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Strength of functional signature correlates with effect size in autism

Sara Ballouz, Jesse Gillis
doi: https://doi.org/10.1101/043422
Sara Ballouz
1The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
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Jesse Gillis
1The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
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Abstract

Background Disagreements over genetic signatures associated with disease have been particularly prominent in the field of psychiatric genetics, creating a sharp divide between disease burdens attributed to common and rare variation, with study designs independently targeting each. Meta-analysis within each of these study designs is routine, whether using raw data or summary statistics, but combining results across study designs is atypical. However, tests of functional convergence are used across all study designs, where candidate gene sets are assessed for overlaps with previously known properties. This suggests one possible avenue for combining not study data, but the functional conclusions that they reach.

Method In this work, we test for functional convergence in autism spectrum disorder (ASD) across different study types, and specifically whether the degree to which a gene is implicated in autism is correlated with the degree to which it drives functional convergence. Because different study designs are distinguishable by their differences in effect size, this also provides a unified means of incorporating the impact of study design into the analysis of convergence.

Results We detected remarkably significant positive trends in aggregate (p < 2.2e-16) with 14 individually significant properties (FDR<0.01), many in areas researchers have targeted based on different reasoning, such as the fragile X mental retardation protein (FMRP) interactor enrichment (FDR 0.003). We are also able to detect novel technical effects and we see that network enrichment from protein-protein interaction data is heavily confounded with study design, arising readily in control data.

Conclusions We see a convergent functional signal for a subset of known and novel functions in ASD from all sources of genetic variation. Meta-analytic approaches explicitly accounting for different study designs can be adapted to other diseases to discover novel functional associations and increase statistical power.

  • Abbreviations

    ASD
    autism spectrum disorder
    CNV
    copy number variant
    FDR
    false discovery rate
    FMRP
    fragile X mental retardation protein
    FWER
    family-wise error rate
    GO
    Gene Ontology
    GWAS
    genome-wide association studies
    HI
    happloinsufficiency
    LoF
    Loss-of-function mutations
    PGC
    Psychiatric Genomics Consortium
    PPI
    protein-protein interactions
    PPIN
    protein-protein interaction network
    RVIS
    Residual Variation Intolerance Score
    SNP
    single nucleotide polymorphism
    SNV
    single nucleotide variant
    SSC
    Simons Simplex Collection
    WES
    whole exome sequencing
    WGS
    whole genome sequencing
  • Copyright 
    The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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    Posted February 21, 2017.
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    Strength of functional signature correlates with effect size in autism
    Sara Ballouz, Jesse Gillis
    bioRxiv 043422; doi: https://doi.org/10.1101/043422
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    Strength of functional signature correlates with effect size in autism
    Sara Ballouz, Jesse Gillis
    bioRxiv 043422; doi: https://doi.org/10.1101/043422

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