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

Disturbed glucose homeostasis and its increased allostatic load in response to individual, joint and fluctuating air pollutants exposure: Evidence from a longitudinal study in prediabetes

We investigated the effect of individual, joint and fluctuating exposure to air pollution (PM2.5, BC, NO3-, NH4+, OM, SO42-, PM10, NO2, SO2, O3) on glucose metabolisms among prediabetes, and simultaneously explored the modifying effect of lifestyle. We conducted a longitudinal study among prediabetes during 2018-2022. Exposure windows within 60-days moving averages and their variabilities were calculated. FBG, insulin, HOMA-IR, HOMA-B, triglyceride glucose index (TyG), glucose insulin ratio (GI) and allostatic load of glucose homeostasis system (AL-GHS) was included. Linear mixed-effects model and BKMR were adopted to investigate the individual and overall effects, respectively. We also explored the preventive role of lifestyle. Individual air pollutant was associated with increased FBG, insulin, HOMA-IR, HOMA-B, TyG, and decreased GI. People with FBG ≥6.1 mmol/L were more susceptible. Air pollutants mixture were only associated with increased HOMA-B, and constituents have the highest group-PIP. Air pollutants variation also exert harmful effect. We observed similar diabetic effect on AL-GHS. Finally, the diabetic effect of air pollutants disappeared if participants adopt a favorable lifestyle. Our findings highlighted the importance of comprehensively assessing multiple air pollutants and their variations, focusing on metabolic health status in the early prevention of T2D, and adopting healthy lifestyle to mitigate such harmful effect.

National burden and risk factors of diabetes mellitus in China from 1990 to 2021: Results from the Global Burden of Disease study 2021

BACKGROUND

In recent years, the prevalence and mortality rates of diabetes have been rising continuously, posing a significant threat to public health and placing a heavy burden on the population. This study was conducted to describe and analyze the burden of diabetes in China from 1990 to 2021 and its attributable risk factors.

METHODS

Utilizing data from the Global Burden of Disease Study 2021, we analyzed the incidence, prevalence, and disability-adjusted life years (DALYs) of type 1 diabetes (T1DM) and type 2 diabetes (T2DM) in China from 1990 to 2021. We extracted sex- and age-specific data on diabetes, focusing on DALYs, years lived with disability, and years of life lost. Bayesian meta-regression and spatiotemporal Gaussian process regression were used to estimate disease parameters. Age-standardized rates (ASRs) and estimated annual percentage changes (EAPC) were calculated using direct standardization and log-linear regression. The population-attributable fractions were also determined for each risk factor.

RESULTS

In 2021, the absolute number of incident diabetes mellitus (DM) cases was estimated at 4003543.82, including 32 000 T1DM and 3971486.24 T2DM cases. The ASRs were 244.57 for DM, 2.67 for T1DM, and 241.9 for T2DM (per 100 000 population). The absolute number of prevalent DM cases was 117288553.93, including 1442775.09 T1DM and 115845778.84 T2DM cases. The ASRs were 6142.29 for DM, 86.78 for T1DM, and 6055.51 for T2DM (per 100 000 population). In 2021, there were 178475.73 deaths caused by DM, with an ASR of mortality of 8.98 per 100 000 population. The DALYs due to DM in 2021 were 11713613.86, with an ASR of 585.43 per 100 000 population and an EAPC of 0.57. This increase can be attributed to several factors, including high body mass index, air pollution, and dietary habits.

CONCLUSIONS

The burden of diabetes is considerable, with high prevalence and incidence rates, highlighting the urgent need for public health interventions. Addressing factors like high fasting plasma glucose, body mass index, air pollution, and dietary risks through effective interventions is critical.

Role of microglia polarization induced by glucose metabolism disorder in the cognitive impairment of mice from PM2.5 exposure

Studies have found that PM2.5 can damage the brain, accelerate cognitive impairment, and increase the risk of developing a variety of neurodegenerative diseases. However, the potential molecular mechanisms by which PM2.5 causes learning and memory problems are yet to be explored. In this study, we evaluated the neurotoxic effects in mice after 12 weeks of PM2.5 exposure, and found that this exposure resulted in learning and memory disorders, pathological brain damage, and M1 phenotype polarization on microglia, especially in the hippocampus. The severity of this damage increased with increasing PM2.5 concentration. Proteomic analysis, as well as validation results, suggested that PM2.5 exposure led to abnormal glucose metabolism in the mouse brain, which is mainly characterized by significant expression of hexokinase, phosphofructokinase, and lactate dehydrogenase. We therefore administered the glycolysis inhibitor 2-deoxy-d-glucose (2-DG) to the mice exposed to PM2.5, and showed that inhibition of glycolysis by 2-DG significantly alleviated PM2.5-induced hippocampal microglia M1 phenotype polarization, and reduced the release of inflammatory factors, improved synaptic structure and related protein expression, which alleviated the cognitive impairment induced by PM2.5 exposure. In summary, our study found that abnormal glucose metabolism-mediated inflammatory polarization of microglia played a role in learning and memory disorders in mice exposed to PM2.5. This study provides new insights into the neurotoxicity caused by PM2.5 exposure, and provides some theoretical references for the prevention and control of cognitive impairment induced by PM2.5 exposure.

The mediating effect of TyG-related indicators between long-term exposure to particulate matter and cardiovascular disease: evidence from a national longitudinal cohort study

BACKGROUND

Ambient particulate matter (PM) exposure is recognized as a risk factor for cardiovascular disease (CVD). However, the extent to which PM exposure is associated with CVD via triglyceride glucose (TyG)-related indicators remains unknown. This study examines the relationship between long-term PM exposure and CVD events, further assessing whether TyG-related indicators mediate this association.

METHODS

This cohort study involved 7,532 individuals aged at least 45 years who were not diagnosed with CVD in 2011 from the China Longitudinal Study of Health and Retirement (CHARLS) and were followed up for the occurrence of CVD until 2020. The annual PM concentration data at the city level, with aerodynamic diameters ≤ 1 μm (PM1), ≤ 2.5 μm (PM2.5), and ≤ 10 μm (PM10), were obtained from the ChinaHighAirPollutants (CHAP). The average concentration of PM in the 3 years before the baseline survey in 2011 was defined as the long-term exposure level of the individual. The relationship between PM exposure and CVD incidence was examined via Cox proportional hazards models, with a focus on probing the role of TyG-related indicators through mediation analysis.

RESULTS

A total of 1,865 individuals with CVD were diagnosed over the span of a 7.4-year follow-up period. The 3-year average concentrations before baseline were 31.29 µg/m³ for PM1, 56.03 µg/m³ for PM2.5, and 95.73 µg/m³ for PM10. In fully adjusted model, the Cox proportional hazards models revealed that an increase of 10 µg/m³ in the PM1, PM2.5, and PM10 exposure concentrations corresponded to elevated CVD risk, with HRs (95% CI) of 1.135 (1.078-1.195), 1.092 (1.062-1.123), and 1.075 (1.059-1.090), respectively. Mediation analyses further suggested that the correlation between PM exposure and CVD could be partly mediated via TyG-BMI, TyG-WC, and TyG-WHtR, with mediation proportions varying from 5.54 to 15.30%.

CONCLUSION

A significant correlation was observed between long-term PM exposure and increased CVD risk, with TyG-related indicators, such as TyG-BMI, TyG-WC, and TyG-WHtR, partially mediating this relationship.

Gut microbiota mediates ambient PM2.5 exposure-induced abnormal glucose metabolism via short-chain fatty acids

PM2.5 exposure has been found to cause gut dysbiosis and impair glucose homeostasis in human and animals, yet their underlying biological connection remain unclear. In the present study, we aim to investigate the biological significance of gut microbiota in PM2.5-induced glucose metabolic abnormalities. Our results showed that microbiota depletion by antibiotics treatment significantly alleviated PM2.5-induced glucose intolerance and insulin resistance, as indicated by the intraperitoneal glucose tolerance test, glucose-induced insulin secretion, insulin tolerance test, insulin-induced phosphorylation levels of Akt and GSK-3β in insulin sensitive tissues. In addition, faecal microbiota transplantation (FMT) from PM2.5-exposed donor mice successfully remodeled the glucose metabolism abnormalities in recipient mice, while the transplantation of autoclaved faecal materials did not. Faecal microbiota analysis demonstrated that the composition and alpha diversity of the gut bacterial community were altered by PM2.5 exposure and in FMT recipient mice. Furthermore, short-chain fatty acids levels analysis showed that the circulating acetate was significantly decreased in PM2.5-exposed donor and FMT recipient mice, and supplementation of sodium acetate for 3 months successfully improved the glucose metabolism abnormalities induced by PM2.5 exposure. These results indicate that manipulating gut microbiota or its metabolites could be a potential strategy for preventing the adverse health effects of ambient PM2.5.

Research on the causal relationship between fine particulate matter and type 2 diabetes mellitus: A two-sample multivariable mendelian randomization study

BACKGROUND AND AIMS

Previous research has suggested a correlation between fine particulate matter (PM2.5) and type 2 diabetes mellitus (T2DM). However, the causality was vulnerable to confounding variables.

METHODS AND RESULTS

A two-sample multivariable mendelian randomization study was designed to examine the causal connection between PM2.5 and T2DM. PM2.5 trait was investigated as exposure while T2DM-related traits as outcomes. The summary data were obtained from the Finngen database and the open genome-wide association study database. The mendelian randomization estimates were obtained using the inverse-variance weighted approach, and multiple sensitivity analyses were conducted. There were potential causal relationships between PM2.5 and T2DM (OR = 2.418; P = 0.019), PM2.5 and glycated hemoglobin (HbA1c) (OR = 1.590; P = 0.041), and PM2.5 and insulin metabolism. PM2.5 was found to have no causal effect on fasting glucose and insulin, 2-h glucose, and insulin-like growth factor binding protein-1 (P > 0.05), while had a potential protective effect against some diabetes complications.

CONCLUSIONS

Our findings indicated potential causal relationships among PM2.5 and T2DM, especially the causal relationship between PM2.5 and long-term glucose levels.

Health effect of multiple air pollutant mixture on sarcopenia among middle-aged and older adults in China

BACKGROUND

As the global aging process accelerates, the health challenges posed by sarcopenia among middle-aged and older adults are becoming increasingly prominent. However, the available evidence on the adverse effects of air pollution on sarcopenia is limited, particularly in the Western Pacific region. This study aimed to explore relationships of multiple air pollutants with sarcopenia and related biomarkers using the nationally representative database.

