The study got its start after Dr. Amit V. Khera, one of Dr. Kathiresan’s postdoctoral fellows, noticed that researchers had looked at genetic risks of heart disease and had, in different studies, looked at the effect of environment and lifestyle risks. So, he wondered, why not look at lifestyles and genetics in the same populations and see how much each contributes? 
 
 The researchers began about a year and a half ago, analyzing data from four large studies that not only had genetic data on participants but also had information on lifestyles and on which participants developed heart disease. 
 
 The investigators developed a genetic score based on 50 genes associated with heart disease. They developed a lifestyle score based on whether people smoked, whether they exercised at least once a week, whether they followed a healthy diet — one with fruits, vegetables, fish, whole grains and nuts — and whether they were obese. 
 
 An optimum lifestyle score was defined as having three or all four of these elements, which is important, Dr. Kathiresan said, because many people who are obese have enormous difficulty losing weight and maintaining their weight loss. “You can get into this group even if you are obese by not smoking, exercising and eating a healthy diet, “ he said. 
 
 Even better, said Dr. Lawrence J. Appel, the director of the Welch Center for Prevention, Epidemiology and Clinical Research at Johns Hopkins Medicine, you do not have to have an exemplary lifestyle to reap a big benefit. It looks as if the biggest protective effect by far came from going from a terrible lifestyle to one that was at least moderately good. 
 
 Dr. John Michael Gaziano, a preventive cardiologist at the VA Boston Healthcare System and at Brigham and Women’s Hospital, said the work showed the power of large data sets. Until recently, researchers mostly used much smaller data sets, which tend to have a lot of random variation, making results hard to interpret. The Million Veteran Program, a study that he is leading, and the National Institutes of Health’s precision medicine initiative that is recruiting a million participants should provide the sort of data that can make results like Dr. Kathiresan’s more feasible and more powerful. 
 
 For Dr. Gaziano, the biggest surprise was that a test based on combining 50 genes, each of which had a tiny role in heart disease, was such a powerful predictor of risk. The larger studies underway now should allow researchers to understand more about how much each of those genes contributes, he added. 

 Table 1. Table 1. Characteristics of the Participants at Baseline. 
 
 The populations in the prospective cohort studies included 7814 of 11,478 white participants in the ARIC cohort, 21,222 of 23,294 white women in the WGHS cohort, and 22,389 of 30,446 participants in the MDCS cohort for whom genotype and covariate data were available (Table 1). During follow-up, 1230 coronary events were observed in the ARIC cohort (median follow-up, 18.8 years), 971 coronary events in the WGHS cohort (median follow-up, 20.5 years), and 2902 coronary events in the MDCS cohort (median follow-up, 19.4 years) (Table S4 in the Supplementary Appendix). Categories of genetic and lifestyle risk were mutually independent within each cohort (Fig. S1 in the Supplementary Appendix). 
 
 Figure 1. Figure 1. Standardized Coronary Events Rates, According to Genetic and Lifestyle Risk in the Prospective Cohorts. Shown are the standardized rates of coronary events, according to the genetic risk and lifestyle risk of participants in the Atherosclerosis Risk in Communities (ARIC) cohort, the Women’s Genome Health Study (WGHS) cohort, and the Malmö Diet and Cancer Study (MDCS) cohort. The 95% confidence intervals for the hazard ratios are provided in parentheses. Cox regression models were adjusted for age, sex (in ARIC and MDCS), randomization to receive vitamin E or aspirin (in WGHS), education level, and principal components of ancestry (in ARIC and WGHS). Standardization was performed to cohort-specific population averages for each covariate. 
 
