Short-Term PM2.5 Exposure and DNA Methylation Changes of Circadian Rhythm Genes: Evidence from Two Experimental Studies.

The circadian rhythm regulates many crucial physiological processes, impacting human aging and aging-related outcomes. Observational evidence links circadian rhythm disturbance to PM2.5 exposure, yet the underlying DNA methylation mechanisms remain unclear due to limited PM2.5-dominated experimental settings. Therefore, we investigated the associations between short-term PM2.5 exposure and DNA methylation changes of 1188 CpG candidates across circadian genes among 32 young adults in the FDU study, with the validation in 26 individuals from the PKU study. Further mediation analyses tested whether DNA methylation of circadian genes could mediate the influence of PM2.5 on aging measured by three epigenetic ages: DNAmGrimAge, DunedinPoAm, and the mortality risk score. We identified three CpG sites associated with personal PM2.5 exposure: cg01248361 (CSNK2A2), cg17728065 (RORA), and cg22513396 (PRKAG2). Acute effects of PM2.5 on the three loci could be mediated by several circulating biomarkers, including MDA and EGF, with up to ∼30% of mediated proportions. Three loci further showed varying potentials in mediating the aging acceleration effect of PM2.5. Locus cg17728065 is the key site exhibiting a robust mediating effect (7.54-12.52%) on PM2.5-induced aging acceleration. Our findings demonstrated that PM2.5, even short-term peaks, could leave imprints on human aging via inducing aberrant temporal fluctuation in circadian homeostasis captured by DNA methylation profiles.

Associations of daily sedentary behavior, physical activity, and sleep with irritable bowel syndrome: A prospective analysis of 362,193 participants.

BACKGROUND: Irritable bowel syndrome (IBS) substantially affects quality of life and requires early prevention. This study aimed to elucidate the relationships between IBS and daily behaviors, including sedentary behavior (SB), physical activity (PA), and sleep. In particular, it seeks to identify healthy behaviors to reduce IBS risk, which previous studies have rarely addressed. METHODS: Daily behaviors were retrieved from self-reported data of 362,193 eligible UK Biobank participants. Incident cases were determined by self-report or health care data according to Rome IV criteria. RESULTS: A total of 345,388 participants were IBS-free at baseline, during a median follow-up of 8.45 years, 19,885 incident IBS cases were recorded. When examined individually, SB and shorter (≤7 h/day) or longer (>7 h/day) sleep duration were each positively associated with increased IBS risk, and PA was associated with lower IBS risk. The isotemporal substitution model suggested that replacing SB with other activities could provide further protective effects against IBS risk. Among people sleeping ≤7 h/day, replacing 1 h of SB with equivalent light PA, vigorous PA, or sleep was associated with 8.1% (95% confidence interval (95%CI): 0.901-0.937), 5.8% (95%CI: 0.896-0.991), and 9.2% (95%CI: 0.885-0.932) reduced IBS risk, respectively. For people sleeping >7 h/day, light and vigorous PA were associated with a 4.8% (95%CI: 0.926-0.978) and a 12.0% (95%CI: 0.815-0.949) lower IBS risk, respectively. These benefits were mostly independent of genetic risk for IBS. CONCLUSION: SB and unhealthy sleep duration are risk factors for IBS. A promising way to mitigate IBS risk for individuals sleeping ≤7 h/day and for those sleeping >7 h/day appears to be by replacing SB with adequate sleep or vigorous PA, respectively, regardless of the genetic predisposition of IBS.

Accelerated biological aging elevates the risk of cardiometabolic multimorbidity and mortality.

Associations of biological aging with the development and mortality of cardiometabolic multimorbidity (CMM) remain unclear. Here we conducted a multistate analysis in 341,159 adults of the UK Biobank. CMM was defined as the coexistence of two or three cardiometabolic diseases (CMDs), including type 2 diabetes, ischemic heart disease and stroke. Biological aging was measured using the Klemera-Doubal Method Biological Age and PhenoAge algorithms. Over a median follow-up of 8.84 years, biologically older participants demonstrated robust higher risks from first CMD to CMM and then to death. In particular, adjusted hazard ratios for first CMD to CMM and for CMM to death were 1.15 (95% confidence interval (CI): 1.12, 1.19) and 1.26 (95% CI: 1.17, 1.35) per 1 s.d. increase in PhenoAge acceleration, respectively. Compared with frailty, Framingham Risk Score and Systematic Coronary Risk Evaluation 2 (SCORE2), biological aging measures yielded consistent substantial associations with CMM development. Accelerated biological aging may help identify individuals with CMM risks, potentially enabling early intervention and subclinical prevention.

Clean air policy reduces the atherogenic lipid profile levels: Results from China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) Study.

