Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Physician-Scientist Development
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • In-Press Preview
    • Resource and Technical Advances
    • Clinical Research and Public Health
    • Research Letters
    • Editorials
    • Perspectives
    • Physician-Scientist Development
    • Reviews
    • Top read articles

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Resource and Technical Advances
  • Clinical Research and Public Health
  • Research Letters
  • Editorials
  • Perspectives
  • Physician-Scientist Development
  • Reviews
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
Air pollution modulates brown adipose tissue function through epigenetic regulation by HDAC9 and KDM2B
Rengasamy Palanivel, Jean-Eudes Dazard, Bongsoo Park, Sarah Costantino, Skanda T. Moorthy, Armando Vergara-Martel, Elaine Ann Cara, Jonnelle Edwards-Glenn, Shyam Biswal, Lung Chi Chen, Mukesh K. Jain, Francesco Paneni, Sanjay Rajagopalan
Rengasamy Palanivel, Jean-Eudes Dazard, Bongsoo Park, Sarah Costantino, Skanda T. Moorthy, Armando Vergara-Martel, Elaine Ann Cara, Jonnelle Edwards-Glenn, Shyam Biswal, Lung Chi Chen, Mukesh K. Jain, Francesco Paneni, Sanjay Rajagopalan
View: Text | PDF
Research Article Cell biology Metabolism

Air pollution modulates brown adipose tissue function through epigenetic regulation by HDAC9 and KDM2B

  • Text
  • PDF
Abstract

Recent experimental and epidemiologic data have strongly associated air pollution in the pathogenesis of insulin resistance and type 2 diabetes mellitus. We explored the effect of inhalational exposure to concentrated ambient particulate matter smaller than 2.5 μm (PM2.5), or filtered air, using a whole-body inhalation system (6 hours/day, 5 days/week) for 24 weeks on metabolism and brown adipose tissue (BAT) function. Mechanistic evaluation of insulin resistance, glucose uptake with 18F-fluorodeoxyglucose positron emission tomography, alongside evaluation for differentially methylated regions, chromatin accessibility, and differential expression of genes was performed. PM2.5 exposure impaired metabolism through changes in key BAT transcriptional programs involved in redox stress, lipid deposition, fibrosis, and altered thermogenesis. Significant differential methylation and widespread chromatin remodeling was noted in BAT with PM2.5. Integrated analysis uncovered a role for the histone deacetylase HDAC9 and histone demethylase KDM2B. The latter demethylates Lys-4 and Lys-36 of histone H3. Specifically, studies using ChIP combined with quantitative PCR confirmed HDAC9 and KDM2B occupancy and reduced H3K36me2 on the promoter of target BAT genes in PM2.5 mice, while Hdac9/Kdm2b knockdown and overexpression increased and reduced BAT metabolism, respectively. Collectively, our results provide insights into air pollution exposure and changes in BAT and metabolism.

Authors

Rengasamy Palanivel, Jean-Eudes Dazard, Bongsoo Park, Sarah Costantino, Skanda T. Moorthy, Armando Vergara-Martel, Elaine Ann Cara, Jonnelle Edwards-Glenn, Shyam Biswal, Lung Chi Chen, Mukesh K. Jain, Francesco Paneni, Sanjay Rajagopalan

×

Figure 6

DNA accessibility data analysis of PM2.5-exposed BAT and integrative analysis with transcriptome data: overall integrative analysis.

Options: View larger image (or click on image) Download as PowerPoint
DNA accessibility data analysis of PM2.5-exposed BAT and integrative ana...
Integrative analysis of transcriptome and methylome data on curated DMR-DEG interaction pairs identified by MPLS (see Methods). (A) Categories of DMR-DEG interaction pairs by interaction type (homologous [top] vs. heterologous [bottom]), directionality of change (between hypermethylated and hypomethylated DMRs and up- vs. downregulated DEGs) and correlation sign (between regression and correlation coefficients). (B and C) Scatter plots of DMR-DEG interaction pairs in the correlation-regression space (B, homologous vs. C, heterologous). For each interaction type, a point represents a DMR-DEG pair. Correlation and regression coefficient thresholds of significance are shown (in-plot dotted lines). Full (middle plot) and close-up views (left- and right-hand sides of plots) of all significant pairs are highlighted and mapped on the plots. Lists of up to top 10 significant pairs are shown. (B) Top 5 homologous DMR-DEG pairs. Left: 3 homologous negatively correlated DMR-DEG pairs. Right: 2 homologous positively correlated DMR-DEG pairs. (C). Top 616 heterologous DMR-DEG pairs. Left: 319 heterologous negatively correlated DMR-DEG pairs. Right: 297 heterologous positively correlated DMR-DEG pairs. (D) DMR-DEG interaction mechanism model. Left: Cis regulatory elements (CREs) corresponding to homologous (cis) DMR-DEG pairs. Right: Trans regulatory elements (TREs) corresponding to heterologous (trans) DMR-DEG pairs.

Copyright © 2026 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts