Abstract
Abstract
Background
Polygenic risk scores (PRS) have been widely applied in research studies, showing how population groups can be stratified into risk categories for many common conditions. As healthcare systems consider applying PRS to keep their populations healthy, little work has been carried out demonstrating their implementation at an individual level.
Case presentation
We performed a systematic curation of PRS sources from established data repositories, selecting 15 phenotypes, comprising an excess of 37 million SNPs related to cancer, cardiovascular, metabolic and autoimmune diseases. We tested selected phenotypes using whole genome sequencing data for a family of four related individuals. Individual risk scores were given percentile values based upon reference distributions among 1000 Genomes Iberians, Europeans, or all samples. Over 96 billion allele effects were calculated in order to obtain the PRS for each of the individuals analysed here.
Conclusions
Our results highlight the need for further standardisation in the way PRS are developed and shared, the importance of individual risk assessment rather than the assumption of inherited averages, and the challenges currently posed when translating PRS into risk metrics.
Publisher
Springer Science and Business Media LLC
Subject
Genetics (clinical),Genetics
Reference117 articles.
1. Lewis CM, Vassos E. Polygenic risk scores: from research tools to clinical instruments. Genome Med. 2020;12:44.
2. Department of Health and Social Care. Genome UK: the future of healthcare. 2020. https://www.gov.uk/government/publications/genome-uk-the-future-of-healthcare. Accessed 7 Apr 2021.
3. Khera AV, Chaffin M, Aragam KG, Haas ME, Roselli C, Choi SH, et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat Genet. 2018;50:1219–24.
4. Fullerton JM, Nurnberger JI. Polygenic risk scores in psychiatry: Will they be useful for clinicians. F1000Res. 2019. https://doi.org/10.12688/f1000research.18491.1.
5. Machini K, Ceyhan-Birsoy O, Azzariti DR, Sharma H, Rossetti P, Mahanta L, et al. Analyzing and reanalyzing the genome: findings from the MedSeq project. Am J Hum Genet. 2019;105:177–88.
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