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      Interactions Between Enhanced Polygenic Risk Scores and Lifestyle for Cardiovascular Disease, Diabetes, and Lipid Levels

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          Both lifestyle and genetic factors confer risk for cardiovascular diseases, type 2 diabetes, and dyslipidemia. However, the interactions between these 2 groups of risk factors were not comprehensively understood due to previous poor estimation of genetic risk. Here we set out to develop enhanced polygenic risk scores (PRS) and systematically investigate multiplicative and additive interactions between PRS and lifestyle for coronary artery disease, atrial fibrillation, type 2 diabetes, total cholesterol, triglyceride, and LDL-cholesterol.


          Our study included 276 096 unrelated White British participants from the UK Biobank. We investigated several PRS methods (P+T, LDpred, PRS continuous shrinkage, and AnnoPred) and showed that AnnoPred achieved consistently improved prediction accuracy for all 6 diseases/traits. With enhanced PRS and combined lifestyle status categorized by smoking, body mass index, physical activity, and diet, we investigated both multiplicative and additive interactions between PRS and lifestyle using regression models.


          We observed that healthy lifestyle reduced disease incidence by similar multiplicative magnitude across different PRS groups. The absolute risk reduction from lifestyle adherence was, however, significantly greater in individuals with higher PRS. Specifically, for type 2 diabetes, the absolute risk reduction from lifestyle adherence was 12.4% (95% CI, 10.0%–14.9%) in the top 1% PRS versus 2.8% (95% CI, 2.3%–3.3%) in the bottom PRS decile, leading to a ratio of >4.4. We also observed a significant interaction effect between PRS and lifestyle on triglyceride level.


          By leveraging functional annotations, AnnoPred outperforms state-of-the-art methods on quantifying genetic risk through PRS. Our analyses based on enhanced PRS suggest that individuals with high genetic risk may derive similar relative but greater absolute benefit from lifestyle adherence.

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          Evidence of Lifestyle Modification in the Management of Hypercholesterolemia

          Background: Coronary heart disease (CHD) is the leading cause of morbidity and mortality worldwide. The growth of ageing populations in developing countries with progressively urbanized lifestyles are major contributors. The key risk factors for CHD such as hypercholesterolemia, diabetes mellitus, and obesity are likely to increase in the future. These risk factors are modifiable through lifestyle. Objectives: To review current literature on the potential benefit of cholesterol lowering in CHD risk reduction with a particular focus on the evidence of non-pharmacological/lifestyle management of hypercholesterolemia. Methods: Medline/PubMed systematic search was conducted using a two-tier approach limited to all recent English language papers. Primary search was conducted using key words and phrases and all abstracts were subsequently screened and relevant papers were selected. The next tier of searching was conducted by (1) reviewing the citation lists of the selected papers and (2) by using PubMed weblink for related papers. Over 3600 reports were reviewed. Results: Target cholesterol levels set out in various guidelines could be achieved by lifestyle changes, including diet, weight reduction, and increased physical activity with the goal of reducing total cholesterol to <200 mg/dL and LDL-C <100mg/dL. Various dietary constituents such as green tea, plant sterols, soy protein have important influences on total cholesterol. Medical intervention should be reserved for those patients who have not reached this goal after 3 months of non-pharmacological approach. Conclusion: CHD remains as a leading cause of death worldwide and hypercholesterolemia is an important cause of CHD. Non-pharmacological methods provide initial as well as long-term measures to address this issue.

            Author and article information

            Circulation: Genomic and Precision Medicine
            Circ: Genomic and Precision Medicine
            Ovid Technologies (Wolters Kluwer Health)
            February 2021
            February 2021
            : 14
            : 1
            [1 ]Program of Computational Biology and Bioinformatics (Y.Y., H.Z.), Yale University.
            [2 ]Department of Statistics and Data Science (X.C., J.H.), Yale University.
            [3 ]Department of Molecular Biophysics and Biochemistry (X.C., J.H.), Yale University.
            [4 ]Department of Biostatistics, Yale School of Public Health, New Haven, CT (W.J., H.Z.).
            [5 ]Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston (P.N.).
            [6 ]Program in Medical and Population Genetics, Broad Institute of Harvard &amp; Massachusetts Institute of Technology, Cambridge, MA (P.N.).
            © 2021


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