Evidence map›Paper›PMID 42920124›Full record

ArticleBMC medicine2026

Polygenicity shapes distinct brain patterns and clinical profiles of bipolar disorder.

Yu Feng, Xiaonan Guo, Peng Huang, Ningning Jia, Li Wang, Xiaolong Ji, Zeyu Qin, Meng Li, Jianbo Lai, Xiaofeng Qin and 3 more

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Article in BMC medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Yu Feng *Department of Psychiatry, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Xiaonan Guo *Department of Psychiatry, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Peng Huang *Department of Epidemiology, Centre for Global Health, School of Public Health, Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, National Vaccine Innovation Platform, Nanjing Medical University, Nanjing, Jiangsu, China.
Ningning Jia *Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China.
Li Wang *Huai'an No.3 People's Hospital, Jiangsu, China.
Xiaolong JiDepartment of Epidemiology, Centre for Global Health, School of Public Health, Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, National Vaccine Innovation Platform, Nanjing Medical University, Nanjing, Jiangsu, China.
Zeyu QinDepartment of Psychiatry, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Meng LiDepartment of Psychiatry and Psychotherapy, Jena University Hospital, Jena, 07743, Germany.
Jianbo LaiDepartment of Psychiatry, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Xiaofeng QinHuai'an No.3 People's Hospital, Jiangsu, China. huaianqxf@163.com.
Weihua YuePeking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China. dryue@bjmu.edu.cn.
Sheng YangDivision of Pediatric Pulmonary Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, USA. shy229@pitt.edu.
Shaohua HuDepartment of Psychiatry, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China. dorhushaohua@zju.edu.cn.ORCID https://orcid.org/0000-0003-0570-670X

Funding

Key R&D Program of Zhejiang Province 2025C02109, 2024C03098National Key Research and Development Program of China 2023YFC2506200National Natural Science Foundation of China 82173585National Natural Science Foundation of China 82571735Ningbo Key Research and Development Program 2025Z156
6 · The paper itself

Abstract

backgroundBipolar disorder (BD) manifests both genetic predispositions and brain imaging abnormalities. Genetic analyses provide a powerful approach to disentangling the associations between BD and brain imaging-derived phenotype (IDP). However, in East Asian (EAS) populations, the genetic basis of these neuroimaging changes and their clinical relevance remains underexplored due to limited integrative evidence.

methodsWe investigated the genetic architecture and clinical relevance of BD and brain IDPs in East Asian populations using individual-level data from the Chinese Bipolar Disorder (CN-BD) cohort (N = 3,920), summary statistics of BD from the Psychiatric Genomics Consortium (PGC) (N = 16,915) and of IDPs from the CHIMGEN Consortium (N = 7,058), and genotype and clinical data from the Chinese Longitudinal and Systematic Study of Bipolar Disorder cohort (CLASS-BD). We employed genetic correlation (GNOVA), multi-trait meta-analysis (MTAG, CPASSOC), and ancestry-specific fine-mapping (MESuSiE) to identify shared genetic loci. Functional annotation, protein association (SMR, BLISS), and spatiotemporal expression trajectory analyses were conducted. Bidirectional Mendelian Randomization (MR) assessed causal relationships, and polygenic risk score (PRS)-PheWAS explored phenome-level associations with clinical traits.

resultsOur multi-trait meta-analysis identified 11 pleiotropic single nucleotide variants (SNVs) implicated in BD-IDP pairs, showing convergent enrichment in lipid metabolism and neurotransmitter biosynthesis pathways. Fine-mapping revealed an EAS-specific causal signal (rs7941324 near RPS27P20), which demonstrated high posterior inclusion probability in EAS but not European ancestries, and colocalized with BD and specific brain alterations. MR revealed 27 IDP-to-BD and 35 BD-to-IDP causal relationships, distinguishing structural changes of the parietal and temporal gyri as markers preceding BD onset and the right precuneus area as a state marker that followed BD onset. Clinically, BD-IDP polygenic risk scores were significantly associated with depressive symptoms, anxiety, and suicide risk. Mediation analysis further indicated that depressive and anxiety symptoms statistically mediated the relationship between BD-IDP PRS and suicide risk. Moreover, PRS-PheWAS identified 135 significant associations with metabolic phenotypes, highlighting a psycho-metabolic nexus in BD.

conclusionsOur findings reveal associations between polygenicity and distinct BD brain patterns and clinical profiles. We identified ancestry-specific causal variants and bidirectional BD-IDP relationships. PRS associations with depressive symptoms, anxiety, suicide risk, and metabolic phenotypes highlight precision medicine potential for BD.

Indexed as

Bipolar DisorderBrainMultifactorial InheritanceAsian PeopleFemaleGenetic Predisposition to DiseaseGenetic Risk ScoreHumansMalePhenotypePolymorphism, Single NucleotideBipolar disorderBrain imaging-derived phenotypesEast AsianGenetic pleiotropyPolygenic risk scorePsycho-metabolic nexus

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.