METHODS

Totally, 6585 participants aged over 45 years were enrolled from the China Health and Retirement Longitudinal Study (CHARLS) in 2011 and 3443 of them were followed up until 2015. Air pollutants were estimated from high-resolution satellite-based spatial-temporal models. In the cross-sectional analysis, we used generalized linear regression, unconditional logistic regression analytical and restricted cubic spline (RCS) methods to assess the single-exposure and non-linear effects of multiple air pollutants on sarcopenia and related surrogate biomarkers (serum creatinine and cystatin C). Several popular mixture analysis techniques such as Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS) regression, and quantile-based g-computation (Qgcomp) were further used to examinate the combined effects of multiple air pollutants. Logistic regression was used to further analyze the longitudinal association between air pollution and sarcopenia.

RESULTS

Each interquartile range increase in PM2.5, PM10 and NO2 was significantly associated with an increased risk of sarcopenia, with adjusted odds ratios (aORs) of 1.09 [95 % confidence interval (CI): 1.01, 1.20], 1.24 (95 % CI: 1.14, 1.35) and 1.18 (95 % CI: 1.08, 1.28), respectively. Our findings also showed that five air pollutants were significantly associated with the sarcopenia index. In addition, employing a mixture analysis approach, we confirmed significant combined effects of air pollution mixtures on sarcopenia risk and associated biomarkers, with PM10 and PM2.5 identified as major contributors to the combined effect. The results of the exposure-response (E-R) relationships, subgroup analysis, longitudinal analysis and sensitivity analysis all showed the unfavorable impact of air pollution on sarcopenia risk and related vulnerable populations.

CONCLUSIONS

Single-exposure and co-exposure to multiple air pollutants were positively associated with sarcopenia among middle-aged and older adults in China. Our study provided new evidence that air pollution mixture was significantly associated with sarcopenia related biomarkers.

Choices of morbidity outcomes and concentration-response functions for health risk assessment of long-term exposure to air pollution

Background

Air pollution health risk assessment (HRA) has been typically conducted for all causes and cause-specific mortality based on concentration-response functions (CRFs) from meta-analyses that synthesize the evidence on air pollution health effects. There is a need for a similar systematic approach for HRA for morbidity outcomes, which have often been omitted from HRA of air pollution, thus underestimating the full air pollution burden. We aimed to compile from the existing systematic reviews and meta-analyses CRFs for the incidence of several diseases that could be applied in HRA. To achieve this goal, we have developed a comprehensive strategy for the appraisal of the systematic reviews and meta-analyses that examine the relationship between long-term exposure to particulate matter with an aerodynamic diameter smaller than 2.5 µm (PM2.5), nitrogen dioxide (NO2), or ozone (O3) and incidence of various diseases.

Methods

To establish the basis for our evaluation, we considered the causality determinations provided by the US Environmental Protection Agency Integrated Science Assessment for PM2.5, NO2, and O3. We developed a list of pollutant/outcome pairs based on these assessments and the evidence of a causal relationship between air pollutants and specific health outcomes. We conducted a comprehensive literature search using two databases and identified 75 relevant systematic reviews and meta-analyses for PM2.5 and NO2. We found no relevant reviews for long-term exposure to ozone. We evaluated the reliability of these studies using an adaptation of the AMSTAR 2 tool, which assesses various characteristics of the reviews, such as literature search, data extraction, statistical analysis, and bias evaluation. The tool's adaptation focused on issues relevant to studies on the health effects of air pollution. Based on our assessment, we selected reviews that could be credible sources of CRF for HRA. We also assessed the confidence in the findings of the selected systematic reviews and meta-analyses as the sources of CRF for HRA. We developed specific criteria for the evaluation, considering factors such as the number of included studies, their geographical distribution, heterogeneity of study results, the statistical significance and precision of the pooled risk estimate in the meta-analysis, and consistency with more recent studies. Based on our assessment, we classified the outcomes into three lists: list A (a reliable quantification of health effects is possible in an HRA), list B+ (HRA is possible, but there is greater uncertainty around the reliability of the CRF compared to those included on list A), and list B- (HRA is not recommended because of the substantial uncertainty of the CRF).

Results

In our final evaluation, list A includes six CRFs for PM2.5 (asthma in children, chronic obstructive pulmonary disease, ischemic heart disease events, stroke, hypertension, and lung cancer) and three outcomes for NO2 (asthma in children and in adults, and acute lower respiratory infections in children). Three additional outcomes (diabetes, dementia, and autism spectrum disorders) for PM2.5 were included in list B+. Recommended CRFs are related to the incidence (onset) of the diseases. The International Classification of Diseases, 10th revision codes, age ranges, and suggested concentration ranges are also specified to ensure consistency and applicability in an HRA. No specific suggestions were given for ozone because of the lack of relevant systematic reviews.

Conclusion

The suggestions formulated in this study, including CRFs selected from the available systematic reviews, can assist in conducting reliable HRAs and contribute to evidence-based decision-making in public health and environmental policy. Future research should continue to update and refine these suggestions as new evidence becomes available and methodologies evolve.

Effect of fine particulate matter exposure on gestational diabetes mellitus risk: a retrospective cohort study

BACKGROUND

The literature on the association between fine particulate matter (PM2.5) exposure and gestational diabetes mellitus (GDM) risk has focused mainly on exposure during the first and second trimesters, and the research results are inconsistent. Therefore, this study aimed to investigate the associations between PM2.5 exposure during preconception, the first trimester and second trimester and GDM risk in pregnant women in Guangzhou.

METHODS

A retrospective cohort study of 26 354 pregnant women was conducted, estimating PM2.5, particulate matter with a diameter >10 µm (PM10), sulphur dioxide (SO2), carbon monoxide (CO) and ozone (O3) exposure during preconception and the first and second trimesters. Analyses were performed using Cox proportional hazards models and nonlinear distributed lag models.

RESULTS

The study found that exposure to PM2.5 or a combination of two pollutants (PM2.5+PM10, PM2.5+SO2, PM2.5+CO and PM2.5+O3) was found to be significantly associated with GDM risk (P < 0.05). In the second trimester, with significant interactions found for occupation and anaemia between PM2.5 and GDM. When the PM2.5 concentrations were ≥19.56, ≥25.69 and ≥23.87 μg/m3 during preconception and the first and second trimesters, respectively, the hazard ratio for GDM started to increase. The critical window for PM2.5 exposure was identified to be from 9 to 11 weeks before conception.

CONCLUSIONS

Our study results suggest that PM2.5 exposure during preconception and the first and second trimesters increases the risk of GDM, with the preconception period appearing to be the critical window for PM2.5 exposure.

Diabetes mellitus-Progress and opportunities in the evolving epidemic

Diabetes, a complex multisystem metabolic disorder characterized by hyperglycemia, leads to complications that reduce quality of life and increase mortality. Diabetes pathophysiology includes dysfunction of beta cells, adipose tissue, skeletal muscle, and liver. Type 1 diabetes (T1D) results from immune-mediated beta cell destruction. The more prevalent type 2 diabetes (T2D) is a heterogeneous disorder characterized by varying degrees of beta cell dysfunction in concert with insulin resistance. The strong association between obesity and T2D involves pathways regulated by the central nervous system governing food intake and energy expenditure, integrating inputs from peripheral organs and the environment. The risk of developing diabetes or its complications represents interactions between genetic susceptibility and environmental factors, including the availability of nutritious food and other social determinants of health. This perspective reviews recent advances in understanding the pathophysiology and treatment of diabetes and its complications, which could alter the course of this prevalent disorder.

Associations of insulin sensitivity and immune inflammatory responses with child blood lead (Pb) and PM2.5 exposure at an e-waste recycling area during the COVID-19 lockdown

Fine particular matter (PM2.5) and lead (Pb) exposure can induce insulin resistance, elevating the likelihood of diabetes onset. Nonetheless, the underlying mechanism remains ambiguous. Consequently, we assessed the association of PM2.5 and Pb exposure with insulin resistance and inflammation biomarkers in children. A total of 235 children aged 3-7 years in a kindergarten in e-waste recycling areas were enrolled before and during the Corona Virus Disease 2019 (COVID-19) lockdown. Daily PM2.5 data was collected and used to calculate the individual PM2.5 daily exposure dose (DED-PM2.5). Concentrations of whole blood Pb, fasting blood glucose, serum insulin, and high mobility group box 1 (HMGB1) in serum were measured. Compared with that before COVID-19, the COVID-19 lockdown group had lower DED-PM2.5 and blood Pb, higher serum HMGB1, and lower blood glucose and homeostasis model assessment of insulin resistance (HOMA-IR) index. Decreased DED-PM2.5 and blood Pb levels were linked to decreased levels of fasting blood glucose and increased serum HMGB1 in all children. Increased serum HMGB1 levels were linked to reduced levels of blood glucose and HOMA-IR. Due to the implementation of COVID-19 prevention and control measures, e-waste dismantling activities and exposure levels of PM2.5 and Pb declined, which probably reduced the association of PM2.5 and Pb on insulin sensitivity and diabetes risk, but a high level of risk of chronic low-grade inflammation remained. Our findings add new evidence for the associations among PM2.5 and Pb exposure, systemic inflammation and insulin resistance, which could be a possible explanation for diabetes related to environmental exposure.

Insulin resistance and its relationship with long-term exposure to ozone: Data based on a national population cohort

The relationship of ozone (O3), particularly the long-term exposure, with impacting metabolic homeostasis in population was understudied and under-recognised. Here, we used data from ChinaHEART, a nationwide, population-based cohort study, combined with O3 and PM2.5 concentration data with high spatiotemporal resolution, to explore the independent association of exposure to O3 with the prevalence of insulin resistance (IR). Among the 271 540 participants included, the crude prevalence of IR was 39.1%, while the age and sex standardized prevalence stood at 33.0%. Higher IR prevalence was observed with each increase of 10.0 μg/m3 in long-term O3 exposure, yielding adjusted odds ratios (OR) of 1.084 (95% CI: 1.079-1.089) in the one-pollutant model and 1.073 (95% CI: 1.067-1.079) in the two-pollutant model. Notably, a significant additive interaction between O3 and PM2.5 on the prevalence of IR was observed (P for additive interaction < 0.001). Our main findings remained consistent and robust in the sensitivity analyses. Our study suggests long-term exposure to O3 was independently and positively associated with prevalence of IR. It emphasized the benefits of policy interventions to reduce O3 and PM2.5 exposure jointly, which could ultimately alleviate the health and economic burden related to DM.

