Associations Between Epigenetic Age Acceleration and microRNA Expression Among U.S. Firefighters
Epigenetic changes may be biomarkers of health. Epigenetic age acceleration (EAA), the discrepancy between epigenetic age measured via epigenetic clocks and chronological age, is associated with morbidity and mortality. However, the intersection of epigenetic clocks with microRNAs (miRNAs) and corre...
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| Veröffentlicht in: | Epigenetics insights 2023-01, Vol.16, p.25168657231206301-25168657231206301 |
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| creator | Jung, Alesia M Furlong, Melissa A Goodrich, Jaclyn M Cardenas, Andres Beitel, Shawn C Littau, Sally R Caban-Martinez, Alberto J Gulotta, John J Wallentine, Darin D Urwin, Derek Gabriel, Jamie Hughes, Jeffrey Graber, Judith M Grant, Casey Burgess, Jefferey L |
| description | Epigenetic changes may be biomarkers of health. Epigenetic age acceleration (EAA), the discrepancy between epigenetic age measured via epigenetic clocks and chronological age, is associated with morbidity and mortality. However, the intersection of epigenetic clocks with microRNAs (miRNAs) and corresponding miRNA-based health implications have not been evaluated. We analyzed DNA methylation and miRNA profiles from blood sampled among 332 individuals enrolled across 2 U.S.-based firefighter occupational studies (2015-2018 and 2018-2020). We considered 7 measures of EAA in leukocytes (PhenoAge, GrimAge, Horvath, skin-blood, and Hannum epigenetic clocks, and extrinsic and intrinsic epigenetic age acceleration). We identified miRNAs associated with EAA using individual linear regression models, adjusted for sex, race/ethnicity, chronological age, and cell type estimates, and investigated downstream effects of associated miRNAs with miRNA enrichment analyses and genomic annotations. On average, participants were 38 years old, 88% male, and 75% non-Hispanic white. We identified 183 of 798 miRNAs associated with EAA (FDR q |
| doi_str_mv | 10.1177/25168657231206301 |
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Epigenetic age acceleration (EAA), the discrepancy between epigenetic age measured via epigenetic clocks and chronological age, is associated with morbidity and mortality. However, the intersection of epigenetic clocks with microRNAs (miRNAs) and corresponding miRNA-based health implications have not been evaluated. We analyzed DNA methylation and miRNA profiles from blood sampled among 332 individuals enrolled across 2 U.S.-based firefighter occupational studies (2015-2018 and 2018-2020). We considered 7 measures of EAA in leukocytes (PhenoAge, GrimAge, Horvath, skin-blood, and Hannum epigenetic clocks, and extrinsic and intrinsic epigenetic age acceleration). We identified miRNAs associated with EAA using individual linear regression models, adjusted for sex, race/ethnicity, chronological age, and cell type estimates, and investigated downstream effects of associated miRNAs with miRNA enrichment analyses and genomic annotations. On average, participants were 38 years old, 88% male, and 75% non-Hispanic white. We identified 183 of 798 miRNAs associated with EAA (FDR q < 0.05); 126 with PhenoAge, 59 with GrimAge, 1 with Horvath, and 1 with the skin-blood clock. Among miRNAs associated with Horvath and GrimAge, there were 61 significantly enriched disease annotations including age-related metabolic and cardiovascular conditions and several cancers. Enriched pathways included those related to proteins and protein modification. We identified miRNAs associated with EAA of multiple epigenetic clocks. PhenoAge had more associations with individual miRNAs, but GrimAge and Horvath had greater implications for miRNA-associated pathways. Understanding the relationship between these epigenetic markers could contribute to our understanding of the molecular underpinnings of aging and aging-related diseases.