A Mendelian randomization approach to assess the causal relationship of gamma-glutamyl transferase with blood pressure and insulin

Background: Elevated levels of g-glutamyl transferase (GGT) have been associated with subsequent risk of elevated blood pressure (BP), hypertension and diabetes. However, the causality of these relationships has not been addressed. Mendelian randomization refers to the random allocation of alleles at the time of gamete formation. Such allocation is expected to be independent of any behavioural and environmental factors (known or unknown), allowing the analysis of largely unconfounded risk associations that are not due to reverse causation. Methods: We performed a cross-sectional analysis among 4361 participants to the population based CoLaus study. Associations of sex-specific GGT quartiles with systolic BP, diastolic BP and insulin levels were assessed using multivariable linear regression analyses. The rs2017869 GGT1 variant, which explained 1.6% of the variance in GGT levels, was used as an instrument to perform a Mendelian randomization analysis. Results: Median age of the study population was 53 years. After age and sex adjustment, GGT quartiles were strongly associated with systolic and diastolic BP (all p for linear trend <0.0001). After multivariable adjustment, these relationships were significantly attenuated, but remained significant for systolic (b(95%CI)¼1.30 (0.32;2.03), p¼0.007) and diastolic BP (b (95%CI)¼0.57 (0.02;1.13), p¼0.04). Using Mendelian randomization, we observed no positive association of GGT with either systolic BP (b (95%CI)¼-5.68 (-11.51-0.16), p¼0.06) or diastolic BP (b (95%CI)¼ -2.24 (-5.98;1.49) p¼0.24). The association of GGT with insulin was also attenuated after multivariable adjustment. Nevertheless, a strong linear trend persisted in the fully adjusted model (b (95%CI)¼0.07 (0.04;0.09), p<0.0001). Using Mendelian randomization, we observed a similar positive association of GGT with insulin (b (95%CI)¼0.19 (0.01-0.37), p¼0.04). Conclusion: In this study, we found evidence for a direct causal relationship between GGT and insulin, suggesting that oxidative stress may be causally implicated in the pathogenesis of type 2 diabetes mellitus.

Potential impact of single-risk-factor versus total risk management for the prevention of cardiovascular events in Seychelles.

OBJECTIVE: To assess the prevalence of cardiovascular (CV) risk factors in Seychelles, a middle-income African country, and compare the cost-effectiveness of single-risk-factor management (treating individuals with arterial blood pressure >/= 140/90 mmHg and/or total serum cholesterol >/= 6.2 mmol/l) with that of management based on total CV risk (treating individuals with a total CV risk >/= 10% or >/= 20%).METHODS: CV risk factor prevalence and a CV risk prediction chart for Africa were used to estimate the 10-year risk of suffering a fatal or non-fatal CV event among individuals aged 40-64 years. These figures were used to compare single-risk-factor management with total risk management in terms of the number of people requiring treatment to avert one CV event and the number of events potentially averted over 10 years. Treatment for patients with high total CV risk (>/= 20%) was assumed to consist of a fixed-dose combination of several drugs (polypill). Cost analyses were limited to medication.FINDINGS: A total CV risk of >/= 10% and >/= 20% was found among 10.8% and 5.1% of individuals, respectively. With single-risk-factor management, 60% of adults would need to be treated and 157 cardiovascular events per 100 000 population would be averted per year, as opposed to 5% of adults and 92 events with total CV risk management. Management based on high total CV risk optimizes the balance between the number requiring treatment and the number of CV events averted.CONCLUSION: Total CV risk management is much more cost-effective than single-risk-factor management. These findings are relevant for all countries, but especially for those economically and demographically similar to Seychelles.

Alcohol drinking, the metabolic syndrome and diabetes in a population with high mean alcohol consumption.

