medRxivGenetic & Genomic MedicinePreprint
Proteogenomic mapping of multimorbidity identifies C1R linking coronary artery disease and dementia
Li LiiD, Zhixin Tang, Zhong Z, Tingting GengiD, Yanjun Guo, Yunfei Liao, Ayşe DemirkaniD, Jack BowdeniD, Fiona BraggiD, An PaniD, Xufang SuniD, Jiang LiuiD, Gang LiuiD, Jun LiuiD
Abstract
Multimorbidity is highly prevalent in ageing populations, yet its shared molecular basis remains poorly defined, limiting the development of therapies that target multiple conditions. We systematically integrated measurements of 1,954 circulating proteins from 54,219 individuals in discovery and 35,559 in replication, focusing on ten common age-related diseases: coronary artery disease, chronic kidney disease, chronic obstructive pulmonary disease, dementia, heart failure, major depressive disorder, osteoarthritis, Parkinsons disease, stroke, and type 2 diabetes. Coronary artery disease emerged as a central condition in the multimorbidity network, sharing circulating protein signatures with seven other diseases. Through genetic causal-inference analyses, we identified 40 circulating proteins with cross-disease relevance, of which four were further supported by colocalization of genetic variant associations. Among these, complement C1r, encoded by C1R, emerged as a key link between coronary artery disease and dementia, supported by independent colocalization evidence (PP.H4 = 0.86). Phenome-wide association analyses of C1R variants suggested that this signal was not driven by widespread unrelated genetic effects, but instead may reflect a more specific contribution to coronary artery disease-dementia pathogenesis. In vitro experiments further suggested that fibroblast-derived C1R promotes endothelial inflammation and neuronal apoptosis, providing mechanistic plausibility. Together, these findings position C1R as a biologically plausible and therapeutically relevant molecular link between coronary artery disease and dementia.
- organism: human
- assay: proteomics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
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