Influence of maximum diameter on fine-needle aspiration biopsy outcomes in ACR TI-RADS 5 thyroid nodules.

Introduction: Fine needle aspiration (FNA) biopsy is a widely accepted method for diagnosing thyroid nodules. However, the influence of maximum diameter (MD) of ACR TIRADS 5 (TR5) thyroid nodules on the FNA outcomes remains debated. This study examined the influence of MD on the FNA outcomes and investigated the optimal MD threshold for FNA in TR5 nodules. Methods: We conducted a retrospective analysis of 280 TR5 thyroid nodules from 226 patients who underwent FNA from January to June 2022 in our department. Probably malignant (PM) group was defined as Bethesda V in cytopathology with confirmed BRAF V600E mutation or Bethesda VI, the other cytopathology outcomes were defined as probably benign (PB) group. We examined factors influencing malignant cytopathology outcomes and determined the optimal MD threshold for FNA in TR5 nodules using logistic regression and restricted cubic spline (RCS) analysis. Results: Among these nodules, 58.2% (163/280) had PM outcomes. The PM group had a significantly larger MD than the PB group [6.5mm (range 5.0-8.4) vs. 5.3mm (range 4.0-7.0), p < 0.001]. In multivariate logistic regression fully adjusted for confounders, MD was significantly associated with PM outcomes [odds ratio 1.16, 95%CI 1.05-1.31; p = 0.042]. The highest quartile of MD had a greater likelihood of PM outcomes compared to the lowest quartile [odds ratio 4.71, 95% CI 1.97-11.69, p = 0.001]. The RCS analysis identified 6.2 mm as the optimal MD threshold for FNA in TR5 nodules. Conclusion: MD significantly affects the probability of malignant outcomes in FNA of TR5 thyroid nodules. A MD threshold of ≥6.2mm is suggested for FNA in these nodules.

Acute Effects of Exposure to Fine Particulate Matter and Its Constituents on Sex Hormone Among Postmenopausal Women - Beijing, Tianjin, and Hebei PLADs, China, 2018-2019.

What is already known on this topic?: Exposure to fine particulate matter (PM2.5) was linked to endocrine hormone disruption in the reproductive system. Nonetheless, it was unclear which specific components of PM2.5 were primarily responsible for these associations. What is added by this report?: The study presented the initial epidemiological evidence that brief exposure to PM2.5 can elevate estradiol levels in postmenopausal women. Various particle components had unique effects, with water-soluble ions and specific inorganic elements like Ag, As, Cd, Hg, Ni, Sb, Se, Sn, and Tl potentially playing significant roles in increasing estradiol levels. What are the implications for public health practice?: The study established that the prevalence of air pollution, along with its specific components, has been recognized as a novel risk factor affecting the balance of sex hormones.

Association between exposure to chemical mixtures and epigenetic ageing biomarkers: Modifying effects of thyroid hormones and physical activity.

Evidence on the effects of internal chemical mixture exposures on biological age is limited. It also remains unclear whether hormone homeostasis and lifestyle factors can modify such a relationship. Based on the Biomarkers for Air Pollutants Exposure (BAPE) study, which involved healthy older adults aged 60-69 years in China, we found that chemical mixture exposures, including metals, polycyclic aromatic hydrocarbons (PAHs), per- and polyfluoroalkyl substances (PFASs), phthalates (PAEs), and organophosphate esters (OPEs), were significantly associated with shortened DNAmTL and accelerated SkinBloodClock, in which PFASs and OPEs in blood were the primary contributors to DNAmTL, while metals and PAEs had relatively higher contributions in urine. Furthermore, lower levels of thyroxin appeared to exacerbate the adverse effects of environmental chemicals on epigenetic ageing but relatively higher levels of physical activity had the beneficial impact. These findings may have important implications for the development of healthy ageing strategy and aged care policy, particularly in light of the global acceleration of population ageing.

Associations of environmental cadmium exposure with kidney damage: Exploring mediating DNA methylation sites in Chinese adults.

