Abstract

Bipolar disorder (BPD) and major depressive disorder (MDD) are primary major mood disorders. Recent studies suggest that they share certain psychopathological features and common risk genes, but unraveling the full genetic architecture underlying the risk of major mood disorders remains an important scientific task. The public genome-wide association study (GWAS) data sets offer the opportunity to examine this topic by utilizing large amounts of combined genetic data, which should ultimately allow a better understanding of the onset and development of these illnesses. Genome-wide meta-analysis was performed by combining two GWAS data sets on BPD and MDD (19,637 cases and 18,083 controls), followed by replication analyses for the loci of interest in independent 12,364 cases and 76,633 controls from additional samples that were not included in the two GWAS data sets. The single-nucleotide polymorphism (SNP) rs10791889 at 11q13.2 was significant in both discovery and replication samples. When combining all samples, this SNP and multiple other SNPs at 2q11.2 (rs717454), 8q21.3 (rs10103191), and 11q13.2 (rs2167457) exhibited genome-wide significant association with major mood disorders. The SNPs in 2q11.2 and 8q21.3 were novel risk SNPs that were not previously reported, and SNPs at 11q13.2 were in high LD with potential BPD risk SNPs implicated in a previous GWAS. The genome-wide significant loci at 2q11.2 and 11q13.2 exhibited strong effects on the mRNA expression of certain nearby genes in cerebellum. In conclusion, we have identified several novel loci associated with major mood disorders, adding further support for shared genetic risk between BPD and MDD. Our study highlights the necessity and importance of mining public data sets to explore risk genes for complex diseases such as mood disorders.

Highlights

  • Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China 2Department of Pharmacology, Provincial Key Laboratory of Pathophysiology, Ningbo University School of Medicine, Ningbo, Zhejiang, ChinaFull list of author information is available at the end of the articleMajor mood disorders, including bipolar disorder (BPD) and major depressive disorder (MDD), are leading causes of disability worldwide that account for a substantial proportion of productivity loss, life quality impairment, poor physical health, and deaths by suicide[1,2]

  • We first conducted a meta-analysis of a BPD genomewide association study (GWAS) and a MDD GWAS comprising of 19,637 cases and 18,083 controls of European ancestry

  • After quality control exclusions, ~1.3 million single-nucleotide polymorphism (SNP) with minor allele frequency (MAF) > 5% were meta-analyzed in the discovery stage using an appropriate effect model selected according to the heterogeneity test results

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Summary

Introduction

Major mood disorders, including bipolar disorder (BPD) and major depressive disorder (MDD), are leading causes of disability worldwide that account for a substantial proportion of productivity loss, life quality impairment, poor physical health, and deaths by suicide[1,2]. Though the current GWAS of mood disorders have identified fewer genome-wide significant genes than expected, their genome-wide statistical results have been (completely or partially) released publicly and these are valuable resources for further larger-scale GWAS meta-analysis. This systematic utilization of these public GWAS resources offers a great opportunity to perform genome-wide screens of the underlying shared genetic factors and will provide valuable information that will benefit other studies of major mood disorders. This study highlights that there are undiscovered “treasures” underlying the current mood disorder GWAS data sets, and illustrates an example of utilizing available public resources to further dissect the genetic basis of mood disorders

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