1,122 research outputs found
Genetic loci on chromosome 5 are associated with circulating levels of interleukin-5 and eosinophil count in a European population with high risk for cardiovascular disease
IL-5 is a Th2 cytokine which activates eosinophils and is suggested to have an atheroprotective role. Genetic variants in the IL5 locus have been associated with increased risk of CAD and ischemic stroke. In this study we aimed to identify genetic variants associated with IL-5 concentrations and apply a Mendelian randomisation approach to assess IL-5 levels for causal effect on intima-media thickness in a European population at high risk of coronary artery disease. We analysed SNPs within robustly associated candidate loci for immune, inflammatory, metabolic and cardiovascular traits. We identified 2 genetic loci for IL-5 levels (chromosome 5, rs56183820, BETA = 0.11, P = 6.73E−5 and chromosome 14, rs4902762, BETA = 0.12, P = 5.76E−6) and one for eosinophil count (rs72797327, BETA = −0.10, P = 1.41E−6). Both chromosome 5 loci were in the vicinity of the IL5 gene, however the association with IL-5 levels failed to replicate in a meta-analysis of 2 independent cohorts (rs56183820, BETA = 0.04, P = 0.2763, I2 = 24, I2 − P = 0.2516). No significant associations were observed between SNPs associated with IL-5 levels or eosinophil count and IMT measures. Expression quantitative trait analyses indicate effects of the IL-5 and eosinophil-associated SNPs on RAD50 mRNA expression levels (rs12652920 (r2 = 0.93 with rs56183820) BETA = −0.10, P = 8.64E−6 and rs11739623 (r2 = 0.96 with rs72797327) BETA = −0.23, P = 1.74E−29, respectively). Our data do not support a role for IL-5 levels and eosinophil count in intima-media thickness, however SNPs associated with IL-5 and eosinophils might influence stability of the atherosclerotic plaque via modulation of RAD50 levels
Sodium Thiosulfate in the Pregnant Dahl Salt-Sensitive Rat, a Model of Preeclampsia
Aberrant production of hydrogen sulfide (H2S) has been linked to preeclampsia. We hypothesized that sodium thiosulfate (STS), a H2S donor, reduces hypertension and proteinuria, and diminishes fetal growth restriction in the Dahl salt-sensitive (S) rat, a spontaneous model of superimposed preeclampsia. In addition to a control group (n = 13), two groups received STS via drinking water at a dose of 2 g (n = 9) or 3 g per kg body weight per day (n = 8) from gestational day (GD) 10 to 20. Uterine artery resistance index was measured (GD18), urinary protein excretion rate was determined (GD19), and blood pressure and fetal outcomes were evaluated (GD20). At 2 g, STS had no effect on preeclamptic symptoms or fetal outcome. At 3 g, STS reduced maternal hypertension (121.8 ± 3.0 vs. 136.3 ± 2.9), but increased proteinuria (89 ± 15 vs. 56 ± 5 mg/24h), and relative kidney weight (0.86 ± 0.04 vs. 0.73 ± 0.02%). Fetal/placental weight ratio was reduced (3.83 ± 0.07 vs. 4.31 ± 0.08) without affecting litter size. No differences in uterine artery flow or renal histological damage were noted across treatment groups. While these data suggest a promising antihypertensive effect that could imply prolongation of preeclamptic pregnancies, the unfavorable effects on proteinuria, kidney weight, and fetal/placental weight ratio implies that clinical implementation of STS is contra-indicated until safety for mother and child can be verified.</p
Impaired skeletal muscle kynurenine metabolism in patients with chronic obstructive pulmonary disease
Background: Loss of peripheral muscle oxidative phenotype, cognitive impairment, and depression are well-recognized systemic manifestations of chronic obstructive pulmonary disease (COPD). Kynurenine (KYN), known to be associated with disturbed mental health, can be metabolized in muscle by kynurenine aminotransferases (KAT) 1–4. These KATs are regulated by peroxisome proliferator-activated receptor gamma (PPARγ) coactivator-1α (PGC1α). We hypothesize that impaired PGC1α signaling in COPD is associated with reduced muscle KAT expression and increased KYN plasma levels. Methods: Retrospective collected and metabolically phenotyped muscle tissue and blood obtained from 29 well-characterized COPD patients and 15 healthy controls were analyzed. KYN was measured in plasma and KAT1–4 expression and major constituents of PGC1α signaling were assessed in quadriceps muscle biopsies. Results: Circulating KYN levels were increased in COPD. Furthermore, both gene and protein expression levels of KAT4 were reduced in muscle tissue from COPD patients. Finally, in the whole group (even when controlled for airflow obstruction) and in each subgroup separately, KAT4 gene expression correlated significantly with constituents of the PGC1α signaling pathway. Conclusions: These data support our hypothesis that KYN plasma levels are elevated in COPD through impaired KYN clearance in muscle. Our findings show a pathway via which exercise training and/or nutritional modulation may improve physical and mental health in COPD patients