Environmental exposure is widely recognized as the primary sources of Cadmium (Cd) in the human body, and exposure to Cd is associated with kidney damage in adults. Nevertheless, the role of DNA methylation in Cd-induced kidney damage remains unclear. This study aimed to investigate the epigenome-wide association of environmental Cd-related DNA methylation changes with kidney damage. We included 300 non-smoking adults from the China in 2019. DNA methylation profiles were measured with Illumina Infinium MethylationEPIC BeadChip array. Linear mixed-effect model was employed to estimate the effects of urinary Cd with DNA methylation. Differentially methylated positions (DMPs) associated with urinary Cd were then tested for the association with kidney damage indicators. The mediation analysis was further applied to explore the potential DNA methylation based mediators. The prediction model was developed using a logistic regression model, and used 1000 bootstrap resampling for the internal validation. We identified 27 Cd-related DMPs mapped to 20 genes after the adjustment of false-discovery-rate for multiple testing among non-smoking adults. 17 DMPs were found to be associated with both urinary Cd and kidney damage, and 14 of these DMPs were newly identified within the Chinese. Mediation analysis revealed that DNA methylation of cg26907612 and cg16848624 mediated the Cd-related reduced kidney damage. In addition, ten variables were selected using the LASSO regression analysis and were utilized to develop the prediction model. It found that the nomogram model predicted the risk of kidney damage caused by environmental Cd with a corrected C-index of 0.779. Our findings revealed novel DMPs associated with both environmental Cd exposure and kidney damage among non-smoking adults, and developed an easy-to-use nomogram-illustrated model using these novel DMPs. These findings could provide a theoretical basis for formulating prevention and control strategies for kidney damage from the perspective of environmental pollution and epigenetic regulation.

Regression equation for predicting dietary phosphorus intake based on estimated dietary protein intake: A multicenter cross-sectional study in China.

BACKGROUND: Protein and phosphorus intake, which affect chronic kidney disease (CKD), is assessed using cumbersome food diaries. Therefore, more straightforward and accurate methods of assessing protein and phosphorus intake are needed. We decided to investigate the nutrition status and dietary protein and phosphorus intake of patients with stages 3, 4, 5, or 5D CKD. METHODS: This cross-sectional survey included outpatients with CKD at seven class A tertiary hospitals in Beijing, Shanghai, Sichuan, Shandong, Liaoning, and Guangdong in China. Protein and phosphorus intake levels were calculated using 3-day food records. Protein levels and calcium and phosphorus serum concentrations were measured; urinary urea nitrogen was determined using a 24-h urine test. Protein and phosphorus intakes were calculated using the Maroni and Boaz formulas, respectively. The calculated values were compared with the recorded dietary intakes. An equation that regressed phosphorus intake on protein intake was constructed. RESULTS: The average recorded energy and protein intake was 1637.5 ± 595.74 kcal/day and 56.97 ± 25.25 g/day, respectively. Overall, 68.8% of patients had a good nutrition status (grade A on the Subjective Global Assessment). The correlation coefficient between protein intake and calculated intake was 0.145 (P = 0.376) and that between phosphorus intake and calculated intake was 0.713 (P < 0.001). CONCLUSION: Protein and phosphorus intakes correlated linearly. Chinese patients with stage 3-5 CKD had low daily energy intake but high protein intake. Malnutrition was present in 31.2% of patients with CKD. The phosphorus intake could be estimated from the protein intake.

Hourly Air Pollution Exposure and Emergency Hospital Admissions for Stroke: A Multicenter Case-Crossover Study.

BACKGROUND: Daily exposure to ambient air pollution is associated with stroke morbidity and mortality; however, the association between hourly exposure to air pollutants and risk of emergency hospital admissions for stroke and its subtypes remains relatively unexplored. METHODS: We obtained hourly concentrations of fine particulate matter (PM2.5), respirable particulate matter (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO) from the China National Environmental Monitoring Center. We conducted a time-stratified case-crossover study among 86 635 emergency hospital admissions for stroke across 10 hospitals in 3 cities (Jinhua, Hangzhou, and Zhoushan) in Zhejiang province, China, between January 1, 2016 and December 31, 2021. Using a conditional logistic regression combined with a distributed lag linear model, we estimated the association between hourly exposure to multiple air pollutants and risk of emergency hospital admissions for total stroke, ischemic stroke, hemorrhagic stroke, and undetermined type. RESULTS: Hourly exposure to PM2.5, PM10, NO2, and SO2 was associated with an increased risk of hospital admissions for total stroke and ischemic stroke. The associations were most pronounced during the concurrent hour of exposure and lasted for ≈2 hours. We found that the risk was more pronounced among male patients or those aged <65 years old. CONCLUSIONS: Our findings suggest that exposure to PM2.5, PM10, NO2, and SO2, but not CO and O3, is associated with emergency hospital admissions for total stroke or ischemic stroke shortly after exposure. Implementing targeted pollution emission reduction measures may have significant public health implications in controlling and reducing the burden of stroke.

