Association entre consommation d'alcool et facteurs de risque cardiovasculaire: une étude sur la population lausannoise. [Association between alcohol consumption and cardiovascular risk factors: a narrative review]

Alors que la consommation modérée d'alcool est liée à un risque plus faible de développer une maladie coronarienne, l'impact d'une consommation plus importante d'alcool sur les facteurs de risque cardiovasculaire (FRCV) et la maladie coronarienne est moins clair. Nous avons étudié l'association entre la consommation d'alcool, les FRCV et l'estimation du risque à dix ans de faire un événement cardiovasculaire dans l'étude populationnelle lausannoise CoLaus. Dans cette étude, 73% des participants consomment de l'alcool, 16% consomment de 14 à 34 unités d'alcool par semaine et 2% consomment 35 unités ou plus par semaine. Cet article montre notamment l'impact d'une consommation importante d'alcool sur les FRCVet passe en revue les liens entre la consommation d'alcool, le type de boissons et les FRCV. [Abstract] Moderate alcohol consumption has been associated with lower coronary heart disease (CHD) risk. However, the impact of higher alcohol consumption on cardiovascular risk factors (CVRFs) is conflicting. We examined the association between alcohol consumption, CVRFs and the estimated 10-year CHD risk in the population-based CoLaus study in Lausanne, Switzerland. Among 5'769 participants without cardiovascular disease, 73% of the participants were alcohol drinkers; 16% consumed 14-34 drinks/week and 2% consumed >= 35 drinks/week. This article shows the impact of high alcohol consumption on CVRFs and reviews the literature on the associations between alcohol consumption and CVRFs.

Association of urethral toxicity with dose exposure in combined high-dose-rate brachytherapy and intensity-modulated radiation therapy in intermediate- and high-risk prostate cancer.

INTRODUCTION: To report acute and late toxicities in patients with intermediate- and high-risk prostate cancer treated with combined high-dose-rate brachytherapy (HDR-B) and intensity-modulated radiation therapy (IMRT). MATERIALS AND METHODS: From March 2003 to September 2005, 64 men were treated with a single implant HDR-B with 21 Gy given in three fractions, followed by 50 Gy IMRT along with organ tracking. Median age was 66.1 years, and risk of recurrence was intermediate in 47% of the patients or high in 53% of the patients. Androgen deprivation therapy was received by 69% of the patients. Toxicity was scored according to the CTCAE version 3.0. Median follow-up was 3.1 years. RESULTS: Acute grade 3 genitourinary (GU) toxicity was observed in 7.8% of the patients, and late grades 3 and 4 GU toxicity was observed in 10.9% and 1.6% of the patients. Acute grade 3 gastrointestinal (GI) toxicity was experienced by 1.6% of the patients, and late grade 3 GI toxicity was absent. The urethral V(120) (urethral volume receiving > or =120% of the prescribed HDR-B dose) was associated with acute (P=.047) and late > or = grade 2 GU toxicities (P=.049). CONCLUSIONS: Late grades 3 and 4GU toxicity occurred in 10.9% and 1.6% of the patients after HDR-B followed by IMRT in association with the irradiated urethral volume. The impact of V(120) on GU toxicity should be validated in further studies.

Impact of phenotype definition on genome-wide association signals: empirical evaluation in human immunodeficiency virus type 1 infection.

Discussion on improving the power of genome-wide association studies to identify candidate variants and genes is generally centered on issues of maximizing sample size; less attention is given to the role of phenotype definition and ascertainment. The authors used genome-wide data from patients infected with human immunodeficiency virus type 1 (HIV-1) to assess whether differences in type of population (622 seroconverters vs. 636 seroprevalent subjects) or the number of measurements available for defining the phenotype resulted in differences in the effect sizes of associations between single nucleotide polymorphisms and the phenotype, HIV-1 viral load at set point. The effect estimate for the top 100 single nucleotide polymorphisms was 0.092 (95% confidence interval: 0.074, 0.110) log(10) viral load (log(10) copies of HIV-1 per mL of blood) greater in seroconverters than in seroprevalent subjects. The difference was even larger when the authors focused on chromosome 6 variants (0.153 log(10) viral load) or on variants that achieved genome-wide significance (0.232 log(10) viral load). The estimates of the genetic effects tended to be slightly larger when more viral load measurements were available, particularly among seroconverters and for variants that achieved genome-wide significance. Differences in phenotype definition and ascertainment may affect the estimated magnitude of genetic effects and should be considered in optimizing power for discovering new associations.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data.

The R package EasyStrata facilitates the evaluation and visualization of stratified genome-wide association meta-analyses (GWAMAs) results. It provides (i) statistical methods to test and account for between-strata difference as a means to tackle gene-strata interaction effects and (ii) extended graphical features tailored for stratified GWAMA results. The software provides further features also suitable for general GWAMAs including functions to annotate, exclude or highlight specific loci in plots or to extract independent subsets of loci from genome-wide datasets. It is freely available and includes a user-friendly scripting interface that simplifies data handling and allows for combining statistical and graphical functions in a flexible fashion. AVAILABILITY: EasyStrata is available for free (under the GNU General Public License v3) from our Web site www.genepi-regensburg.de/easystrata and from the CRAN R package repository cran.r-project.org/web/packages/EasyStrata/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Polymorphisms in candidate genes and their association with carcass traits and meat quality in Nellore cattle

