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BACKGROUND: Diabetes is a multifactorial disease with significant genetic predisposition. Polygenic risk scores (PRS) have been developed to estimate an individual's genetic risk of a disease. Traditionally, PRS utilize sex-combined genome-wide association studies (GWAS) due to the limited availability of sex-stratified summary statistics. This study explores sex-dimorphic genetic effects and evaluates the potential benefits of incorporating sex-stratified effects in PRS for type 2 diabetes mellitus (T2DM) and glycemic traits by comparing PRS performance derived from sex-combined versus sex-stratified GWAS.METHODS: We performed a sex-heterogeneity test across sex-specific GWAS and identified nine signals with sex-dimorphic effects for T2DM. PRS[sex-combined] and PRS[sex-stratified] were developed using sex-combined and sex-stratified GWAS results for T2DM (41,444 cases and 354,539 controls), fasting glucose (n=120,595) and fasting insulin (n=98,210). We evaluated these PRS models in 8,379 participants (1,303 cases and 7,076 controls) from the Framingham Heart Study not included in the PRS derivation.RESULTS: Our findings suggest that sex-combined PRS currently offer better predictive performance for T2DM and glycemic traits.CONCLUSION: These results highlight the need for larger sex-stratified studies and the optimization of sex-stratified risk models for clinical practice.