Extrathyroidal extension or tumor size of primary lesion influences thyroid cancer outcomes.

AIMS: Extrathyroidal extension (ETE) is a determined factor of T3 and T4 stage of differentiated thyroid cancer (DTC) in American Joint Committee on Cancer. We aimed to compare clinical outcomes between different extent of ETE according to tumor size. METHODS: Patients diagnosed with DTC were collected from the Surveillance, Epidemiology, and End Results database from 2004 to 2015. They were categorized into two groups by presence of lymph node metastases (LNM) or distant metastases (DM): group A: no presence of LNM and DM, and group B: presence of LNM or DM. Each group was further divided into four groups according to tumor size: <1 cm, 1-2 cm, 2-4 cm, >4 cm. ETE was divided into three groups by the extent: no ETE, microscopic ETE, and macroscopic ETE. Kaplan-Meier method and log-rank test were used to analyze cancer-specific survival (CSS). RESULTS: 91,975 patients were included. In groups A and B, for tumor size 1 cm, there was no significant difference in CSS between no ETE and microscopic ETE, while a significant difference was observed between no ETE and macroscopic ETE. For tumor size >1 cm, there were significant differences in CSS (both no ETE vs. micro ETE and no ETE vs. macro ETE). CONCLUSION: We suggests that when tumor size is more than 1 cm, micro ETE is significantly associated with poorer outcome. T3 and T4 stages may take account into tumor size rather than merely based on the presence and extent of ETE. It may be prudent to revisit the omission of micro ETE in TNM staging.

Association between Organophosphate Ester Exposure and Insulin Resistance with Glycometabolic Disorders among Older Chinese Adults 60-69 Years of Age: Evidence from the China BAPE Study.

BACKGROUND: Organophosphate esters (OPEs) are common endocrine-disrupting chemicals, and OPE exposure may be associated with type 2 diabetes (T2D). However, greater knowledge regarding the biomolecular intermediators underlying the impact of OPEs on T2D in humans are needed to understand biological etiology. OBJECTIVES: We explored the associations between OPE exposure and glycometabolic markers among older Chinese adults 60-69 years of age to elucidate the underlying mechanisms using a multi-omics approach. METHODS: This was a longitudinal panel study comprising 76 healthy participants 60-69 years of age who lived in Jinan city of northern China. The study was conducted once every month for 5 months, from September 2018 to January 2019. We measured a total of 17 OPEs in the blood, 11 OPE metabolites in urine, and 4 glycometabolic markers (fasting plasma glucose, glycated serum protein, fasting insulin, and homeostatic model assessment for insulin resistance). The blood transcriptome and serum/urine metabolome were also evaluated. The associations between individual OPEs and glycometabolic markers were explored. An adverse outcome pathway (AOP) was established to determine the biomolecules mediating the associations. RESULTS: Exposure to five OPEs and OPE metabolites (trimethylolpropane phosphate, triphenyl phosphate, tri-iso-butyl phosphate, dibutyl phosphate, and diphenyl phosphate) was associated with increased levels of glycometabolic markers. The mixture effect analysis further indicated the adverse effect of OPE mixtures. Multi-omics analyses revealed that the endogenous changes in the transcriptional and metabolic levels were associated with OPE exposure. The putative AOPs model suggested that triggers of molecular initiation events (e.g., insulin receptor and glucose transporter type 4) with subsequent key events, including disruptions in signal transduction pathways (e.g., phosphatidylinositol 3-kinase/protein kinase B and insulin secretion signaling) and biological functions (glucose uptake and insulin secretion), may constitute the diabetogenic effects of OPEs. DISCUSSION: OPEs are associated with the elevated risk of T2D among older Chinese adults 60-69 years of age. Implementing OPE exposure reduction strategies may help reduce the T2D burden among these individuals, if the relationship is causal. https://doi.org/10.1289/EHP11896.