AIMS: To investigate the relationship of alcohol consumption with the metabolic syndrome and diabetes in a population-based study with high mean alcohol consumption. Few data exist on these conditions in high-risk drinkers. METHODS: In 6172 adults aged 35-75 years, alcohol consumption was categorized as 0, 1-6, 7-13, 14-20, 21-27, 28-34 and ≥ 35 drinks/week or as non-drinkers (0), low-risk (1-13), medium-to-high-risk (14-34) and very-high-risk (≥ 35) drinkers. Alcohol consumption was objectively confirmed by biochemical tests. In multivariate analysis, we assessed the relationship of alcohol consumption with adjusted prevalence of the metabolic syndrome, diabetes and insulin resistance, determined with the homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS: Seventy-three per cent of participants consumed alcohol, 16% were medium-to-high-risk drinkers and 2% very-high-risk drinkers. In multivariate analysis, the prevalence of the metabolic syndrome, diabetes and mean HOMA-IR decreased with low-risk drinking and increased with high-risk drinking. Adjusted prevalence of the metabolic syndrome was 24% in non-drinkers, 19% in low-risk (P<0.001 vs. non-drinkers), 20% in medium-to-high-risk and 29% in very-high-risk drinkers (P=0.005 vs. low-risk). Adjusted prevalence of diabetes was 6.0% in non-drinkers, 3.6% in low-risk (P<0.001 vs. non-drinkers), 3.8% in medium-to-high-risk and 6.7% in very-high-risk drinkers (P=0.046 vs. low-risk). Adjusted HOMA-IR was 2.47 in non-drinkers, 2.14 in low-risk (P<0.001 vs. non-drinkers), 2.27 in medium-to-high-risk and 2.53 in very-high-risk drinkers (P=0.04 vs. low-risk). These relationships did not differ according to beverage types. CONCLUSIONS: Alcohol has a U-shaped relationship with the metabolic syndrome, diabetes and HOMA-IR, without differences between beverage types.

Cardiovascular risk estimation and eligibility for statins in primary prevention comparing different strategies

Recommendations for statin use for primary prevention of coronary heart disease (CHD) are based on estimation of the 10-year CHD risk. It is unclear which risk algorithm and guidelines should be used in European populations. Using data from a population-based study in Switzerland, we first assessed 10-year CHD risk and eligibility for statins in 5,683 women and men 35 to 75 years of age without cardiovascular disease by comparing recommendations by the European Society of Cardiology without and with extrapolation of risk to age 60 years, the International Atherosclerosis Society, and the US Adult Treatment Panel III. The proportions of participants classified as high-risk for CHD were 12.5% (15.4% with extrapolation), 3.0%, and 5.8%, respectively. Proportions of participants eligible for statins were 9.2% (11.6% with extrapolation), 13.7%, and 16.7%, respectively. Assuming full compliance to each guideline, expected relative decreases in CHD deaths in Switzerland over a 10-year period would be 16.4% (17.5% with extrapolation), 18.7%, and 19.3%, respectively; the corresponding numbers needed to treat to prevent 1 CHD death would be 285 (340 with extrapolation), 380, and 440, respectively. In conclusion, the proportion of subjects classified as high risk for CHD varied over a fivefold range across recommendations. Following the International Atherosclerosis Society and the Adult Treatment Panel III recommendations might prevent more CHD deaths at the cost of higher numbers needed to treat compared with European Society of Cardiology guidelines.

Blood pressure modifies the association between serum adiponectin and uric acid, in a sex-dependent manner