Metabolite correlation permutation after mice acute exposure to PM2.5: Holistic exploration of toxicometabolomics by network analysis

Many environmental toxicants can cause systemic effects, such as fine particulate matter (PM2.5), which can penetrate the respiratory barrier and induce effects in multiple tissues. Although metabolomics has been used to identify biomarkers for PM2.5, its multi-tissue toxicology has not yet been explored holistically. Our objective is to explore PM2.5 induced metabolic alterations and unveil the intra-tissue responses along with inter-tissue communicational effects. In this study, following a single intratracheal instillation of multiple doses (0, 25, and 150 μg as the control, low, and high dose), non-targeted metabolomics was employed to evaluate the metabolic impact of PM2.5 across multiple tissues. PM2.5 induced tissue-specific and dose-dependent disturbances of metabolites and their pathways. The remarkable increase of both intra- and inter-tissue correlations was observed, with emphasis on the metabolism connectivity among lung, spleen, and heart; the tissues' functional specificity has marked their toxic modes. Beyond the inter-status comparison of the metabolite fold-changes, the current correlation network built on intra-status can offer additional insights into how the multiple tissues and their metabolites coordinately change in response to external stimuli such as PM2.5 exposure.

Association between PM2.5 constituents and cardiometabolic risk factors: Exploring individual and combined effects, and mediating inflammation

BACKGROUND

The individual and combined effects of PM2.5 constituents on cardiometabolic risk factors are sparsely investigated. Besides, the key cardiometabolic risk factor that PM2.5 constituents targeted and the biological mechanisms remain unclear.

METHOD

A multistage, stratified cluster sampling survey was conducted in two typically air-polluted Chinese cities. The PM2.5 and its constituents including sulfate, nitrate, ammonium, organic matter, and black carbon were predicted using a machine learning model. Twenty biomarkers in three category were simultaneously adopted as cardiometabolic risk factors. We explored the individual and mixture association of long-term PM2.5 constituents with these markers using generalized additive model and quantile-based g-computation, respectively. To minimize potential confounding effects, we accounted for covariates including demographic, lifestyle, meteorological, temporal trends, and disease-related information. We further used ROC curve and mediation analysis to identify the key subclinical indicators and explore whether inflammatory mediators mediate such association, respectively.

RESULT

PM2.5 constituents was positively correlated with HOMA-B, TC, TG, LDL-C and LCI, and negatively correlated with PP and RC. Further, PM2.5 constituent mixture was positive associated with DBP, MAP, HbA1c, HOMA-B, AC, CRI-1 and CRI-2, and negative associated with PP and HDL-C. The ROC analysis further reveals that multiple cardiometabolic risk factors can collectively discriminate exposure to PM2.5 constituents (AUC>0.9), among which PP and CRI-2 as individual indicators exhibit better identifiable performance for nitrate and ammonium (AUC>0.75). We also found that multiple blood lipid indicators may be affected by PM2.5 and its constituents, possibly mediated through complement C3 or hsCRP.

CONCLUSION

Our study suggested associations of individual and combined PM2.5 constituents exposure with cardiometabolic risk factors. PP and CRI-2 were the targeted markers of long-term exposure to nitrate and ammonium. Inflammation may serve as a mediating factor between PM2.5 constituents and dyslipidemia, which enhance current understanding of potential pathways for PM2.5-induced preclinical cardiovascular responses.

Association between Personal Abiotic Airborne Exposures and Body Composition Changes among Healthy Adults (60-69 Years Old): A Combined Exposome-Wide and Lipidome Mediation Approach from the China BAPE Study

BACKGROUND

Evidence suggested that abiotic airborne exposures may be associated with changes in body composition. However, more evidence is needed to identify key pollutants linked to adverse health effects and their underlying biomolecular mechanisms, particularly in sensitive older adults.

OBJECTIVES

Our research aimed to systematically assess the relationship between abiotic airborne exposures and changes in body composition among healthy older adults, as well as the potential mediating mechanisms through the serum lipidome.

METHODS

From September 2018 to January 2019, we conducted a monthly survey among 76 healthy adults (60-69 years old) in the China Biomarkers of Air Pollutant Exposure (BAPE) study, measuring their personal exposures to 632 abiotic airborne pollutions using MicroPEM and the Fresh Air wristband, 18 body composition indicators from the InBody 770 device, and lipidomics from venous blood samples. We used an exposome-wide association study (ExWAS) and deletion/substitution/addition (DSA) model to unravel complex associations between exposure to contaminant mixtures and body composition, a Bayesian kernel machine regression (BKMR) model to assess the overall effect of key exposures on body composition, and mediation analysis to identify lipid intermediators.

RESULTS

The ExWAS and DSA model identified that 2,4,5-T methyl ester (2,4,5-TME), 9,10-Anthracenedione (ATQ), 4b,8-dimethyl-2-isopropylphenanthrene, and 4b,5,6,7,8,8a,9,10-octahydro-(DMIP) were associated with increased body fat mass (BFM), fat mass indicators (FMI), percent body fat (PBF), and visceral fat area (VFA) in healthy older adults [Bonferroni-Hochberg false discovery rate ( FD R BH ) < 0.05 ]. The BKMR model demonstrated a positive correlation between contaminants (anthracene, ATQ, copaene, di-epi-α -cedrene, and DMIP) with VFA. Mediation analysis revealed that phosphatidylcholine [PC, PC(16:1e/18:1), PC(16:2e/18:0)] and sphingolipid [SM, SM(d18:2/24:1)] mediated a significant portion, ranging from 12.27% to 26.03% (p-value < 0.05 ), of the observed increase in VFA.

DISCUSSION

Based on the evidence from multiple model results, ATQ and DMIP were statistically significantly associated with the increased VFA levels of healthy older adults, potentially regulated through lipid intermediators. These findings may have important implications for identifying potentially harmful environmental chemicals and developing targeted strategies for the control and prevention of chronic diseases in the future, particularly as the global population is rapidly aging. https://doi.org/10.1289/EHP13865.

Fine particulate matter exposure and systemic inflammation: A potential mediating role of bioactive lipids

Inflammation is a key mechanism underlying the adverse health effects of exposure to fine particulate matter (PM2.5). Bioactive lipids in the arachidonic acid (ARA) pathway are important in the regulation of inflammation and are reportedly altered by PM2.5 exposure. Ceramide-1-phosphate (C1P), a class of sphingolipids, is required to initiate ARA metabolism. We examined the role of C1P in the alteration of ARA metabolism after PM2.5 exposure and explored whether changes in the ARA pathway promoted systemic inflammation based on a panel study involving 112 older adults in Beijing, China. Ambient PM2.5 levels were continuously monitored at a fixed station from 2013 to 2015. Serum cytokine levels were measured to assess systemic inflammation. Multiple bioactive lipids in the ARA pathway and three subtypes of C1P were quantified in blood samples. Mediation analyses were performed to test the hypotheses. We observed that PM2.5 exposure was positively associated with inflammatory cytokines and the three subtypes of C1P. Mediation analyses showed that C1P significantly mediated the associations of ARA and 5, 6-dihydroxyeicosatrienoic acid (5, 6-DHET), an ARA metabolite, with PM2.5 exposure. ARA, 5, 6-DHET, and leukotriene B4 mediated systemic inflammatory response to PM2.5 exposure. For example, C1P C16:0 (a subtype of C1P) mediated a 12.9 % (95 % confidence interval: 3.7 %, 32.5 %) increase in ARA associated with 3-day moving average PM2.5 exposure, and ARA mediated a 27.1 % (7.8 %, 61.2 %) change in interleukin-8 associated with 7-day moving average PM2.5 exposure. Our study indicates that bioactive lipids in the ARA and sphingolipid metabolic pathways may mediate systemic inflammation after PM2.5 exposure.

Chronic PM2.5 exposure disrupts intestinal barrier integrity via microbial dysbiosis-triggered TLR2/5-MyD88-NLRP3 inflammasome activation

BACKGROUND

PM2.5, a known public health risk, is increasingly linked to intestinal disorders, however, the mechanisms of its impact are not fully understood.

PURPOSE

This study aimed to explore the impact of chronic PM2.5 exposure on intestinal barrier integrity and to uncover the underlying molecular mechanisms.

METHODS

C57BL/6 J mice were exposed to either concentrated ambient PM2.5 (CPM) or filtered air (FA) for six months to simulate urban pollution conditions. We evaluated intestinal barrier damage, microbial shifts, and metabolic changes through histopathology, metagenomics, and metabolomics. Analysis of the TLR signaling pathway was also conducted.

RESULTS

The mean concentration of PM2.5 in the CPM exposure chamber was consistently measured at 70.9 ± 26.8 μg/m³ throughout the study period. Our findings show that chronic CPM exposure significantly compromises intestinal barrier integrity, as indicated by reduced expression of the key tight junction proteins Occludin and Tjp1/Zo-1. Metagenomic sequencing revealed significant shifts in the microbial landscape, identifying 35 differentially abundant species. Notably, there was an increase in pro-inflammatory nongastric Helicobacter species and a decrease in beneficial bacteria, such as Lactobacillus intestinalis, Lactobacillus sp. ASF360, and Eubacterium rectale. Metabolomic analysis further identified 26 significantly altered metabolites commonly associated with intestinal diseases. A strong correlation between altered bacterial species and metabolites was also observed. For example, 4 Helicobacter species all showed positive correlations with 13 metabolites, including Lactate, Bile acids, Pyruvate and Glutamate. Additionally, increased expression levels of TLR2, TLR5, Myd88, and NLRP3 proteins were noted, and their expression patterns showed a strong correlation, suggesting a possible involvement of the TLR2/5-MyD88-NLRP3 signaling pathway.

CONCLUSIONS

Chronic CPM exposure induces intestinal barrier dysfunction, microbial dysbiosis, metabolic imbalance, and activation of the TLR2/5-MyD88-NLRP3 inflammasome. These findings highlight the urgent need for intervention strategies to mitigate the detrimental effects of air pollution on intestinal health and identify potential therapeutic targets.

Gut microbiota in insulin resistance: a bibliometric analysis

Background

Insulin resistance (IR) is considered the pathogenic driver of diabetes, and can lead to obesity, hypertension, coronary artery disease, metabolic syndrome, and other metabolic disorders. Accumulating evidence indicates that the connection between gut microbiota and IR. This bibliometric analysis aimed to summarize the knowledge structure of gut microbiota in IR.

Methods

Articles and reviews related to gut microbiota in IR from 2013 to 2022 were retrieved from the Web of Science Core Collection (WoSCC), and the bibliometric analysis and visualization were performed by Microsoft Excel, Origin, R package (bibliometrix), Citespace, and VOSviewer.

