Identification of a Risk Locus at 7p22.3 for Schizophrenia and Bipolar Disorder in East Asian Populations.

Wenqiang Li,Yongfeng Yang,Xiao Xiao,Jiewei Liu,Xi Su,Yan Zhang,Chu-Yi Zhang,Fanglin Guan,Ming Li,Qing Liu,Luxian Lv,Luwen Zhang,Xiong-Jian Luo,Minglong Shao

doi:10.3389/fgene.2021.789512

Abstract

Background: Shared psychopathological features and mechanisms have been observed between schizophrenia (SZ) and bipolar disorder (BD), but their common risk genes and full genetic architectures remain to be fully characterized. The genome-wide association study (GWAS) datasets offer the opportunity to explore this scientific question using combined genetic data from enormous samples, ultimately allowing a better understanding of the onset and development of these illnesses. Methods: We have herein performed a genome-wide meta-analysis in two GWAS datasets of SZ and BD respectively (24,600 cases and 40,012 controls in total, discovery sample), followed by replication analyses in an independent sample of 4,918 SZ cases and 5,506 controls of Han Chinese origin (replication sample). The risk SNPs were then explored for their correlations with mRNA expression of nearby genes in multiple expression quantitative trait loci (eQTL) datasets. Results: The single nucleotide polymorphisms (SNPs) rs1637749 and rs3800908 at 7p22.3 region were significant in both discovery and replication samples, and exhibited genome-wide significant associations when combining all East Asian SZ and BD samples (29,518 cases and 45,518 controls). The risk SNPs were also significant in GWAS of SZ and BD among Europeans. Both risk SNPs significantly predicted lower expression of MRM2 in the whole blood and brain samples in multiple datasets, which was consistent with its reduced mRNA level in the brains of SZ patients compared with normal controls. The risk SNPs were also associated with MAD1L1 expression in the whole blood sample. Discussion: We have identified a novel genome-wide risk locus associated with SZ and BD in East Asians, adding further support for the putative common genetic risk of the two illnesses. Our study also highlights the necessity and importance of mining public datasets to explore risk genes for complex psychiatric diseases.

Highlights

Within family members of a proband with schizophrenia (SZ), there is normally an increased prevalence of bipolar disorder (BD), and vice versa (Berrettini, 2000)
Recent analyses suggested a substantial overlap of genetic risk factors between SZ and BD (Lichtenstein et al, 2009), and genome-wide association studies (GWAS) have revealed multiple genomic loci showing significant associations with both illnesses in European populations (Ruderfer et al, 2014; Bipolar Disorder Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2018), such as loci of CACNA1C, VRK2, TRANK1, ZNF804A, NCAN and the extended MHC region (Ripke et al, 2020; Mullins et al, 2021)
0.8) from the SZ GWAS in East Asian populations (22,778 cases and 35,362 controls) (Lam et al, 2019), and conducted a metaanalysis combining these samples with the non-overlapped BD

Summary

Introduction

Within family members of a proband with schizophrenia (SZ), there is normally an increased prevalence of bipolar disorder (BD), and vice versa (Berrettini, 2000). Recent analyses suggested a substantial overlap of genetic risk factors between SZ and BD (Lichtenstein et al, 2009), and genome-wide association studies (GWAS) have revealed multiple genomic loci showing significant associations with both illnesses in European populations (Ruderfer et al, 2014; Bipolar Disorder Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2018), such as loci of CACNA1C, VRK2, TRANK1, ZNF804A, NCAN and the extended MHC region (Ripke et al, 2020; Mullins et al, 2021). GWAS resources offer important opportunities to conduct genome-wide screenings of the shared genetic risk between SZ and BD, which may provide valuable insight for future studies (Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013; Ruderfer et al, 2014; Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2018; Cross-Disorder Group of the Psychiatric Genomics Consortium, 2019). The genome-wide association study (GWAS) datasets offer the opportunity to explore this scientific question using combined genetic data from enormous samples, allowing a better understanding of the onset and development of these illnesses

Methods

Results

Conclusion