Most genome-wide association studies have been conducted in European individuals, even though most genetic variation in humans is seen only in non-European samples. To search for novel loci associated with blood lipid levels and clarify the mechanism of action at previously identified lipid loci, we examined protein-coding genetic variants in 47,532 East Asian individuals using an exome array. We identified 255 variants at 41 loci reaching chip-wide significance, including 3 novel loci and 14 East Asian-specific coding variant associations. After meta-analysis with > 300,000 European samples, we identified an additional 9 novel loci. The same 16 genes were identified by the protein-altering variants in both East Asians and Europeans, likely pointing to the functional genes. Our data demonstrate that most of the low-frequency or rare coding variants associated with lipids are population-specific, and that examining genomic data across diverse ancestries may facilitate the identification of functional genes at associated loci.
ObjectiveTo investigate the associations of sleep duration, midday napping, sleep quality, and change in sleep duration with risk of incident stroke and stroke subtypes.MethodsAmong 31,750 participants aged 61.7 years on average at baseline from the Dongfeng-Tongji cohort, we used Cox regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for incident stroke.ResultsCompared with sleeping 7 to <8 hours/night, those reporting longer sleep duration (≥9 hours/night) had a greater risk of total stroke (hazard ratio [HR] 1.23; 95% confidence interval [CI] 1.07–1.41), while shorter sleep (<6 hours/night) had no significant effect on stroke risk. The HR (95% CI) of total stroke was 1.25 (1.03–1.53) for midday napping >90 minutes vs 1–30 minutes. The results were similar for ischemic stroke. Compared with good sleep quality, those with poor sleep quality showed a 29%, 28%, and 56% higher risk of total, ischemic, and hemorrhagic stroke, respectively. Moreover, we observed significant joint effects of sleeping ≥9 hours/night and midday napping >90 minutes (HR 1.85; 95% CI 1.28–2.66), and sleeping ≥9 hours/night and poor sleep quality (HR 1.82; 95% CI 1.33–2.48) on risk of total stroke. Furthermore, compared with persistently sleeping 7–9 hours/night, those who persistently slept ≥9 hours/night or switched from 7 to 9 hours to ≥9 hours/night had a higher risk of total stroke.ConclusionsLong sleep duration, long midday napping, and poor sleep quality were independently and jointly associated with higher risks of incident stroke. Persistently long sleep duration or switch from average to long sleep duration increased the risk of stroke.
Background:Smoking is a risk factor for many human diseases. DNA methylation has been related to smoking, but genome-wide methylation data for smoking in Chinese populations is limited.Objectives:We aimed to investigate epigenome-wide methylation in relation to smoking in a Chinese population.Methods:We measured the methylation levels at > 485,000 CpG sites (CpGs) in DNA from leukocytes using a methylation array and conducted a genome-wide meta-analysis of DNA methylation and smoking in a total of 596 Chinese participants. We further evaluated the associations of smoking-related CpGs with internal polycyclic aromatic hydrocarbon (PAH) biomarkers and their correlations with the expression of corresponding genes.Results:We identified 318 CpGs whose methylation levels were associated with smoking at a genome-wide significance level (false discovery rate < 0.05), among which 161 CpGs annotated to 123 genes were not associated with smoking in recent studies of Europeans and African Americans. Of these smoking-related CpGs, methylation levels at 80 CpGs showed significant correlations with the expression of corresponding genes (including RUNX3, IL6R, PTAFR, ANKRD11, CEP135 and CDH23), and methylation at 15 CpGs was significantly associated with urinary 2-hydroxynaphthalene, the most representative internal monohydroxy-PAH biomarker for smoking.Conclusion:We identified DNA methylation markers associated with smoking in a Chinese population, including some markers that were also correlated with gene expression. Exposure to naphthalene, a byproduct of tobacco smoke, may contribute to smoking-related methylation.Citation:Zhu X, Li J, Deng S, Yu K, Liu X, Deng Q, Sun H, Zhang X, He M, Guo H, Chen W, Yuan J, Zhang B, Kuang D, He X, Bai Y, Han X, Liu B, Li X, Yang L, Jiang H, Zhang Y, Hu J, Cheng L, Luo X, Mei W, Zhou Z, Sun S, Zhang L, Liu C, Guo Y, Zhang Z, Hu FB, Liang L, Wu T. 2016. Genome-wide analysis of DNA methylation and cigarette smoking in Chinese. Environ Health Perspect 124:966–973; http://dx.doi.org/10.1289/ehp.1509834