Results

A total of 4 749 publications from WoSCC were retrieved, including 3 050 articles and 1 699 reviews. The majority of publications were from China and USA. The University Copenhagen and Shanghai Jiao Tong University were the most active institutions. The journal of Nutrients published the most papers, while Nature was the top 1 co-cited journal, and the major area of these publications was molecular, biology, and immunology. Nieuwdorp M published the highest number of papers, and Cani PD had the highest co-citations. Keyword analysis showed that the most frequently occurring keywords were "gut microbiota", "insulin-resistance", "obesity", and "inflammation". Trend topics and thematic maps showed that serum metabolome and natural products, such as resveratrol, flavonoids were the research hotspots in this field.

Conclusion

This bibliometric analysis summarised the hotspots, frontiers, pathogenesis, and treatment strategies, providing a clear and comprehensive profile of gut microbiota in IR.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01342-x.

Serum metabolome perturbation in relation to noise exposure: Exploring the potential role of serum metabolites in noise-induced arterial stiffness

Noise pollution has grown to be a major public health issue worldwide. We sought to profile serum metabolite expression changes related to occupational noise exposure by untargeted metabolomics, as well as to evaluate the potential roles of serum metabolites in occupational noise-associated arterial stiffness (AS). Our study involved 30 noise-exposed industrial personnel (Lipo group) and 30 noise-free controls (Blank group). The untargeted metabolomic analysis was performed by employing a UPLC-HRMS. The associations of occupational noise and significant differential metabolites (between Blank/Lipo groups) with AS were evaluated using multivariable-adjusted generalized linear models. We performed the least absolute shrinkage and selection operator regression analysis to further screen for AS's risk metabolites. We explored 177 metabolites across 21 categories significantly differentially expressed between Blank/Lipo groups, and these metabolites were enriched in 20 metabolic pathways. Moreover, 15 metabolites in 4 classes (including food, glycerophosphocholine, sphingomyelin [SM] and triacylglycerols [TAG]) were adversely associated with AS (all P < 0.05). Meanwhile, five metabolites (homostachydrine, phosphatidylcholine (PC) (32:1e), PC (38:6p), SM (d41:2) and TAG (45:1) have been proven to be useful predictors of AS prevalence. However, none of these 15 metabolites were found to have a mediating influence on occupational noise-induced AS. Our study reveals specific metabolic changes caused by occupational noise exposure, and several metabolites may have protective effects on AS. However, the roles of serum metabolites in noise-AS association remain to be validated in future studies.

Relationship of long-term exposure to air pollutant mixture with metabolic-associated fatty liver disease and subtypes: A retrospective cohort study of the employed population of Southwest China

BACKGROUND

While evidence suggests that PM2.5 is associated with overall prevalence of Metabolic (dysfunction)-Associated Fatty Liver Disease (MAFLD), effects of comprehensive air pollutant mixture on MAFLD and its subtypes remain unclear.

OBJECTIVE

To investigate individual and joint effects of long-term exposure to comprehensive air pollutant mixture on MAFLD and its subtypes.

METHODS

Data of 27,699 participants of the Chinese Cohort of Working Adults were analyzed. MAFLD and subtypes, including overweight/obesity, lean, and diabetes MAFLD, were diagnosed according to clinical guidelines. Concentrations of NO3-, SO42-, NH4+, organic matter (OM), black carbon (BC), PM2.5, SO2, NO2, O3 and CO were estimated as a weighted average over participants' residential and work addresses for the three years preceding outcome assessment. Logistic regression and weighted quantile sum regression were used to estimate individual and joint effects of air pollutant mixture on presence of MAFLD.

RESULTS

Overall prevalence of MAFLD was 26.6 % with overweight/obesity, lean, and diabetes MAFLD accounting for 92.0 %, 6.4 %, and 1.6 %, respectively. Exposure to SO42-, NO3-, NH4+, BC, PM2.5, NO2, O3and CO was significantly associated with overall MAFLD, overweight/obesity MAFLD, or lean MAFLD in single pollutant models. Joint effects of air pollutant mixture were observed for overall MAFLD (OR = 1.10 [95 % CI: 1.03, 1.17]), overweight/obesity (1.09 [1.02, 1.15]), and lean MAFLD (1.63 [1.28, 2.07]). Contributions of individual air pollutants to joint effects were dominated by CO in overall and overweight/obesity MAFLD (Weights were 42.31 % and 45.87 %, respectively), while SO42- (36.34 %), SO2 (21.00 %) and BC (12.38 %) were more important in lean MAFLD. Being male, aged above 45 years and smoking increased joint effects of air pollutant mixture on overall MAFLD.

CONCLUSIONS

Air pollutant mixture was associated with MAFLD, particularly the lean MAFLD subtype. CO played a pivotal role in both overall and overweight/obesity MAFLD, whereas SO42- were associated with lean MAFLD.

Identification of Circulating Plasma Proteins as a Mediator of Hypertension-Driven Cardiac Remodeling: A Mediation Mendelian Randomization Study

BACKGROUND

This study focused on circulating plasma protein profiles to identify mediators of hypertension-driven myocardial remodeling and heart failure.

METHODS

A Mendelian randomization design was used to investigate the causal impact of systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure on 82 cardiac magnetic resonance traits and heart failure risk. Mediation analyses were also conducted to identify potential plasma proteins mediating these effects.

RESULTS

Genetically proxied higher SBP, DBP, and pulse pressure were causally associated with increased left ventricular myocardial mass and alterations in global myocardial wall thickness at end diastole. Elevated SBP and DBP were linked to increased regional myocardial radial strain of the left ventricle (basal anterior, mid, and apical walls), while higher SBP was associated with reduced circumferential strain in specific left ventricular segments (apical, mid-anteroseptal, mid-inferoseptal, and mid-inferolateral walls). Specific plasma proteins mediated the impact of blood pressure on cardiac remodeling, with FGF5 (fibroblast growth factor 5) contributing 2.96% (P=0.024) and 4.15% (P=0.046) to the total effect of SBP and DBP on myocardial wall thickness at end diastole in the apical anterior segment and leptin explaining 15.21% (P=0.042) and 23.24% (P=0.022) of the total effect of SBP and DBP on radial strain in the mid-anteroseptal segment. Additionally, FGF5 was the only mediator, explaining 4.19% (P=0.013) and 4.54% (P=0.032) of the total effect of SBP and DBP on heart failure susceptibility.

CONCLUSIONS

This mediation Mendelian randomization study provides evidence supporting specific circulating plasma proteins as mediators of hypertension-driven cardiac remodeling and heart failure.

Short-term exposures to PM2.5, PM2.5 chemical components, and antenatal depression: Exploring the mediating roles of gut microbiota and fecal short-chain fatty acids

BACKGROUND

PM2.5 and its chemical components increase health risks and are associated with depression and gut microbiota. However, there is still limited evidence on whether gut microbiota and short-chain fatty acids (SCFAs) mediate the association between PM2.5, PM2.5 chemical components, and antenatal depression. The purpose of this study was to investigate the mediating role of maternal gut microbiota in correlations between short-term exposure to PM2.5, short-term exposure to PM2.5 chemical components, and antenatal depression.

METHODS

Demographic information and stool samples were collected from 75 pregnant women in their third trimester. Their exposure to PM2.5 and PM2.5 chemical components was measured. Participants were divided into the non-antenatal depression group or the antenatal depression group according to the cut-off of 10 points on the Edinburgh Postnatal Depression Scale (EPDS). The gut microbiota were analyzed using the 16 S rRNA-V3/V4 gene sequence, and the concentration of PM2.5 and its chemical components was calculated using the Tracking Air Pollution in China (TAP) database. Gas chromatography-mass spectrometry was used to analyze SCFAs in stool samples. In order to assess the mediating effects of gut microbiota and SCFAs, mediation models were utilized.

RESULTS

There were significant differences between gut microbial composition and SCFAs concentrations between the non-antenatal depression group and the antenatal depression group. PM2.5 and its chemical components were positively associated with EPDS scores and negatively associated with genera Enterococcus and Enterobacter. Genera Candidatus_Soleaferrea (β = -7.21, 95%CI -11.00 to -3.43, q = 0.01) and Enterococcus (β = -2.37, 95%CI -3.87 to -0.87, q = 0.02) were negatively associated with EPDS scores, indicating their potential protective effects against antenatal depression. There was no significant association between SCFAs and EPDS scores. The mediating role of Enterococcus between different lagged periods of PM2.5, PM2.5 chemical component exposure, and antenatal depression was revealed. For instance, Enterococcus explained 29.23% (95%CI 2.16-87.13%, p = 0.04) of associations between PM2.5 exposure level at the day of sampling (lag 0) and EPDS scores.

CONCLUSION

Our study highlights that Enterococcus may mediate the associations between PM2.5, PM2.5 chemical components, and antenatal depression. The mediating mechanism through which the gut microbiota influences PM2.5-induced depression in pregnant women still needs to be further studied.

Mapping multi-omics characteristics related to short-term PM2.5 trajectory and their impact on type 2 diabetes in middle-aged and elderly adults in Southern China

The relationship between PM2.5 and metabolic diseases, including type 2 diabetes (T2D), has become increasingly prominent, but the molecular mechanism needs to be further clarified. To help understand the mechanistic association between PM2.5 exposure and human health, we investigated short-term PM2.5 exposure trajectory-related multi-omics characteristics from stool metagenome and metabolome and serum proteome and metabolome in a cohort of 3267 participants (age: 64.4 ± 5.8 years) living in Southern China. And then integrate these features to examine their relationship with T2D. We observed significant differences in overall structure in each omics and 193 individual biomarkers between the high- and low-PM2.5 groups. PM2.5-related features included the disturbance of microbes (carbohydrate metabolism-associated Bacteroides thetaiotaomicron), gut metabolites of amino acids and carbohydrates, serum biomarkers related to lipid metabolism and reducing n-3 fatty acids. The patterns of overall network relationships among the biomarkers differed between T2D and normal participants. The subnetwork membership centered on the hub nodes (fecal rhamnose and glycylproline, serum hippuric acid, and protein TB182) related to high-PM2.5, which well predicted higher T2D prevalence and incidence and a higher level of fasting blood glucose, HbA1C, insulin, and HOMA-IR. Our findings underline crucial PM2.5-related multi-omics biomarkers linking PM2.5 exposure and T2D in humans.

Ambient particulate matter and renal function decline in people with HIV/AIDS

OBJECTIVE

We aimed to explore the effect of particulate matter exposure on renal function in people with HIV/AIDS (PWHA).

