1000 resultados para Colaus Study


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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.

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METHODS. We analyzed data from a population-based sample of 2561 participants (1163 men and 1398 women) aged 55-75 years from the city of Lausanne, Switzerland (CoLaus study). Participants were stratified by the number of parents (0, 1, 2) who survived to 85 years or more. Trend across these strata was assessed using a non-parametric kmean test. The associations of parental age (independent covariate used as a proxy for longevity) with fasting blood glucose, blood pressures, blood lipids, body mass index (BMI), weight, height or liver enzymes (continuous dependent variables) were analyzed using multiple linear regressions. Models were adjusted for age, sex, alcohol consumption, smoking and educational level, and BMI for liver enzymes. RESULTS. For subjects with 0 (N = 1298), 1 (N = 991) and 2 (N = 272) long-lived parents, median BMI (interquartile range) was 25.4 (6.5), 24.9 (6.1) and 23.7 (4.8) kg/m2 in women (P <0.001), and 27.3 (4.8), 27.0 (4.5) and 25.9 (4.9) kg/m2 in men (P = 0.04), respectively; median weight was 66.5 (16.1), 65.0 (16.4) and 63.4 (13.7) kg in women (P = 0.003), and 81.5 (17.0), 81.4 (16.4) and 80.3 (17.1) kg in men (P = 0.36). Median height was 161 (8), 162 (9) and 163 (8) cm in women (P = 0.005) and 173 (9), 174 (9) and 174 (11) cm in men (P = 0.09). The corresponding medians for AST (Aspartate Aminotransferase) were 31 (13), 29 (11) and 28 (10) U/L (P = 0.002), and 28 (17), 27 (14) and 26 (19) U/L for ALT (Alanin Aminotransferase, P = 0.053) in men. In multivariable analyses, greater parental longevity was associated with lower BMI, lower weight and taller stature in women (P < 0.01) and lower AST in men (P = 0.011). No significant associations were observed for the other variables analyzed. Sensitivity analyses restricted to subjects whose parents were dead (N = 1844) led to similar results, with even stronger associations of parental longevity with liver enzymes in men. CONCLUSIONS. In women, increased parental longevity was associated with smaller BMI, attributable to lower weight and taller stature. In men, the association of increased parental longevity with lower liver enzymes, independently of BMI, suggests that parental longevity may be associated with decreased nonalcoholic fatty liver disease.

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AIMS: Smoking cessation has been suggested to increase the short-term risk of type 2 diabetes mellitus (T2DM). This study aimed at assessing the association between smoking cessation and incidence of T2DM and impaired fasting glucose (IFG). METHODS: Data from participants in the CoLaus study, Switzerland, aged 35-75 at baseline and followed for 5.5years were used. Participants were classified as smokers, recent (≤5years), long-term (>5years) quitters, and non-smokers at baseline. Outcomes were IFG (fasting serum glucose (FSG) 5.6-6.99mmol/l) and T2DM (FSG ≥7.0mmol/l and/or treatment) at follow up. RESULTS: 3,166 participants (63% women) had normal baseline FSG, of whom 26.7% were smokers, 6.5% recent quitters, and 23.5% long-term quitters. During follow-up 1,311 participants (41.4%) developed IFG (33.6% women, 54.7% men) and 47 (1.5%) developed T2DM (1.1% women, 2.1% men). Former smokers did not have statistically significant increased odds of IFG compared with smokers after adjustment for age, education, physical activity, hypercholesterolemia, hypertension and alcohol intake, with OR of 1.29 [95% confidence interval 0.94-1.76] for recent quitters and 1.03 [0.84-1.27] for long-term quitters. Former smokers did not have significant increased odds of T2DM compared with smokers with multivariable-adjusted OR of 1.53 [0.58-4.00] for recent quitters and 0.64 [0.27-1.48] for long-term quitters. Adjustment for body-mass index and waist circumference attenuated the association between recent quitting and IFG (OR 1.07 [0.78-1.48]) and T2DM (OR 1.28 [0.48-3.40]. CONCLUSION: In this middle-aged population, smoking cessation was not associated with an increased risk of IFG or T2DM.

