Genetic risk modeling approaches to resolve phenotypic and molecular heterogeneity in psychiatric disorders

Psychiatric disorders are highly heterogeneous, with variable symptoms, illness course, and treatment response that complicate diagnosis and management. Genetic risk modeling approaches have increasingly been used to quantify individual differences in liability across and within diagnostic categories. Among these, polygenic risk scores have evolved from modest predictors of disease risk to tools for stratifying patients by symptom profiles, treatment responsiveness, and comorbidities. Complementary statistical methods, including multivariate modeling and pleiotropy-aware analyses, further refine shared versus disorder-specific genetic architectures. The advent of whole-genome sequencing has expanded this scope to rare variants, with new analytic frameworks and functional assays. Together, these advances highlight the growing potential of genetic scoring to inform psychiatric nosology and guide personalized interventions, while emphasizing the need for integrative, multi-ancestry, and functionally validated approaches to realize clinical translation.