 Polygenic risk scores approximated a normal distribution within each cohort (Fig. S2 in the Supplementary Appendix). A risk gradient was noted across quintiles of genetic risk such that the participants at high genetic risk (i.e., in the top quintile of the polygenic scores) were at significantly higher risk of coronary events than those at low genetic risk (i.e., in the lowest quintile), with adjusted hazard ratios of 1.75 (95% confidence interval [CI], 1.46 to 2.10) in the ARIC cohort, 1.94 (95% CI, 1.58 to 2.39) in the WGHS cohort, and 1.98 (95% CI, 1.76 to 2.23) in the MDCS cohort (Figure 1, and Table S5 and Fig. S3 in the Supplementary Appendix). Across all three cohorts, the relative risk of incident coronary events was 91% higher among participants at high genetic risk than among those at low genetic risk (hazard ratio, 1.91; 95% CI, 1.75 to 2.09). A family history of coronary artery disease was an imperfect surrogate for genotype-defined risk, although the prevalence of such a self-reported family history tended to be higher among participants at high genetic risk than among those at low genetic risk. Levels of low-density lipoprotein (LDL) cholesterol were modestly increased across categories of genetic risk within each cohort. By contrast, genetic risk categories were independent of other cardiometabolic risk factors and 10-year cardiovascular risk as predicted by the pooled cohorts equation of the American College of Cardiology–AHA (Tables S6 through S9 in the Supplementary Appendix). 
 
 Each of the four healthy lifestyle factors was associated with a decreased risk of coronary events in a combined analysis of the prospective cohorts: no current smoking (hazard ratio, 0.56; 95% CI, 0.47 to 0.66), no obesity (hazard ratio, 0.66; 95% CI, 0.58 to 0.76), regular physical activity (hazard ratio, 0.88; 95% CI, 0.80 to 0.97), and healthy diet (hazard ratio, 0.91; 95% CI, 0.83 to 0.99) (Table S10 in the Supplementary Appendix). Coronary risk increased among participants with fewer healthy lifestyle factors within each cohort (Table S11 in the Supplementary Appendix). 
 
 Each cohort was divided into three lifestyle risk categories: favorable (at least three of the four healthy lifestyle factors), intermediate (two healthy lifestyle factors), or unfavorable (no or only one healthy lifestyle factor). Participants with an unfavorable lifestyle had higher rates of baseline hypertension and diabetes, a higher body-mass index, and less favorable levels of circulating lipids than did those with a favorable lifestyle (Tables S12, S13, and S14 in the Supplementary Appendix). An unfavorable lifestyle was associated with a higher risk of coronary events than a favorable lifestyle, with an adjusted hazard ratio of 1.71 (95% CI, 1.47 to 1.98) in the ARIC cohort, 2.27 (95% CI, 1.92 to 2.67) in the WGHS cohort, and 1.77 (95% CI, 1.61 to 1.95) in the MDCS cohort (Figure 1, and Fig. S3 in the Supplementary Appendix). 
 
 Figure 2. Figure 2. Risk of Coronary Events, According to Genetic and Lifestyle Risk in the Prospective Cohorts. Shown are adjusted hazard ratios for coronary events in each of the three prospective cohorts, according to genetic risk and lifestyle risk. In these comparisons, participants at low genetic risk with a favorable lifestyle served as the reference group. There was no evidence of a significant interaction between genetic and lifestyle risk factors (P=0.38 for interaction in the Atherosclerosis Risk in Communities (ARIC) cohort, P=0.31 in the Women’s Genome Health Study (WGHS) cohort, and P=0.24 in the Malmö Diet and Cancer Study (MDCS) cohort). Unadjusted incidence rates are reported per 1000 person-years of follow-up. A random-effects meta-analysis was used to combine cohort-specific results. 
 
 Figure 3. Figure 3. 10-Year Coronary Event Rates, According to Lifestyle and Genetic Risk in the Prospective Cohorts. Shown are standardized 10-year cumulative incidence rates for coronary events in the three prospective cohorts, according to lifestyle and genetic risk. Standardization was performed to cohort-specific population averages for each covariate. The I bars represent 95% confidence intervals. 
 