Purpose: Plasma adiponectin and serum uric acid (SUA) levels are negatively correlated. To better understand the possible mechanisms linking adiponectin and uric acid, we analyzed whether the association between adiponectin and SUA differed by hypertension status (or blood pressure level) and by sex. Methods and materials: We analyzed data from the populationbased CoLaus study (Switzerland). Fasting plasma adiponectin levels were assessed by ELISA and SUA by uricase-PAP. Blood pressure (BP) was measured using a validated automated device and hypertension was defined as having office BP 140/90 mm Hg or being on current antihypertensive treatment. Results: In the 2897 men and 3181 women, aged 35-74, BMI (mean ± SD) was 26.6 ± 4.0 and 25.1 ± 4.8 Kg/m2, systolic blood pressure (SBP) was 132.2 ± 16.6 and 124.8 ± 18.3 mm Hg, median (interquartile range) plasma adiponectin was 6.2 (4.1-9.2) and 10.6 (6.9-15.4) mg/dL, and hypertension prevalence was 42.0% and 30.2%, respectively. The age- and BMI- adjusted partial correlation coefficients between log-adiponectin and SUA were 0.09 and 0.06 in normotensive men and women (P <0.01), and 0.004 (P = 0.88) and 0.15 (P <0.001) in hypertensive men and women, respectively. In median regression adjusted for BMI, insulin, smoking, alcohol consumption, menopausal status and HDL-cholesterol, there was a significant three-way interaction between SUA, SBP and sex for their effect on adiponectin (dependent variable, P = 0.005), as well as interactions between SBP and sex (P = 0.014) and between SUA and sex (P = 0.033). Conclusion: Plasma adiponectin and SUA are negatively associated, independently of BMI and insulin, in a population-based study in Caucasians. However, BP modifies this inverse relationship, as it was significant mainly in women with elevated BP. This observation suggests that the link between adiponectin and SUA may be mediated by sex hormones and the hypertension status.

Prognostic role of KRAS and BRAF in stage II and III resected colon cancer: results of the translational study on the PETACC-3, EORTC 40993, SAKK 60-00 trial.

PURPOSE: Mutations within the KRAS proto-oncogene have predictive value but are of uncertain prognostic value in the treatment of advanced colorectal cancer. We took advantage of PETACC-3, an adjuvant trial with 3,278 patients with stage II to III colon cancer, to evaluate the prognostic value of KRAS and BRAF tumor mutation status in this setting. PATIENTS AND METHODS: Formalin-fixed paraffin-embedded tissue blocks (n = 1,564) were prospectively collected and DNA was extracted from tissue sections from 1,404 cases. Planned analysis of KRAS exon 2 and BRAF exon 15 mutations was performed by allele-specific real-time polymerase chain reaction. Survival analyses were based on univariate and multivariate proportional hazard regression models. RESULTS: KRAS and BRAF tumor mutation rates were 37.0% and 7.9%, respectively, and were not significantly different according to tumor stage. In a multivariate analysis containing stage, tumor site, nodal status, sex, age, grade, and microsatellite instability (MSI) status, KRAS mutation was associated with grade (P = .0016), while BRAF mutation was significantly associated with female sex (P = .017), and highly significantly associated with right-sided tumors, older age, high grade, and MSI-high tumors (all P < 10(-4)). In univariate and multivariate analysis, KRAS mutations did not have a major prognostic value regarding relapse-free survival (RFS) or overall survival (OS). BRAF mutation was not prognostic for RFS, but was for OS, particularly in patients with MSI-low (MSI-L) and stable (MSI-S) tumors (hazard ratio, 2.2; 95% CI, 1.4 to 3.4; P = .0003). CONCLUSION: In stage II-III colon cancer, the KRAS mutation status does not have major prognostic value. BRAF is prognostic for OS in MS-L/S tumors.

Underdiagnosed and undertreated: obesity in the portuguese population.

Comment on: Post RE, Mainous AG 3rd, Gregorie SH, Knoll ME, Diaz VA, Saxena SK. The influence of physician acknowledgment of patients' weight status on patient perceptions of overweight and obesity in the United States. Arch Intern Med. 2011 Feb 28;171(4):316-21. PMID: 21357807.

Projections de l'utilisation des lits dans le canton de Vaud : hôpitaux de zone, 1990-2010

La projection utilise toujours le programme de simulation SIMULIT, dans sa treizième version. (...) Seule l'évolution démographique a été considérée dans les projections du nombre de lits: aucune des autres variables susceptibles de changer dans le futur n'a été prise en compte, ni celle en relation avec l'activité hospitalière elle-même (modification des taux d'hospitalisation, des durées de séjour, etc.), ni celles concernant l'état de santé de la population (modification de l'incidence ou de la prévalence des maladies). En d'autres termes, cette projection montre l'effet de l'évolution démographique sur l'activité hospitalière, si les caractéristiques de cette activité devaient rester celles observées dans les années 80. Il ne s'agit donc pas d'une prévision. [Auteurs, p. 1]