Prognosis of thyroid carcinoma patients with osseous metastases: an SEER-based study with machine learning.

OBJECTIVE: Osseous metastasis (OM) is the second most common site of thyroid cancer distant metastasis and presents a poor prognosis. Accurate prognostic estimation for OM has clinical significance. Ascertain the risk factors for survival and develop an effective model to predict the 3-year, 5-year overall survival (OS) and cancer-specific survival (CSS) for thyroid cancer patients with OM. METHODS: We retrieved the information of patients with OMs between 2010 and 2016 from the Surveillance, Epidemiology, and End Result Program. The Chi-square test, and univariate and multivariate Cox regression analyses were performed. Four machine learning (ML) algorithms, which were most commonly used in this field, were applied. RESULT: A total of 579 patients having OMs were eligible. Advanced age, tumor size ≥ 40 mm, combined with other distant metastasis were associated with worse OS in DTC OMs patients. Radioactive iodine (RAI) significantly improved CSS in both males and females. Among four ML models [logistic regression, support vector machines, extreme gradient boosting, and random forest (RF)], RF had the best performance [area under the receiver-operating characteristic curve: 0.9378 for 3-year CSS, 0.9105 for 5-year CSS, 0.8787 for 3-year OS, 0.8909 for 5-year OS]. The accuracy and specificity of RF were also the best. CONCLUSIONS: RF model shall be used to establish an accurate prognostic model for thyroid cancer patients with OM, not only from the SEER cohort but also intended for all thyroid cancer patients in the general population, which may be applicable in clinical practice in the future.

Single-cell transcriptomics reveals the interaction between peripheral CD4+ CTLs and mesencephalic endothelial cells mediated by IFNG in Parkinson's disease.

Parkinson's disease (PD) is characterized by dopaminergic neurons degeneration in the substantia nigra pars compacta. Increasing evidence indicates that peripheral CD4+ T cells, a vital pathological component of PD, have been implicated in systemic inflammation activation, blood-brain barrier (BBB) dysfunction, central nervous system infiltration, and consequent neurons degeneration. However, there is no consensus on CD4+ T cell types' exact phenotypic characteristics in systemic inflammation and the mechanism of CD4+ T cells traffic into the BBB in patients with PD. In this study, we employed single-cell RNA sequencing (scRNA-seq) to elucidate the potential mechanism of T cells on the breakdown of BBB. The PD-associated Cytotoxic CD4+ T cells (CD4+ CTLs) were characterized by a significant increase in proportion as well as enhancement of interferon-gamma (IFNG) response and cell adhesion. Meanwhile, TBX21, IRF1 and NFATC2, identified as the key transcription factors in effector CD4+ T cells differentiation, induced overexpression of target genes-IFNG in CD4+ CTLs. Interestingly, endothelial cells (ECs) in PD patients were discovered to be more responsive to IFNG than other cell types of midbrain. Furthermore, the cell-cell communication analysis between CD4+ T cells and midbrain cells identified IFNG/IFNGR1 and SPP1/ITGB1 as the ligand-receptor pairs to mediate CD4+ CTLs' infiltration into the central nervous system (CNS) through the weakened ECs' tight junction. Together, these results suggested that PD-specific peripheral CD4+ CTLs might influence BBB function by migrating to mesencephalic endothelial cells (ECs) and activating the IFNG response in ECs.

Short-term exposure to ozone and cause-specific mortality risks and thresholds in China: Evidence from nationally representative data, 2013-2018.