Resveratrol and metabolic health in COPD:A proof-of-concept randomized controlled trial
Background: Patients with COPD are often characterized by disturbed metabolic health which is reflected in altered body composition. Current studies in healthy subjects suggest that resveratrol improves metabolic health by enhancing muscle mitochondrial function and adipose tissue morphology. The primary objective was to investigate the effect of four weeks resveratrol supplementation on muscle mitochondrial function in patients with COPD. Secondary objectives were to investigate the effect of resveratrol on adipose tissue inflammatory and metabolic gene expression, systemic inflammation and body composition in patients with COPD. Methods: In a double-blind randomized placebo-controlled proof-of-concept study, 21 COPD patients (FEVi: 53 +/- 15% predicted; age: 67 +/- 9 years and BMI: 24.5 +/- 3.3 kg/m(2)) received resveratrol (150 mg/day) or placebo for four weeks. Before and after intervention, blood samples, quadriceps muscle and subcutaneous abdominal fat biopsies were obtained for metabolic and inflammatory profiling. Body composition was assessed by dual energy X-ray absorptiometry. Results: Muscle mitochondrial biogenesis regulators AMPK, SIRT1 and PGC-1 alpha as well as mitochondrial respiration, Oxphos complexes, oxidative enzyme activities and kynurenine aminotransferases were not improved by resveratrol. Plasma high-sensitive C-reactive protein and kynurenine did not change after resveratrol supplementation. Adipose tissue inflammatory markers were unaffected by resveratrol, while markers of glycolysis and lipolysis were significantly increased compared to placebo supplementation. Body weight decreased after resveratrol supplementation (resveratrol -0.95 +/- 1.01 kg vs placebo -0.16 +/- 0.66 kg, p = 0.049) due to a reduction in lean mass (resveratrol -1.79 +/- 1.67 kg vs 0.37 +/- 0.86 kg, p = 0.026). Conclusion: We do not confirm previously reported positive effects of resveratrol on skeletal muscle mitochondrial function in patients with COPD, but show an unexpected decline in lean mass. (C) 2020 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved
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Comparing Benefits from Many Possible Computed Tomography Lung Cancer Screening Programs: Extrapolating from the National Lung Screening Trial Using Comparative Modeling
Background: The National Lung Screening Trial (NLST) demonstrated that in current and former smokers aged 55 to 74 years, with at least 30 pack-years of cigarette smoking history and who had quit smoking no more than 15 years ago, 3 annual computed tomography (CT) screens reduced lung cancer-specific mortality by 20% relative to 3 annual chest X-ray screens. We compared the benefits achievable with 576 lung cancer screening programs that varied CT screen number and frequency, ages of screening, and eligibility based on smoking. Methods and Findings: We used five independent microsimulation models with lung cancer natural history parameters previously calibrated to the NLST to simulate life histories of the US cohort born in 1950 under all 576 programs. ‘Efficient’ (within model) programs prevented the greatest number of lung cancer deaths, compared to no screening, for a given number of CT screens. Among 120 ‘consensus efficient’ (identified as efficient across models) programs, the average starting age was 55 years, the stopping age was 80 or 85 years, the average minimum pack-years was 27, and the maximum years since quitting was 20. Among consensus efficient programs, 11% to 40% of the cohort was screened, and 153 to 846 lung cancer deaths were averted per 100,000 people. In all models, annual screening based on age and smoking eligibility in NLST was not efficient; continuing screening to age 80 or 85 years was more efficient. Conclusions: Consensus results from five models identified a set of efficient screening programs that include annual CT lung cancer screening using criteria like NLST eligibility but extended to older ages. Guidelines for screening should also consider harms of screening and individual patient characteristics
