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How Communicating Polygenic and Clinical Risk for Atherosclerotic Cardiovascular Disease Impacts Health Behavior : an Observational Follow-up Study

Widén, Elisabeth (author)
University of Helsinki
Junna, Nella (author)
University of Helsinki
Ruotsalainen, Sanni (author)
University of Helsinki
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Surakka, Ida (author)
University of Helsinki
Mars, Nina (author)
University of Michigan Medical School,University of Helsinki
Ripatti, Pietari (author)
Helsinki University Central Hospital,University of Helsinki
Partanen, Juulia J. (author)
University of Helsinki,Folkhälsan Research Center
Aro, Johanna (author)
University of Helsinki
Mustonen, Pekka (author)
Duodecim Publishing Company Ltd
Tuomi, Tiinamaija (author)
Lund University,Lunds universitet,Diabetiska komplikationer,Forskargrupper vid Lunds universitet,Diabetic Complications,Lund University Research Groups,University of Helsinki
Palotie, Aarno (author)
University of Helsinki,Massachusetts General Hospital
Salomaa, Veikko (author)
Finnish National Institute for Health and Welfare
Kaprio, Jaakko (author)
University of Helsinki
Partanen, Jukka (author)
Finnish Red Cross Blood Transfusion Service
Hotakainen, Kristina (author)
Mehiläinen Oy
Pöllänen, Pasi (author)
University of Helsinki
Ripatti, Samuli (author)
University of Helsinki
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 (creator_code:org_t)
2022
2022
English.
In: Circulation: Genomic and Precision Medicine. - 2574-8300. ; 15:2, s. 003459-003459
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Background: Prediction tools that combine polygenic risk scores with clinical factors provide a new opportunity for improved prediction and prevention of atherosclerotic cardiovascular disease, but the clinical utility of polygenic risk score has remained unclear. Methods: We collected a prospective cohort of 7342 individuals (64% women, mean age 56 years) and estimated their 10-year risk for atherosclerotic cardiovascular disease both by a traditional risk score and a composite score combining the effect of a polygenic risk score and clinical risk factors. We then tested how returning the personal risk information with an interactive web-tool impacted on the participants' health behavior. Results: When reassessed after 1.5 years by a clinical visit and questionnaires, 20.8% of individuals at high (>10%) 10-year atherosclerotic cardiovascular disease risk had seen a doctor, 12.4% reported weight loss, 14.2% of smokers had quit smoking, and 15.4% had signed up for health coaching online. Altogether, 42.6% of persons at high risk had made one or more health behavioral changes versus 33.5% of persons at low/average risk such that higher baseline risk predicted a favorable change (OR [CI], 1.53 [1.37-1.72] for persons at high risk versus the rest, P<0.001), with both high clinical (P<0.001) and genomic risk (OR [CI], 1.10 [1.03-1.17], P=0.003) contributing independently. Conclusions: Web-based communication of personal atherosclerotic cardiovascular disease risk-data including polygenic risk to middle-aged persons motivates positive changes in health behavior and the propensity to seek care. It supports integration of genomic information into clinical risk calculators as a feasible approach to enhance disease prevention.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Kardiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cardiac and Cardiovascular Systems (hsv//eng)

Keyword

cardiovascular disease
communication
genomics
risk factor
weight loss

Publication and Content Type

art (subject category)
ref (subject category)

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