Multi-organ network of cardiometabolic disease-depression multimorbidity revealed by phenotypic and genetic analyses of MR images

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Authors: Jingxuan Wang, Mianxin Liu, F. H. Liu, Guangrui Yang, Zhongshang Yuan, Hao Huang, Zheng Zhang, Lilong Wang, Ye Wu, Wenliang Fan, Shuxiao Shi, M. L. Chen
+7 more Xuanwei Jiang, Qiaoling Yan, Jun Lan, Xiaoming Liu, Shuang Rong, Nannan Feng, Victor W Zhong
Cited by: 2
References: 82

Abstract

The development and progression of cardiometabolic diseases and depression multimorbidity involves pathophysiological processes across multiple organs. Using multi-organ imaging data from 31,246 UK Biobank participants, we investigate the multi-organ manifestations and their phenotypic connections and shared genetic architecture underlying the multimorbidity. Phenotypic analyses identify seven abdominal, 16 cardiac, and 107 brain traits forming 1418 abdomen-heart-brain cliques, with liver volume, myocardial wall thickness, and white matter hyperintensity volume as central nodes. Genetic analyses reveal 43 distinct genomic loci (21 novel) shared by these cliques, with the most widely shared loci mapped to genes NUDC, ARID1A, and CRHR1. The 224 protein-coding genes mapped by these loci are enriched in 39 biological processes related to cardiometabolic and neuropsychiatric functions, with 15 genes expressed across liver-heart-brain axis tissues. Combining biochemical and multi-organ imaging indicators significantly improves multimorbidity prediction. These findings uncover multi-organ network underlying physical-mental multimorbidity and highlight the necessity of holistic management. Cardiometabolic disease and depression often co-occur, but their multi-organ basis was unclear. Here, the authors analyse UK Biobank imaging and genetics, identifying abdomen-heart-brain networks and 43 shared loci, improving multimorbidity prediction

Fields of Study & Subjects

Genetic Associations and Epidemiology Functional Brain Connectivity Studies Bioinformatics and Genomic Networks

Publication details

Journal / source
Nature Communications
Publisher
Springer Science and Business Media LLC
Volume
17
Issue
1
Pages
1333–1333
Publication date
7 January 2026
Language
EN