Epigenetic predictors of all-cause mortality are associated with objective measures of neighborhood disadvantage in an urban population.
DNA methylation
Mortality predictors
Neighborhood disadvantage
Social determinants of health
Urban populations
Journal
Clinical epigenetics
ISSN: 1868-7083
Titre abrégé: Clin Epigenetics
Pays: Germany
ID NLM: 101516977
Informations de publication
Date de publication:
11 03 2020
11 03 2020
Historique:
received:
04
11
2019
accepted:
17
02
2020
entrez:
13
3
2020
pubmed:
13
3
2020
medline:
4
6
2021
Statut:
epublish
Résumé
Neighborhood characteristics are robust predictors of overall health and mortality risk for residents. Though there has been some investigation of the role that molecular indicators may play in mediating neighborhood exposures, there has been little effort to incorporate newly developed epigenetic biomarkers into our understanding of neighborhood characteristics and health outcomes. Using 157 participants of the Detroit Neighborhood Health Study with detailed assessments of neighborhood characteristics and genome-wide DNA methylation profiling via the Illumina 450K methylation array, we assessed the relationship between objective neighborhood characteristics and a validated DNA methylation-based epigenetic mortality risk score (eMRS). Associations were adjusted for age, race, sex, ever smoking, ever alcohol usage, education, years spent in neighborhood, and employment. A secondary model additionally adjusted for personal neighborhood perception. We summarized 19 neighborhood quality indicators assessed for participants into 9 principal components which explained over 90% of the variance in the data and served as metrics of objective neighborhood quality exposures. Of the nine principal components utilized for this study, one was strongly associated with the eMRS (β = 0.15; 95% confidence interval = 0.06-0.24; P = 0.002). This principal component (PC7) was most strongly driven by the presence of abandoned cars, poor streets, and non-art graffiti. Models including both PC7 and individual indicators of neighborhood perception indicated that only PC7 and not neighborhood perception impacted the eMRS. When stratified on neighborhood indicators of greenspace, we observed a potentially protective effect of large mature trees as this feature substantially attenuated the observed association. Objective measures of neighborhood disadvantage are significantly associated with an epigenetic predictor of mortality risk, presenting a potential novel avenue by which neighborhood-level exposures may impact health. Associations were independent of an individual's perception of their neighborhood and attenuated by neighborhood greenspace features. More work should be done to determine molecular risk factors associated with neighborhoods, and potentially protective neighborhood features against adverse molecular effects.
Sections du résumé
BACKGROUND
Neighborhood characteristics are robust predictors of overall health and mortality risk for residents. Though there has been some investigation of the role that molecular indicators may play in mediating neighborhood exposures, there has been little effort to incorporate newly developed epigenetic biomarkers into our understanding of neighborhood characteristics and health outcomes.
METHODS
Using 157 participants of the Detroit Neighborhood Health Study with detailed assessments of neighborhood characteristics and genome-wide DNA methylation profiling via the Illumina 450K methylation array, we assessed the relationship between objective neighborhood characteristics and a validated DNA methylation-based epigenetic mortality risk score (eMRS). Associations were adjusted for age, race, sex, ever smoking, ever alcohol usage, education, years spent in neighborhood, and employment. A secondary model additionally adjusted for personal neighborhood perception. We summarized 19 neighborhood quality indicators assessed for participants into 9 principal components which explained over 90% of the variance in the data and served as metrics of objective neighborhood quality exposures.
RESULTS
Of the nine principal components utilized for this study, one was strongly associated with the eMRS (β = 0.15; 95% confidence interval = 0.06-0.24; P = 0.002). This principal component (PC7) was most strongly driven by the presence of abandoned cars, poor streets, and non-art graffiti. Models including both PC7 and individual indicators of neighborhood perception indicated that only PC7 and not neighborhood perception impacted the eMRS. When stratified on neighborhood indicators of greenspace, we observed a potentially protective effect of large mature trees as this feature substantially attenuated the observed association.
CONCLUSION
Objective measures of neighborhood disadvantage are significantly associated with an epigenetic predictor of mortality risk, presenting a potential novel avenue by which neighborhood-level exposures may impact health. Associations were independent of an individual's perception of their neighborhood and attenuated by neighborhood greenspace features. More work should be done to determine molecular risk factors associated with neighborhoods, and potentially protective neighborhood features against adverse molecular effects.
