Predicting Polygenic Risk of Psychiatric Disorders

Area of Science:

• Genetics and Psychiatry
• Biomarker Discovery
• Disease Etiology

Background:

• Psychiatric disorders require novel biomarkers due to diagnostic heterogeneity and limited insight into disease mechanisms.
• Genetic biomarkers are particularly promising given the challenges of accessing and studying human brain tissue.
• Genome-wide association studies (GWAS) have advanced genetic risk prediction for common diseases.

Purpose of the Study:

• To review fundamental concepts, methods, strengths, weaknesses, and applications of genetic risk prediction in psychiatry.
• To discuss the current utility and future potential of genetic risk prediction for psychiatric disorders.
• To highlight emerging data and methods for improving genetic risk prediction's value in research and clinical settings.

Main Methods:

• Review of current methodologies for computing polygenic risk scores (PRS).
• Assessment of the utility and application of PRS across various psychiatric disorders and related traits.
• Discussion of pitfalls and confounding factors in PRS application, referencing historical challenges like the candidate gene era.

Main Results:

• Genetic risk prediction is increasingly applied in studies, but its clinical utility remains low.
• Significant promise exists for future clinical applications, contingent on increased ancestral diversity and sample sizes in GWAS.
• Emerging data and methods aim to enhance PRS for disentangling disease mechanisms and subject stratification.

Conclusions:

• Genetic risk prediction holds substantial promise for psychiatric research and potentially clinical applications.
• Careful methodology and control for confounding are critical to avoid past errors and maximize the value of PRS.
• Continued growth in GWAS data and refined analytical approaches are key to realizing the full potential of genetic risk prediction.