
                   Protein  + 
                 
                   85 
                 
                 
                   84.6 
                 
                   88.1     
                 
                   68.8 
                 
                 
                   94.9 
                 
                 
                   87.2 
                 
                 
                   0.84 
                 
               
               
                 
                   APOE 
                 
                   
                   
                   
                   
                   
                   
                   
               
               
                 Protein  
                 85 
                 84.6 
                 71.4    
                 47.8 
                 93.8 
                 74.5 
                 0.78 
               
               
                 only 
               
               
                   
               
               
                 Sensitivity (SN), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), Accuracy (ACC) and ROC for the protein and APOE classifier. 
               
             
          
         
       
     
         [0306]    It was then investigated whether combining structural MRI data with the 10 markers observed in the MCI conversion data would improve classification accuracy. MRI brain measures for a subset of subjects were combined with the protein data and the Naive Bayes algorithm was applied. In this smaller dataset the proteins alone performed very well when tested at the 3 different sensitivity cut-off (Cut-off: 
         [0307]    accuracy; 30%: 83.33%, 50%: 80.56%, 85%: 69.44%). The addition of MRI data only marginally improved the accuracy at the 2 cut-off points (Cut-off: accuracy 30%: 86%; 50%: 83%). However at the 85% sensitivity cut-off the accuracy reduced to 64%. The ROC curve, sensitivity, specificity, positive and negative predictive values of each classifier is shown in Table 6. 
         [0000]    
       
         
               
             
               
               
               
               
               
               
               
               
             
           
               
                 TABLE 6 
               
             
             
               
                   
               
               
                 Characteristics of the ROC curve for the subset with protein 
               
               
                 plus MRI imaging data 
               
             
          
           
               
                   
                 Sensi- 
                   
                   
                   
                   
                   
                   
               
               
                 Class- 
                 tivity 
                   
                   
                   
                   
                   
                   
               
               
                 ification 
                 cut- 
                 SN  
                 SP  
                 PPV  
                 NPV  
                 ACC  
                   
               
               
                 model 
                 off % 
                 % 
                 % 
                 % 
                 % 
                 % 
                 ROC 
               
               
                   
               
               
                 Protein +  
                 30 
                 33.3 
                 96.7 
                 66.7 
                 87.9 
                 86.1 
                 0.75 
               
               
                 APOE + MRI 
                   
                   
                   
                   
                   
                   
                   
               
               
                 Protein only 
                 30 
                 33.3 
                 93.3 
                 50.0 
                 87.5 
                 83.3 
                 0.82 
               
               
                 MRI only 
                 30 
                 33.3 
                 80.0 
                 25.0 
                 85.7 
                 72.2 
                 0.54 
               
               
                 Protein +  
                 50 
                 50.0 
                 90.0 
                 50.0 
                 90.0 
                 83.3 
                 0.75 
               
               
                 APOE + MRI 
                   
                   
                   
                   
                   
                   
                   
               
               
                 Protein only 
                 50 
                 50.0 
                 86.7 
                 42.9 
                 89.7 
                 80.6 
                 0.82 
               
               
                 MRI only 
                 50 
                 50.0 
                 63.3 
                 21.3 
                 86.4 
                 61.1 
                 0.54 
               
               
                 Protein +  
                 85 
                 83.3 
                 60.0 
                 29.4 
                 94.7 
                 63.9 
                 0.75 
               
               
                 APOE + MRI 
                   
                   
                   
                   
                   
                   
                   
               
               
                 Protein only 
                 85 
                 83.3 
                 66.7 
                 33.3 
                 95.2 
                 69.4 
                 0.82 
               
               
                 MRI only 
                 85 
                 83.3 
                 13.3 
                 16.1 
                 80.0 
                 25.0 
                 0.54 
               
               
                   
               
               
                 Sensitivity (SN), specificity (SP), positive predictive value (PPV), negative predictive value (NPV) Accuracy (ACC) and ROC for the protein and APOE classifier. 
               