</description><identifier>ISSN: 2516-8657</identifier><identifier>EISSN: 2516-8657</identifier><identifier>DOI: 10.1177/25168657231206301</identifier><identifier>PMID: 37953967</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Age ; Aging ; Blood ; DNA methylation ; Epigenetics ; Leukocytes ; MicroRNAs ; miRNA ; Morbidity ; Original Research ; Regression analysis</subject><ispartof>Epigenetics insights, 2023-01, Vol.16, p.25168657231206301-25168657231206301</ispartof><rights>The Author(s) 2023</rights><rights>The Author(s) 2023.</rights><rights>The Author(s) 2023. This work is licensed under the Creative Commons Attribution – Non-Commercial License https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2023 2023 SAGE Publications Ltd unless otherwise noted. Manuscript content on this site is licensed under Creative Commons Licenses</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c419t-af2ee97e8ccd763e0743e003a081bc19f446e56ebfc0b25bd835898fed2f51f83</cites><orcidid>0000-0003-0055-2545 ; 0000-0003-2284-3298</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634256/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634256/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37953967$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jung, Alesia M</creatorcontrib><creatorcontrib>Furlong, Melissa A</creatorcontrib><creatorcontrib>Goodrich, Jaclyn M</creatorcontrib><creatorcontrib>Cardenas, Andres</creatorcontrib><creatorcontrib>Beitel, Shawn C</creatorcontrib><creatorcontrib>Littau, Sally R</creatorcontrib><creatorcontrib>Caban-Martinez, Alberto J</creatorcontrib><creatorcontrib>Gulotta, John J</creatorcontrib><creatorcontrib>Wallentine, Darin D</creatorcontrib><creatorcontrib>Urwin, Derek</creatorcontrib><creatorcontrib>Gabriel, Jamie</creatorcontrib><creatorcontrib>Hughes, Jeffrey</creatorcontrib><creatorcontrib>Graber, Judith M</creatorcontrib><creatorcontrib>Grant, Casey</creatorcontrib><creatorcontrib>Burgess, Jefferey L</creatorcontrib><title>Associations Between Epigenetic Age Acceleration and microRNA Expression Among U.S. Firefighters</title><title>Epigenetics insights</title><addtitle>Epigenet Insights</addtitle><description>Epigenetic changes may be biomarkers of health. Epigenetic age acceleration (EAA), the discrepancy between epigenetic age measured via epigenetic clocks and chronological age, is associated with morbidity and mortality. However, the intersection of epigenetic clocks with microRNAs (miRNAs) and corresponding miRNA-based health implications have not been evaluated. We analyzed DNA methylation and miRNA profiles from blood sampled among 332 individuals enrolled across 2 U.S.-based firefighter occupational studies (2015-2018 and 2018-2020). We considered 7 measures of EAA in leukocytes (PhenoAge, GrimAge, Horvath, skin-blood, and Hannum epigenetic clocks, and extrinsic and intrinsic epigenetic age acceleration). We identified miRNAs associated with EAA using individual linear regression models, adjusted for sex, race/ethnicity, chronological age, and cell type estimates, and investigated downstream effects of associated miRNAs with miRNA enrichment analyses and genomic annotations. On average, participants were 38 years old, 88% male, and 75% non-Hispanic white. We identified 183 of 798 miRNAs associated with EAA (FDR q < 0.05); 126 with PhenoAge, 59 with GrimAge, 1 with Horvath, and 1 with the skin-blood clock. Among miRNAs associated with Horvath and GrimAge, there were 61 significantly enriched disease annotations including age-related metabolic and cardiovascular conditions and several cancers. Enriched pathways included those related to proteins and protein modification. We identified miRNAs associated with EAA of multiple epigenetic clocks. PhenoAge had more associations with individual miRNAs, but GrimAge and Horvath had greater implications for miRNA-associated pathways. Understanding the relationship between these epigenetic markers could contribute to our understanding of the molecular underpinnings of aging and aging-related diseases.