The CYP2J2 G-50T polymorphism and myocardial infarction in patients with cardiovascular risk profile

<p>Abstract</p> <p>Background</p> <p>Cytochrome P450 (CYP) enzyme 2J2, an epoxygenase predominantly expressed in the heart, metabolises arachidonic acid to biologically active eicosanoids. One of the CYP2J2 products, 11, 12-epoxyeicosatrienoic acid, has several vasoprotective effects. The CYP2J2-G-50T-promotor polymorphism decreases gene expression and is associated with coronary artery disease. This association supports the vascular protective role of CYP-derived eicosanoids in cardiovascular disease. In the present study, we investigated the influence of this polymorphism on survived myocardial infarction in two study groups of patients with on average high cardiovascular risk profile.</p> <p>Methods</p> <p>The CYP2J2 polymorphism was genotyped in two groups of patients that were collected with the same method of clinical data collection. Data from 512 patients with sleep apnoea (group: OSA) and on average high cardiovascular risk profile and from another 488 patients who were admitted for coronary angiography (CAR-group) were evaluated for a potential correlation of the CYP2J2 polymorphism G-50T and a history of myocardial infarction. The G-50T polymorphism of the CYP2J2 gene was genotyped by allele specific restriction and light cycler analysis.</p> <p>Results</p> <p>The T-allele of the polymorphism was found in 111 (11.1%; CAR-group: N = 65, 13.3%; OSA: N = 46, 9.0%). 146 patients had a history of myocardial infarction (CAR: N = 120, 24.6%; OSA: N = 26, 5.1%). Cardiovascular risk factors were equally distributed between the different genotypes of the CYP2J2 G-50T polymorphism. In the total group of 1000 individuals, carriers of the T-allele had significantly more myocardial infarctions compared to carriers of the wild type (T/T or G/T: 21.6%; G/G: 13.7%; p = 0.026, odds ratio 1.73, 95%-CI [1.06–2.83]). In the multivariate logistic regression analysis the odds ratio for a history of myocardial infarction in carriers of the T-allele was 1.611, 95%-CI [0.957–2.731] but this trend was not significant (p = 0.073).</p> <p>Conclusion</p> <p>In presence of other risk factors, the CYP2J2 G-50T failed to show a significant role in the development of myocardial infarction. However, since our result is close to the border of significance, this question should be clarified in larger, prospective studies in the future.</p

Social factors and obesity: an investigation of the role of health behaviours

OBJECTIVES: This study evaluated a behavioural model of the relation between social factors and obesity, in which differences in body mass index (BMI) across sociodemographic groups were hypothesized to be attributable to social group differences in health behaviours affecting energy expenditure (physical activity, diet and alcohol consumption and weight control). METHODS: A total of 8667 adults who participated in the 1995 Australian National Health and Nutrition Surveys provided data on a range of health factors including objectively measured height and weight, health behaviours, and social factors including family status, employment status, housing situation and migration status. RESULTS: Social factors remained significant predictors of BMI after controlling for all health behaviours. Neither social factors alone, nor health behaviours alone, adequately explained the variance in BMI. Gender-specific interactions were found between social factors and individual health behaviours. CONCLUSIONS: These results suggest that social factors moderate the relation between BMI and weight-related behaviours, and that the mechanisms underlying sociodemographic group differences in obesity may vary among men and women. Additional factors are likely to act in conjunction with current health behaviours to explain variation in obesity prevalence across sociodemographic groups.<br /

Genetic Testing for Early Detection of Individuals at Risk of Coronary Heart Disease and Monitoring Response to Therapy: Challenges and Promises

Coronary heart disease (CHD) often presents suddenly with little warning. Traditional risk factors are inadequate to identify the asymptomatic high-risk individuals. Early identification of patients with subclinical coronary artery disease using noninvasive imaging modalities would allow the early adoption of aggressive preventative interventions. Currently, it is impractical to screen the entire population with noninvasive coronary imaging tools. The use of relatively simple and inexpensive genetic markers of increased CHD risk can identify a population subgroup in which benefit of atherosclerotic imaging modalities would be increased despite nominal cost and radiation exposure. Additionally, genetic markers are fixed and need only be measured once in a patient’s lifetime, can help guide therapy selection, and may be of utility in family counseling

Mapping transcription mechanisms from multimodal genomic data

Background Identification of expression quantitative trait loci (eQTLs) is an emerging area in genomic study. The task requires an integrated analysis of genome-wide single nucleotide polymorphism (SNP) data and gene expression data, raising a new computational challenge due to the tremendous size of data. Results We develop a method to identify eQTLs. The method represents eQTLs as information flux between genetic variants and transcripts. We use information theory to simultaneously interrogate SNP and gene expression data, resulting in a Transcriptional Information Map (TIM) which captures the network of transcriptional information that links genetic variations, gene expression and regulatory mechanisms. These maps are able to identify both cis- and trans- regulating eQTLs. The application on a dataset of leukemia patients identifies eQTLs in the regions of the GART, PCP4, DSCAM, and RIPK4 genes that regulate ADAMTS1, a known leukemia correlate. Conclusions The information theory approach presented in this paper is able to infer the dependence networks between SNPs and transcripts, which in turn can identify cis- and trans-eQTLs. The application of our method to the leukemia study explains how genetic variants and gene expression are linked to leukemia.National Human Genome Research Institute (U.S.) (R01HG003354)National Institute of Allergy and Infectious Diseases (U.S.) (U19 AI067854-05)National Heart, Lung, and Blood Institute (grant T32 HL007427-28)National Institutes of Health (U.S.) (grant K99 LM009826