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ABSTRACT: BACKGROUND: Recent data indicate a slight decrease in the prevalence of smoking in Switzerland, but little is known regarding the intention and difficulty to quit smoking among current smokers. Hence, we aimed to quantify the difficulty and intention to quit smoking among current smokers in Switzerland. METHODS: Cross-sectional study including 607 female and 658 male smokers. Difficulty, intention and motivation to quit smoking were assessed by questionnaire. RESULTS: 90% of women and 85% of men reported being "very difficult" or "difficult" to quit smoking. Almost three quarters of smokers (73% of women and 71% of men) intended to quit; however, less than 20% of them were in the preparation stage and 40% were in the precontemplation stage. On multivariate analysis, difficulty to quit was lower among men (Odds ratio and 95% [confidence interval]: 0.51 [0.35-0.74]) and increased with nicotine dependence and number of previous quitting attempts (OR=3.14 [1.75-5.63] for 6+ attempts compared to none). Intention to quit decreased with increasing age (OR=0.48 [0.30-0.75] for [greater than or equal to]65 years compared to <45 years) and increased with nicotine dependence, the number of previous quitting attempts (OR=4.35 [2.76-6.83] for 6+ attempts compared to none) and among non-cigarette smokers (OR=0.51 [0.28-0.92]). Motivation to quit was inversely associated with nicotine dependence and positively associated with the number of previous quitting attempts and personal history of lung disease. CONCLUSION: Over two thirds of Swiss smokers want to quit. However, only a small fraction wishes to do so in the short term. Nicotine dependence, previous attempts to quit or previous history of lung disease are independently associated with difficulty and intention to quit.

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OBJECTIVE: To assess the relationships and possible interactions between polymorphisms related to HDL levels and alcohol consumption. METHODS: Cross-sectional population-based study including 2863 women and 2546 men aged 35-75 years (CoLaus study). Alcohol intake was assessed by the reported alcohol consumption of the last 7 days. Nineteen candidate genes known to influence HDL levels were studied. RESULTS: Alcohol consumption increased HDL cholesterol levels in both genders. After multivariate adjustment for gender, age, body mass index, smoking, hypolipidaemic drug treatment, physical activity and alcohol consumption, APOA5, CETP, LIPC and LPL gene polymorphisms were significantly (10(-5) threshold) related with HDL cholesterol levels, while no genexalcohol intake interaction was found for all SNPs studied. ABCA1 polymorphisms were related to HDL cholesterol levels on bivariate analysis but the relationship was no longer significant after multivariate analysis. CONCLUSION: Our data confirm the association of alcohol consumption and of APOA5, CETP, LIPC and LPL gene polymorphisms with HDL cholesterol levels. Conversely, no genexalcohol consumption interactions were found, suggesting that the effect of alcohol consumption on HDL cholesterol levels is not mediated via a modulation of HDL related genes.

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Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻&supl;³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.

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ABSTRACT: BACKGROUND: Although smokers tend to have a lower body-mass index than non-smokers, smoking may favour abdominal body fat accumulation. To our knowledge, no population-based studies have assessed the relationship between smoking and body fat composition. We assessed the association between cigarette smoking and waist circumference, body fat, and body-mass index. METHODS: Height, weight, and waist circumference were measured among 6,123 Caucasians (ages 35-75) from a cross-sectional population-based study in Switzerland. Abdominal obesity was defined as waist circumference>=102 cm for men and >=88 cm for women. Body fat (percent total body weight) was measured by electrical bioimpedance. Age- and sex-specific body fat cut-offs were used to define excess body fat. Cigarettes smoked per day were assessed by self-administered questionnaire. Age-adjusted means and odds ratios were calculated using linear and logistic regression. RESULTS: Current smokers (29% of men and 24% of women) had lower mean waist circumference, body fat percentage, and body-mass index compared with non-smokers. Age-adjusted mean waist circumference and body fat increased with cigarettes smoked per day among smokers. The association between cigarettes smoked per day and body-mass index was non-significant. Compared with light smokers, the adjusted odds ratio (OR) for abdominal obesity in men was 1.28 (0.78-2.10) for moderate smokers and 1.94 (1.15-3.27) for heavy smokers (P=0.03 for trend), and 1.07 (0.72-1.58) and 2.15 (1.26-3.64) in female moderate and heavy smokers, respectively (P<0.01 for trend). Compared with light smokers, the OR for excess body fat in men was 1.05 (95% CI: 0.58-1.92) for moderate smokers and 1.15 (0.60-2.20) for heavy smokers (P=0.75 for trend) and 1.34 (0.89-2.00) and 2.11 (1.25-3.57), respectively in women (P=0.07 for trend). CONCLUSION: Among smokers, cigarettes smoked per day were positively associated with central fat accumulation, particularly in women.