             
          
         
       
     
       Concentration Cut-Offs Points for Proteins Predicting MCI to AD 
       [0308]    Individual protein cut-off values were derived for the 10 markers identified by feature selection in the MCI conversion model. These are as follows; ApoC3 105.5 ug/ml, TTR 222 ug/ml, A1AT 9.5 ug/ml, PEDF 10.7 ug/ml, CC4 78.5 ug/ml, ICAM-1 99.72 ng/ml, RANTES 33.8 ng/ml, A1AcidG 768.3 ug/ml, cystatin C 3.21 ug/ml, clusterin 402ug/ml. Logistic regression analysis was used to test the 10 markers cut-off concentrations and APOE genotype, the overall model accuracy was 94.9%, with a sensitivity 73.6%, and specificity of 94.9% when using the full dataset. 
       Discussion 
       [0309]    Previous studies using data-driven pan-proteomic approaches have identified a number of proteins as diagnostic 1 , progression 7, 20  and pathology markers 18 . The advent of high throughput multiplex platforms facilitates the replication of such findings and raises the potential of high throughput multiplexed markers for use in clinical practice and in clinical trials 21-22 . Here the inventors have determined if any of those putative biomarkers are associated with early disease stages and might have value as prognostic markers. Using MRI as a surrogate of disease pathology, a number of markers associated with atrophy either early in the disease process (MCI) or in established dementia were found. 
         [0310]    This approach of using MRI as a proxy for in vivo pathology has previously been shown to be useful in biomarker discovery, such as identifying clusterin as a putative marker of disease 7 . 
         [0311]    In the present study, however, it was surprisingly found that RANTES, NSE and transthyretin, in addition to clusterin, are associated with cortical atrophy in the MCI group, with clusterin showing the strongest correlation with all brain regions assessed. 
         [0312]    RANTES, also known as chemokine ligand 5 (CCL5), is a protein known to have an active role in recruiting leukocytes into inflammatory sites. A negative association was unexpectedly found between RANTES and ventricular volume, suggesting a decreased level with increased pathology; this is the opposite to previous reports in neurodegeneration 24-26 . Without wishing to be bound by theory, it is believed that the association of the protein RANTES with atrophy only in MCI and not in AD may be due to a decrease early in disease process followed by a later increase. Similar findings have been previously reported for other proteins 27 . 
         [0313]    This atypical behaviour was surprisingly found in association with pathology for the neuron-specific enolase (NSE) protein. This protein is thought to be a good indicator of acute neuronal damage 28-29  and has been associated with AD in some but not all previous studies 30 31 . In contrast, an unanticipated positive association between NSE and volume of hippocampus and whole brain was found in MCI subjects. However, in the AD group the positive association was instead found with ventricular volume. This inverse relationship with atrophy in pre-disease and then positive correlation with atrophy in disease suggests that, like RANTES, NSE might be decreased in early disease stages (i.e. MCI) with a rebound elevation in established AD. 
         [0314]    In established AD, a different set of proteins associated with pathology as measured by atrophy on MRI are found. A number of these belong to the group of apolipoproteins (ApoE, ApoC3 and ApoA1). All of these proteins are found to be negatively associated with hippocampal, entorhinal cortical and whole brain volumes. The roles of apolipoproteins in neurodegenerative disorders have been studied extensively since the discovery that APOE was a major susceptibility gene for AD 32-33 . In the peripheral system, ApoE serves the transport of triglycerides, phospholipids and cholesterol into cells 34 . The literature on ApoE is conflicting with some groups reporting lower ApoE in AD 35-36 , with others showing increased levels 37-38 . ApoE plasma measurements derived from this study have been recently published and are in agreement with the findings from the North American Alzheimer&#39;s Disease Neuroimaging Initiative which shows an APOE genotype effect 39 . 
         [0315]    Accordingly, this represents the first time that a panel of markers in plasma, associated with neuroimaging measures of the disease, has been identified as a biomarker panel of early disease severity. Moreover, a set of ten markers that can prospectively predict disease conversion from MCI to AD within a year (12 months) of test sampling is disclosed herein. This time-frame is crucial as it is important to identify early the subset of MCI subjects that will progress to clinical AD, as eventually all converters will progress to AD given time. These results are supported by further evidence from other studies that plasma proteins can have a role in early disease detection with inflammatory proteins in particular identified as possible predictors of conversion from MCI  23, 40 . Combining MRI with protein measures did not improve predictive power in contrast to previous studies where CSF (not plasma) marker performance was improved in combination with MRI 41 . 
         [0316]    In summary, three large multicentre cohorts coupled with multiplex protein assays lead to validate a plasma biomarker panel reflecting disease pathology and for predicting disease progression. Such a biomarker panel might have considerable value in triaging patients with early memory disorders to yet more specific but more invasive and costly approaches such as molecular markers in CSF and on PET imaging in clinical trials and possibly in clinical practice. 
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