The objective of this work was to estimate the allele polymorphism frequencies of genes in Nellore cattle and associate them with meat quality and carcass traits. Six hundred males were genotyped for the following polymorphisms: DGAT1 (VNTR with 18 nucleotides at the promoter region); ANK1, a new polymorphism, identified and mapped here at the gene regulatory region NW_001494427.3; TCAP (AY428575.1:g.346G>A); and MYOG (NW_001501985:g.511G>C). In the association study, phenotype data of hot carcass weight, ribeye area, backfat thickness, percentage of intramuscular fat, shear force, myofibrillar fragmentation index, meat color (L*, a*, b*), and cooking losses were used. Allele B from the ANK1 gene was associated with greater redness (a*). Alleles 5R, 6R, and 7R from the DGAT1 VNTR gene were associated with increased intramuscular fat, reduced cooking losses and increased ribeye area, respectively. The single nucleotide polymorphism (SNP) of the TCAP gene was not polymorphic, and MYOG alleles were not associated with any of the evaluated characteristics. These results indicate that ANK1 and DGAT1 genes can be used in the selection of Nellore cattle for carcass and meat quality.

Association of electrocardiogram abnormalities and incident heart failure events.

Unless effective preventive strategies are implemented, aging of the population will result in a significant worsening of the heart failure (HF) epidemic. Few data exist on whether baseline electrocardiographic (ECG) abnormalities can refine risk prediction for HF. METHODS: We examined a prospective cohort of 2,915 participants aged 70 to 79 years without preexisting HF, enrolled between April 1997 and June 1998 in the Health, Aging, and Body Composition (Health ABC) study. Minnesota Code was used to define major and minor ECG abnormalities at baseline and at year 4 follow-up. Using Cox models, we assessed (1) the association between ECG abnormalities and incident HF and (2) the incremental value of adding ECG to the Health ABC HF Risk Score using the net reclassification index. RESULTS: At baseline, 380 participants (13.0%) had minor, and 620 (21.3%) had major ECG abnormalities. During a median follow-up of 11.4 years, 485 participants (16.6%) developed incident HF. After adjusting for the Health ABC HF Risk Score variables, the hazard ratio (HR) was 1.27 (95% CI 0.96-1.68) for minor and 1.99 (95% CI 1.61-2.44) for major ECG abnormalities. At year 4, 263 participants developed new and 549 had persistent abnormalities; both were associated with increased subsequent HF risk (HR 1.94, 95% CI 1.38-2.72 for new and HR 2.35, 95% CI 1.82-3.02 for persistent ECG abnormalities). Baseline ECG correctly reclassified 10.5% of patients with HF events, 0.8% of those without HF events, and 1.4% of the overall population. The net reclassification index across the Health ABC HF risk categories was 0.11 (95% CI 0.03-0.19). CONCLUSIONS: Among older adults, baseline and new ECG abnormalities are independently associated with increased risk of HF. The contribution of ECG screening for targeted prevention of HF should be evaluated in clinical trials.

The PsyCoLaus study: methodology and characteristics of the sample of a population-based survey on psychiatric disorders and their association with genetic and cardiovascular risk factors.

ABSTRACT: BACKGROUND: The Psychiatric arm of the population-based CoLaus study (PsyCoLaus) is designed to: 1) establish the prevalence of threshold and subthreshold psychiatric syndromes in the 35 to 66 year-old population of the city of Lausanne (Switzerland); 2) test the validity of postulated definitions for subthreshold mood and anxiety syndromes; 3) determine the associations between psychiatric disorders, personality traits and cardiovascular diseases (CVD), 4) identify genetic variants that can modify the risk for psychiatric disorders and determine whether genetic risk factors are shared between psychiatric disorders and CVD. This paper presents the method as well as somatic and sociodemographic characteristics of the sample. METHODS: All 35 to 66 year-old persons previously selected for the population-based CoLaus survey on risk factors for CVD were asked to participate in a substudy assessing psychiatric conditions. This investigation included the Diagnostic Interview for Genetic Studies to elicit diagnostic criteria for threshold disorders according to DSM-IV and algorithmically defined subthreshold syndromes. Complementary information was gathered on potential risk and protective factors for psychiatric disorders, migraine and on the morbidity of first-degree family members, whereas the collection of DNA and plasma samples was part of the original somatic study (CoLaus). RESULTS: A total of 3,691 individuals completed the psychiatric evaluation (67% participation). The gender distribution of the sample did not differ significantly from that of the general population in the same age range. Although the youngest 5-year band of the cohort was underrepresented and the oldest 5-year band overrepresented, participants of PsyCoLaus and individuals who refused to participate revealed comparable scores on the General Health Questionnaire, a self-rating instrument completed at the somatic exam. CONCLUSIONS: Despite limitations resulting from the relatively low participation in the context of a comprehensive and time-consuming investigation, the PsyCoLaus study should significantly contribute to the current understanding of psychiatric disorders and comorbid somatic conditions by: 1) establishing the clinical relevance of specific psychiatric syndromes below the DSM-IV threshold; 2) determining comorbidity between risk factors for CVD and psychiatric disorders; 3) assessing genetic variants associated with common psychiatric disorders and 4) identifying DNA markers shared between CVD and psychiatric disorders.