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To identify loci for age at menarche, we performed a meta-analysis of 32 genome-wide association studies in 87,802 women of European descent, with replication in up to 14,731 women. In addition to the known loci at LIN28B (P = 5.4 × 10⁻⁶⁰) and 9q31.2 (P = 2.2 × 10⁻³³), we identified 30 new menarche loci (all P < 5 × 10⁻⁸) and found suggestive evidence for a further 10 loci (P < 1.9 × 10⁻⁶). The new loci included four previously associated with body mass index (in or near FTO, SEC16B, TRA2B and TMEM18), three in or near other genes implicated in energy homeostasis (BSX, CRTC1 and MCHR2) and three in or near genes implicated in hormonal regulation (INHBA, PCSK2 and RXRG). Ingenuity and gene-set enrichment pathway analyses identified coenzyme A and fatty acid biosynthesis as biological processes related to menarche timing.

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Genetic determinants of blood pressure are poorly defined. We undertook a large-scale, gene-centric analysis to identify loci and pathways associated with ambulatory systolic and diastolic blood pressure. We measured 24-hour ambulatory blood pressure in 2020 individuals from 520 white European nuclear families (the Genetic Regulation of Arterial Pressure of Humans in the Community Study) and genotyped their DNA using the Illumina HumanCVD BeadChip array, which contains ≈50 000 single nucleotide polymorphisms in >2000 cardiovascular candidate loci. We found a strong association between rs13306560 polymorphism in the promoter region of MTHFR and CLCN6 and mean 24-hour diastolic blood pressure; each minor allele copy of rs13306560 was associated with 2.6 mm Hg lower mean 24-hour diastolic blood pressure (P=1.2×10(-8)). rs13306560 was also associated with clinic diastolic blood pressure in a combined analysis of 8129 subjects from the Genetic Regulation of Arterial Pressure of Humans in the Community Study, the CoLaus Study, and the Silesian Cardiovascular Study (P=5.4×10(-6)). Additional analysis of associations between variants in gene ontology-defined pathways and mean 24-hour blood pressure in the Genetic Regulation of Arterial Pressure of Humans in the Community Study showed that cell survival control signaling cascades could play a role in blood pressure regulation. There was also a significant overrepresentation of rare variants (minor allele frequency: <0.05) among polymorphisms showing at least nominal association with mean 24-hour blood pressure indicating that a considerable proportion of its heritability may be explained by uncommon alleles. Through a large-scale gene-centric analysis of ambulatory blood pressure, we identified an association of a novel variant at the MTHFR/CLNC6 locus with diastolic blood pressure and provided new insights into the genetic architecture of blood pressure.

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BACKGROUND AND AIM: There is an ongoing debate on which obesity marker better predicts cardiovascular disease (CVD). In this study, the relationships between obesity markers and high (>5%) 10-year risk of fatal CVD were assessed. METHODS AND RESULTS: A cross-sectional study was conducted including 3047 women and 2689 men aged 35-75years. Body fat percentage was assessed by tetrapolar bioimpedance. CVD risk was assessed using the SCORE risk function and gender- and age-specific cut points for body fat were derived. The diagnostic accuracy of each obesity marker was evaluated through receiver operating characteristics (ROC) analysis. In men, body fat presented a higher correlation (r=0.31) with 10-year CVD risk than waist/hip ratio (WHR, r=0.22), waist (r=0.22) or BMI (r=0.19); the corresponding values in women were 0.18, 0.15, 0.11 and 0.05, respectively (all p<0.05). In both genders, body fat showed the highest area under the ROC curve (AUC): in men, the AUC (95% confidence interval) were 76.0 (73.8-78.2), 67.3 (64.6-69.9), 65.8 (63.1-68.5) and 60.6 (57.9-63.5) for body fat, WHR, waist and BMI, respectively. In women, the corresponding values were 72.3 (69.2-75.3), 66.6 (63.1-70.2), 64.1 (60.6-67.6) and 58.8 (55.2-62.4). The use of the body fat percentage criterion enabled the capture of three times more subjects with high CVD risk than the BMI criterion, and almost twice as much as the WHR criterion. CONCLUSION: Obesity defined by body fat percentage is more related with 10-year risk of fatal CVD than obesity markers based on WHR, waist or BMI.

