medRxivGenetic & Genomic MedicinePreprint
Genes associated with depression and coronary artery disease are enriched for inflammation and cardiomyopathy-associated pathways.
Kritika SinghiD, Hyunjoon LeeiD, Julia SealockiD, Tyne W. Miller‐FlemingiD, Péter StraubiD, Nancy Jean CoxiD, Quinn Stanton WellsiD, Jordan W. SmolleriD, Emily C. HodgesiD, Lea Karatheodoris DavisiD
Abstract
BackgroundDepression and Coronary Artery Disease (CAD) are highly comorbid conditions. Approximately 40% of individuals who have one diagnosis will also develop the other within their lifetime. Prior research indicates that polygenic risk for depression increases the odds of developing CAD even in the absence of clinical depression. However, the specific genes and pathways involved in comorbid depression-CAD remain unknown. ResultsWe identified genes that are significantly associated with both depression and CAD, and are enriched for pathways involved in inflammation and for previous association with cardiomyopathy. We observed increased rate of prevalent, but not incident, cardiomyopathy cases in individuals with comorbid depression-CAD compared to those with CAD alone in three electronic large health record (EHR) datasets. ConclusionsThe results of our study implicate genetically regulated inflammatory mechanisms in depression-CAD. Our results also raise the hypothesis that depression-associated CAD may be enriched for cardiomyopathy. Clinical PerspectiveO_LIWhats New? O_LIGene associations shared between depression and CAD are enriched for prior association with cardiomyopathy phenotypes. C_LIO_LICardiomyopathy is significantly more prevalent in individuals with comorbid depression-CAD than in CAD or depression alone. C_LI C_LIO_LIWhat are the Clinical Implications? O_LIOur work suggests that individuals with comorbid depression-CAD may benefit from screening for cardiomyopathy. C_LI C_LI
- organism: human
- assay: GWAS summary statistics
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- Citations
- 1
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