BACKGROUND: Ambient ozone pollution is steadily increasing and becoming a major environmental risk factor contributing to the global disease burden. Although the association between short-term ozone exposure and mortality has been widely studied, results are mostly reported on deaths from non-accidental or total cardiopulmonary disease rather than a spectrum of causes. In particular, a knowledge gap still exists for the potential thresholds in mortality risks. METHODS: This nationwide time-series study in China included 323 counties totaling 230,266,168 residents. Daily maximum 8-hour average was calculated as the ozone exposure metric. A two-stage statistical approach was adopted to assess ozone effects on 21 cause-specific deaths for 2013-2018. The subset approach and threshold approach were utilized to explore potential thresholds, and stratification analysis was used to evaluate population susceptibility. RESULTS: On average, the annual mean ozone concentration was 93.4 µg/m3 across 323 counties. A 10-µg/m3 increase in lag 0-1 day of ozone was associated with increases of 0.12 % in mortality risk from non-accidental disease, 0.11 % from circulatory disease, 0.09 % from respiratory disease, 0.29 % from urinary system disease, and 0.20 % from nervous system disease. There may be a "safe" threshold in the ozone-mortality association, which may be between 60 and 100 µg/m3, and vary by cause of death. Women and older adults (especially those over 75) are more affected by short-term ozone exposure. Populations in North China had a higher risk of ozone-related circulatory mortality, while populations in South China had a higher risk of ozone-related respiratory mortality. CONCLUSIONS: National findings link short-term ozone exposure to premature death from circulatory, respiratory, neurological, and urinary diseases, and provide evidence for a potential "safe" threshold in the association of ozone and mortality. These findings have important implications for helping policymakers tighten the relevant air quality standards and developing early warning systems for public health protection in China.

Personal airborne chemical exposure and epigenetic ageing biomarkers in healthy Chinese elderly individuals: Evidence from mixture approaches.

BACKGROUND: Air pollution is associated with accelerated biological ages determined by DNA methylation (DNAm) patterns, imposing further risks of age-related adverse effects. However, little is known about the independent and joint effects of exposure to gaseous organic chemicals that may share a common source. METHODS: We conducted a panel study with the 3-day exposure assessment monthly among 73 Chinese healthy elderly people aged 60 to 69 years in Jinan, Shandong province during September 2018 to January 2019.Exposure to 26 ambient organic chemical contaminants were measured by wearable passive samplers, including volatile organic compounds, polycyclic aromatic hydrocarbons (PAHs), phthalates (PAEs), nitroaromatics (NIs), polybrominated diphenyl ethers, chlorinated hydrocarbons, and organophosphate esters. The Illumina MethylationEPIC BeadChip was used to measure DNA methylation levels in blood samples, and based on which, epigenetic ageing biomarkers, including Hannum clock, Horvath clock, DNAm PhenoAge, DNAm GrimAge, and DNAm estimator of telomere length (DNAmTL) were calculated. Linear mixed effect models were used to estimate the linear associations between 3-day personal chemical exposure and the epigenetic biomarkers, Weighted quantile sum (WQS) regression and the Bayesian kernel machine regression (BKMR) model were further used to evaluate the effect of chemical mixtures. RESULTS: Multiple linear mixed effects regression models showed that DNAmPhenoAge acceleration was significantly and positively associated with exposure to PAEs, NIs, and PAHs in healthy elderly individuals. Both WQS regression and BKMR models showed a significant positive association with DNAmPhenoAge acceleration with chemical exposures, in which the effect of di-n-butyl phthalate exposure showed the greatest importance. CONCLUSION: These findings suggest that exposure to a mixture of airborne chemicals significantly increase the acceleration of the epigenetic biomarker of phenotypic age. These findings serve to identify toxic chemicals in the air and facilitate the evaluation of their potentially severe health effects.

Associations between Individual Exposure to Fine Particulate Matter Elemental Constituent Mixtures and Blood Lipid Profiles: A Panel Study in Chinese People Aged 60-69 Years.

Dyslipidemia may be a potential mechanism linking fine particulate matter (PM2.5) to adverse cardiovascular outcomes. However, inconsistent associations between PM2.5 and blood lipids have resulted from the existing research, and the joint effect of PM2.5 elemental constituents on blood lipid profiles remains unclear. We aimed to explore the overall associations between PM2.5 elemental constituents and blood lipid profiles and to identify the significant PM2.5 elemental constituents in this association. Sixty-nine elderly people were recruited between September 2018 and January 2019. Each participant completed a survey questionnaire, 3 days of individual exposure monitoring, health examination, and biological sample collection at each follow-up visit. Bayesian kernel machine regression (BKMR) models were used to identify the joint effects of the 17 elemental constituents on blood lipid profiles. Total cholesterol, low-density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C) levels were significantly increased in older adults when exposed to the mixture of PM2.5 elemental constituents. Copper and titanium had higher posterior inclusion probabilities than other constituents, ranging from 0.76 to 0.90 (Cu) and 0.74 to 0.94 (Ti). Copper and titanium in the PM2.5 elemental constituent mixture played an essential role in changes to blood lipid levels. This study highlights the importance of identifying critical hazardous PM2.5 constituents that may cause adverse cardiovascular outcomes in the future.

