Genetics and Comorbidity

Abstract

Comorbidity—the co-occurrence of multiple conditions within the same individual—is a defining feature of both psychiatric and physical illness, yet the biological mechanisms driving comorbidity remain poorly understood. This thesis investigates shared genetic lia- bility underlying comorbid traits and disorders using genome-wide association study (GWAS) summary statistics, spanning psychiatric disorders and cardiovascular diseases. A cross-disorder analysis of twelve psychiatric conditions demonstrates that genetic overlap is largely pair-specific and that cross-trait meta-analytic signal is heavily driven by schizophrenia, cautioning against interpreting such signal as reflecting general psychiatric liability. Pairing schiz- ophrenia with height as a model trait reveals that near-zero global genetic correlation can mask meaningful local genetic overlap, with convergent evidence implicating immune-developmental and thyro- trophic processes in schizophrenia risk. A sex-stratified analysis of ischaemic heart disease and depression shows that shared genetic liability is substantially stronger in females than males, with hor- monal and inflammatory pathways predominating in females and behavioural and metabolic factors in males. Mapping genetic over- lap across eight cardiovascular diseases identifies three recurring biological programmes—systemic metabolic risk, cardiac structural and electrical mechanisms, and vascular wall biology—that replicate across independent biobanks and ancestries. Together, these find- ings demonstrate that genetic overlap between comorbid conditions is readily detectable but difficult to translate into biological insight when phenotypes are heterogeneous or highly polygenic, and argue for a staged research strategy that pairs diagnosis-based discovery with biology-first phenotyping to identify the specific biological systems underlying disease comorbidity.