Uncovering the genetic underpinnings for different psychiatric disorder combinations

Psychiatric disorders are highly heterogeneous. Clinically, it is meaningful to distinguish psychiatric disorders by the presence or absence of a specific comorbid condition. In this study, we employed a recently developed algorithm (CombGWAS) to decipher the genetic basis of psychiatric disorder combinations using GWAS summary statistics. We focused on comorbidities and combinations of diseases, such as schizophrenia(SCZ) with and without depression, which can be considered as two 'subtypes' of SCZ. We also studied psychiatric disorders comorbid with obesity as disease subtypes. Our study identified genetic signatures that distinguish different 'subtypes' and revealed the genetic architecture underlying 16 psychiatric disorder combinations. We discovered both shared and unique susceptibility genes/variants across different psychiatric disorder 'subtypes'. Notably, despite high genetic correlations between subtypes, most subtype pairs exhibited distinct genetic correlations with the same cardiovascular disease (CVD). Some pairs even displayed opposite genetic correlations, especially those involving obesity. For instance, the genetic correlation (rg) between SCZ with obesity and type 2 diabetes(T2DM) was 0.248(p=4.42E-28), while the rg between SCZ without obesity and T2DM was -0.154(p=6.79E-12). Many psychiatric disease combinations studied were causally associated with increased CVD risks. Moreover, comorbid psychiatric disorders often showed different causal relationships with CVD compared to single psychiatric disorders. This study represents a significant step toward understanding the genetic heterogeneity underlying psychiatric disorder comorbidities, providing new insights into their pathophysiology.