Role of the gut-microbiota-metabolite axis in the rotenone model of early-stage Parkinson's Disease.

Gastrointestinal symptoms are common in the early-stage Parkinson's disease (PD), but its potential pathogenesis remains unclear. Therefore, in the present study, we used the 16S ribosomal RNA gene sequencing and gas chromatography coupled with mass spectrometry-based metabolomics to investigate the alterations of gut microbiome and serum amino acid levels in the early-stage PD mice model induced with rotenone. The results demonstrated that the microbial taxa at phylum, family and genus levels remarkably altered in rotenone-induced mice relative to vehicle-induced mice. The rotenone-induced mice had higher relative abundance of Flavobacteriaceae, Staphylococcaceae, and Prevotellaceae as well as lower relative abundance of Lachnospiraceae_UCG-001, Ruminiclostridium, and Prevotellaceae_NK3B31_group than vehicle-induced mice. The evaluation of serum amino acids revealed the alterations in several classes of amino acids, including L-proline, L-alanine, L-serine, L-asparagine, L-threonine, L-glutamine, L-methionine, and L-4-hydroxyproline. Notably, the altered serum amino acid levels were significantly associated with the abundance of gut microbiota, especially Ruminococcaceae and Ruminiclostridium. Our study explored the possible role of the gut-microbiota-metabolite axis in the early-stage PD and provided the possibility of prevention and treatment of PD by gut-microbiota-metabolite axis in the future.

Impact of Heavy PM2.5 Pollution Events on Mortality in 250 Chinese Counties.

We explored the impact of heavy PM2.5 pollution events on the health of residents in 250 counties in China. A time-series approach involving a two-stage analysis was applied to estimate the association between heavy PM2.5 pollution events and mortality from 2013 to 2018. The associations between heavy (PM2.5 ≥75 µg/m3 and <150 µg/m3) and extremely heavy (PM2.5 ≥150 µg/m3) PM2.5 pollution days with mortality were explored. The added effects of the heavy PM2.5 pollution events were evaluated by controlling PM2.5 concentration in the model. From 2013 to 2018, there were 57,279 county days of heavy PM2.5 pollution and 21,248 county days of extremely heavy PM2.5 pollution. The risks of mortality during this period of heavy PM2.5 pollution events increased by 1.22% (95% CI: 0.82-1.63%), 1.14% (95% CI: 0.74-1.53%), 1.09% (95% CI: 0.58-1.60%), and 1.30% (95% CI: 0.40-2.20%), for all-cause, nonaccidental, circulatory, and respiratory mortality, respectively. We also observed that heavy PM2.5 pollution events had an added effect on mortality risk associated with all-cause, nonaccidental, circulatory, and respiratory mortality, evident from an observed increase by 0.77% (95% CI: 0.29-1.24%), 0.73% (95% CI: 0.27-1.19%), 0.96% (95% CI: 0.37-1.55%), and 0.55% (95% CI: -0.52-1.63%), respectively. Heavy PM2.5 pollution events increased mortality risks and caused an independent added effect. The findings serve as a foundation for policymakers in developing early warning systems and policy interventions.

Sleep disturbance exacerbates the cardiac conduction abnormalities induced by persistent heavy ambient fine particulate matter pollution: A multi-center cross-sectional study.

