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

J Hazard Mater

Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China. Electronic address:

Published: April 2024

AI Article Synopsis

  • The study investigates the links between particulate matter (PM) exposure and metabolic diseases, especially type 2 diabetes (T2D), using multi-omics analysis from stool and serum samples of 3,267 participants in Southern China.
  • Researchers found significant differences in biomarkers and metabolic profiles between participants exposed to high and low PM levels, notably affecting gut microbes, metabolites, and lipid-related serum indicators.
  • The results suggest specific biomarkers related to PM exposure, such as fecal rhamnose and serum hippuric acid, are associated with increased T2D risk and higher blood glucose levels, highlighting the need for further understanding of PM's impact on human health.

Article Abstract

The relationship between PM 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 PM exposure and human health, we investigated short-term PM 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-PM groups. PM-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-PM, 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 PM-related multi-omics biomarkers linking PM exposure and T2D in humans.

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Source
http://dx.doi.org/10.1016/j.jhazmat.2024.133784DOI Listing

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