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Moderate alcohol consumption has been associated with lower coronary artery disease (CAD) risk. However, data on the CAD risk associated with high alcohol consumption are conflicting. The aim of this study was to examine the impact of heavier drinking on 10-year CAD risk in a population with high mean alcohol consumption. In a population-based study of 5,769 adults (aged 35 to 75 years) without cardiovascular disease in Switzerland, 1-week alcohol consumption was categorized as 0, 1 to 6, 7 to 13, 14 to 20, 21 to 27, 28 to 34, and > or =35 drinks/week or as nondrinkers (0 drinks/week), moderate (1 to 13 drinks/week), high (14 to 34 drinks/week), and very high (> or =35 drinks/week). Blood pressure and lipids were measured, and 10-year CAD risk was calculated according to the Framingham risk score. Seventy-three percent (n = 4,214) of the participants consumed alcohol; 16% (n = 909) were high drinkers and 2% (n = 119) very high drinkers. In multivariate analysis, increasing alcohol consumption was associated with higher high-density lipoprotein cholesterol (from a mean +/- SE of 1.57 +/- 0.01 mmol/L in nondrinkers to 1.88 +/- 0.03 mmol/L in very high drinkers); triglycerides (1.17 +/- 1.01 to 1.32 +/- 1.05 mmol/L), and systolic and diastolic blood pressure (127.4 +/- 0.4 to 132.2 +/- 1.4 mm Hg and 78.7 +/- 0.3 to 81.7 +/- 0.9 mm Hg, respectively) (all p values for trend <0.001). Ten-year CAD risk increased from 4.31 +/- 0.10% to 4.90 +/- 0.37% (p = 0.03) with alcohol use, with a J-shaped relation. Increasing wine consumption was more related to high-density lipoprotein cholesterol levels, whereas beer and spirits were related to increased triglyceride levels. In conclusion, as measured by 10-year CAD risk, the protective effect of alcohol consumption disappears in very high drinkers, because the beneficial increase in high-density lipoprotein cholesterol is offset by the increases in blood pressure levels.

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Objective: Limited information is available on the quantitative relationship between family history and the corresponding underlying traits. We analyzed these associations for blood pressure, fasting blood glucose, and cholesterol levels. Methods: Data were obtained from 6,102 Caucasian participants (2,903 men and 3,199 women) aged 35-75 years using a population-based cross-sectional survey in Switzerland. Cardiovascular disease risk factors were measured, and the corresponding family history was self-reported using a structured questionnaire. Results: The prevalence of a positive family history (in first-degree relatives) was 39.6% for hypertension, 22.3% for diabetes, and 29.0% for hypercholesterolemia. Family history was not known for at least one family member in 41.8% of participants for hypertension, 14.4% for diabetes, and 50.2% for hypercholesterolemia. A positive family history was strongly associated with higher levels of the corresponding trait, but not with the other traits. Participants who reported not to know their family history of hypertension had a higher systolic blood pressure than participants with a negative history. Sibling histories had higher positive predictive values than parental histories. The ability to discriminate, calibrate, and reclassify was best for the family history of hypertension. Conclusions: Family history of hypertension, diabetes, and hypercholesterolemia was strongly associated with the corresponding dichotomized and continuous phenotypes.

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Adult height is a model polygenic trait, but there has been limited success in identifying the genes underlying its normal variation. To identify genetic variants influencing adult human height, we used genome-wide association data from 13,665 individuals and genotyped 39 variants in an additional 16,482 samples. We identified 20 variants associated with adult height (P < 5 x 10(-7), with 10 reaching P < 1 x 10(-10)). Combined, the 20 SNPs explain approximately 3% of height variation, with a approximately 5 cm difference between the 6.2% of people with 17 or fewer 'tall' alleles compared to the 5.5% with 27 or more 'tall' alleles. The loci we identified implicate genes in Hedgehog signaling (IHH, HHIP, PTCH1), extracellular matrix (EFEMP1, ADAMTSL3, ACAN) and cancer (CDK6, HMGA2, DLEU7) pathways, and provide new insights into human growth and developmental processes. Finally, our results provide insights into the genetic architecture of a classic quantitative trait.

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To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 x 10(-50)) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 x 10(-15)). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 x 10(-7)) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 x 10(-57)) and GCK (rs4607517, P = 1.0 x 10(-25)) loci.