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Recent discoveries in human genetics are driving precision medicine forward. Large-scale genome-wide association studies (GWAS) have mapped thousands of variants related to complex diseases, offering insight into their biology. Polygenic risk scores (PRS) pull together these small genetic signals to flag people who might warrant earlier screening or closer monitoring. Mendelian Randomization (MR) provides a statistical framework to evaluate potential causal relationships between exposures and disease outcomes, offering support for targeted intervention. Furthermore, the use of disease-disease networks (DDN), which integrate molecular, genetic, and clinical data, allows for the exploration of biological connections and comorbidities across diseases. Considering evidence from GWAS, PRS, MR, and DDN together provides a multi-dimensional perspective—linking genetic association, risk prediction, causal inference, and disease interconnection. The findings from these approaches make us more understanding of disease mechanisms and guide more effective prevention and treatment efforts in both clinical and population health contexts.