Statistical genetics and polygenic risk score for precision medicine
Autor: | Yukinori Okada, Takahiro Konuma |
---|---|
Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
0301 basic medicine
medicine.medical_specialty Genome-wide association study Immunology Population Psychological intervention Disease Review 03 medical and health sciences 0302 clinical medicine Polygenic risk score medicine Pathology Immunology and Allergy Statistical genomics RB1-214 Generalizability theory Intensive care medicine education education.field_of_study business.industry Precision medicine 030104 developmental biology Statistical genetics Personalized medicine business 030217 neurology & neurosurgery |
Zdroj: | Inflammation and Regeneration, Vol 41, Iss 1, Pp 1-5 (2021) Inflammation and Regeneration |
ISSN: | 1880-8190 |
Popis: | The prediction of disease risks is an essential part of personalized medicine, which includes early disease detection, prevention, and intervention. The polygenic risk score (PRS) has become the standard for quantifying genetic liability in predicting disease risks. PRS utilizes single-nucleotide polymorphisms (SNPs) with genetic risks elucidated by genome-wide association studies (GWASs) and is calculated as weighted sum scores of these SNPs with genetic risks using their effect sizes from GWASs as their weights. The utilities of PRS have been explored in many common diseases, such as cancer, coronary artery disease, obesity, and diabetes, and in various non-disease traits, such as clinical biomarkers. These applications demonstrated that PRS could identify a high-risk subgroup of these diseases as a predictive biomarker and provide information on modifiable risk factors driving health outcomes. On the other hand, there are several limitations to implementing PRSs in clinical practice, such as biased sensitivity for the ethnic background of PRS calculation and geographical differences even in the same population groups. Also, it remains unclear which method is the most suitable for the prediction with high accuracy among numerous PRS methods developed so far. Although further improvements of its comprehensiveness and generalizability will be needed for its clinical implementation in the future, PRS will be a powerful tool for therapeutic interventions and lifestyle recommendations in a wide range of diseases. Thus, it may ultimately improve the health of an entire population in the future. |
Databáze: | OpenAIRE |
Externí odkaz: |