METHODS

A total of 37 739 repeated measurements were conducted on eGFR levels, serum creatinine (Scr), and the triglyceride-glucose (TyG) index in 6958 PWHAs. The relationship between 1 and 28 day moving averages of particulate matter concentrations with Scr and eGFR was assessed using linear mixed-effects models. Modified Poisson regression models were employed to assess the associations of cumulative particulate matter exposure with the incidence of chronic kidney disease (CKD). Mediation analyses were used to examine the role of TyG index.

RESULTS

Short-term exposure to particulate matter was related to reduced renal function. The strongest associations between exposure to particulate matter (PM) 1 , PM 2.5 , and PM 10 and percentage changes in eGFR were observed at 7-day moving average exposure windows, with a respective decrease of 0.697% (-1.008%, -0.386%), 0.429% (-0.637%, -0.220%), and 0.373% (-0.581%, -0.164%) per IQR increment. Long-term exposure to PM 1 , PM 2.5 , and PM 10 was positively linked with the incidence of CKD, with each IQR increment corresponding to fully adjusted RRs (95% CIs) of 1.631 (1.446-1.839), 1.599 (1.431-1.787), and 1.903 (1.665-2.175), respectively. TyG index-mediated 8.87, 8.88, and 7.58% of the relationship between cumulative exposure to PM 1 , PM 2.5 , and PM 10 and increased risk of CKD, respectively.

CONCLUSION

Exposure to particulate matter among PWHAs is linked to reduced renal function, potentially contributing to increased CKD incidence, where the TyG index might serve as a partial mediator.

Effects of inhaled fine particulate matter on the lung injury as well as gut microbiota in broilers

Fine particulate matter (PM2.5) has been widely regarded as an important environmental risk factor that has widely influenced health of both animals and humans. Lung injury is the main cause of PM2.5 affecting respiratory tract health. Gut microbiota participates in the development of lung injury in many pathological processes. However, there is still unknown the specific effects of PM2.5 on the gut-lung axis in broilers. Thus, we conducted a broiler model based on 3-wk-old male Arbor Acres broiler to explore the underlying mechanism. Our results showed that PM2.5 exposure triggered TLR4 signaling pathway and induced the increase of IL-6, IFN-γ, TNF-α expression as well as the decrease of IL-10 expression in the lung. Inhaled PM2.5 exposure significantly altered the gut microbiota diversity and community. Specifically, PM2.5 exposure decreased α diversity and altered β diversity of gut microbiota, and reduced the abundance of DTU089, Oscillospirales, Staphylococcus, and increased the Escherichia-Shigella abundance, leading to the increase of gut-derived lipopolysaccharides (LPS). Moreover, PM2.5 significantly disrupted the intestinal epithelial barrier by reducing the expression of muc2 and claudin-1 to increase intestinal permeability, which possibly facilitated the LPS translocation into the blood. Spearman analysis revealed that gut microbiota dysbiosis was positively related to TLR4, TNF-α, and IFN-γ expression in the lung. In summary, our results showed that PM2.5 exposure induced lung injury by causing inflammation and triggering TLR4 signaling pathway, and also induced gut microbiota dysbiosis resulting in the overproduction of gut-derived LPS. And gut microbiota dysbiosis may be associated with lung injury. The above results provide basis data to comprehend the potential role of gut microbiota dysbiosis in the lung injury as well as providing a new regulatory target for alleviating lung injury associated with environmental pollutants.

Dietary intake changes the associations between long-term exposure to fine particulate matter and the surrogate indicators of insulin resistance

The relationship of fine particulate matter (PM2.5) exposure and insulin resistance remains inclusive. Our study aimed to investigate this association in the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR). Specifically, we examined the associations between long-term PM2.5 exposure and three surrogate indicators of insulin resistance: the triglyceride-glucose index (TyG), TyG with waist circumference (TyG-WC) and metabolic score for insulin resistance (METS-IR). Additionally, we explored potential effect modification of dietary intake and components. Generalized estimating equations were used to evaluate the associations between PM2.5 and the indicators with an unbalanced repeated measurement design. Our analysis incorporated a total of 162,060 observations from 99,329 participants. Each 10 μg/m3 increment of PM2.5 was associated with an increase of 0.22 % [95 % confidence interval (CI): 0.20 %, 0.25 %], 1.60 % (95 % CI: 1.53 %, 1.67 %), and 2.05 % (95 % CI: 1.96 %, 2.14 %) in TyG, TyG-WC, and METS-IR, respectively. These associations were attenuated among participants with a healthy diet, particularly those with sufficient intake of fruit and vegetable, fish or tea (pinteraction < 0.0028). For instance, among participants with a healthy diet, TyG increased by 0.11 % (95 % CI: 0.08 %, 0.15 %) per 10 μg/m3 PM2.5 increment, significantly lower than the association observed in those with an unhealthy diet. The findings of this study emphasize the potential of a healthy diet to mitigate these associations, highlighting the urgency for improving air quality and implementing dietary interventions among susceptible populations in China.

The association between long-term exposure to ambient PM2.5 and high-density lipoprotein cholesterol level among chinese middle-aged and older adults

BACKGROUND

Recently, the impact of PM2.5 on human health has been intensively studied, especially the respiratory system. High-density lipoprotein plays a crucial role in removing excess cholesterol from cells and transporting it to the liver for excretion. However, the effects of ambient PM2.5 on high-density lipoprotein (HDL) level have not been further studied. Our research aims to investigate the potential association between ambient PM2.5 concentrations and high-density lipoprotein (HDL) levels within the middle-aged and older adults in China.

METHODS

We employed data from individuals aged 45 years and above who were participants in Wave 3 of the China Health and Retirement Longitudinal Study (CHARLS). The high-quality, high-resolution PM2.5 exposure concentration data for each participant were obtained from the ChinaHighAirPollutants (CHAP) dataset, while the HDL levels were derived from blood samples collected during CHARLS Wave 3. This analysis constitutes a cross-sectional study involving a total of 12,519 participants. To investigate associations, we conducted multivariate linear regression analysis, supplemented by subgroup analysis.

RESULTS

In this cross-sectional investigation, we discerned a negative association between prolonged exposure to ambient PM2.5 constituents and high-density lipoprotein (HDL) levels. The observed correlation between ambient PM2.5 and HDL levels suggests that older individuals residing in areas with elevated PM2.5 concentrations exhibit a reduction in HDL levels (Beta: -0.045; 95% CI: -0.056, -0.035; P < 0.001). Upon adjusting for age in Model I, the Beta coefficient remained consistent at -0.046 (95% CI: -0.056, -0.035; p < 0.001). This association persisted even after accounting for various potential confounding factors (Beta = -0.031, 95% CI: -0.041, -0.021, p < 0.001).

CONCLUSIONS

Our study reveals a statistically significant negative correlation between sustained exposure to higher concentrations of ambient PM2.5 and high-density lipoprotein (HDL) levels among Chinese middle-aged and older individuals.

Altered metabolome and microbiome associated with compromised intestinal barrier induced hepatic lipid metabolic disorder in mice after subacute and subchronic ozone exposure

Exposure to ozone has been associated with metabolic disorders in humans, but the underlying mechanism remains unclear. In this study, the role of the gut-liver axis and the potential mechanism behind the metabolic disorder were investigated by histological examination, microbiome and metabolome approaches in mice during the subacute (4-week) and subchronic (12-week) exposure to 0.5 ppm and 2.5 ppm ozone. Ozone exposure resulted in slowed weight gain and reduced hepatic lipid contents in a dose-dependent manner. After exposure to ozone, the number of intestinal goblet cells decreased, while the number of tuft cells increased. Tight junction protein zonula occludens-1 (ZO-1) was significantly downregulated, and the apoptosis of epithelial cells increased with compensatory proliferation, indicating a compromised chemical and physical layer of the intestinal barrier. The hepatic and cecal metabolic profiles were altered, primarily related to lipid metabolism and oxidative stress. The abundance of Muribaculaceae increased dose-dependently in both colon and cecum, and was associated with the decrease of metabolites such as bile acids, betaine, and L-carnitine, which subsequently disrupted the intestinal barrier and lipid metabolism. Overall, this study found that subacute and subchronic exposure to ozone induced metabolic disorder via disturbing the gut-liver axis, especially the intestinal barrier. These findings provide new mechanistic understanding of the health risks associated with environmental ozone exposure and other oxidative stressors.

Urinary metabolite biomarkers of pregnancy complications associated with maternal exposure to particulate matter

Particulate matter 2.5 (PM2.5) is associated with reproductive health and adverse pregnancy outcomes. However, studies evaluating biological markers of PM2.5 are lacking, and identifying biomarkers for estimating prenatal exposure to prevent pregnancy complications is essential. Therefore, we aimed to explore urine metabolites that are easy to measure as biomarkers of exposure. In this matched case-control study based on the PM2.5 exposure, 30 high PM2.5 group (>15 μg/m3) and 30 low PM2.5 group (<15 μg/m3) were selected from air pollution on pregnancy outcome (APPO) cohort study. We used a time-weighted average model to estimate individual PM exposure, which used indoor PM2.5 and outdoor PM2.5 concentrations by atmospheric measurement network based on residential addresses. Clinical characteristics and urine samples were collected from participants during the second trimester of pregnancy. Urine metabolites were quantitatively measured using gas chromatography-mass spectrometry following multistep chemical derivatization. Statistical analyses were conducted using SPSS version 21 and MetaboAnalyst 5.0. Small for gestational age and gestational diabetes (GDM) were significantly increased in the high PM2.5 group, respectively (P = 0.042, and 0.022). Fifteen metabolites showed significant differences between the two groups (P < 0.05). Subsequent pathway enrichment revealed that four pathways, including pentose and glucuronate interconversion with three pentose sugars (ribose, arabinose, and xylose; P < 0.05). The concentration of ribose increased preterm births (PTB) and GDM (P = 0.044 and 0.049, respectively), and the arabinose concentration showed a tendency to increase in PTB (P = 0.044). Therefore, we identified urinary pentose metabolites as biomarkers of PM2.5 and confirmed the possibility of their relationship with pregnancy complications.

Causal effect of air pollution on the risk of cardiovascular and metabolic diseases and potential mediation by gut microbiota

BACKGROUND

Epidemiological studies have explored the relationship between air pollution and cardiovascular and metabolic diseases (CVMDs). Accumulating evidence has indicated that gut microbiota deeply affects the risk of CVMDs. However, the findings are controversial and the causality remains uncertain. To evaluate whether there is the causal association of four air pollutants with 19 CVMDs and the potential effect of gut microbiota on these relationships.