Fine particulate matter (PM2.5) exposure and sleep disturbance have been significantly associated with adverse cardiovascular outcomes, however, the combined effects of these two factors are still unclear. We conducted a multi-center cross-sectional study from November 2018 to May 2019 in the Beijing-Tianjin-Hebei region in China to investigate the potential modifying effects of sleep disturbance on associations between cardiac conduction abnormalities and PM2.5 exposure, as well as the combined effects of sleep disturbance and heavy pollution episodes, which were defined based on the PM2.5 mass concentration (≥75 µg/m3, falling in the 75th/90th percentile) and duration (1 day and ≥2 days). The sleep quality and sleep duration of all participants were evaluated using the Pittsburgh Sleep Quality Index. Standard 12-lead electrocardiogram (ECG) test was performed to measure the heart rate (HR), QRS duration (time taken for ventricular depolarization), HR corrected QT interval (time for ventricular depolarization and repolarization) and PR interval (time for atrioventricular conduction). Multivariable linear regression models were performed to evaluate the associations of PM2.5 and heavy pollution events on ECG parameters and the joint effects with sleep disturbance. We found PM2.5 exposure was independently associated with prolonged QRS and QTc intervals. Association between PM2.5 and the QTc interval was significantly stronger in participants with poor sleep quality. For each 10-µg/m3 increase in PM2.5 concentration, the QTc interval in the participants with poor sleep quality increased by 0.41 % (95 % confidence interval: 0.19, 0.64). In addition, heavy PM2.5 pollution episodes, especially extremely heavy pollution of long duration, were found to have synergistic effects with sleep disturbance on ECG parameters. Our findings provide evidence that PM2.5 exposure, especially heavy pollution episodes, may increase abnormal cardiac conduction and have a synergistic effect with sleep disturbance. Improving sleep hygiene is crucial to protect the heart health of the general population.

Linking the Fasting Blood Glucose Level to Short-Term-Exposed Particulate Constituents and Pollution Sources: Results from a Multicenter Cross-Sectional Study in China.

Ambient PM2.5 (fine particulate matter with aerodynamic diameters ≤ 2.5 µm) is thought to be associated with the development of diabetes, but few studies traced the effects of PM2.5 components and pollution sources on the change in the fasting blood glucose (FBG). In the present study, we assessed the associations of PM2.5 constituents and their sources with the FBG in a general Chinese population aged over 40 years. Exposure to PM2.5 was positively associated with the FBG level, and each interquartile range (IQR) increase in a lag period of 30 days (18.4 µg/m3) showed the strongest association with an elevated FBG of 0.16 mmol/L (95% confidence interval: 0.04, 0.28). Among various constituents, increases in exposed elemental carbon, organic matter, arsenic, and heavy metals such as silver, cadmium, lead, and zinc were associated with higher FBG, whereas barium and chromium were associated with lower FBG levels. The elevated FBG level was closely associated with the PM2.5 from coal combustion, industrial sources, and vehicle emissions, while the association with secondary sources was statistically insignificant. Improving air quality by tracing back to the pollution sources would help to develop well-directed policies to protect human health.

Epigenetic age stratifies the risk of blood pressure elevation related to short-term PM2.5 exposure in older adults.

BACKGROUND: Exposure to fine particulate matter (PM2.5) is a prominent risk factor for cardiovascular aging in older adults and causes mild syndromes or other comorbidities in otherwise healthy older adults. Accordingly, a precise tool for PM2.5 exposure risk stratification is urgently needed. We aimed to address this need by comparing the performances of seven types of epigenetic age and chronological age to classify the effects of short-term PM2.5 exposure on blood pressure (BP), a typical clinical surrogate marker of cardiovascular aging. METHODS: We conducted a panel study of the Chinese healthy adults aged 60-69 years through five monthly visits. Personal PM2.5 exposures were measured using wearable monitoring devices for three consecutive days, and DNA methylation was determined by the Illumina MethylationEPIC BeadChip using blood samples collected at each visit. Systolic BP, diastolic BP, mean arterial pressure and pulse pressure were measured by the electronic BP monitor. Linear mixed models with interaction terms between PM2.5 and different ages were used to assess their potential usefulness for stratification. RESULTS: DNAmPhenoAge, Skin & blood clock, DNAmGrimAge acceleration, and DunedinPoAm had significant modifying effects on the relationship between PM2.5 and BP. For instance, a 10-µg/m3 increase in the 72-h moving mean PM2.5 was significantly associated with 0.30% (95% CI: 0.10%, 0.51%) and -0.07% (95% CI: -0.32%, 0.18%) increases in systolic BP at higher and lower DNAmPhenoAge acceleration, respectively. Joint models further revealed that using a combination of epigenetic ages could more precisely stratify the effect of PM2.5 on BP. CONCLUSIONS: Our research indicates that epigenetic age may be a useful tool for evaluating the effect of short-term PM2.5 exposure on cardiovascular aging status.

