Last
Posted:
May 30, 2024
Highlights
The acceptability and clinical impact of using polygenic scores for risk-estimation of common cancers in primary care: a systematic review
From the abstract: "A total of 190 papers were identified, 18 of which were eligible for inclusion. A cancer risk-assessment tool incorporating PGS was acceptable to the general practice population and their healthcare providers but major challenges to implementation were identified, including lack of evidence for PGS in non-European ancestry and a need for healthcare provider education in genomic medicine. A PGS cancer risk-assessment had relatively limited impact on psychosocial outcomes and health behaviours. However, for prostate cancer, potential applications for its use in primary care were shown. "
Managing differential performance of polygenic risk scores across groups: Real-world experience of the eMERGE Network
From the abstract: "The differential performance of polygenic risk scores (PRSs) by group is one of the major ethical barriers to their clinical use. It is also one of the main practical challenges for any implementation effort. The social repercussions of how people are grouped in PRS research must be considered in communications with research participants, including return of results. Here, we outline the decisions faced and choices made by a large multi-site clinical implementation study returning PRSs to diverse participants in handling this issue of differential performance. "
Utility of polygenic scores across diverse diseases in a hospital cohort for predictive modeling
TH Sun et al, Nature Comm, April 12, 2024
From the abstract: "Polygenic scores estimate genetic susceptibility to diseases. We systematically calculated polygenic scores across 457 phenotypes using genotyping array data from Medical University Hospital. Logistic regression models assessed polygenic scores’ ability to predict disease traits. The polygenic score model with the highest accuracy, based on maximal area under the receiver operating characteristic curve (AUC), is provided on the GeneAnaBase website of the hospital. Our findings indicate 49 phenotypes with AUC greater than 0.6, predominantly linked to endocrine and metabolic diseases. "
Future implications of polygenic risk scores for life insurance underwriting.
Tatiane Yanes et al. NPJ Genom Med 2024 3 (1) 25
From the abstract: "As PGS is increasingly utilized in research and clinical practice, it is pivotal that careful consideration is given to the potential insurance implications of PGS to ensure consumer protection against GD. For the full potential benefits of PGS to be realized, and its clinical utility determined across various use cases, individuals will need to be confident that they can participate in research studies and access clinical genetic testing without fear of insurance discrimination. Clarification is needed regarding the extent to which existing protections and legislation relating to monogenic testing may also extend to PGS test results. "