METHODS

Genetic instruments for particulate matter (PM) with aerodynamic diameter < 2.5 μm (PM2.5), <10 μm (PM10), PM2.5 absorbance, nitrogen oxides (NOx) and 211 gut microbiomes were screened. Univariable Mendelian randomization (UVMR) was used to estimate the causal effect of air pollutants on CVMDs in multiple MR methods. Additionally, to account for the phenotypic correlation among pollutant, the adjusted model was constructed using multivariable Mendelian randomization (MVMR) analysis to strength the reliability of the predicted associations. Finally, gut microbiome was assessed for the mediated effect on the associations of identified pollutants with CVMDs.

RESULTS

Causal relationships between NOx and angina, heart failure and hypercholesterolemia were observed in UVMR. After adjustment for air pollutants in MVMR models, the genetic correlations between PM2.5 and hypertension, type 2 diabetes mellitus (T2DM) and obesity remained significant and robust. In addition, genus-ruminococcaceae-UCG003 mediated 7.8 % of PM2.5-effect on T2DM.

CONCLUSIONS

This study firstly provided the genetic evidence linking air pollution to CVMDs and gut microbiota may mediate the association of PM2.5 with T2DM. Our findings highlight the significance of air quality in CVMDs risks and suggest the potential of modulating intestinal microbiota as novel therapeutic targets between air pollution and CVMDs.

Association of residential greenness, air pollution with adverse birth outcomes: Results from 61,762 mother‑neonatal pairs in project ELEFANT (2011-2021)

BACKGROUND

Emerging evidence has demonstrated the benefits of greenness exposure on human health, while conflicts remain unsolved in issue of adverse birth outcomes.

METHODS

Utilizing data from project ELEFANT spanning the years 2011 to 2021, we assessed residential greenness using the NDVI from MODIS data and residential PM2.5 exposure level from CHAP data. Our primary concerns were PTD, LBW, LGA, and SGA. Cox proportional hazard regression model was used to examine the association of residential greenness and air pollution exposure with risk of adverse birth outcomes. We performed mediation and modification effect analyses between greenness and air pollutant.

RESULTS

We identified 61,762 mother‑neonatal pairs in final analysis. For per 10 μg/m3 increase in PM2.5 concentration during entire pregnancy was associated with 19.8 % and 20.7 % increased risk of PTD and LGA. In contrast, we identified that an 0.1 unit increment in NDVI were associated with 24 %, 43 %, 26.5 %, and 39.5 % lower risk for PTD, LBW, LGA, and SGA, respectively. According to mediation analysis, NDVI mediated 7.70 % and 7.89 % of the associations between PM2.5 and PTD and LGA. Residential greenness could reduce the risk of PTD among mothers under 35 years old, living in rural areas, primigravidae and primiparity..

CONCLUSIONS

In summary, our results highlighted the potential of residential greenness to mitigate the risk of adverse birth outcomes, while also pointing to the adverse impact of PM2.5 on increased risk of multiple adverse birth outcomes (PTD and LGA). The significant mediation effect of NDVI emphasizes its potential as an important protective factor of PM2.5 exposure. Additionally, the identification of susceptible subgroups can inform targeted interventions to reduce adverse birth outcomes related to air pollution and lack of green spaces. Further research and understanding of these associations can contribute to better public health strategies aimed at promoting healthier pregnancies and birth outcomes.

Associations of low levels of air pollution with cardiometabolic outcomes and the role of diet quality in individuals with obesity

BACKGROUND

Exposure to air pollution is associated with adverse cardiometabolic health effects and increased mortality, even at low concentrations. Some of the biological mechanisms through which air pollution can affect cardiometabolic health overlap with health outcomes associated with diet quality and changes in diet.

OBJECTIVE

The objective of this study is to investigate associations of air pollutants at average concentrations below the World Health Organization, 2021 air quality guidelines with cardiometabolic outcomes. Furthermore, potential interaction between air pollutants and diet quality will be assessed.

METHODS

82 individuals with obesity participated in a combined weight loss and weight loss maintenance study for a total of 33 weeks. A secondary analysis was conducted incorporating air pollution measurements. Data were analysed with linear mixed-effects models.

RESULTS

A total of 17 significant associations were observed for single pollutants with 10 cardiometabolic outcomes, predominantly related to blood lipids, hormones, and glucose regulation. Diet quality, as measured by the Baltic Sea Diet score, did not appear to mediate the association of air pollution with cardiometabolic outcomes, however, diet quality was observed to significantly modify the association of PM2.5 with total cholesterol, and the associations of NO and O3 with ghrelin.

DISCUSSION

These findings suggest that exposure to ambient air pollutants, especially particulate matter, at levels below World Health Organization, 2021 air quality guidelines, were associated with changes in cardiometabolic risk factors. Diet may be a personal-level approach for individuals to modify the impact of exposure to air pollution on cardiometabolic health.

[Advances in the applications of exposomics in the identification of environmental pollutants and their health hazards]

Environmental pollution has become a prominent global problem, and the potential health hazards of pollutants have caused widespread concern. However, revealing the relationship between complex-pollutant exposure and disease development remains an immense challenge. The core of environmental-health research and risk assessment is the identification of contaminants and their effects. Exposomics provides a new approach in the study of the relationship between environmental factors and human health. Both "top-down" and "bottom-up" strategies are employed in exposomics research. The development of new technologies for chemical detection and "multi-omics" has greatly facilitated the implementation of these strategies. Exposomics focuses on the measurement of an individual's lifelong exposure and aims to identify the health effects of such exposure. It involves the dynamic monitoring of external and internal exposure levels at different stages of life through traditional biomonitoring and exposomic methods. It also includes the identification of biomarkers, which indicate specific environmental exposures and the adverse effects of these exposures on health. Compared with traditional environmental-health studies, exposomics can more accurately reflect the diversity of exposure factors such as pollutants, natural factors, and lifestyles in the real environment, as well as the complexity of their in vivo processes and the responses they trigger in an organism. Powerful chemical analytical tools such as high-resolution mass spectrometry (HRMS) are widely used in studies related to the field of exposomics. Liquid chromatography-mass spectrometry (LC-MS) has been applied in the detection and analysis of environmental pollutants. Proteomics and metabolomics, as two important tools for biomarker identification and effects analysis, are widely used to explore the relationship between environmental factors and diseases. Pollutants can lead to pathological changes and even toxic effects by interacting with proteins. In the case of mixed exposure, some contaminants may present joint toxicity. The interaction between contaminants may change their environmental behavior or the amount of each contaminant that enters the human body, which, in turn, affects their health effects.

Long-term exposure to ambient air pollution with sarcopenia among middle-aged and older adults in China

BACKGROUND

Few studies have examined the role of outdoor air pollution exposure in sarcopenia in Asia. We aimed to investigate the association of outdoor air pollutants exposure with sarcopenia among Chinese adults.

METHODS

This nationally population-representative study used data from the China Health and Retirement Longitudinal Study (CHARLS) in 2015, 11,700 participants at least 45 years old from 125 Chinese cities were included. Sarcopenia status was identified according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria. Ambient annual average air pollutants including fine particulate matter (PM2.5), inhalable particles (PM10), coarse particulate matter (PMcoarse), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) were estimated by satellite models and ground-based measurements. Multinomial logistic regression models were performed to examine the associations of air pollutants exposure with different status of sarcopenia (including possible sarcopenia and sarcopenia). Stratified analyses were utilized to assess the effect modifiers.

RESULTS

Among the 11,700 participants (52.6% women), the average age was 61.0 years. Each 10 μg/m3 increment of annual PMcoarse was associated with a higher risk of possible sarcopenia (odds ratio (OR) = 1.08, 95% confidence interval (CI) 1.04-1.11). Stratified analyses showed a positive risk of possible sarcopenia in women after exposure to PM10, PMcoarse, and NO2. Ambient NO2 exposure was positively associated with sarcopenia (OR = 1.13, 95% CI 1.04-1.22) in those aged 65 years and older. However, we have not observed differences by sex, age, residence, smoking, and drinking. Robustness results were found for PMcoarse in the sensitivity analyses.

CONCLUSION

This nationwide study suggested that long-term exposure to outdoor air pollution, especially for PMcoarse, was associated with the risk of sarcopenia among Chinese adults. Our findings provide epidemiological implications for protecting healthy ageing by improving air quality.

Serum metabolome responses induced by long-term inoculation of suspended PM2.5 in chicken

The adverse effects of exposure to fine particulate matter (PM2.5) on body health have attracted global public attention. However, there is limited research on PM2.5 in animal houses. Numerous studies have indicated that long-term exposure to high levels of PM2.5 can cause damage to multiple systems in animals. Poultry houses are one of the primary sources of PM2.5 emissions. However, there is limited research on the effects of PM2.5 exposure on poultry organisms. This study analyzed the histopathological changes in the lung tissue of poultry under PM2.5 exposure conditions. It used the LC-MS method to analyze the alterations in the serum metabolomic profile of poultry. This study confirmed that long-term exposure to high levels of PM2.5 had significantly reduced the growth performance of poultry. Histopathological slides of the lung tissue in chickens exposed to long-term retention of PM2.5 clearly showed significant damage. Furthermore, the serum metabolome analysis revealed significant changes in the serum metabolic profile of chickens exposed to long-term PM2.5 exposure. Specifically, there were notable alterations in the Glycerophospholipid metabolism, Steroid hormone biosynthesis, and Phenylalanine, tyrosine, and tryptophan biosynthesis pathways.

Desipramine ameliorates fine particulate matter-induced hepatic insulin resistance by modulating the ceramide metabolism in mice

Recent research has highlighted a correlation between exposure to ambient fine particulate matter (PM2.5) and the development of systemic insulin resistance (IR) along with an elevated risk of diabetes. Ceramide has emerged as one of the pathogenic mechanisms contributing to IR. The inhibition of acid sphingomyelinase (ASMase) activity by desipramine (DES) has been shown to effectively reduce ceramide levels. In the present study, 24 female C57BL/6 N mice were randomized into one of the four groups: the filtered air exposure (FA) group, the concentrated PM2.5 exposure (PM) group, the concentrated PM2.5 treated with low-dose DES (DL) group, and the concentrated PM2.5 treated with high-dose DES (DH) group. The PM, DL and DH groups were exposed to PM2.5 for an 8-week period within a whole-body exposure system. The study encompassed extensive examinations of glucose homeostasis, liver lipid profile, ceramide pathway, and insulin signaling pathway. Our results demonstrated that PM2.5 exposure caused impaired glucose tolerance, elevated ceramide levels, increased phosphorylation PP2A, reduced Akt phosphorylation, and hindered GLUT2 expression. Remarkably, DES administration mitigated PM2.5-induced IR by effectively lowering ceramide levels. In conclusion, the reduction of ceramide levels by DES may be a promising therapeutic strategy for coping PM2.5-induced IR.

