Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration

Timothy Reynolds, Emma C. Johnson, Spencer B. Huggett, Jason A. Bubier, Rohan H.C. Palmer, Arpana Agrawal, Erich J. Baker, Elissa J. Chesler

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Genome-wide association studies and other discovery genetics methods provide a means to identify previously unknown biological mechanisms underlying behavioral disorders that may point to new therapeutic avenues, augment diagnostic tools, and yield a deeper understanding of the biology of psychiatric conditions. Recent advances in psychiatric genetics have been made possible through large-scale collaborative efforts. These studies have begun to unearth many novel genetic variants associated with psychiatric disorders and behavioral traits in human populations. Significant challenges remain in characterizing the resulting disease-associated genetic variants and prioritizing functional follow-up to make them useful for mechanistic understanding and development of therapeutics. Model organism research has generated extensive genomic data that can provide insight into the neurobiological mechanisms of variant action, but a cohesive effort must be made to establish which aspects of the biological modulation of behavioral traits are evolutionarily conserved across species. Scalable computing, new data integration strategies, and advanced analysis methods outlined in this review provide a framework to efficiently harness model organism data in support of clinically relevant psychiatric phenotypes.

Original languageEnglish
Pages (from-to)86-97
Number of pages12
JournalNeuropsychopharmacology
Volume46
Issue number1
DOIs
StatePublished - Jan 2021

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