TY - JOUR
T1 - Surrounding greenness and biological aging based on DNA methylation
T2 - A twin and family study in Australia
AU - Xu, Rongbin
AU - Li, Shuai
AU - Li, Shanshan
AU - Wong, Ee Ming
AU - Southey, Melissa C.
AU - Hopper, John L.
AU - Abramson, Michael J.
AU - Guo, Yuming
N1 - Funding Information:
M.J.A. holds investigator-initiated grants from Pfizer and Boehringer-Ingelheim for unrelated research. He has undertaken an unrelated consultancy for and received assistance with conference attendance from Sanofi. He also received a speaker’s fee from GlaxoSmithKline. All other authors declare they have no actual or potential competing financial interests.
Funding Information:
R.X. is supported by China Scholarship Council (201806010405). Shuai Li is supported by an Early Career Fellowship of the Australian National Health and Medical Research Council (NHMRC; APP1109193). Y.G. is supported by a Career Development Fellowship of the Australian National Health and Medical Research Council (APP1163693). Shuai Li is supported by an Early Career Research Fellowship of the Victorian Cancer Agency (ECRF 19020). M.C.S. is a NHMRC Senior Research Fellow (APP1155163). J.L.H. is a NHMRC Senior Principal Research Fellow. The Australian Mammographic Density Twins and Sisters Study (AMDTSS) was facilitated through access to Twins Research Australia, a national resource supported by a Centre of Research Excellence Grant (1079102) from the NHMRC. The AMDTSS was supported by NHMRC (1050561 and 1079102), Cancer Australia and National Breast Cancer Foundation (509307). The raw and processed DNA methylation data set are open accessed or free on Gene Expression Omnibus (accession number GSE100227). As required by the ethics approval, the authors are not allowed to open other data (e.g., data on covariates) used in this study in order to protect the privacy of participants. If anyone wants to use the data to repeat our analyses or to perform other research, please contact J.L.H. (j.hopper@unimelb. edu.au), who is happy to engage with external collaborators. This person would have to be added to the ethics approval to access the data. Working with the AMDTSS group as collaborators would likely result in better science given this is family data and the nuances of this, as well as the sampling issues, need to be understood to guard against making false conclusions from a naïve use of data without such knowledge.
Publisher Copyright:
© 2021, Public Health Services, US Dept of Health and Human Services. All rights reserved.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/8
Y1 - 2021/8
N2 - BACKGROUND: High surrounding greenness has many health benefits and might contribute to slower biological aging. However, very few studies have evaluated this from the perspective of epigenetics. OBJECTIVES: We aimed to evaluate the association between surrounding greenness and biological aging based on DNA methylation. METHODS: We derived Horvath’s DNA methylation age (DNAmAge), Hannum’s DNAmAge, PhenoAge, and GrimAge based on DNA methylation measured in peripheral blood samples from 479 Australian women in 130 families. Measures of DNAmAge acceleration (DNAmAgeAC) were derived from the residuals after regressing each DNAmAge metric on chronological age. Greenness was represented by satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) metrics within 300-, 500-, 1,000-, and 2,000-m buffers surrounding par-ticipant addresses. Greenness-DNAmAgeAC associations were estimated using a within-sibship design fitted by linear mixed effect models, adjusting for familial clustering and important covariates. RESULTS: Greenness metrics were associated with significantly lower DNAmAgeAC based on GrimAge acceleration, suggesting slower biological aging with higher greenness based on both NDVI and EVI in 300–2,000 m buffer areas. For example, each interquartile range increase in NDVI within 1,000 m was associated with a 0.59 (95% CI: 0.18, 1.01)–year decrease in GrimAge acceleration. Greenness was also inversely associated with three of the eight components of GrimAge, specifically, DNA methylation-based surrogates of serum cystatin-C, serum growth differentiation factor 15, and smoking pack years. Associations between greenness and biological aging measured by Horvath’s and Hannum’s DNAmAgeAC were less consistent, and depended on neighborhood socioeconomic status. No significant associations were estimated for PhenoAge acceleration. DISCUSSION: Higher surrounding greenness was associated with slower biological aging, as indicated by GrimAge age acceleration, in Australian women. Associations were also evident for three individual components of GrimAge, but were inconsistent for other measures of biological aging. Additional studies are needed to confirm our results. https://doi.org/10.1289/EHP8793.
AB - BACKGROUND: High surrounding greenness has many health benefits and might contribute to slower biological aging. However, very few studies have evaluated this from the perspective of epigenetics. OBJECTIVES: We aimed to evaluate the association between surrounding greenness and biological aging based on DNA methylation. METHODS: We derived Horvath’s DNA methylation age (DNAmAge), Hannum’s DNAmAge, PhenoAge, and GrimAge based on DNA methylation measured in peripheral blood samples from 479 Australian women in 130 families. Measures of DNAmAge acceleration (DNAmAgeAC) were derived from the residuals after regressing each DNAmAge metric on chronological age. Greenness was represented by satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) metrics within 300-, 500-, 1,000-, and 2,000-m buffers surrounding par-ticipant addresses. Greenness-DNAmAgeAC associations were estimated using a within-sibship design fitted by linear mixed effect models, adjusting for familial clustering and important covariates. RESULTS: Greenness metrics were associated with significantly lower DNAmAgeAC based on GrimAge acceleration, suggesting slower biological aging with higher greenness based on both NDVI and EVI in 300–2,000 m buffer areas. For example, each interquartile range increase in NDVI within 1,000 m was associated with a 0.59 (95% CI: 0.18, 1.01)–year decrease in GrimAge acceleration. Greenness was also inversely associated with three of the eight components of GrimAge, specifically, DNA methylation-based surrogates of serum cystatin-C, serum growth differentiation factor 15, and smoking pack years. Associations between greenness and biological aging measured by Horvath’s and Hannum’s DNAmAgeAC were less consistent, and depended on neighborhood socioeconomic status. No significant associations were estimated for PhenoAge acceleration. DISCUSSION: Higher surrounding greenness was associated with slower biological aging, as indicated by GrimAge age acceleration, in Australian women. Associations were also evident for three individual components of GrimAge, but were inconsistent for other measures of biological aging. Additional studies are needed to confirm our results. https://doi.org/10.1289/EHP8793.
UR - http://www.scopus.com/inward/record.url?scp=85114163832&partnerID=8YFLogxK
U2 - 10.1289/EHP8793
DO - 10.1289/EHP8793
M3 - Article
C2 - 34460342
AN - SCOPUS:85114163832
SN - 0091-6765
VL - 129
JO - Environmental Health Perspectives
JF - Environmental Health Perspectives
IS - 8
M1 - 087007
ER -
