The contribution of six polymorphisms to cardiovascular risk in a Dutch high-risk primary care population: the HIPPOCRATES project

Abstract

This study was designed to examine the contribution of six polymorphisms to the occurrence of cardiovascular disease (CVD) in a Dutch primary care population with a high prevalence of cardiovascular risk factors. In this cross-sectional case-control study, 232 patients with CVD and 571 event-free controls were studied. Patients were genotyped for the AGTR1 (A1166C), AGT (M235T), ACE (4656rpt), NOS3 (E298D), GNB3 (C825T) and ADD1 (G460W) polymorphisms. Univariate and multivariate odds ratios (ORs) were calculated to assess the relationship between genotypes and CVD. Receiver operating characteristic (ROC) analysis was used to quantify the contribution of the polymorphisms to the prediction of CVD. No differences in either genotype or allele frequencies were found between CVD cases and controls. Multivariate analyses, corrected for multiple testing according to Bonferroni, showed significant protective associations for the T-allele of AGT (OR ¼ 0.55 (0.34-0.84)) and for the T-allele of ADD1 (OR ¼ 0.52 (0.31-0.82)). ROC analysis showed only a very small improvement of CVD risk prediction by adding the six polymorphisms to a model with traditional risk factors. Our data suggest that a major attribution of the six polymorphisms to the cardiovascular risk prediction in a primary care population such as HIPPOCRATES is unlikely.

Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration

“…Note that several studies have presented adjusted effect sizes for genetic variants (e.g. [40,45,48]) that were PSA at diagnosis or interview (ng mL Other treatment 11 0AE8…”

“…Age and gender, both demographic variables, were incorporated in both the univariate as well as in the multivariate linear regression analyses […] Adjustment for potential confounders was performed by incorporating smoking, alcohol, diabetes mellitus, waist circumference, serum creatinine, mean systolic and diastolic blood pressure, microalbuminuria and dyslipidaemia into these models. To avoid collinearity, waist circumference was used instead of waist-to-hip ratio or body mass index and condensed measures such as diabetes and dyslipidaemia were used, as defined earlier' [48].…”

“…(Sources of data) 'Phenotyping was performed by the participating gastroenterologist from each university medical center by reviewing a patient's chart retrospectively' [7]. (Sources of data) 'All clinical measurements were performed in practice by [the first author] (first measurement) and a nurse practitioner (second, third and fourth measurements with in-between periods of 3 months)' [48].…”

Strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS): explanation and elaboration

“…To avoid collinearity, waist circumference was used instead of waist-to-hip ratio or body mass index and condensed measures such as diabetes and dyslipidaemia were used, as defined earlier' . 51 Explanation: Because of the potential for flexibility in the derivation of the risk model, authors need to clarify why and how they constructed the model as they did and which data they used. This clarification includes a specification of the variables, defined in item 6, that were initially considered and which procedures were followed for a final selection (eg, backward deletion or forward inclusion, and the criteria for deletion and inclusion), if applicable.…”

“…7 (Sources of data) 'All clinical measurements were performed in practice by [the first author] (first measurement) and a nurse practitioner (second, third and fourth measurements with in-between periods of 3 months)' . 51 (Methods of assessment) 'Weight was measured in underwear to the nearest 0.1 kg on Soehnle electronic scales. We measured height in bare feet to the nearest 1 mm by using a stadiometer with the participant standing erect with head in the Frankfort plane.…”