Multimorbidity

Multimorbidity characterizes shared genetic bases of comorbidities among common diseases using UK Biobank hospital inpatient records to elucidate loci-, network-, and overall genetic-architecture level risks.

Key Features:

• Comprehensive Data Analysis: Utilizes UK Biobank hospital inpatient records for 385,335 patients to examine relationships among 439 prevalent diseases and identify 11,285 comorbidities.
• Genetic Interpretability: Approximately 46% of identified comorbidities are genetically interpretable at loci, network, and overall genetic-architecture levels.
• Post-GWAS Analyses: Conducts post-GWAS analyses to pinpoint shared genetic risks at genomic loci, network levels, and overall genetic architecture.
• Network Decomposition: Applies network decomposition techniques to construct interpretable comorbidity networks, identify hub diseases, and define comorbidity modules and molecular players.
• Physiological Insights: Reveals that comorbidities within the same physiological system more often share loci-level components, whereas cross-system comorbidities more often share network-level components, with convergence on cell immunity, protein metabolism, and gene silencing.
• Module Formation: Shows genetically interpretable comorbidities frequently form network modules mediated by hub diseases and characterized by specific physiological categories.

Scientific Applications:

• Research Facilitation: Provides a systematic resource to explore genetic predispositions of comorbidities and to prioritize shared loci and network components as candidate therapeutic targets.
• Clinical Insights: Identifies hub diseases and convergent molecular functions to inform hypotheses about treatment strategies and management of comorbid conditions.

Methodology:

Analyses used UK Biobank hospital inpatient records and applied post-GWAS analyses to identify shared genetic risks at loci, network, and overall genetic-architecture levels, together with network decomposition to construct comorbidity networks and modules.