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World Trade Center Exposure, DNA Methylation Changes, and Cancer: A Review of Current Evidence.

Epigenomes | 2023

Introduction: Known carcinogens in the dust and fumes from the destruction of the World Trade Center (WTC) towers on 9 November 2001 included metals, asbestos, and organic pollutants, which have been shown to modify epigenetic status. Epigenome-wide association analyses (EWAS) using uniform (Illumina) methodology have identified novel epigenetic profiles of WTC exposure. Methods: We reviewed all published data, comparing differentially methylated gene profiles identified in the prior EWAS studies of WTC exposure. This included DNA methylation changes in blood-derived DNA from cases of cancer-free "Survivors" and those with breast cancer, as well as tissue-derived DNA from "Responders" with prostate cancer. Emerging molecular pathways related to the observed DNA methylation changes in WTC-exposed groups were explored and summarized. Results: WTC dust exposure appears to be associated with DNA methylation changes across the genome. Notably, WTC dust exposure appears to be associated with increased global DNA methylation; direct dysregulation of cancer genes and pathways, including inflammation and immune system dysregulation; and endocrine system disruption, as well as disruption of cholesterol homeostasis and lipid metabolism. Conclusion: WTC dust exposure appears to be associated with biologically meaningful DNA methylation changes, with implications for carcinogenesis and development of other chronic diseases.

Pubmed ID: 38131903 RIS Download

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Associated grants

  • Agency: AHRQ HHS, United States
    Id: T32 HS026120
  • Agency: NCI NIH HHS, United States
    Id: P30 CA016087
  • Agency: NIOSH CDC HHS, United States
    Id: U01 OH010396
  • Agency: NIOSH CDC HHS, United States
    Id: R21 OH012238
  • Agency: ACL HHS, United States
    Id: U01OH010396
  • Agency: NIOSH CDC HHS, United States
    Id: OH010396

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KEGG (tool)

RRID:SCR_012773

Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

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Cluster (tool)

RRID:SCR_013505

Software R package. Methods for Cluster analysis. Performs variety of types of cluster analysis and other types of processing on large microarray datasets.

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