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Generalization of Cortical Multivariate Genome-Wide Associations within and across Samples

bioRxiv, ISSN: 2692-8205
2021
  • 5
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Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    5
    • Citation Indexes
      5
      • CrossRef
        5

Article Description

Genome-Wide Association studies have typically been limited to single phenotypes, given that high dimensional phenotypes incur a large multiple comparisons burden: ~1 million tests across the genome times the number of phenotypes. Recent work demonstrates that a Multivariate Omnibus Statistic Test (MOSTest) is well powered to discover genomic effects distributed across multiple phenotypes. Applied to cortical brain MRI morphology measures, MOSTest has resulted in a drastic improvement in power to discover loci – a 10-fold increase in discovered loci compared to established approaches (min-P). One question that arises is how well these discovered loci replicate in independent data. Here we perform 10 -imes cross validation within 35,644 individuals from UK Biobank for imaging measures of cortical area, thickness and sulcal depth (>1,000 dimensionality for each). By deploying a replication method that aggregates discovered effects distributed across multiple phenotypes, termed PolyVertex Score (PVS), we demonstrate a higher replication yield and comparable replication rate of discovered loci for MOSTest (# replicated loci: 428-1,037, replication rate: 95-96%) in independent data when compared with the established min-P approach (# replicated loci: 30-71, replication rate: 70-84%). An out-of-sample generalization of discovered loci was conducted with a sample of 8,336 individuals from the Adolescent Brain Cognitive Development (ABCD) study, who are on average 50 years younger than UK Biobank individuals. We observe a higher replication yield and comparable replication rate of MOSTest compared to min-P. This finding underscores the importance of using multivariate techniques for both discovery and replication of high dimensional phenotypes in Genome-Wide Association studies.

Bibliographic Details

Robert J. Loughnan; Weiqi Zhao; Terry L. Jernigan; Anders M. Dale; Wesley K. Thompson; Chun Chieh Fan; Oleksandr Frei; Dennis van der Mer; Alexey A. Shadrin; Ole A. Andreassen; Clare E. Palmer; Carolina Makowski

Cold Spring Harbor Laboratory

Biochemistry, Genetics and Molecular Biology; Agricultural and Biological Sciences; Immunology and Microbiology; Neuroscience; Pharmacology, Toxicology and Pharmaceutics

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