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Abstract
The amygdala is a crucial interconnecting structure in the brain that performs several regulatory functions, yet its genetic architectures and involvement in brain disorders remain largely unknown. We carried out the first multivariate genome-wide association study (GWAS) of amygdala subfield volumes in 27,866 UK Biobank individuals. The whole amygdala was segmented into nine nuclei groups using Bayesian amygdala segmentation. The post-GWAS analysis allowed us to identify causal genetic variants in phenotypes at the SNP, locus, and gene levels, as well as genetic overlap with brain health-related traits. We further generalized our GWAS in Adolescent Brain Cognitive Development (ABCD) cohort. The multivariate GWAS identified 98 independent significant variants within 32 genomic loci associated (P < 5 × 10−8) with amygdala volume and its nine nuclei. The univariate GWAS identified significant hits for eight of the ten volumes, tagging 14 independent genomic loci. Overall, 13 of the 14 loci identified in the univariate GWAS were replicated in the multivariate GWAS. The generalization in ABCD cohort supported the GWAS results with the 12q23.2 (RNA gene RP11-210L7.1) being discovered. All of these imaging phenotypes are heritable, with heritability ranging from 15% to 27%. Gene-based analyses revealed pathways relating to cell differentiation/development and ion transporter/homeostasis, with the astrocytes found to be significantly enriched. Pleiotropy analyses revealed shared variants with neurological and psychiatric disorders under the conjFDR threshold of 0.05. These findings advance our understanding of the complex genetic architectures of amygdala and their relevance in neurological and psychiatric disorders.
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1 Qingdao University, Department of Neurology, Qingdao Municipal Hospital, Qingdao, China (GRID:grid.410645.2) (ISNI:0000 0001 0455 0905)
2 Fudan University, National Center for Neurological Disorders, Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443)
3 Fudan University, Institute of Science and Technology for Brain-Inspired Intelligence, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China (GRID:grid.419897.a) (ISNI:0000 0004 0369 313X)
4 Fudan University, Institute of Science and Technology for Brain-Inspired Intelligence, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China (GRID:grid.419897.a) (ISNI:0000 0004 0369 313X); Zhejiang Normal University, Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Jinhua, China (GRID:grid.453534.0) (ISNI:0000 0001 2219 2654); Fudan University, MOE Frontiers Center for Brain Science, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Zhangjiang Fudan International Innovation Center, Shanghai, China (GRID:grid.8547.e)
5 Fudan University, National Center for Neurological Disorders, Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Fudan University, Institute of Science and Technology for Brain-Inspired Intelligence, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China (GRID:grid.419897.a) (ISNI:0000 0004 0369 313X); Zhejiang Normal University, Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Jinhua, China (GRID:grid.453534.0) (ISNI:0000 0001 2219 2654)