Co-variations and Clustering of Chronic Disease Behavioral Risk Factors in China: China Chronic Disease and Risk Factor Surveillance, 2007

BACKGROUND: Chronic diseases have become the leading causes of mortality in China and related behavioral risk factors (BRFs) changed dramatically in past decades. We aimed to examine the prevalence, co-variations, clustering and the independent correlates of five BRFs at the national level. METHODOLOGY/PRINCIPAL FINDINGS: We used data from the 2007 China Chronic Disease and Risk Factor Surveillance, in which multistage clustering sampling was adopted to collect a nationally representative sample of 49,247 Chinese aged 15 to 69 years. We estimated the prevalence and clustering (mean number of BRFs) of five BRFs: tobacco use, excessive alcohol drinking, insufficient intake of vegetable and fruit, physical inactivity, and overweight or obesity. We conducted binary logistic regression models to examine the co-variations among five BRFs with adjustment of demographic and socioeconomic factors, chronic conditions and other BRFs. Ordinal logistic regression was constructed to investigate the independent associations between each covariate and the clustering of BRFs within individuals. Overall, 57.0% of Chinese population had at least two BRFs and the mean number of BRFs is 1.80 (95% confidence interval: 1.78-1.83). Eight of the ten pairs of bivariate associations between the five BRFs were found statistically significant. Chinese with older age, being a male, living in rural areas, having lower education level and lower yearly household income experienced increased likelihood of having more BRFs. CONCLUSIONS/SIGNIFICANCE: Current BRFs place the majority of Chinese aged 15 to 69 years at risk for the future development of chronic disease, which calls for urgent public health programs to reduce these risk factors. Prominent correlations between BRFs imply that a combined package of interventions targeting multiple BRFs might be appropriate. These interventions should target elder population, men, and rural residents, especially those with lower SES

Long term life dissatisfaction and subsequent major depressive disorder and poor mental health

<p>Abstract</p> <p>Background</p> <p>Poor mental health, especially due to depression, is one of the main public health problems. Early indicators of poor mental health in general population are needed. This study examined the relationship between long-term life dissatisfaction and subsequent mental health, including major depressive disorder.</p> <p>Method</p> <p>Health questionnaires were sent to a randomly selected population-based sample in 1998 and repeated in 1999 and 2001. In 2005, a clinically studied sub-sample (n = 330) was composed of subjects with (n = 161) or without (n = 169) repeatedly reported adverse mental symptoms at all three previous data collection times. Clinical symptom assessments were performed with several psychometric scales: life satisfaction (<b>LS</b>), depression (<b>HDRS, BDI</b>), hopelessness (<b>HS</b>), mental distress (<b>GHQ</b>), dissociative experiences (<b>DES</b>), and alexithymia (<b>TAS</b>). The long-term life dissatisfaction burden was calculated by summing these life satisfaction scores in 1998, 1999, 2001 and dividing the sum into tertiles. Psychiatric diagnoses were confirmed by SCID-I for DSM-IV in 2005. Logistic regression analyses were performed to assess the studied relationship.</p> <p>Results</p> <p>The previous life dissatisfaction burden associated with adverse socio-demographic, life style and clinical factors. In adjusted logistic regression analyses, it was independently and strongly associated with subsequent major depressive disorder in 2005, even when the concurrent LS score in 2005 was included in the model. Excluding those with reported major depressive disorder in 1999 did not alter this finding.</p> <p>Limitations</p> <p>MDD in 1999 was based on self-reports and not on structured interview and LS data in 2001-2005 was not available.</p> <p>Conclusions</p> <p>The life satisfaction burden is significantly related to major depressive disorder and poor mental health, both in cross-sectional and longitudinal settings.</p

Psychosocial factors and cancer incidence (PSY-CA): Protocol for individual participant data meta-analyses

Objectives: Psychosocial factors have been hypothesized to increase the risk of cancer. This study aims (1) to test whether psychosocial factors (depression, anxiety, recent loss events, subjective social support, relationship status, general distress, and neuroticism) are associated with the incidence of any cancer (any, breast, lung, prostate, colorectal, smoking-related, and alcohol-related); (2) to test the interaction between psychosocial factors and factors related to cancer risk (smoking, alcohol use, weight, physical activity, sedentary behavior, sleep, age, sex, education, hormone replacement therapy, and menopausal status) with regard to the incidence of cancer; and (3) to test the mediating role of health behaviors (smoking, alcohol use, weight, physical activity, sedentary behavior, and sleep) in the relationship between psychosocial factors and the incidence of cancer. Methods: The psychosocial factors and cancer incidence (PSY-CA) consortium was established involving experts in the field of (psycho-)oncology, methodology, and epidemiology. Using data collected in 18 cohorts (N = 617,355), a preplanned two-stage individual participant data (IPD) meta-analysis is proposed. Standardized analyses will be conducted on harmonized datasets for each cohort (stage 1), and meta-analyses will be performed on the risk estimates (stage 2). Conclusion: PSY-CA aims to elucidate the relationship between psychosocial factors and cancer risk by addressing several shortcomings of prior meta-analyses