Exposure to PM2.5, seminal plasma metabolome, and semen quality among Chinese adult men: Association and potential mediation analyses

Exposure to ambient fine particulate matter (PM2.5) has been linked to a decline in semen quality, but the underlying mechanisms for this association remain unclear. We aimed to examine whether specific metabolites act as mediators in the association between PM2.5 exposure and changes in semen quality. We conducted untargeted metabolomics analysis using LC-MS/MS platforms to identified seminal plasma metabolites associated with various semen quality parameters among 200 Chinese adult men. Additionally, we performed mediation analyses to examine the effects of the seminal plasma metabolites on the association between PM2.5 exposure and semen quality. We identified 140 differential metabolites between the normal and abnormal semen groups, involving two metabolic pathways: Alanine, aspartate and glutamate metabolism, and Aminoacyl-tRNA biosynthesis. We additionally identified 7 specific seminal plasma metabolites that were associated with discrepant metabolic networks related to semen quality. The mediation analysis revealed that D-Aspartate might play a mediating role in the adverse effects of ambient PM2.5 exposure on both total and progressive motility during spermatogenesis period (70-90 days before ejaculation), with a proportion of mediation up to 16% and 17%, respectively. Exposure to PM2.5 was associated with alterations in D-Aspartate levels, which might partially mediate the association between PM2.5 and reduced sperm motility.

Unravelling the Crosstalk between Estrogen Deficiency and Gut-biotaDysbiosis in the Development of Diabetes Mellitus

Estrogens are classically considered essential hormonal signals, but they exert profound effects in a number of physiological and pathological states, including glucose homeostasis and insulin resistance. Estrogen deficiency after menopause in most women leads to increased androgenicity and changes in body composition, and it is recommended to manipulate the β-cell function of the pancreas, insulin-induced glucose transport, and hepatic glucose output, hence, the increasing incidence of type 2 diabetes mellitus. Recently, studies have reported that gut biota alteration due to estrogen deficiency contributes to altered energy metabolism and, hence, accentuates the pathology of diabetes mellitus. Emerging research suggests estrogen deficiency via genetic disposition or failure of ovaries to function in old age modulates the insulin resistance and glucose secretion workload on pancreatic beta cells by decreasing the levels of good bacteria such as Akkermansia muciniphila, Bifidobacterium spp., Lactobacillus spp., Faecalibacterium prausnitzii, Roseburia spp., and Prevotella spp., and increasing the levels of bad bacteria's such as Bacteroides spp., Clostridium difficile, Escherichia coli, and Enterococcus spp. Alteration in these bacteria's concentrations in the gut further leads to the development of impaired glucose uptake by the muscles, increased gluconeogenesis in the liver, and increased lipolysis and inflammation in the adipose tissues. Thus, the present review paper aims to clarify the intricate interactions between estrogen deficiency, gut microbiota regulation, and the development of diabetes mellitus.

Methylomic, Proteomic, and Metabolomic Correlates of Traffic-Related Air Pollution in the Context of Cardiorespiratory Health: A Systematic Review, Pathway Analysis, and Network Analysis

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead to cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease and highlight contemporary challenges and opportunities associated with such efforts.

Association of indoor solid fuel use and long-term exposure to ambient PM2.5 with sarcopenia in China: A nationwide cohort study

BACKGROUND

Little is known about the association between air pollution exposure and sarcopenia in Asia. We aimed to investigate the associations of indoor solid fuel use and long-term exposure to ambient fine particulate matter (PM2.5) with sarcopenia in China.

METHODS

Using a nationally population-representative study, 12,723 participants aged at least 45 years across 125 cities from the China Health and Retirement Longitudinal Study were enrolled in 2011, and further 3110 participants were followed up until 2013. Sarcopenia status was classified according to the Asian Working Group for Sarcopenia 2019 criteria. Household fuel types used for heating and cooking were assessed using a standard questionnaire. Ambient annual PM2.5 was estimated using satellite-based spatiotemporal models. Multinomial logistic regression as well as the multiplicative interaction and additive interaction analysis were used to explore the associations of indoor solid fuel and ambient PM2.5 with different status of sarcopenia.

RESULTS

Of the 12,723 participants, 6071 (47.7%) were men. In the cross-sectional analyses, compared with clean fuel, using solid fuel for heating and cooking, separately or simultaneously, was significantly associated with a higher risk of both possible sarcopenia and sarcopenia. Each 10 μg/m3 increment of PM2.5 was positively related to possible sarcopenia (adjusted odds ratio, [aOR] 1.04, 1.02-1.07) and sarcopenia (1.06, 1.01-1.12). We found a significant interaction between solid fuel use for heating and ambient PM2.5 exposure with possible sarcopenia. During a two-year follow-up, solid fuel use was associated with incident possible sarcopenia (aOR 1.59, 1.17-2.15). These associations did not differ by sex and age, while participants living in a house with poor cleanliness might have a higher risk of sarcopenia.

CONCLUSIONS

Indoor solid fuel use and long-term exposure to ambient PM2.5 were associated with a higher risk of sarcopenia among Chinese adults. These findings provide implications for promoting healthy aging by reducing air pollution.

Cumulative and lagged effects of varying-sized particulate matter exposure associates with toddlers' gut microbiota

Particulate matter (PM) is an important component of air pollutants and is associated with various health risks. However, the impact of PM on toddlers' gut microbiota is rarely investigated. This study aimed to assess the cumulative and lagged effects of varying-sized PMs on toddlers' gut microbiota. We collected demographic information, stool samples, and exposure to PM from 36 toddlers aged 2-3 years. The toddlers were divided into warm season group and cooler season group according to the collection time of stool samples. The gut microbiota was processed and analyzed using 16S rRNA V3-V4 gene regions. The concentration of PM was calculated using China High Air Pollutants (CHAP) database. To assess the mixed effects of varying-sized PM, multiple-PM models were utilized. There were significant differences between the community composition, α- and β-diversity between two groups. In multiple-PM models, there was a significant effect of weight quantile sum (PM1, PM2.5, and PM10) on α-diversity indices. In weight quantile sum models, after adjusting for a priori confounders, we found a negative effect of weight quantile sum on Enterococcus (β = -0.134, 95% CI -0.263 to -0.006), positive effects of weight quantile sum on unclassified_f__Ruminococcaceae (β = 0.247, 95% CI 0.102 to 0.393), Ruminococcus_1 (β = 0.444, 95% CI 0.238 to 0.650), unclassified_f__Lachnospiraceae (β = 0.278, 95% CI 0.099 to 0.458), and Family_XIII_AD_3011_group (β = 0.254, 95% CI 0.086 to 0.422) in WSG and CSG. In lagged weight quantile sum models, the correlation between lag time PM levels and the gut microbiota showed seasonal trends, and weights of PM changed with lag periods. This is the first study to highlight that cumulative and lagged effects of PMs synergistically affect the diversities (α- and β-diversity) and abundance of the gut microbiota in toddlers. Further research is needed to explore the mediating mechanism of varying-sized PMs exposure on the gut microbiota in toddlers.

Metabolic diseases and healthy aging: identifying environmental and behavioral risk factors and promoting public health

Aging is a progressive and irreversible pathophysiological process that manifests as the decline in tissue and cellular functions, along with a significant increase in the risk of various aging-related diseases, including metabolic diseases. While advances in modern medicine have significantly promoted human health and extended human lifespan, metabolic diseases such as obesity and type 2 diabetes among the older adults pose a major challenge to global public health as societies age. Therefore, understanding the complex interaction between risk factors and metabolic diseases is crucial for promoting well-being and healthy aging. This review article explores the environmental and behavioral risk factors associated with metabolic diseases and their impact on healthy aging. The environment, including an obesogenic environment and exposure to environmental toxins, is strongly correlated with the rising prevalence of obesity and its comorbidities. Behavioral factors, such as diet, physical activity, smoking, alcohol consumption, and sleep patterns, significantly influence the risk of metabolic diseases throughout aging. Public health interventions targeting modifiable risk factors can effectively promote healthier lifestyles and prevent metabolic diseases. Collaboration between government agencies, healthcare providers and community organizations is essential for implementing these interventions and creating supportive environments that foster healthy aging.

Methylomic, proteomic, and metabolomic correlates of traffic-related air pollution: A systematic review, pathway analysis, and network analysis relating traffic-related air pollution to subclinical and clinical cardiorespiratory outcomes

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease, and highlight contemporary challenges and opportunities associated with such efforts.

Exploring the impact of fungal spores from agricultural environments on the mice lung microbiome and metabolic profile

Exposure to particulate matter (PM) from agricultural environments has been extensively reported to cause respiratory health concerns in both animals and agricultural workers. Furthermore, PM from agricultural environments, containing fungal spores, has emerged as a significant threat to public health and the environment. Despite its potential toxicity, the impact of fungal spores present in PM from agricultural environments on the lung microbiome and metabolic profile is not well understood. To address this gap in knowledge, we developed a mice model of immunodeficiency using cyclophosphamide and subsequently exposed the mice to fungal spores via the trachea. By utilizing metabolomics techniques and 16 S rRNA sequencing, we conducted a comprehensive investigation into the alterations in the lung microbiome and metabolic profile of mice exposed to fungal spores. Our study uncovered significant modifications in both the lung microbiome and metabolic profile post-exposure to fungal spores. Additionally, fungal spore exposure elicited noticeable changes in α and β diversity, with these microorganisms being closely associated with inflammatory factors. Employing non-targeted metabolomics analysis via GC-TOF-MS, a total of 215 metabolites were identified, among which 42 exhibited significant differences. These metabolites are linked to various metabolic pathways, with amino sugar and nucleotide sugar metabolism, as well as galactose metabolism, standing out as the most notable pathways. Cysteine and methionine metabolism, along with glycine, serine and threonine metabolism, emerged as particularly crucial pathways. Moreover, these metabolites demonstrated a strong correlation with inflammatory factors and exhibited significant associations with microbial production. Overall, our findings suggest that disruptions to the microbiome and metabolome may hold substantial relevance in the mechanism underlying fungal spore-induced lung damage in mice.

