Shared Genetic Architecture Between Mental Disorders and Heart Failure Subtypes: A Comprehensive Multitrait Genome-Wide Analysis.

Mental disorders were associated with a higher risk of incident heart failure in prospective UK Biobank analyses.

• Prospective Cox regression analysis in the UK Biobank quantified risk of incident heart failure associated with mental disorders.
• Posttraumatic stress disorder, depression, and bipolar disorder were named as mental disorders associated with higher incident heart failure risk.
• The abstract does not report hazard ratios, confidence intervals, or sample sizes.

Multitrait genome-wide analysis identified 607 pleiotropic variants shared between mental disorders and heart failure.

• Methods included multitrait genome-wide association analysis and cross-phenotype association analysis to identify candidate pleiotropic loci.
• Linkage disequilibrium score regression was used to estimate genetic correlations between the traits.
• The abstract reports the total as 607 pleiotropic variants without further breakdown.

Fine-mapping and colocalization converged on prioritized candidate loci including TMEM18, NKX2-2, and XRN2.

• Statistical fine mapping and gene-level association analyses were used to prioritize candidate variants and genes.
• Bayesian colocalization assessed evidence for shared candidate variants between mental disorders and heart failure.
• TMEM18, NKX2-2, and XRN2 were named as prioritized candidate loci.

Single-cell expression profiling and genetically informed spatial mapping provided cellular and tissue-level context for the prioritized genes.

• Single-cell RNA sequencing and gsMap (genetically informed spatial mapping) were applied to the prioritized genes.
• Gene Ontology biological-process overrepresentation analysis was exploratory and provided descriptive biological context.

Geneformer-based in silico perturbation prioritized FOXP1 and TMEM106B as leading pleiotropic candidate genes in cardiac cellular contexts.

• The analysis used a cardiac cell atlas of dilated cardiomyopathy.
• Prioritization was based on predicted changes in downstream gene embeddings and identified cardiac cell states showing predicted embedding shifts.
• These are computational predictions that are described as exploratory.

The study concludes that mental disorders and heart failure share genetic architecture, but findings require functional validation before mechanistic or therapeutic interpretation.

• Transcriptomic and in silico perturbation analyses provide exploratory cellular, spatial, and cardiac functional context.
• The authors explicitly state functional validation is required.