Abstract
Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and a leading cause of disability worldwide. Though recent genome-wide association studies (GWAS) have identified multiple risk variants for MDD, how these variants confer MDD risk remains largely unknown. Here we systematically characterize the regulatory mechanism of MDD risk variants using a functional genomics approach. By integrating chromatin immunoprecipitation sequencing (ChIP-Seq) (from human brain tissues or neuronal cells) and position weight matrix (PWM) data, we identified 34 MDD risk SNPs that disrupt the binding of 15 transcription factors (TFs). We verified the regulatory effect of the TF binding–disrupting SNPs with reporter gene assays, allelic-specific expression analysis, and CRISPR-Cas9-mediated genome editing. Expression quantitative trait loci (eQTL) analysis identified the target genes that might be regulated by these regulatory risk SNPs. Finally, we found that NEGR1 (regulated by the TF binding–disrupting MDD risk SNP rs3101339) was dysregulated in the brains of MDD cases compared with controls, implying that rs3101339 may confer MDD risk by affecting NEGR1 expression. Our findings reveal how genetic variants contribute to MDD risk by affecting TF binding and gene regulation. More importantly, our study identifies the potential MDD causal variants and their target genes, thus providing pivotal candidates for future mechanistic study and drug development.
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Acknowledgements
This work was equally supported by the National Key R&D Program of China (2018YFC1314600) and the National Key Research and Development Program of China (Stem Cell and Translational Research) (2016YFA0100900). This study was also supported by the Innovative Research Team of Science and Technology Department of Yunnan Province (2019HC004) and the Key Research Project of Yunnan Province (2017FA008 to X-JL). One of the brain eQTL datasets used in this study was generated as part of the Common Mind Consortium supported by funding from Takeda Pharmaceuticals Company Limited, F. Hoffman-La Roche Ltd, and NIH grants R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1-MH-075916, P50M096891, P50MH084053S1, R37MH057881 and R37MH057881S1, HHSN271201300031C, AG02219, AG05138, and MH06692. Brain tissue for the study was obtained from the following brain bank collections: the Mount Sinai NIH Brain and Tissue Repository, the University of Pennsylvania Alzheimer’s Disease Core Center, the University of Pittsburgh NeuroBioBank and Brain and Tissue Repositories, and the NIMH Human Brain Collection Core. CMC leadership: Pamela Sklar, Joseph Buxbaum (Icahn School of Medicine at Mount Sinai), Bernie Devlin, David Lewis (University of Pittsburgh), Raquel Gur, Chang-Gyu Hahn (University of Pennsylvania), Keisuke Hirai, Hiroyoshi Toyoshiba (Takeda Pharmaceuticals Company Limited), Enrico Domenici, Laurent Essioux (F. Hoffman-La Roche Ltd), Lara Mangravite, Mette Peters (Sage Bionetworks), and Thomas Lehner, Barbara Lipska (NIMH). The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS.
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X-JL conceived and designed the study. YH performed most of the bioinformatic analyses, including the processing of the raw ChIP-seq data, the identification of PWMs from the ChIP-seq peaks, and the identification of TF binding–disrupting SNPs. SL, YL, and JW performed the reporter gene assays, knock down of transcription factors, and CRISPR-Cas9 mediated genome editing. XL carried out the eQTL analysis. JL conducted spatio-temporal expression pattern and cell type-specific expression analysis. SL, YL, XL, JL, JW, ZL, ML, and X-JL contributed to this work in data generation and analysis, results interpretation, and manuscript writing. X-JL oversaw the project and drafted the first version of the manuscript. All authors revised the manuscript critically and approved the final version.
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Li, S., Li, Y., Li, X. et al. Regulatory mechanisms of major depressive disorder risk variants. Mol Psychiatry 25, 1926–1945 (2020). https://doi.org/10.1038/s41380-020-0715-7
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DOI: https://doi.org/10.1038/s41380-020-0715-7
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