Background. Extensive studies have been carried out to investigate the association between obesity and the risk of rheumatoid arthritis (RA); however, the results of the current reported original studies remain inconsistent. This study aimed to clarify the relationship between body mass index and rheumatoid arthritis by conducting an updated overall and dose-response meta-analysis. Methods. The relevant literature was searched using the PubMed and Embase databases (through 20 September 2018) to identify all eligible published studies. Random-effect models and dose-response meta-analyses were used to estimate the pooled risk ratio (RR) with a 95% confidence interval (CI). Subgroup analyses were also conducted based on the characteristics of the participants. Sensitivity analyses and publication bias tests were also performed to explore potential heterogeneity and bias in the meta-analysis. Results. Sixteen studies that included a total of 406,584 participants were included in the meta-analysis. Compared to participants with normal weight, the pooled RRs of rheumatoid arthritis were 1.12 (95% CI, 1.04-1.20) in overweight and 1.23 (95% CI, 1.09-1.39) in obese participants. There was evidence of a nonlinear relationship between body mass index (BMI) and RA (P for nonlinearity less than 0.001 in the overall meta-analysis, P for nonlinearity=0.025 in the case-control studies, P for nonlinearity=0.0029 in the cohort studies). No significant heterogeneity was found among studies (I2=10.9% for overweight and I2=45.5% for obesity). Conclusion. The overall and dose-response meta-analysis showed that increased BMI was associated with an increased risk for rheumatoid arthritis, which might present a prevention strategy for the prevention or control of rheumatoid arthritis. The nonlinear relationship between BMI and RA might present a personal prevention strategy for RA.
Background:Aging is related to an increased risk of morbidity and mortality and is affected by environmental factors. Exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with adverse health outcomes; but the association of such exposure with DNA methylation aging, a novel aging marker, is unclear.Objectives:Our aim was to investigate the association of PAH exposure with methylation aging.Methods:We trained and validated a methylation age predictor suitable for Chinese populations using whole blood methylation data in 989 Chinese and 160 Caucasians. We defined two aging indicators: Δage, as methylation age minus chronological age; and aging rate, the ratio of methylation to chronological age. The association of PAH exposure with aging indicators was evaluated using linear regressions in three panels of healthy Chinese participants (N=539, among the aforementioned 989 Chinese participants) whose exposure levels were assessed by 10 urinary monohydroxy-PAH metabolites.Results:We developed a methylation age predictor providing accurate predictions in both Chinese individuals and Caucasian persons (R=0.94–0.96, RMSE=3.8–4.3). Among the 10 urinary metabolites that we measured, 1-hydroxypyrene and 9-hydroxyphenanthrene were associated with methylation aging independently of other OH-PAHs and risk factors; 1-unit increase in 1-hydroxypyrene was associated with a 0.53-y increase in Δage [95% confidence interval (CI): 0.18, 0.88; false discovery rate (FDR) FDR=0.004] and 1.17% increase in aging rate (95% CI: 0.36, 1.98; FDR=0.02), whereas for 9-hydroxyphenanthrene, the increase was 0.54-y for Δage (95% CI: 0.17, 0.91; FDR=0.004), and 1.15% for aging rate (95% CI: 0.31, 1.99; FDR=0.02). The association direction was consistent across the three Chinese panels with the association magnitude correlating with the panels’ exposure levels; the association was validated by methylation data of purified leukocytes. Several cytosine-phosphoguanines, including those located on FHL2 and ELOVL2, were found associated with both aging indicators and monohydroxy-PAH levels.Conclusions:We developed a methylation age predictor specific for Chinese populations but also accurate for Caucasian populations. Our findings suggest that exposure to PAHs may be associated with an adverse impact on human aging and epigenetic alterations in Chinese populations. https://doi.org/10.1289/EHP2773
Our study identified novel blood methylation alterations associated with ACS and provided potential clinical biomarkers and therapeutic targets. Our results may suggest that immune signaling and cellular functions might be regulated at an epigenetic level in ACS.
SUMMARYA new four-dimensional continuous-time autonomous hyperchaotic Lorenz-type system is introduced and analyzed. This hyperchaotic system is not only visualized by computer simulation but also verified with bifurcation analysis and realized with an electronic circuit. Moreover, explicit formulae for estimating the ultimate bound and positive invariant set of the system are derived by constructing a family of generalized Lyapunov functions. The findings and results of this paper have good potential in control and synchronization of hyperchaos and their engineering applications.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.