Comparing benefits from many possible computed tomography lung cancer screening programs: Extrapolating from the National Lung Screening Trial using comparative modeling
Background: The National Lung Screening Trial (NLST) demonstrated that in current and former smokers aged 55 to 74 years, with at least 30 pack-years of cigarette smoking history and who had quit smoking no more than 15 years ago, 3 annual computed tomography (CT) screens reduced lung cancer-specific mortality by 20% relative to 3 annual chest X-ray screens. We compared the benefits achievable with 576 lung cancer screening programs that varied CT screen number and frequency, ages of screening, and eligibility based on smoking. Methods and Findings: We used five independent microsimulation models with lung cancer natural history parameters previously calibrated to the NLST to simulate life histories of the US cohort born in 1950 under all 576 programs. 'Efficient' (within model) programs prevented the greatest number of lung cancer deaths, compared to no screening, for a given number of CT screens. Among 120 'consensus efficient' (identified as efficient across models) programs, the average starting age was 55 years, the stopping age was 80 or 85 years, the average minimum pack-years was 27, and the maximum years since quitting was 20. Among consensus efficient programs, 11% to 40% of the cohort was screened, and 153 to 846 lung cancer deaths were averted per 100,000 people. In all models, annual screening based on age and smoking eligibility in NLST was not efficient; continuing screening to age 80 or 85 years was more efficient. Conclusions: Consensus results from five models identified a set of efficient screening programs that include annual CT lung cancer screening using criteria like NLST eligibility but extended to older ages. Guidelines for screening should also consider harms of screening and individual patient characteristics
Can big data solve a big problem? Reporting the obesity data landscape in line with the Foresight obesity system map.
BACKGROUND: Obesity research at a population level is multifaceted and complex. This has been characterised in the UK by the Foresight obesity systems map, identifying over 100 variables, across seven domain areas which are thought to influence energy balance, and subsequent obesity. Availability of data to consider the whole obesity system is traditionally lacking. However, in an era of big data, new possibilities are emerging. Understanding what data are available can be the first challenge, followed by an inconsistency in data reporting to enable adequate use in the obesity context. In this study we map data sources against the Foresight obesity system map domains and nodes and develop a framework to report big data for obesity research. Opportunities and challenges associated with this new data approach to whole systems obesity research are discussed. METHODS: Expert opinion from the ESRC Strategic Network for Obesity was harnessed in order to develop a data source reporting framework for obesity research. The framework was then tested on a range of data sources. In order to assess availability of data sources relevant to obesity research, a data mapping exercise against the Foresight obesity systems map domains and nodes was carried out. RESULTS: A reporting framework was developed to recommend the reporting of key information in line with these headings: Background; Elements; Exemplars; Content; Ownership; Aggregation; Sharing; Temporality (BEE-COAST). The new BEE-COAST framework was successfully applied to eight exemplar data sources from the UK. 80% coverage of the Foresight obesity systems map is possible using a wide range of big data sources. The remaining 20% were primarily biological measurements often captured by more traditional laboratory based research. CONCLUSIONS: Big data offer great potential across many domains of obesity research and need to be leveraged in conjunction with traditional data for societal benefit and health promotion
New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.
Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes
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