84. SCHEMA 3.0: INCREASING GENETIC DIVERSITY AND GENE DISCOVERY FOR RARE-VARIANT ANALYSIS OF SCHIZOPHRENIA

• Published in: European neuropsychopharmacology Vol. 75; p. S101
• Main Authors: Sealock, Julia, Neale, Benjamin
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2023
• ISSN: 0924-977X; 1873-7862
• DOI: 10.1016/j.euroneuro.2023.08.188

Schizophrenia is a severe psychiatric disorder, marked by hallucinations, delusions, and deterioration in cognitive function. Rare variant association scans (RVAS) are a powerful approach to identify specific genes associated with schizophrenia by leveraging variants predicted to disrupt protein function. In RVAS, ultra-rare variants (URVs) with predicted damaging effects are collapsed into a single gene-based test. The largest RVAS of schizophrenia to date from the SCHEMA consortium found 10 exome-wide significant genes. However, most of the SCHEMA samples are of European ancestry, limiting the generalizability of the results. The Stanley Global Neuropsychiatric Genetics Initiative (Stanley Global) and the Populations Underrepresented in Mental Illness Association Studies (PUMAS) are initiatives dedicated to increasing ancestral diversity in psychiatric genetics studies. We will present results from the first wave of Stanley Global and PUMAS data as well as RVAS results from combining new data with existing SCHEMA exomes. We sequenced the exomes of 32,286 cases and 43,908 controls from Central and South America (NeuroMex and Paisa), Africa (Neuro-GAP and Kenya-Prodromal), and Asia (BioX). Thus far, we have analyzed the exomes of 4,611 individuals of Admixed American ancestry (AMR, N cases = 2,351; N controls = 2,260). We assigned variants as protein-truncating variants (PTVs), damaging missense, or synonymous using the Ensembl Variant Effect Predictor (VEP). We restricted our analysis to URVs, defined as variants with minor allele count of less than or equal to five across the entire cohort. First, we determined if AMR schizophrenia cases exhibited enrichment of URVs compared to controls by regressing schizophrenia status on the number of URVs in constrained genes within each variant annotation class, controlling for sex and top five principal components of ancestry. Next, we assessed if AMR cases were enriched for URVs in genes previously identified by SCHEMA. Finally, we combined the AMR data with existing SCHEMA data to conduct an RVAS of ultra-rare PTVs in 27,002 cases and 83,023 controls. In the AMR samples, schizophrenia cases showed increased burden of damaging URVs, including PTVs (pvalue = 7 × 10-6, OR = 1.32) and damaging missense variants (pvalue = 0.026, OR = 1.09), consistent with previous SCHEMA results. Additionally, schizophrenia cases were enriched for PTVs (pvalue = 0.02, OR = 4.18) and damaging missense variants (pvalue = 0.36, OR = 1.26) within previously identified SCHEMA genes. The RVAS replicated previously identified schizophrenia risk genes, including SETD1A, SP4, and XPO7. Increasing genetic diversity of exome samples will provide a more complete understanding of the genetic architecture of schizophrenia as well as increase equity within genetic research. In a cohort of AMR samples, we have so far shown schizophrenia cases have increased URVs compared to controls, consistent with previous results of largely European ancestry samples and previously identified schizophrenia-associated genes are enriched for URVs among schizophrenia cases. We plan to incorporate incoming data with existing data to enable the largest multi-ancestry RVAS of schizophrenia of 77,620 cases and 155,367 controls.