PM2.5 exposure associated with microbiota gut-brain axis: Multi-omics mechanistic implications from the BAPE study.

Recent studies have shown that PM2.5 may activate the hypothalamus-pituitary-adrenal (HPA) axis by inducing hormonal changes, potentially explaining the increase in neurological and cardiovascular risks. In addition, an association between PM2.5 and gut microbiota and metabolites was established. The above evidence represents crucial parts of the gut-brain axis (GBA). In view of this evidence, we proposed a hypothesis that PM2.5 exposure may affect the HPA axis through the gastrointestinal tract microbiota pathway (GBA mechanism), leading to an increased risk of neurological and cardiovascular diseases. We conducted a real-world prospective repeated panel study in Jinan, China. At each visit, we measured real-time personal PM2.5 and collected fecal and blood samples. A linear mixed-effects model was used to analyze the association between PM2.5 and serum biomarkers, gut microbiota, and metabolites. We found that PM2.5 was associated with increased serum levels of hormones, especially the adrenocorticotropic hormone (ACTH) and cortisol, which are reliable hormones of the HPA axis. Gut microbiota and tryptophan metabolites and inflammation, which are important components of the GBA, were significantly associated with PM2.5. We also found links between PM2.5 and changes in the nervous and cardiovascular outcomes, e.g., increases of 19.77% (95% CI: -36.44, 125.69) in anxiety, 1.19% (95% CI: 0.65, 1.74) in fasting blood glucose (FBG), 2.09% (95% CI: 1.48, 2.70) in total cholesterol (TCHOL), and 0.93% (95% CI: 0.14, 1.72) in triglycerides (TG), were associated with 10 µg/m3 increase in PM2.5 at the lag 0-72 h, which represent the main effects of GBA. This study indicated the link between PM2.5 and the microbiota GBA for the first time, providing evidence of the potential mechanism for PM2.5 with neurological and cardiovascular system dysfunction.

PM2.5 and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China.

BACKGROUND: Insulin resistance (IR) affects the development of type 2 diabetes mellitus (T2DM), which is also influenced by accumulated fine particle air pollution [particulate matter (PM) with aerodynamic diameter of <2.5µm (PM2.5)] exposure. Previous experimental and epidemiological studies have proposed several potential mechanisms by which PM2.5 contributes to IR/T2DM, including inflammation imbalance, oxidative stress, and endothelial dysfunction. Recent evidence suggests that the imbalance of the gut microbiota affects the metabolic process and may precede IR. However, the underlying mechanisms of PM2.5, gut microbiota, and metabolic diseases are unclear. OBJECTIVES: We investigated the associations between personal exposure to PM2.5 and fasting blood glucose and insulin levels, the IR index, and other related biomarkers. We also explored the potential underlying mechanisms (systemic inflammation and sphingolipid metabolism) between PM2.5 and insulin resistance and the mediating effects between PM2.5 and sphingolipid metabolism. METHODS: We recruited 76 healthy seniors to participate in a repeated-measures panel study and conducted clinical examinations every month from September 2018 to January 2019. Linear mixed-effects (LME) models were used to analyze the associations between PM2.5 and health data (e.g., functional factors, the IR index, inflammation and other IR-related biomarkers, metabolites, and gut microbiota). We also performed mediation analyses to evaluate the effects of mediators (gut microbiota) on the associations between exposures (PM2.5) and featured metabolism outcomes. RESULTS: Our prospective panel study illustrated that exposure to PM2.5 was associated with an increased risk of higher IR index and functional biomarkers, and our study provided mechanistic evidence suggesting that PM2.5 exposure may contribute to systemic inflammation and altered sphingolipid metabolism. DISCUSSION: Our findings demonstrated that PM2.5 was associated with the genera of the gut microbiota, which partially mediated the association between PM2.5 and sphingolipid metabolism. These findings may extend our current understanding of the pathways of PM2.5 and IR. https://doi.org/10.1289/EHP9688.