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Active NON-SBIR/STTR RPGS NIH (US)

Expanding Genetic Understanding of Depression, Anxiety, and their Treatments

$7.07M USD

Funder NATIONAL INSTITUTE OF MENTAL HEALTH
Recipient Organization Yale University
Country United States
Start Date Aug 01, 2024
End Date Feb 28, 2029
Duration 1,672 days
Number of Grantees 2
Roles Principal Investigator; Co-Investigator
Data Source NIH (US)
Grant ID 10980010
Grant Description

ABSTRACT Major depressive disorder (MDD) and anxiety disorders (ANX) are genetically related traits that cause very substantial morbidity and mortality worldwide. The large, diverse, and actively expanding Veterans Affairs (VA) Million Veteran Program (MVP) is an ideal setting for study of these problems. We have identified risk loci

for MDD and ANX in large genomewide association studies (GWAS), but the size and power of the MVP dataset, and other datasets worldwide, continue to grow, and considerable work still needs to be done to develop and maximize the scientific value of the MVP for these traits, and in relation to other datasets available

worldwide. The MVP sample (currently at >900,000 participants) is continuing to expand, and with more subjects there will be increased power to map relevant traits, including constituent traits (i.e., social phobia). Extensive phenotype data are available. MVP data releases for the coming year will include whole genome

sequence (WGS) data that will be available for novel analyses; and array data increasing marker density for non-European populations. Together, availability of these data presents an enormous opportunity. We will make our GWAS data available via dbGAP and make further use of it for the present project

We will conduct gene-discovery analysis and leverage polygenicity to dissect the predisposition to MDD, ANX (and specific anxiety and anxiety -related disorders and subphenotypes which may have distinct as well as overlapping genetic risk). We will also study medication response genetics and traits phenotypically associated

with MDD and ANX in the MVP sample, e.g. cardiovascular disease, using approaches that permit testing of likely causality among these correlated traits (e.g., Mendelian Randomization [MR]). We will use genomic structural equation modeling (gSEM) to investigate the underlying genetic relationships of ANX, MDD, and

other related psychiatric and medical traits. We will complete polygenic risk score (PRS) analysis within MVP and with respect to external samples using MVP data. WGS data will facilitate study of rare and structural variants. As the VA has electronic health record (EHR) data going back to the 1990’s and the MVP has EHR

linkage, longitudinal and repeated measures can be constructed. We will replicate findings in collaboration with other consortia such as the Psychiatric Genomics Consortium MDD (PGC-MDD) and anxiety (PGC-ANX) working groups (we participate presently). Considering the MVP and other samples we will be able to access,

we predict that case numbers of both traits will increase 2-3 fold over the next five years, greatly increasing power for locus discovery and thus for post-GWAS analyses. Finally, we will investigate these traits in non- European populations including African Americans and Latinx – both particularly well-represented in the MVP

sample -- and other populations. Increased understanding of the underlying genetics of these traits should ultimately lead to repositioning of currently-approved medications and identification of novel treatment targets.

All Grantees

Yale University

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