Identifiants
pubmed: 32160902
doi: 10.1186/s13148-020-00830-8
pii: 10.1186/s13148-020-00830-8
pmc: PMC7065313
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
44Subventions
Organisme : NIMHD NIH HHS
ID : R01 MD011728
Pays : United States
Organisme : NIEHS NIH HHS
ID : P30 ES010126
Pays : United States
Organisme : NIMH NIH HHS
ID : RC1 MH088283
Pays : United States
Organisme : NCI NIH HHS
ID : T32 CA128582
Pays : United States
Organisme : NICHD NIH HHS
ID : T32 HD007186
Pays : United States
Organisme : NIDA NIH HHS
ID : R01 DA022720
Pays : United States
Organisme : NICHD NIH HHS
ID : P2C HD050924
Pays : United States
Organisme : NICHD NIH HHS
ID : T32 HD091058
Pays : United States
Organisme : NIMHD NIH HHS
ID : K99 MD012808
Pays : United States
Références
Bioinformatics. 2012 Mar 15;28(6):882-3
pubmed: 22257669
Am J Epidemiol. 2018 Nov 1;187(11):2346-2354
pubmed: 30060108
Genome Biol. 2018 Sep 27;19(1):136
pubmed: 30257690
Environ Health Perspect. 2016 Jul;124(7):983-90
pubmed: 26731791
Epigenetics. 2013 Jan;8(1):23-7
pubmed: 23196856
Nat Clin Pract Oncol. 2005 Dec;2 Suppl 1:S4-11
pubmed: 16341240
Am J Med Genet B Neuropsychiatr Genet. 2017 Sep;174(6):619-630
pubmed: 28691784
PLoS One. 2015 Apr 09;10(4):e0122601
pubmed: 25856389
Curr Dir Psychol Sci. 2006 Aug;15(4):188-192
pubmed: 18185846
Epigenetics. 2017 Aug;12(8):662-673
pubmed: 28678593
Bioinformatics. 2013 Jan 15;29(2):189-96
pubmed: 23175756
BMC Bioinformatics. 2012 May 08;13:86
pubmed: 22568884
Neurosci Biobehav Rev. 2010 Sep;35(1):2-16
pubmed: 19822172
Nat Rev Genet. 2018 Jun;19(6):371-384
pubmed: 29643443
Am J Public Health. 2012 Sep;102(9):1706-14
pubmed: 22873478
Depress Anxiety. 2011 Aug;28(8):639-47
pubmed: 21608084
Epigenetics. 2018;13(8):846-857
pubmed: 30152726
Proc Natl Acad Sci U S A. 2010 May 18;107(20):9470-5
pubmed: 20439746
Epigenomics. 2018 Dec;10(12):1585-1601
pubmed: 30456986
Diabetes Care. 2008 Feb;31(2):273-8
pubmed: 18000180
PLoS One. 2012;7(7):e41361
pubmed: 22848472
PLoS Med. 2017 Jan 17;14(1):e1002215
pubmed: 28095459
Lancet. 2018 Feb 3;391(10119):462-512
pubmed: 29056410
Int J Epidemiol. 2012 Feb;41(1):62-74
pubmed: 22422449
Nature. 2017 Jan 5;541(7635):81-86
pubmed: 28002404
Health Place. 2012 May;18(3):683-93
pubmed: 22401803
Hum Mol Genet. 2016 Nov 1;25(21):4739-4748
pubmed: 28172975
Oncotarget. 2016 Nov 15;7(46):74510-74525
pubmed: 27793020
Ann N Y Acad Sci. 2010 Feb;1186:125-45
pubmed: 20201871
Biol Res Nurs. 2012 Oct;14(4):311-46
pubmed: 23007870
J Trauma Stress. 2011 Dec;24(6):747-51
pubmed: 22144187
Curr Environ Health Rep. 2018 Sep;5(3):317-327
pubmed: 30047075
Fam Community Health. 2010 Jan-Mar;33(1):68-78
pubmed: 20010006
Int J Epidemiol. 2015 Aug;44(4):1320-30
pubmed: 25889032
PLoS One. 2012;7(9):e45419
pubmed: 23049799
Aging (Albany NY). 2016 Sep 28;8(9):1844-1865
pubmed: 27690265
Nat Genet. 2003 Mar;33 Suppl:245-54
pubmed: 12610534
Drug Alcohol Depend. 2010 Nov 1;112(1-2):18-26
pubmed: 20541875
Soc Sci Med. 2013 May;85:50-8
pubmed: 23540366
Soc Sci Med. 2008 Feb;66(4):862-72
pubmed: 18160194
Nat Commun. 2017 Mar 17;8:14617
pubmed: 28303888
Environ Res. 2017 Oct;158:508-521
pubmed: 28709033
Environ Health Perspect. 2018 Feb 06;126(2):027004
pubmed: 29410382
Soc Sci Med. 2006 Nov;63(10):2575-90
pubmed: 16905230
Am J Epidemiol. 2012 Oct 1;176 Suppl 7:S164-74
pubmed: 23035140
Health Place. 2010 Sep;16(5):1058-60
pubmed: 20627796
Health Place. 2010 Sep;16(5):811-9
pubmed: 20434941
Lancet. 2008 Nov 8;372(9650):1655-60
pubmed: 18994663
Am J Community Psychol. 2007 Dec;40(3-4):261-71
pubmed: 17924185
Soc Sci Med. 2008 Mar;66(6):1256-70
pubmed: 18248865
Bioinformatics. 2012 May 1;28(9):1280-1
pubmed: 22451269
Environ Res. 2017 Oct;158:301-317
pubmed: 28672128
Sci Rep. 2015 Jul 09;5:11610
pubmed: 26158911
Epigenetics. 2013 Feb;8(2):203-9
pubmed: 23314698
Clin Epigenetics. 2017 May 15;9:54
pubmed: 28515798
BMC Genomics. 2013 May 01;14:293
pubmed: 23631413
J Affect Disord. 2016 Dec;206:181-188
pubmed: 27475889