Socioeconomic Inequalities and Molecular Risk for Aging in Young Adulthood

Cecilia Potente; Justin Chumbley; Wenjia Xu; Brandt Levitt; Steven W Cole; Sudharshan Ravi; Julien Stephane Bodelet; Lauren Gaydosh; Kathleen Mullan Harris; Michael J Shanahan

doi:10.1093/aje/kwad155

Socioeconomic Inequalities and Molecular Risk for Aging in Young Adulthood

Cecilia Potente, Justin Chumbley, Wenjia Xu, Brandt Levitt, Steven W Cole, Sudharshan Ravi, Julien Stephane Bodelet, Lauren Gaydosh, Kathleen Mullan Harris, Michael J Shanahan

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Abstract

Diverse manifestations of biological aging often reflect disparities in socioeconomic status (SES). In this paper, we examine associations between indicators of SES and an mRNA-based aging signature during young adulthood, before clinical indications of aging are common. We use data from wave V (2016-2018) of the National Longitudinal Study of Adolescent to Adult Health, a nationally representative study of adults aged 33-43 years, with transcriptomic data from a subset of 2,491 participants. Biological aging is measured using 1) a composite transcriptomic aging signature previously identified by Peters et al.'s out-of-sample meta-analysis (Nat Commun. 2015;6:8570) and 2) 9 subsets that represent functional pathways of coexpressed genes. SES refers to income, education, occupation, subjective social status, and a composite measure combining these 4 dimensions. We examine hypothesized mechanisms through which SES could affect aging: body mass index, smoking, health insurance status, difficulty paying bills, and psychosocial stress. We find that SES - especially the composite measure and income - is associated with transcriptomic aging and immune, mitochondrial, ribosomal, lysosomal, and proteomal pathways. Counterfactual mediational models suggest that the mediators partially account for these associations. The results thus reveal that numerous biological pathways associated with aging are already linked to SES in young adulthood.

Original language	English
Article number	kwad155
Pages (from-to)	1981-1990
Number of pages	10
Journal	American Journal of Epidemiology
Volume	192
Issue number	12
Early online date	11 Jul 2023
DOIs	https://doi.org/10.1093/aje/kwad155
Publication status	Published - 1 Dec 2023
Externally published	Yes

Bibliographical note

Funding information:
M.J.S. and K.M.H. acknowledge receiving support from National Institutes of Health grants R01-HD087061, P30-AG017265, R01-AG043404, and R01-AG033590; M.J.S. acknowledges receiving support from the Swiss
National Science Foundation (grant 10531C_197964, “Social Status and the Regulation of the Genome: Longitudinal and Cross-Species Studies”); and C.P., J.C., W.X., S.R., J.S.B., and M.J.S. acknowledge receiving support from the Jacobs Center for Productive Youth Development, University of Zürich. This research used data from Add Health, a program project directed by K.M.H., designed by Drs. J. Richard Udry, Peter S. Bearman, and K.M.H. at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations.

Copyright:
© The Author(s) 2023. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

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kwad155Final published version, 578 KBLicence: CC BY-NC

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title = "Socioeconomic Inequalities and Molecular Risk for Aging in Young Adulthood",

abstract = "Diverse manifestations of biological aging often reflect disparities in socioeconomic status (SES). In this paper, we examine associations between indicators of SES and an mRNA-based aging signature during young adulthood, before clinical indications of aging are common. We use data from wave V (2016-2018) of the National Longitudinal Study of Adolescent to Adult Health, a nationally representative study of adults aged 33-43 years, with transcriptomic data from a subset of 2,491 participants. Biological aging is measured using 1) a composite transcriptomic aging signature previously identified by Peters et al.'s out-of-sample meta-analysis (Nat Commun. 2015;6:8570) and 2) 9 subsets that represent functional pathways of coexpressed genes. SES refers to income, education, occupation, subjective social status, and a composite measure combining these 4 dimensions. We examine hypothesized mechanisms through which SES could affect aging: body mass index, smoking, health insurance status, difficulty paying bills, and psychosocial stress. We find that SES - especially the composite measure and income - is associated with transcriptomic aging and immune, mitochondrial, ribosomal, lysosomal, and proteomal pathways. Counterfactual mediational models suggest that the mediators partially account for these associations. The results thus reveal that numerous biological pathways associated with aging are already linked to SES in young adulthood.",

