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The evolution of genetic-based risk scores for lipids and cardiovascular disease

Dron, Jacqueline S.a,b; Hegele, Robert A.a,b,c

Current Opinion in Lipidology: April 2019 - Volume 30 - Issue 2 - p 71–81
doi: 10.1097/MOL.0000000000000576

Purpose of review With improved next-generation sequencing technology, open-access genetic databases and increased awareness of complex trait genetics, we are entering a new era of risk assessment in which genetic-based risk scores (GRSs) will play a clinical role. We review the concepts underlying polygenic models of disease susceptibility and challenges in clinical implementation.

Recent findings Polygenic risk scores are currently used in genetic research on dyslipidemias and cardiovascular disease (CVD). Although the underlying principles for constructing polygenic scores for lipids are established, the lack of consensus on which score to use is indicated by the large number — about 50 — that have been published. Recently, large-scale polygenic scores for CVD appear to afford superior risk prediction compared to small-scale scores. Despite the potential benefits of GRSs, certain biases towards ethnicity and sex need to be worked through.

Summary We are on the verge of clinical application of GRSs to provide incremental information on dyslipidemia and CVD risk above and beyond traditional clinical variables. Additional work is required to develop a consensus of how such scores will be constructed and measured in a validated manner, as well as clinical indications for their use.

aDepartment of Biochemistry, Schulich School of Medicine and Dentistry, Western University

bRobarts Research Institute, Schulich School of Medicine and Dentistry, Western University

cDepartment of Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada

Correspondence to Robert A. Hegele, MD, FRCPC, Robarts Research Institute, Western University, 4288A-1151 Richmond Street North, London, ON N6A 5K8, Canada. Tel: +1 519-931-5271; fax: +1 519-931-5218; E-mail:

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