</description><subject>Age</subject><subject>Aging</subject><subject>Blood</subject><subject>DNA methylation</subject><subject>Epigenetics</subject><subject>Leukocytes</subject><subject>MicroRNAs</subject><subject>miRNA</subject><subject>Morbidity</subject><subject>Original Research</subject><subject>Regression analysis</subject><issn>2516-8657</issn><issn>2516-8657</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kctu1DAUhi0EolXbB2CDLLFhM1Nf4ktWKFTTi1QVCejaOM5J6mpiD3YG2revp9MbIDa29fs7_7kh9I6SOaVKHTJBpZZCMU4ZkZzQV2h3o8024usX7x10kPM1IYQRUUku3qIdrmrBa6l20Y8m5-i8nXwMGX-G6TdAwIuVHyDA5B1uBsCNc7CEdA9hGzo8epfi14sGL25WCXLe6M0Yw4Av59_m-Ngn6P1wNUHK--hNb5cZDh7uPXR5vPh-dDo7_3JydtScz1xF62lmewZQK9DOdUpyIKoqB-GWaNo6WvdVJUFIaHtHWibaTnOha91Dx3pBe8330Ket72rdjtA5CFOyS7NKfrTp1kTrzZ8_wV-ZIf4ytAyvYkIWh48PDin-XEOezOhzaXxpA8R1NkzrWmhVyi3oh7_Q67hOofRnWM0IlUwqVSi6pcqwci4jeaqGErPZoflnhyXm_cs2niIeN1aA-RbIdoDntP93vAPpiKRB</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Jung, Alesia M</creator><creator>Furlong, Melissa A</creator><creator>Goodrich, Jaclyn M</creator><creator>Cardenas, Andres</creator><creator>Beitel, Shawn C</creator><creator>Littau, Sally R</creator><creator>Caban-Martinez, Alberto J</creator><creator>Gulotta, John J</creator><creator>Wallentine, Darin D</creator><creator>Urwin, Derek</creator><creator>Gabriel, Jamie</creator><creator>Hughes, Jeffrey</creator><creator>Graber, Judith M</creator><creator>Grant, Casey</creator><creator>Burgess, Jefferey L</creator><general>SAGE Publications</general><general>Sage Publications Ltd</general><scope>AFRWT</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8AO</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AYAGU</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-0055-2545</orcidid><orcidid>https://orcid.org/0000-0003-2284-3298</orcidid></search><sort><creationdate>20230101</creationdate><title>Associations Between Epigenetic Age Acceleration and microRNA Expression Among U.S. Firefighters</title><author>Jung, Alesia M ; 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Epigenetic age acceleration (EAA), the discrepancy between epigenetic age measured via epigenetic clocks and chronological age, is associated with morbidity and mortality. However, the intersection of epigenetic clocks with microRNAs (miRNAs) and corresponding miRNA-based health implications have not been evaluated. We analyzed DNA methylation and miRNA profiles from blood sampled among 332 individuals enrolled across 2 U.S.-based firefighter occupational studies (2015-2018 and 2018-2020). We considered 7 measures of EAA in leukocytes (PhenoAge, GrimAge, Horvath, skin-blood, and Hannum epigenetic clocks, and extrinsic and intrinsic epigenetic age acceleration). We identified miRNAs associated with EAA using individual linear regression models, adjusted for sex, race/ethnicity, chronological age, and cell type estimates, and investigated downstream effects of associated miRNAs with miRNA enrichment analyses and genomic annotations. On average, participants were 38 years old, 88% male, and 75% non-Hispanic white. We identified 183 of 798 miRNAs associated with EAA (FDR q < 0.05); 126 with PhenoAge, 59 with GrimAge, 1 with Horvath, and 1 with the skin-blood clock. Among miRNAs associated with Horvath and GrimAge, there were 61 significantly enriched disease annotations including age-related metabolic and cardiovascular conditions and several cancers. Enriched pathways included those related to proteins and protein modification. We identified miRNAs associated with EAA of multiple epigenetic clocks. PhenoAge had more associations with individual miRNAs, but GrimAge and Horvath had greater implications for miRNA-associated pathways. Understanding the relationship between these epigenetic markers could contribute to our understanding of the molecular underpinnings of aging and aging-related diseases.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><pmid>37953967</pmid><doi>10.1177/25168657231206301</doi><orcidid>https://orcid.org/0000-0003-0055-2545</orcidid><orcidid>https://orcid.org/0000-0003-2284-3298</orcidid><oa>free_for_read</oa></addata></record> |
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| source | PubMed Central Open Access; PubMed Central |
| subjects | Age Aging Blood DNA methylation Epigenetics Leukocytes MicroRNAs miRNA Morbidity Original Research Regression analysis |
| title | Associations Between Epigenetic Age Acceleration and microRNA Expression Among U.S. Firefighters |
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