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Genome-wide meta-analysis, functional genomics and integrative analyses implicate new risk genes and therapeutic targets for anxiety disorders

Nature Human Behaviour volume 8, pages 361–379 (2024)Cite this article

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Abstract

Anxiety disorders are the most prevalent mental disorders. However, the genetic etiology of anxiety disorders remains largely unknown. Here we conducted a genome-wide meta-analysis on anxiety disorders by including 74,973 (28,392 proxy) cases and 400,243 (146,771 proxy) controls. We identified 14 risk loci, including 10 new associations near CNTNAP5, MAP2, RAB9BP1, BTN1A1, PRR16, PCLO, PTPRD, FARP1, CDH2 and RAB27B. Functional genomics and fine-mapping pinpointed the potential causal variants, and expression quantitative trait loci analysis revealed the potential target genes regulated by the risk variants. Integrative analyses, including transcriptome-wide association study, proteome-wide association study and colocalization analyses, prioritized potential causal genes (including CTNND1 and RAB27B). Evidence from multiple analyses revealed possibly causal genes, including RAB27B, BTN3A2, PCLO and CTNND1. Finally, we showed that Ctnnd1 knockdown affected dendritic spine density and resulted in anxiety-like behaviours in mice, revealing the potential role of CTNND1 in anxiety disorders. Our study identified new risk loci, potential causal variants and genes for anxiety disorders, providing insights into the genetic architecture of anxiety disorders and potential therapeutic targets.

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Fig. 1: Manhattan plot of the GWAS meta-analysis.
Fig. 2: LocusZoom plots for six GWS association loci.
Fig. 3: Results of the reporter gene assays.
Fig. 4: Transcriptome-wide and proteome-wide association results.
Fig. 5: Gene prioritization results.
Fig. 6: Ctnnd1 regulates dendritic spine density, cognitive function and anxiety-like behaviours.

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Data availability

The genome-wide summary statistics of UK Biobank were downloaded from https://biobank.ndph.ox.ac.uk/showcase/label.cgi?id=140. The genome-wide summary statistics of iPSYCH were downloaded from https://ipsych.dk/fileadmin/ipsych.dk/Downloads/daner_woautism_ad_sd8-sd6_woautismad_cleaned.gz. The genome-wide summary statistics of ANGST were downloaded from https://figshare.com/ndownloader/articles/14842689/versions/1. The genome-wide summary statistics of FinnGen were downloaded from https://r4.risteys.finngen.fi/phenocode/F5_ALLANXIOUS. The genome-wide summary statistics of the MVP were downloaded from dbGaP (dbGaP Study Accession, phs001672.v9.p1) at https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001672.v9.p1. The SNP-expression weights of PsychENCODE used in this study were downloaded from http://resource.psychencode.org/. The processed protein weight files were downloaded from https://www.synapse.org/ (Synapse ID: syn9884314 and syn23245237). The PsychENCODE cis-eQTL data were downloaded from the SMR website (https://yanglab.westlake.edu.cn/data/SMR/PsychENCODE_cis_eqtl_HCP100_summary.tar.gz). The gene expression data used for MAGMA were from the GTEx consortium, GTEx_Analysis_2017-06-05_v8_RNASeQCv1.1.9. All Gene Ontology terms (including cellular components, biological processes and molecular functions) and KEGG pathway gene sets were downloaded from the MSigDB database (https://www.gsea-msigdb.org/gsea/msigdb/human/collections.jsp#C5). The CMC eQTL data were downloaded from Synapse (https://www.synapse.org//#!Synapse:syn4622659). The genome-wide summary statistics of the meta-analysis can be obtained at https://doi.org/10.6084/m9.figshare.23659653.v1. Source data are provided with this paper.

Code availability

GWAS meta-analysis was done using the inverse-variance-based fixed-effects and random-effects models meta-analysis implemented in PLINK v.1.09 (https://www.cog-genomics.org/plink/). FUMA v.1.3.7 was used to define the risk loci, with the default parameters (https://fuma.ctglab.nl/). LDSC (https://github.com/bulik/ldsc) was used to estimate the SNP-based heritability and pairwise genetic correlations between the GWASs. FIMO was used to compare the derived binding motifs with the publicly available PWM and the best-matched motifs (https://meme-suite.org/meme/tools/fimo). FINEMAP v.1.4.1 (http://www.christianbenner.com/) and PAINTOR (https://github.com/gkichaev/PAINTOR_V3.0) were used for statistical fine-mapping. The R package TwoSampleMR was used to perform two-sample Mendelian randomization analysis (v.0.5.6, https://mrcieu.github.io/TwoSampleMR/). Other custom codes can be accessed at https://doi.org/10.5281/zenodo.8162792 (ref. 146).

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Acknowledgements

This study was equally supported by the National Nature Science Foundation of China (grant nos. U2102205 to X.-J.L., U22A20304 to L.L., 31970561 to X.-J.L., 82171498 to W.L. and U1904130 to W.L.) and the Key Project of Yunnan Fundamental Research Projects (grant no. 202101AS070055 to X.-J.L.). This study was also supported by the Distinguished Young Scientists grant of the Yunnan Province (no. 202001AV070006 to X.-J.L.) and the Major Science and Technology Projects of Henan Province (grant no. 201300310200 to W.L.). We thank Q. Li for her technical assistance. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Author notes

  1. These authors contributed equally: Wenqiang Li, Rui Chen, Laipeng Feng, Xinglun Dang, Jiewei Liu.

Authors and Affiliations

  1. Henan Mental Hospital, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China

    Wenqiang Li, Laipeng Feng, Tengfei Chen, Xi Su & Luxian Lv

  2. Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China

    Rui Chen, Jiewei Liu & Jinfeng Yang

  3. Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing, China

    Xinglun Dang, Zhijun Zhang & Xiong-Jian Luo

  4. Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China

    Tao Li

  5. Department of Neurology, Affiliated Zhongda Hospital, Southeast University, Nanjing, China

    Zhijun Zhang & Xiong-Jian Luo

  6. Department of Mental Health and Public Health, Faculty of Life and Health Sciences, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Zhijun Zhang

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  1. Wenqiang Li
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Contributions

X.-J.L. conceived, designed and supervised the whole study. W.L., L.F., T.C. and X.S. conducted the behavioural tests. R.C. performed the dendritic spine analysis and reporter gene assays. X.-J.L. performed the meta-analysis and drug–gene interaction analyses. J.L., X.D. and J.Y. conducted the TWAS, PWAS, colocalization and fine mapping analyses. W.L., L.L., T.L. and Z.Z. contributed to the study design, data interpretation and manuscript writing. X.-J.L. oversaw the project and finalized the manuscript. All authors revised the manuscript critically and approved the final version.

Corresponding author

Correspondence to Xiong-Jian Luo.

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Nature Human Behaviour thanks Zhongshan Cheng and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Figs. 1–9, Tables 1–28 and Methods.

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Unprocessed western blots.

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Li, W., Chen, R., Feng, L. et al. Genome-wide meta-analysis, functional genomics and integrative analyses implicate new risk genes and therapeutic targets for anxiety disorders. Nat Hum Behav 8, 361–379 (2024). https://doi.org/10.1038/s41562-023-01746-y

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