Whole Blood Gene Expression Associated With Clinical Biological Age

Honghuang Lin, Kathryn L Lunetta, Qiang Zhao, Pooja R Mandaviya, Jian Rong, Emelia J Benjamin, Roby Joehanes, Daniel Levy, Joyce B J van Meurs, Martin G Larson, Joanne M Murabito

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background: Biologic age may better reflect an individual's rate of aging than chronologic age.

Methods: We conducted a transcriptome-wide association study with biologic age estimated with clinical biomarkers, which included: systolic blood pressure, forced expiratory volume at 1 second (FEV1), total cholesterol, fasting glucose, C-reactive protein, and serum creatinine. We assessed the association between the difference between biologic age and chronologic age (∆age) and gene expression in whole blood measured using the Affymetrix Human Exon 1.0st Array.

Results: Our discovery sample included 2,163 participants from the Framingham Offspring cohort (mean age 67 ± 9 years, 55% women). A total of 481 genes were significantly associated with ∆age (p < 2.8 × 10-6). Among them, 415 genes were validated (p < .05/481 = 1.0 × 10-4) in 2,946 participants from the Framingham Third Generation cohort (mean age 46 ± 9 years, 53% women). Many of the significant genes were involved in the ubiquitin-mediated proteolysis pathway. The replication in 414 Rotterdam Study participants (mean age 59 ± 8, 52% women) found 104 of 415 validated genes reached nominal significance (p < .05).

Conclusion: We identified and validated 415 genes associated with ∆age in a community-based cohort. Future functional characterization of the biologic age-related gene network may identify targets to test for interventions to delay aging in older adults.

Original languageEnglish
Pages (from-to)81-88
Number of pages8
JournalJournals of Gerontology Series A-Biological Sciences and Medical Sciences
Volume74
Issue number1
DOIs
Publication statusPublished - Jan 2019

Keywords

  • ARRAY
  • Biologic aging
  • Epidemiology
  • Gene expression
  • HAPLOTYPES
  • KINASE
  • MORTALITY
  • PRESSURE
  • WIDE ASSOCIATION

Cite this

Lin, Honghuang ; Lunetta, Kathryn L ; Zhao, Qiang ; Mandaviya, Pooja R ; Rong, Jian ; Benjamin, Emelia J ; Joehanes, Roby ; Levy, Daniel ; van Meurs, Joyce B J ; Larson, Martin G ; Murabito, Joanne M. / Whole Blood Gene Expression Associated With Clinical Biological Age. In: Journals of Gerontology Series A-Biological Sciences and Medical Sciences. 2019 ; Vol. 74, No. 1. pp. 81-88.
@article{b58f9fc086de488888a25ec53b1c39e6,
title = "Whole Blood Gene Expression Associated With Clinical Biological Age",
abstract = "Background: Biologic age may better reflect an individual's rate of aging than chronologic age.Methods: We conducted a transcriptome-wide association study with biologic age estimated with clinical biomarkers, which included: systolic blood pressure, forced expiratory volume at 1 second (FEV1), total cholesterol, fasting glucose, C-reactive protein, and serum creatinine. We assessed the association between the difference between biologic age and chronologic age (∆age) and gene expression in whole blood measured using the Affymetrix Human Exon 1.0st Array.Results: Our discovery sample included 2,163 participants from the Framingham Offspring cohort (mean age 67 ± 9 years, 55{\%} women). A total of 481 genes were significantly associated with ∆age (p < 2.8 × 10-6). Among them, 415 genes were validated (p < .05/481 = 1.0 × 10-4) in 2,946 participants from the Framingham Third Generation cohort (mean age 46 ± 9 years, 53{\%} women). Many of the significant genes were involved in the ubiquitin-mediated proteolysis pathway. The replication in 414 Rotterdam Study participants (mean age 59 ± 8, 52{\%} women) found 104 of 415 validated genes reached nominal significance (p < .05).Conclusion: We identified and validated 415 genes associated with ∆age in a community-based cohort. Future functional characterization of the biologic age-related gene network may identify targets to test for interventions to delay aging in older adults.",
keywords = "ARRAY, Biologic aging, Epidemiology, Gene expression, HAPLOTYPES, KINASE, MORTALITY, PRESSURE, WIDE ASSOCIATION",
author = "Honghuang Lin and Lunetta, {Kathryn L} and Qiang Zhao and Mandaviya, {Pooja R} and Jian Rong and Benjamin, {Emelia J} and Roby Joehanes and Daniel Levy and {van Meurs}, {Joyce B J} and Larson, {Martin G} and Murabito, {Joanne M}",
year = "2019",
month = "1",
doi = "10.1093/gerona/gly164",
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Lin, H, Lunetta, KL, Zhao, Q, Mandaviya, PR, Rong, J, Benjamin, EJ, Joehanes, R, Levy, D, van Meurs, JBJ, Larson, MG & Murabito, JM 2019, 'Whole Blood Gene Expression Associated With Clinical Biological Age', Journals of Gerontology Series A-Biological Sciences and Medical Sciences, vol. 74, no. 1, pp. 81-88. https://doi.org/10.1093/gerona/gly164

Whole Blood Gene Expression Associated With Clinical Biological Age. / Lin, Honghuang; Lunetta, Kathryn L; Zhao, Qiang; Mandaviya, Pooja R; Rong, Jian; Benjamin, Emelia J; Joehanes, Roby; Levy, Daniel; van Meurs, Joyce B J; Larson, Martin G; Murabito, Joanne M.

In: Journals of Gerontology Series A-Biological Sciences and Medical Sciences, Vol. 74, No. 1, 01.2019, p. 81-88.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Whole Blood Gene Expression Associated With Clinical Biological Age

AU - Lin, Honghuang

AU - Lunetta, Kathryn L

AU - Zhao, Qiang

AU - Mandaviya, Pooja R

AU - Rong, Jian

AU - Benjamin, Emelia J

AU - Joehanes, Roby

AU - Levy, Daniel

AU - van Meurs, Joyce B J

AU - Larson, Martin G

AU - Murabito, Joanne M

PY - 2019/1

Y1 - 2019/1

N2 - Background: Biologic age may better reflect an individual's rate of aging than chronologic age.Methods: We conducted a transcriptome-wide association study with biologic age estimated with clinical biomarkers, which included: systolic blood pressure, forced expiratory volume at 1 second (FEV1), total cholesterol, fasting glucose, C-reactive protein, and serum creatinine. We assessed the association between the difference between biologic age and chronologic age (∆age) and gene expression in whole blood measured using the Affymetrix Human Exon 1.0st Array.Results: Our discovery sample included 2,163 participants from the Framingham Offspring cohort (mean age 67 ± 9 years, 55% women). A total of 481 genes were significantly associated with ