Validation of an Integrated Risk Tool, Including Polygenic Risk Score, for Atherosclerotic Cardiovascular Disease in Multiple Ethnicities and Ancestries

Abstract

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Transferability of genetic loci and polygenic scores for cardiometabolic traits in British Pakistanis and Bangladeshis

“…We assessed the clinical value of the PGS for CAD on top of the traditional clinical risk factors captured in the QRISK3 algorithm. Similar work has been done previously in research cohorts [9][10][11][12] ; our study represents an important addition since it captures the noise with which QRISK3 is actually measured within a real-world clinical setting (as opposed to using comprehensive measures taken for research purposes), which may affect performance of integrated risk models combining these factors with PGSs. We note that only about 4% of the ~8 million individuals used for developing QRISK3 were of South Asian ancestry 26 , and the weights for each conventional risk factor might not be optimal for SAS individuals.…”

“…Furthermore, the potential clinical utility of a CAD PGS in a real-world healthcare system is largely unknown, since previous studies have mostly examined research cohorts composed of volunteers who are healthier and wealthier than average (e.g. UK Biobank [8][9][10][11][12] ).…”

Implementation and implications for polygenic risk scores in healthcare

“…This means maximizing benefit and minimizing harm associated with unnecessary diagnostic procedures and side-effects of preventative medications and treatments. Already, studies are being published showing that combining standard risk assessment tools with PRSs can improve overall risk prediction [ 41 ], even in multiple ancestries [ 68 ].…”

Of Screening, Stratification, and Scores

“…To ensure that risk stratification algorithms can produce accurate risk-estimates for all members of society, a number of approaches might be practicable. Possibilities discussed in the scientific literature include the creation of separate PRS algorithms or risk stratification methodologies for individuals from distinct genetic ancestry groups, as well as the creation of a singular algorithm trained on holistic training data that are representative of diversity in genetic ancestry (i.e., PRS scores with cross-population portability) [ 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 ]. In either instance, it will be necessary for large quantities of rich data from diverse human populations to be made available to health sector entities to ensure that risk stratification methodologies yield equitable and applicable results [ 68 ].…”