Polygenic risk scores for predicting outcomes and treatment response in psychiatry: hope or hype?. (17th November 2022)

• Record Type: Journal Article
• Authors: Fusar-Poli, Laura; Rutten, Bart P. F.; van Os, Jim; Aguglia, Eugenio; Guloksuz, Sinan
• Is Part Of: International review of psychiatry. Volume 34:Number 7/8(2022)
• Page Start: 663
• Page End: 675
• Publication Date: 2022-11-17
• Subjects: Polygenic risk score -- genetics -- schizophrenia -- depression -- environment -- prediction -- personalized medicine; Mental illness -- Periodicals; Psychiatry -- Periodicals; Psychology, Pathological -- Periodicals; 616.89
• DOI: 10.1080/09540261.2022.2101352
• Languages: English
• ISSNs: 0954-0261

Abstract

Abstract: Over the last years, the decreased costs and enhanced accessibility to large genome-wide association studies datasets have laid the foundations for the development of polygenic risk scores (PRSs). A PRS is calculated on the weighted sum of single nucleotide polymorphisms and measures the individual genetic predisposition to develop a certain phenotype. An increasing number of studies have attempted to utilize the PRSs for risk stratification and prognostic evaluation. The present narrative review aims to discuss the potential clinical utility of PRSs in predicting outcomes and treatment response in psychiatry. After summarizing the evidence on major mental disorders, we have discussed the advantages and limitations of currently available PRSs. Although PRSs represent stable trait features with a normal distribution in the general population and can be relatively easily calculated in terms of time and costs, their real-world applicability is reduced by several limitations, such as low predictive power and lack of population diversity. Even with the rapid expansion of the psychiatric genetic knowledge base, pure genetic prediction in clinical psychiatry appears to be out of reach in the near future. Therefore, combining genomic and exposomic vulnerabilities for mental disorders with a detailed clinical characterization is needed to personalize care.