The global, regional and national burden of type 2 diabetes mellitus in the past, present and future: a systematic analysis of the Global Burden of Disease Study 2019

Aim

To report the global, regional, and national burden of type 2 diabetes mellitus (T2DM) in 2019, assess its trends in the past, and forecast its trends in the future.

Methods

The main data source was the Global Burden of Disease 2019 database. We assessed the changes in T2DM burden from 1990 to 2019 with joinpoint regression analysis. Age-period-cohort analysis was used to forecast the T2DM incidence and mortality rate from 2020 to 2034.

Results

The burden of T2DM has increased from 1990 to 2019 generally. The low-middle socio-demographic index (SDI) region had the highest increase in age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), age-standardized mortality rate (ASMR), and age-standardized disability-adjusted life years (ASDR) due to T2DM. Nationally, the increase in ASIR (r=0.151, p=0.046) and the decrease in ASMR (r=0.355, p<0.001) were positively correlated with SDIs. In 2019, the global ASIR, ASPR, ASMR, ASDR due to T2DM were 259.9 (95% UI 240.3-281.4), 5282.9 (95% UI 4853.6-5752.1), 18.5 (95% UI 17.2-19.7), and 801.5 (95% UI 55477000-79005200) per 100,000 population, respectively. Additionally, the ASIR (r=0.153, p=0.030) and ASPR (r=0.159, p=0.024) of T2DM were positively correlated with SDIs, while ASMR (r=-0.226, p=0.001) and ASDR (r=-0.171, p=0.015) due to T2DM were negatively correlated with SDIs. The ASIR was estimated to increase to 284.42, and ASMR was estimated to increase to 19.1 from 2030 to 2034, per 100,000 population.

Conclusion

Globally, the burden of T2DM has increased in the past and was forecast to continue increasing. Greater investment in T2DM prevention is needed.

Global burden of type 2 diabetes attributable to non-high body mass index from 1990 to 2019

BACKGROUND

The prevalence of type 2 diabetes mellitus (T2DM) currently was increased in some countries of the world like China. However, the epidemiological trends of T2DM attributable to non-high body mass index (BMI) remain unclear. Thus, we aimed to describe the burden of T2DM attributable to non-high BMI.

METHODS

To estimate the burden of T2DM attributable to non-high BMI, data from the Global Burden of Disease Study 2019 were used to calculate the deaths and disability-adjusted life years (DALYs) by age, sex, year, and location. The estimated annual percentage change (EAPC) was applied in the analysis of temporal trends in T2DM from 1990 to 2019.

RESULTS

Globally in 2019, the number of death cases and DALYs of T2DM attributable to non-high BMI accounted for 57.9% and 48.1% of T2DM-death from all risks, respectively. Asia accounted for 59.5% and 63.6% of the global non-high-BMI-related death cases and DALYs of T2DM in 2019, respectively. From 1990 to 2019, regions in the low-income experienced a rise in DALYs attributable to non-high BMI. As compared to other age groups, older participants had higher deaths and DALYs of T2DM attributable to non-high BMI. The death and DALY rates of T2DM due to non-high BMI were higher in males and people in regions with low socio-demographic index (SDI) countries.

CONCLUSIONS

The burden of T2DM attributable to non-high BMI is higher in the elderly and in people in regions with low- and middle-SDI, resulting in a substantial burden on human health and the social cost of healthcare.

Effects of PM2.5 and high-fat diet interaction on blood glucose metabolism in adolescent male Wistar rats: A serum metabolomics analysis based on ultra-high performance liquid chromatography/mass spectrometry

Fine particulate matter (PM_2.5) and high-fat diet (HFD) are known to contribute to blood glucose metabolic disorders. However, limited research has investigated the combined impact of PM_2.5 and HFD on blood glucose metabolism. This study aimed to explore the joint effects of PM_2.5 and HFD on blood glucose metabolism in rats using serum metabolomics and to identify involved metabolites and metabolic pathways. The 32 male Wistar rats were exposed to filtered air (FA) or PM_2.5 (real-world inhaled, concentrated PM_2.5, 8 times the ambient level, ranging from 131.42 to 773.44 μg/m³) and fed normal diet (ND) or HFD for 8 weeks. The rats were divided into four groups (n = 8/group): ND-FA, ND-PM_2.5, HFD-FA and HFD-PM_2.5 groups. Blood samples were collected to determine fasting glucose (FBG), plasma insulin and glucose tolerance test and HOMA Insulin Resistance (HOMA-IR) index was calculated. Finally, the serum metabolism of rats was analyzed by ultra-high performance liquid chromatography/mass spectrometry (UHPLC-MS). Then we constructed the partial least squares discriminant analysis (PLS-DA) model to screen the differential metabolites, and performed pathway analysis to screen the main metabolic pathways. Results showed that combined effect of PM_2.5 and HFD caused changes in glucose tolerance, increased FBG levels and HOMA-IR in rats and there were interactions between PM_2.5 and HFD in FBG and insulin. By metabonomic analysis, the serum differential metabolites pregnenolone and progesterone, which involved in steroid hormone biosynthesis, were two different metabolites in the ND groups. In the HFD groups, the serum differential metabolites were L-tyrosine and phosphorylcholine, which involved in glycerophospholipid metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis. When PM_2.5 and HFD coexist, they may lead to more severe and complex effects on glucose metabolism by affecting lipid metabolism and amino acid metabolism. Therefore, reducing PM_2.5 exposure and controlling dietary structure are important measures for preventing and reducing glucose metabolism disorders.

Multi-omics data reveals the disturbance of glycerophospholipid metabolism and linoleic acid metabolism caused by disordered gut microbiota in PM2.5 gastrointestinal exposed rats

The relationships between fine particulate matter (PM2.5) exposure and health effects are complex and incompletely understood. Evidence suggests that PM2.5 exposure alters gut microbiota composition and metabolites, but the connections between these changes remain unclear. The aim of our study was to investigate how gut microbiota are involved in the systemic metabolic changes following PM2.5 gastrointestinal exposure. We used multi-omics approaches, including 16S rRNA sequencing and serum metabolomics, to identify alterations in gut microbes and metabolites of PM2.5-exposed rats. We then explored correlations between perturbed gut microbiota and metabolic changes, and conducted pathway analyses to determine critical metabolic pathways impacted by PM2.5 exposure. To verify links between gut microbiome and metabolome disruptions, we performed fecal microbiota transplantation (FMT) experiment. A total of 30 differential gut microbe taxa were identified between PM2.5 and control groups, primarily in Firmicutes, Acidobacteria, and Proteobacteria phyla. We also identified 30 differential metabolites, including glycerophospholipids, fatty acyls, amino acids and others. Pathway analysis revealed disruptions in glycerophospholipid metabolism, steroid hormone biosynthesis, and linoleic acid metabolism. Through FMT, we confirmed PM2.5 altered phosphatidylcholine and linoleic acid metabolism by changing specific gut bacteria. Our results suggest that PM2.5 gastrointestinal exposure triggers systemic metabolic changes by disrupting the gut microbiome, especially glycerophospholipid and linoleic acid metabolism pathways.

Ambient particulate air pollution and the intestinal microbiome; a systematic review of epidemiological, in vivo and, in vitro studies

A healthy indigenous intestinal microbiome is indispensable for intra- and extra-intestinal human health. Since well-established factors such as diet and antibiotic use only explain 16 % of the inter-individual variation in gut microbiome composition, recent studies have focused on the association between ambient particulate air pollution and the intestinal microbiome. We systematically summarize and discuss all evidence concerning the effect of particulate air pollution on intestinal bacterial diversity indices, specific bacterial taxa, and potential underlying intestinal mechanisms. To this end, all possibly relevant publications published between February 1982 and January 2023 were screened, and eventually, 48 articles were included. The vast majority (n = 35) of these studies were animal studies. The exposure periods investigated in the human epidemiological studies (n = 12) ranged from infancy through elderly. This systematic review found that intestinal microbiome diversity indices were generally negatively associated with particulate air pollution in epidemiological studies, with an increase in taxa belonging to Bacteroidetes (two studies), Deferribacterota (one study), and Proteobacteria (four studies), a decrease in taxa belonging to Verrucomicrobiota (one study), and no consensus for taxa belonging to Actinobacteria (six studies) and Firmicutes (seven studies). There was no unequivocal effect of ambient particulate air pollution exposure on bacterial indices and taxa in animal studies. Only one study in humans examined a possible underlying mechanism; yet, the included in vitro and animal studies depicted higher gut damage, inflammation, oxidative stress, and permeability in exposed versus unexposed animals. Overall, the population-based studies showed a dose-related continuum of short- and long-term ambient particulate air pollution exposure on lower gut diversity and shifts in taxa over the entire life course.

Air pollution weaken your muscle? Evidence from a cross-sectional study on sarcopenia in central China

BACKGROUND

As the world experiences a demographic shift towards aging populations, there will be a significant surge in the number of sarcopenia patients, along with an unprecedented expansion in the associated economic burden. The multitudinous risk factors for sarcopenia have been reported, but evidence for air pollution remains rare.

METHODS

This cross-sectional study employed multi-stage random sampling to select 1592 participants over 40 years of age from Hubei Province. Daily mean concentrations of air pollutants were collected ChinaHighAirPollutants dataset. Unconditional logistic regression models were utilized to investigate the associations between air pollution and sarcopenia.

RESULTS

For each 1 μg/m³ increase in PM_2.5, PM₁₀, SO₂ and O₃, there were corresponding elevations of 11.1% [95% confidence interval (CI): 4.9, 17.7], 4.3% (95% CI: 1.4, 7.2), 22.6% (95% CI: 7.2, 40.1) and 9.3% (95% CI: 0.7, 18.7) in the risk of sarcopenia, respectively. The associations of PM_2.5/PM₁₀/O₃-sarcopenia were more pronounced in females, with corresponding odds ratios (ORs) and 95% CIs of 1.179 (1.062, 1.310), 1.079 (1.027, 1.135) and 1.180 (1.026, 1.358), separately. Additionally, individuals residing in rural areas were more susceptible to the effects of PM_2.5 and PM₁₀. Current/ever smokers or drinkers were also at higher risk of developing sarcopenia caused by PM_2.5, PM₁₀ and O₃ exposure. Mixture analyses show a surge of 48.4% (95% CI: 3.6%, 112.5%) in the likelihood of suffering from sarcopenia, and the joint impacts of the air pollution were mainly driven by PM_2.5.

CONCLUSIONS

Our results produced evidence for a relationship between air pollution exposure and the increased prevalence of sarcopenia in China. Public health and relevant departments should make efforts to prevent sarcopenia, particularly in China experiencing rapid demographic aging.