ArticleJournal of community genetics2025
The impact of supplementing traditional risk information with polygenic risk score concerning type 2 diabetes and coronary heart disease on health behavior: a randomized controlled trial.
Article in Journal of community genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Supplementing Disease Risk Information for Type 2 Diabetes and Coronary Heart Disease with Polygenic Risk Scores: Testing a Health Action Process Approach-Inspired Path Model to Predict Health Behavior.International journal of behavioral medicine · 2026Article
- Effects of polygenic risk score communication on short term health outcomes: systematic review and meta-analysis.BMJ medicine · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Polygenic risk scores (PRS) for different diseases are expected to become more widely available to the public in the coming decades. In addition to the investigation of the clinical relevance of polygenic risk scores, an assessment of the health behavioral impact is needed. The present study used data from a personalized medicine project that combined genomic and traditional health data to evaluate respondents' risk for common diseases. Specifically, we investigated if supplementing traditional risk estimates of type 2 diabetes and coronary heart disease with PRS influenced respondents' self-reported physical activity, alcohol consumption, fruit/vegetable consumption or prompted the respondents to seek medical treatment/examination. As an exploratory hypothesis, we also tested if there was an interaction between the disease risk level and the experimental/control group for any of the outcomes. A randomized controlled trial was conducted, where the experimental group (n = 216 for seeking treatment and 523-459 for other outcomes) received risk estimates based on traditional risk and PRS, and the control group (n = 216 and 526-498) based solely on traditional risk factors. On average, approximately 80 days elapsed between the risk disclosure and outcome measurements. We found no significant difference between the groups regarding health behavior (ps > .28, ds < 0.07) or likelihood of seeking medical treatment/examination (p = .86, OR = 1.06). Likewise, no significant interactions were detected (ps > .08, ds < .11, ORs < 1.2). We conclude that we did not find support for either a beneficial or detrimental effect of supplementing traditional risk estimates with PRSs. However, several limitations should be noted when generalizing the results.
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Registered trials
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