SynapDx Autism Gene Expression Analysis Study (STORY)
Condition: Autism
MeSH terms: Autistic Disorder; Autism Spectrum Disorder
Study type: Observational

Summary: 
      This study will prospectively enroll approximately 880 children, at least 18 months and less
      than 60 months of age, who have been referred to a pediatric developmental evaluation center.
      Enrolled children will have blood drawn for RNA gene expression analysis and optionally for
      metabolite, lipid and DNA analysis and undergo a clinical evaluation to determine the
      presence or absence of a diagnosis of ASD.

      The primary objective of this study is:

      - To develop an algorithm to classify blood RNA gene expression patterns to maximize
      agreement between the classification and a clinical assessment of presence or absence of
      Autism Spectrum Disorders (ASD).

      The secondary objectives of this study are:

        -  To develop an algorithm to classify plasma metabolite and/or lipid profiles in such a
           way as to maximize agreement between the classification and a clinical assessment of
           presence or absence of ASD.

        -  To prospectively assess the clinical sensitivity and specificity of the plasma
           metabolite and/or lipid profile classification algorithm in a separate population
           consisting of children referred to a developmental evaluation clinic for a possible
           developmental disorder (DD).

        -  To evaluate clinical sensitivity and specificity of various combinations of gene
           expression signature, metabolite and/or lipid signatures, and presence of ASD-associated
           genetic variation detected by chromosomal microarray analysis (CMA) or sequencing
           protein-coding regions of the genome.
    

Detailed description: 
      The primary aim of this study is to define a gene expression signature indicative of ASD and
      to establish its clinical sensitivity and specificity. Clinician diagnosis of ASD will be
      made using DSM-5 as the reference standard instrument. The widely used diagnostic instrument
      Autism Diagnostic Observation Schedule (ADOS-2) is a typical component of the clinical
      assessment for a child diagnosed with ASD and this evaluation will be performed on all study
      participants. Secondary aims of this study are (1) to define metabolite and lipid signatures
      indicative of ASD and establish their clinical sensitivity and specificity and (2) to
      determine clinical sensitivity and specificity of various combinations of gene expression
      signature, metabolite and/or lipid signatures, and presence of ASD-associated genetic
      variation detected by CMA and sequencing protein-coding regions of the genome

      Analyses: Details of the analysis will be specified in a Statistical Analysis Plan (SAP),
      which will include procedures for handling outliers, missing data, and differences across
      sites. The SAP will be reviewed and approved by a committee of Principal Investigators (PIs)
      before unblinding of the validation set.

      Primary analyses: The primary outcomes of the study will be the estimates of the clinical
      sensitivity and specificity of the SDX-002 test to classify subjects according to DSM-5 ASD
      diagnosis, with associated 95% confidence intervals. Sensitivity and specificity will be
      assessed on the Validation Phase population based on agreement with the clinical diagnosis of
      presence or absence of Autism Spectrum Disorder by DSM-5 (published May 2013).

      The gene expression signature will be trained on the 500 subject Development Phase set, using
      5-fold cross validation over the results of several machine learning algorithms, including
      partial least squares, support vector machines, and boosted decision trees. The training
      procedure will generate estimated ROC curves for each method, as well as confidence intervals
      for the area under the curve (AUC). The final choice of a machine-learning algorithm will be
      based on AUC, as well as on the estimated performance at the chosen operating point on the
      ROC curve. The operating point will be chosen to provide high sensitivity at an acceptable
      specificity.

      Secondary analyses: In the majority of patients enrolled to date, consent was obtained for
      collection of an optional bio-repository sample. The intended analysis of the bio-repository
      samples has now been established (see also, secondary objectives listed above). The
      metabolomic and lipomic signatures will be similarly assessed on the subset of the 500
      subjects in the Development Phase set who consent to a bio-repository sample. In addition to
      the gene expression signature, metabolite and/or lipid signatures and DNA analysis will be
      combined with the gene expression signature in various configurations and the impact of these
      additional measures on clinical sensitivity and specificity will be evaluated. If these
      additional metabolomic/lipomic signatures and/or DNA analyses improve test performance, these
      elements may be included in the SDX-002 assay.

      Sensitivity and specificity the final SDX-002 assay will also be assessed among
      subpopulations using demographic information and the results of developmental testing. There
      are likely to be few subjects in many of these subpopulations and caution will be used in
      interpreting the results. Planned subpopulation analyses include gender, age, ethnicity, ASD
      DSM-IV-TR diagnostic subcategory, DSM-5 ASD severity level (social communication and
      restricted interests/repetitive behaviors) and ADOS-2 scores.
    

Observational model: Cohort
Time perspective: Prospective
Sampling method: Probability Sample
Study population: 
        Children 18 months to less than 60 months referred to a developmental evaluation center for
        evaluation of a possible developmental disorder.
      
Biospecimen description: 
      Peripheral blood
    
Keywords: Autism; Autism Spectrum Disorders; RNA; Gene expression; Developmental Delay; Metabolites; DNA