author = "Cecilia Potente and Justin Chumbley and Wenjia Xu and Brandt Levitt and Cole, {Steven W} and Sudharshan Ravi and Bodelet, {Julien Stephane} and Lauren Gaydosh and Harris, {Kathleen Mullan} and Shanahan, {Michael J}",

note = "Funding information: M.J.S. and K.M.H. acknowledge receiving support from National Institutes of Health grants R01-HD087061, P30-AG017265, R01-AG043404, and R01-AG033590; M.J.S. acknowledges receiving support from the Swiss National Science Foundation (grant 10531C_197964, “Social Status and the Regulation of the Genome: Longitudinal and Cross-Species Studies”); and C.P., J.C., W.X., S.R., J.S.B., and M.J.S. acknowledge receiving support from the Jacobs Center for Productive Youth Development, University of Z{\"u}rich. This research used data from Add Health, a program project directed by K.M.H., designed by Drs. J. Richard Udry, Peter S. Bearman, and K.M.H. at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Copyright: {\textcopyright} The Author(s) 2023. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.",

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AU - Chumbley, Justin

AU - Xu, Wenjia

AU - Levitt, Brandt

AU - Cole, Steven W

AU - Ravi, Sudharshan

AU - Bodelet, Julien Stephane

AU - Gaydosh, Lauren

AU - Harris, Kathleen Mullan

AU - Shanahan, Michael J

N1 - Funding information: M.J.S. and K.M.H. acknowledge receiving support from National Institutes of Health grants R01-HD087061, P30-AG017265, R01-AG043404, and R01-AG033590; M.J.S. acknowledges receiving support from the Swiss National Science Foundation (grant 10531C_197964, “Social Status and the Regulation of the Genome: Longitudinal and Cross-Species Studies”); and C.P., J.C., W.X., S.R., J.S.B., and M.J.S. acknowledge receiving support from the Jacobs Center for Productive Youth Development, University of Zürich. This research used data from Add Health, a program project directed by K.M.H., designed by Drs. J. Richard Udry, Peter S. Bearman, and K.M.H. at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Copyright: © The Author(s) 2023. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

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N2 - Diverse manifestations of biological aging often reflect disparities in socioeconomic status (SES). In this paper, we examine associations between indicators of SES and an mRNA-based aging signature during young adulthood, before clinical indications of aging are common. We use data from wave V (2016-2018) of the National Longitudinal Study of Adolescent to Adult Health, a nationally representative study of adults aged 33-43 years, with transcriptomic data from a subset of 2,491 participants. Biological aging is measured using 1) a composite transcriptomic aging signature previously identified by Peters et al.'s out-of-sample meta-analysis (Nat Commun. 2015;6:8570) and 2) 9 subsets that represent functional pathways of coexpressed genes. SES refers to income, education, occupation, subjective social status, and a composite measure combining these 4 dimensions. We examine hypothesized mechanisms through which SES could affect aging: body mass index, smoking, health insurance status, difficulty paying bills, and psychosocial stress. We find that SES - especially the composite measure and income - is associated with transcriptomic aging and immune, mitochondrial, ribosomal, lysosomal, and proteomal pathways. Counterfactual mediational models suggest that the mediators partially account for these associations. The results thus reveal that numerous biological pathways associated with aging are already linked to SES in young adulthood.

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DO - 10.1093/aje/kwad155

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JF - American Journal of Epidemiology

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Socioeconomic Inequalities and Molecular Risk for Aging in Young Adulthood

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