Loss of Cardioprotective Effects at the ADAMTS7 Locus as a Result of Gene-Smoking Interactions

BACKGROUND: Common diseases such as coronary heart disease (CHD) are complex in etiology. The interaction of genetic susceptibility with lifestyle factors may play a prominent role. However, gene-lifestyle interactions for CHD have been difficult to identify. Here, we investigate interaction of smoking behavior, a potent lifestyle factor, with genotypes that have been shown to associate with CHD risk. METHODS: We analyzed data on 60 919 CHD cases and 80 243 controls from 29 studies for gene-smoking interactions for genetic variants at 45 loci previously reported to be associated with CHD risk. We also studied 5 loci associated with smoking behavior. Study-specific gene-smoking interaction effects were calculated and pooled using fixed-effects meta-analyses. Interaction analyses were declared to be significant at a P value of <1.0x10(-3) (Bonferroni correction for 50 tests). RESULTS: We identified novel gene-smoking interaction for a variant upstream of the ADAMTS7 gene. Every T allele of rs7178051 was associated with lower CHD risk by 12% in never-smokers (P= 1.3x10(-16)) in comparison with 5% in ever-smokers (P= 2.5x10(-4)), translating to a 60% loss of CHD protection conferred by this allelic variation in people who smoked tobacco (interaction P value= 8.7x10(-5)). The protective T allele at rs7178051 was also associated with reduced ADAMTS7 expression in human aortic endothelial cells and lymphoblastoid cell lines. Exposure of human coronary artery smooth muscle cells to cigarette smoke extract led to induction of ADAMTS7. CONCLUSIONS: Allelic variation at rs7178051 that associates with reduced ADAMTS7 expression confers stronger CHD protection in never-smokers than in ever-smokers. Increased vascular ADAMTS7 expression may contribute to the loss of CHD protection in smokers.Peer reviewe

Predictive value of long-term changes of growth differentiation factor-15 over a 27-year-period for heart failure and death due to coronary heart disease

<div><p>Background</p><p>Growth differentiation factor-15 (GDF-15), Cystatin C and C-reactive protein (CRP) have been discussed as biomarkers for prediction of cardiac diseases. The aim of this study was to investigate the predictive value of single and repeated measurements of GDF-15 compared to Cystatin C and CRP for incidence of heart failure (HF) and death due to coronary heart disease (CHD) in the general population.</p><p>Methods and results</p><p>Levels of GDF-15, CRP and Cystatin C were determined in three repeated measurements collected 5 years apart in the DAN-MONICA (Danish-Multinational MONitoring of trends and determinants in Cardiovascular disease) cohort (participants at baseline n = 3785). Cox regression models adjusted for cardiovascular risk factors revealed significantly increased hazard ratios (HR) for GDF-15 for incident HF 1.36 (HR per interquartile range (IQR) increase, 95% confidence interval (CI): 1.16; 1.59) and for death from CHD 1.51 (HR per IQR increase, 95% CI: 1.31, 1.75) (both with p<0.001). Joint modeling of time-to-event and longitudinal GDF-15 over a median 27-year follow-up period showed that the marker evolution was positively associated with death of CHD (HR per IQR increase 3.02 95% CI: (2.26, 4.04), p < 0.001) and HF (HR per IQR increase 2.12 95% CI: (1.54, 2.92), p<0.001). However using Cox models with follow-up time starting at the time of the third examination, serial measurement of GDF-15, modeled as changes between the measurements, did not improve prediction over that of the most recent measurement.</p><p>Conclusions</p><p>GDF-15 is a promising biomarker for prediction of HF and death due to CHD in the general population, which may provide prognostic information to already established clinical biomarkers. Repeated measurements of GDF-15 displayed only a slight improvement in the prediction of these endpoints compared to a single measurement.</p></div

Biomarker hazard ratios for the endpoints death from CHD and incidence of HF.

<p>Cox models were adjusted for age (as the time scale), sex, overweight (BMI > 25 kg/m²), systolic blood pressure, diabetes, daily smoker, renal insufficiency (eGFR > 60 ml/min or 1,73m³). The biomarkers were used after being log-transformed. The follow-up time begins at round 1. Only round 1 measurements are used. IQR: interquartile range.</p

Longitudinal biomarker measurements: Hazard ratios for incident HF estimated by joint models.

<p>Longitudinal biomarker measurements: Hazard ratios for incident HF estimated by joint models.</p

C-indices for 25-year prediction of death from CHD and HF.

<p>C-indices for 25-year prediction of death from CHD and HF.</p

Longitudinal biomarker measurements: Hazard ratios for death from CHD estimated by joint models.

<p>Longitudinal biomarker measurements: Hazard ratios for death from CHD estimated by joint models.</p

Survival curves for the endpoints death from CHD and incidence of HF.

<p>Survival curves for the endpoints death from CHD and incidence of HF according to the biomarker quarters. The p-value shown is for the logrank test.</p

Hazard ratios for Cox models with follow-up starting at round 3.

<p>Hazard ratios for Cox models with follow-up starting at round 3.</p

Baseline characteristics of the DAN-MONICA cohort according to round 1–3 (Data for the imputed datasets).

<p>Baseline characteristics of the DAN-MONICA cohort according to round 1–3 (Data for the imputed datasets).</p

A Description of the FINRISK 1992 and 1997 Cohorts

<p>Compared to FINRISK-92, the FINRISK-97 cohort includes an additional sample of individuals aged 65–74 y. Numbers for this additional sample are described at the right-hand side for each endpoint. Persons examined refers to cohort individuals for whom information on smoking, blood pressure, cholesterol, and DNA, as well as consent for the use of DNA to study CHD and stroke, were available. Subcohorts are stratified random samples of the original cohorts including also cases. Mortality cases show total mortality, including also those who died from CHD or stroke. Thus, numbers in the boxes of subcohorts and outcome events are not mutually exclusive (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.0020069#pgen-0020069-t001" target="_blank">Table 1</a>). F, females; M, males.</p