Abstract Body:
Objective
The development of multimorbidity of cardiometabolic diseases (CMDs) and depression likely involves pathophysiological processes across multiple organs. This study aimed to investigate imaging traits in the abdomen-heart-brain axis linked to the CMDs-depression multimorbidity and assess their phenotypic and genetic connections using magnetic resonance imaging (MRI) data.
Methods
This study analyzed multi-organ MRI data including 7 abdominal, 82 cardiac, and 676 brain traits from 31,839 UK Biobank participants. CMDs included coronary artery disease, stroke, heart failure, type 2 diabetes, hypertension and hyperlipidemia. First, multivariable logistic regressions estimated associations of imaging traits with the CMDs-depression multimorbidity. Second, multivariable linear regressions quantified pairwise correlations among significant cross-organ traits. Third, transcriptome-wide association study (TWAS) identified shared genes of traits significantly correlated with each other across all 3 regions (i.e., triads). Fourth, LASSO regressions constructed genomics scores using single nucleotide polymorphisms from the shared genes. Fifth, the prediction performance of imaging traits and genomics scores for the CMDs-depression multimorbidity was evaluated by AUCs. FDR correction was used to adjust for multiple testing.
Results
Seven abdominal, 27 cardiac, and 340 brain traits were significantly associated with the CMDs-depression multimorbidity. Among 11,749 pairs of significant cross-organ imaging traits, 6385 abdomen-heart-brain triads were identified, with liver volume as the most connected node. The directions of associations among imaging traits in these cross-organ triads aligned with directions of their biological functions, suggesting multiple organs acting as a coordinated system. TWAS revealed TNFSF12 from whole blood as the shared gene underlying the significant liver-heart-brain connection associated with the CMDs-depression multimorbidity. The integration of imaging traits with genomics score (AUC = 0.84) improved prediction performance for the CMDs-depression multimorbidity, outperforming demographic and lifestyle models (AUC = 0.78) (P = 0.014).
Conclusions
This study identified highly correlated cross-organ imaging traits that were associated with the CMDs-depression multimorbidity. A shared gene was found for a liver-heart-brain triad. Imaging traits and genomic score significantly enhanced prediction performance on top of traditional factors.