Towards clinical utility of polygenic risk scores

Abstract

Prediction of disease risk is an essential part of preventative medicine, often guiding clinical management. Risk prediction typically includes risk factors such as age, sex, family history of disease and lifestyle (e.g. smoking status); however, in recent years, there has been increasing interest to include genomic information into risk models. Polygenic risk scores (PRS) aggregate the effects of many genetic variants across the human genome into a single score and have recently been shown to have predictive value for multiple common diseases. In this review, we summarize the potential use cases for seven common diseases (breast cancer, prostate cancer, coronary artery disease, obesity, type 1 diabetes, type 2 diabetes and Alzheimer’s disease) where PRS has or could have clinical utility. PRS analysis for these diseases frequently revolved around (i) risk prediction performance of a PRS alone and in combination with other non-genetic risk factors, (ii) estimation of lifetime risk trajectories, (iii) the independent information of PRS and family history of disease or monogenic mutations and (iv) estimation of the value of adding a PRS to specific clinical risk prediction scenarios. We summarize open questions regarding PRS usability, ancestry bias and transferability, emphasizing the need for the next wave of studies to focus on the implementation and health-economic value of PRS testing. In conclusion, it is becoming clear that PRS have value in disease risk prediction and there are multiple areas where this may have clinical utility.

Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics

“…Although the combined-phenotype method we employed did not enable identification of novel loci, ancestral diversity improved characterization of loci containing both ancestry-specific and common variants. The continued underrepresentation of diverse populations in GWAS despite the growing clinical and public health significance of GWAS-enabled tools that are ancestry-specific underscores the continued importance of expanding existing RBC trait GWAS of predominantly European and East Asian populations to global populations [50][51][52][53].…”

<p>Predictors of Current DSM-5 PTSD Diagnosis and Symptom Severity Among Deployed Veterans: Significance of Predisposition, Stress Exposure, and Genetics</p>

“…62 For the current study, we assessed 4 genetic markers using a cumulative risk-allele model to test for an association with PTSD among outpatients, comparable to what has been undertaken to predict genetic associations in other clinical areas. 64,65 Extending previous research, 8,10 we specifically genotyped SNPs located within the FK506 binding protein-5 (FKBP5), retinoid-related orphan receptor alpha (RORA), cholinergic receptor nicotinic alpha-5 (CHRNA5), and the corticotropin-releasing hormone receptor-1 (CRHR1) gene clusters and assessed these markers for cumulative risk for current PTSD.…”

Integrative analysis of the plasma proteome and polygenic risk of cardiometabolic diseases

“…Polygenic risk scores (PRSs) capture this architecture by combining the effects of genome-wide genetic variation on risk of disease into a single score representing the aggregate of an individual's genetic predisposition to disease. While PRSs have shown promise for risk prediction and early stratification [4][5][6][7] , there is parallel interest to utilise PRSs to dissect underlying disease biology. A key area of investigation is identification of the convergent pathways and biomolecules, which are perturbed by these aggregate polygenic effects in asymptomatic individuals, influencing the development and progression of disease over decades of exposure [8][9][10] .…”