Multilayer Genomic Characterization of a Shared Genetic Factor Linking Depression-Related Liability and Reduced Physical Function.

Overview

1. Department of Hematology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091, China

Abstract

Background: Depression-related liability is frequently accompanied by reduced physical function, yet the shared genetic architecture linking mood-related traits and physical-function decline remains incompletely characterized. Methods: We applied genomic structural equation modeling to European-ancestry GWAS summary statistics for five constituent phenotypes: depressive symptoms, depression diagnosis, grip strength, appendicular lean mass, and walking pace. A Depression–Physical Function shared genetic factor was constructed as a cross-trait genetic covariance dimension and evaluated using LDSC-based validation and leave-one-trait-out sensitivity analyses. We then performed factor GWAS, FUMA locus annotation, Bayesian fine-mapping, MAGMA gene-based analysis, transcriptome-wide association analysis, pathway enrichment, CELLECT/MAGMA cell-type specificity analysis, partitioned heritability analysis, and gsMap spatial transcriptomic mapping. Results: The shared factor showed good model fit and retained 755,397 quality-controlled variants for downstream analysis. The factor was positively genetically correlated with depression-related traits and negatively correlated with physical-function-related traits. FUMA identified 245 genome-wide significant SNPs, 44 lead SNPs, and 38 genomic risk loci, with 127 positional mapped genes. Fine-mapping prioritized one high-confidence locus. MAGMA identified 19 Bonferroni-significant genes and 326 FDR-significant genes, while TWAS identified 322 FDR-significant expression-associated genes. Integrating FUMA positional mapping, MAGMA gene-level association and TWAS expression-level association prioritized eight convergent genes: TMEM106B, CENPW, DRD2, LRFN5, NCAPG, DCAF16, SGIP1, and FAM120A. Functional enrichment highlighted postsynaptic structure, neuron spine, synaptic plasticity, and synapse organization. CELLECT/MAGMA prioritized brain non-myeloid neurons and glial populations, with additional endocrine-metabolic and immune-hematopoietic signals. Spatial transcriptomic mapping localized top signals to brain and spinal cord regions in the embryonic neuro-muscle reference. Partitioned heritability analysis showed enrichment in conserved, intronic, promoter, and chromatin-related genomic annotations. Conclusions: These findings support a shared polygenic covariance dimension linking depression-related liability with reduced physical-function-related genetic propensity. Downstream analyses prioritized candidate loci, genes, and biological contexts, with enrichment patterns consistent with neuronal, synaptic, and regulatory genomic processes.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data Availability Statement

All GWAS summary statistics used in this study were obtained from publicly available resources. Detailed GWAS identifiers, public data sources, phenotype definitions, sample sizes, ancestry information, phenotype types, and observed-scale SNP heritability estimates are provided in Supplementary Table S1. The post-GWAS summary results generated in this study are provided in the Supplementary Tables; the code is available upon reasonable request; the analyses were conducted using publicly available software and custom scripts. The main software tools and parameters are described in the Section 2. Custom scripts are available from the corresponding author upon reasonable request. Ethics approval and consent to participate were obtained. This study used publicly available summary-level GWAS data and did not involve new individual-level human participant data. Ethical approval and informed consent were obtained in the original studies. No additional ethical approval was required for this secondary analysis.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 6 keywords, 8 MeSH terms, 2 funders, 47 references.

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This paper

Zeng, W., Yang, X., & Xu, Y. (2026). Multilayer Genomic Characterization of a Shared Genetic Factor Linking Depression-Related Liability and Reduced Physical Function. Genes, 17(7), 813. https://doi.org/10.3390/genes17070813

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