Evidence of the associations between long-term exposure to PM2.5 and O3 and human blood lipid concentrations is abundant yet inconclusive. Whether clean air policies could improve lipid profiles remains unclear. In total, 2979312 participants from a Chinese nationwide prospective study were included. For cross-sectional analyses, linear mixed-effects models were utilized to assess the associations of pollutants with lipid profiles (TC, LDL-C, TG, HDL-C). For longitudinal analyses, a quasi-experimental design and difference-in-differences models were employed to investigate the impact of China's Clean Air Act. In the cross-sectional analyses, each IQR increase in PM2.5 was associated with 2.49 % (95 % CI: 2.36 %, 2.62 %), 2.51 % (95 % CI: 2.26 %, 2.75 %), 3.94 % (95 % CI: 3.65 %, 4.23 %), and 1.54 % (95 % CI: 1.38 %, 1.70 %) increases in TC, LDL-C, TG, and HDL-C, respectively. For each IQR increase in O3, TC, LDL-C, TG, and HDL-C changed by 1.06 % (95 % CI: 0.95 %, 1.17 %), 1.21 % (95 % CI: 1.01 %, 1.42 %), 1.78 % (95 % CI: 1.54 %, 2.02 %), and -0.63 % (95 % CI: -0.76 %, -0.49 %), respectively. Longitudinal analyses showed that the intervention group experienced greater TC, LDL-C, and HDL-C reductions (1.77 %, 4.26 %, and 7.70 %, respectively). Our findings suggest that clean air policies could improve lipid metabolism and should be implemented in countries with heavy air pollution burdens.

Impact of fine particulate matter on latent tuberculosis infection and active tuberculosis in older adults: a population-based multicentre cohort study.

Evidence showed that air pollution was associated with an increased risk of tuberculosis (TB). This study aimed to study the impact of long-term exposure to ambient particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5) on the acquisition of LTBI and on the risk of subsequent active disease development among rural older adults from a multicentre cohort, which have not yet been investigated to date. A total of 4790 older adults were included in a population-based, multicentre, prospective cohort study (LATENTTB-NSTM) from 2013 to 2018. The level of long-term exposure to PM2.5 for each participant was assessed by aggregating satellite-based estimates. Logistic regression and time-varying Cox proportional hazards models with province-level random intercepts were employed to assess associations of long-term exposures to PM2.5 with the risk of LTBI and subsequent development of active TB, respectively. Out of 4790 participants, 3284 were LTBI-free at baseline, among whom 2806 completed the one-year follow-up and 127 developed newly identified LTBI. No significant associations were identified between PM2.5 and the risk of LTBI. And among 1506 participants with LTBI at baseline, 30 active TB cases were recorded during the 5-year follow-up. Particularly, an increment of 5 µg/m3 in 2-year moving averaged PM2.5 was associated with a 50.6% increased risk of active TB (HR = 1.506, 95% CI: 1.161-1.955). Long-term air pollution might be a neglected risk factor for active TB development from LTBI, especially for those living in developing or less-developed areas where the air quality is poor.

Differences in the lipid metabolism profile and clinical characteristics between eosinophilic and non-eosinophilic acute exacerbation of chronic obstructive pulmonary disease.

Objective: In this study, we aimed to investigate the differences in serum lipid metabolite profiles and their relationship with clinical characteristics between patients with eosinophilic and non-eosinophilic AECOPD. Methods: A total of 71 AECOPD patients were enrolled. Eosinophilic AECOPD was defined as blood EOS% ≥ 2% (n = 23), while non-eosinophilic AECOPD, as blood EOS< 2% (n = 48). Clinical data were collected, and serum lipid metabolism profiles were detected by liquid chromatography-mass spectrometry (LC-MS). The XCMS software package was used to pre-process the raw data, and then, lipid metabolite identification was achieved through a spectral match using LipidBlast library. Differences in lipid profiles and clinical features between eosinophilic and non-eosinophilic groups were analyzed by generalized linear regression. The least absolute shrinkage and selection operator (LASSO) was applied to screen the most characteristic lipid markers for the eosinophilic phenotype. Results: Eosinophilic AECOPD patients had less hypercapnic respiratory failures, less ICU admissions, a shorter length of stay in the hospital, and a lower fibrinogen level. In the lipid metabolism profiles, 32 significantly different lipid metabolites were screened through a t-test adjusted by using FDR (FDR-adjusted p < 0.05 and VIP> 1). Nine differential lipid metabolites were found to be associated with the three clinical features, namely, hypercapnia respiratory failure, ICU admission, and fibrinogen in further integration analysis. The species of triacylglycerol (TAG), phosphatidylcholine (PC), lysophosphatidylcholine (LPC), and diacylglyceryl trimethylhomoserine (DGTS) were high in these eosinophilic AECOPD. The LASSO was applied, and three lipid metabolites were retained, namely, LPC (16:0), TAG (17:0/17:2/17:2), and LPC (20:2). The logistic regression model was fitted using these three markers, and the area under the ROC curve of the model was 0.834 (95% CI: 0.740-0.929). Conclusion: Patients with eosinophilic AECOPD had a unique lipid metabolism status. Species of TAGs and LPCs were significantly increased in this phenotype and were associated with better clinical outcomes.