medRxivGenetic & Genomic MedicinePreprint
Rare schizophrenia risk variant burden is conserved in diverse human populations
Dongjing LiuiD, Dara MeyeriD, Brian FennessyiD, Claudia FengiD, Esther ChengiD, Jessica JohnsoniD, You Jeong ParkiD, Marysia-Kolbe Rieder, Steven AscolilloiD, Agathe M. de PinsiD, Amanda L. DobbyniD, Dannielle S. LebovitchiD, Emily MoyaiD, Tan-Hoang NguyeniD, Lillian WilkinsiD, Arsalan HassaniD, Katherine E. BurdickiD, Joseph D. BuxbaumiD, Enrico DomeniciiD, Sophia FrangouiD, Annette M. HartmanniD, Dheeraj MalhotraiD, Carlos N. PatoiD, Michele T. PatoiD, Kerry James RessleriD, , Alexander W. CharneyiD
Abstract
Schizophrenia is a chronic mental illness that is amongst the most debilitating conditions encountered in medical practice. A recent landmark schizophrenia study of the protein-coding regions of the genome identified a causal role for ten genes and a concentration of rare variant signals in evolutionarily constrained genes1. This study -- and most other large-scale human genetic studies -- was mainly composed of individuals of European ancestry, and the generalizability of the findings in non-European populations is unclear. To address this gap in knowledge, we designed a custom sequencing panel based on current knowledge of the genetic architecture of schizophrenia and applied it to a new cohort of 22,135 individuals of diverse ancestries. Replicating earlier work, cases carried a significantly higher burden of rare protein-truncating variants among constrained genes (OR=1.48, p-value = 5.4 x 10-6). In meta-analyses with existing schizophrenia datasets totaling up to 35,828 cases and 107,877 controls, this excess burden was largely consistent across five continental populations. Two genes (SRRM2 and AKAP11) were newly implicated as schizophrenia risk genes, and one gene (PCLO) was identified as a shared risk gene for schizophrenia and autism. Overall, our results lend robust support to the rare allelic spectrum of the genetic architecture of schizophrenia being conserved across diverse human populations.
- organism: human
- assay: whole-exome sequencing
- research focus: differential expression
- approach: statistical model
- Citations
- 5
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