Format

Send to

Choose Destination
Schizophr Bull. 2015 Nov;41(6):1294-308. doi: 10.1093/schbul/sbv017. Epub 2015 Mar 10.

Systematic Integration of Brain eQTL and GWAS Identifies ZNF323 as a Novel Schizophrenia Risk Gene and Suggests Recent Positive Selection Based on Compensatory Advantage on Pulmonary Function.

Author information

1
Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China; These authors contributed equally to this work. luoxiongjian@mail.kiz.ac.cn.
2
Department of Biomedicine and Centre for Integrative Sequencing (iSEQ), Aarhus University, 8000 Aarhus C, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus and Copenhagen, Denmark; Department of Genomics, Life & Brain Center, and Institute of Human Genetics, University of Bonn, Bonn, Germany; These authors contributed equally to this work.
3
Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD;
4
First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China;
5
Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty of Mannheim, University of Heidelberg, Mannheim, Germany;
6
Department of Biomedicine and Centre for Integrative Sequencing (iSEQ), Aarhus University, 8000 Aarhus C, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus and Copenhagen, Denmark; Research Department, Psychiatric Hospital, Aarhus University Hospital, Aarhus, Denmark;
7
Department of Biomedicine and Centre for Integrative Sequencing (iSEQ), Aarhus University, 8000 Aarhus C, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus and Copenhagen, Denmark;
8
Center for Biomarker Research and Personalized Medicine, Virginia Commonwealth University;
9
The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus and Copenhagen, Denmark; Centre for Psychiatric Research, Aarhus University Hospital, Risskov, Denmark;
10
The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus and Copenhagen, Denmark; National Centre for Register-based Research, Aarhus University, Aarhus, Denmark;
11
Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, SC;
12
Department of Genomics, Life & Brain Center, and Institute of Human Genetics, University of Bonn, Bonn, Germany;
13
Division of Medical Genetics, Department of Biomedicine, University Basel, Basel, Switzerland; Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany;
14
Department of Psychiatry and Psychotherapy, University Medical Center Georg-August-Universität, 37075 Goettingen, Germany; Institute of Psychiatric Phenomics and Genomics (IPPG), Ludwig-Maximilians-University Munich;
15
State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China;
16
Departments of Biomedical Informatics and Psychiatry, Vanderbilt University School of Medicine, Nashville, TN 37232, USA;
17
Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China; CAS Center for Excellence in Brain Science, Chinese Academy of Sciences, Shanghai, 200031, China.

Abstract

Genome-wide association studies have identified multiple risk variants and loci that show robust association with schizophrenia. Nevertheless, it remains unclear how these variants confer risk to schizophrenia. In addition, the driving force that maintains the schizophrenia risk variants in human gene pool is poorly understood. To investigate whether expression-associated genetic variants contribute to schizophrenia susceptibility, we systematically integrated brain expression quantitative trait loci and genome-wide association data of schizophrenia using Sherlock, a Bayesian statistical framework. Our analyses identified ZNF323 as a schizophrenia risk gene (P = 2.22×10(-6)). Subsequent analyses confirmed the association of the ZNF323 and its expression-associated single nucleotide polymorphism rs1150711 in independent samples (gene-expression: P = 1.40×10(-6); single-marker meta-analysis in the combined discovery and replication sample comprising 44123 individuals: P = 6.85×10(-10)). We found that the ZNF323 was significantly downregulated in hippocampus and frontal cortex of schizophrenia patients (P = .0038 and P = .0233, respectively). Evidence for pleiotropic effects was detected (association of rs1150711 with lung function and gene expression of ZNF323 in lung: P = 6.62×10(-5) and P = 9.00×10(-5), respectively) with the risk allele (T allele) for schizophrenia acting as protective allele for lung function. Subsequent population genetics analyses suggest that the risk allele (T) of rs1150711 might have undergone recent positive selection in human population. Our findings suggest that the ZNF323 is a schizophrenia susceptibility gene whose expression may influence schizophrenia risk. Our study also illustrates a possible mechanism for maintaining schizophrenia risk variants in the human gene pool.

KEYWORDS:

ZNF323; association; eQTL; hippocampus; positive selection; schizophrenia

PMID:
25759474
PMCID:
PMC4601704
DOI:
10.1093/schbul/sbv017
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Silverchair Information Systems Icon for PubMed Central
Loading ...
Support Center