 Within each category of genetic risk, lifestyle factors were strong predictors of coronary events (Figure 2). Adherence to a favorable lifestyle, as compared with an unfavorable lifestyle, was associated with a 45% lower relative risk among participants at low genetic risk, a 47% lower relative risk among those at intermediate genetic risk, and a 46% lower relative risk (hazard ratio, 0.54; 95% CI, 0.47 to 0.63) among those at high genetic risk. Among participants at high genetic risk, the standardized 10-year coronary event rates were 10.7% among those with an unfavorable lifestyle and 5.1% among those with a favorable lifestyle in the ARIC cohort, 4.6% and 2.0%, respectively, in the WGHS cohort, and 8.2% and 5.3% in the MDCS cohort (Figure 3). Similarly, a low genetic risk was largely offset by an unfavorable lifestyle. Among participants at low genetic risk, standardized 10-year coronary event rates were 5.8% among those with an unfavorable lifestyle and 3.1% among those with a favorable lifestyle in the ARIC cohort, 1.8% and 1.2%, respectively, in the WGHS cohort, and 4.7% and 2.6% in the MDCS cohort. Similar patterns were noted after the exclusion of coronary revascularization from the composite end point (Fig. S4 in the Supplementary Appendix). Adjustment for traditional risk factors attenuated estimates, although the decreased risk among participants with a favorable lifestyle within each genetic risk category remained apparent (Table S15 and Fig. S5 in the Supplementary Appendix). 
 
 Despite a paucity of well-validated genetic loci in black populations, we observed similar findings among black participants and white participants in the ARIC cohort (Fig. S6 in the Supplementary Appendix). However, additional data are needed to confirm the consistency of the effect in populations of African ancestry. 
 
 Figure 4. Figure 4. Coronary-Artery Calcification Score in the BioImage Study, According to Lifestyle and Genetic Risk. Among the participants in the BioImage Study, a standardized score for coronary-artery calcification was determined by means of linear regression after adjustment for age, sex, education level, and principal components of ancestry. Standardization was performed on the basis of study averages for each covariate. Average standardized coronary-artery calcification scores are expressed in Agatston units, with higher scores indicating an increased burden of coronary atherosclerosis. The I bars represent 95% confidence intervals. 
 
 A cross-sectional analysis of 4260 of 4301 white participants with available data from the BioImage Study showed that both genetic and lifestyle factors were associated with coronary-artery calcification (stratified according to the baseline characteristics in Tables S16 and S17 in the Supplementary Appendix). The standardized calcification score was 46 Agatston units (95% CI, 39 to 54) among participants at high genetic risk, as compared with 21 Agatston units (95% CI, 18 to 25) among those at low genetic risk (P<0.001). The calcification score was similarly higher among participants with an unfavorable lifestyle than among those with a favorable lifestyle: 46 Agatston units (95% CI, 40 to 53) versus 28 Agatston units (95% CI, 25 to 31) (P<0.001). Within each subgroup of genetic risk, a significant trend was observed toward decreased coronary-artery calcification among participants who were more adherent to a healthy lifestyle (Figure 4).
– If you lost the genetic lottery when it comes to heart disease, take, well, heart: The upshot of a study published in the New England Journal of Medicine is that "DNA is not destiny; it is not deterministic for this disease," as Dr. Sekar Kathiresan puts it. While the analysis of health data on some 55,000 people did reveal that "bad" genes can double your heart disease risk, researchers found that participants who had high genetic risk but led a "favorable" lifestyle can halve their risk. On the flip side, those dealt a good genetic hand who led an "unfavorable" lifestyle lost about half the genetic advantage, reports the New York Times. So how to move into the favorable category? The study's authors focused on four indicators of a healthy lifestyle: no current smoking, no obesity, regular physical activity (the Times defines this as at least once a week), and healthy diet. Adhering to at least three of the four factors places one in the favorable column; unfavorable is one factor or less. "Patients may equate DNA-based risk estimates with determinism, a perceived lack of control over the ability to improve outcomes," the researchers write. "However, our results provide evidence that lifestyle factors may powerfully modify risk regardless of the patient’s genetic risk profile." But since a favorable lifestyle was tied to a reduced risk across each stratum of genetic risk, even those with "good" genes should take note.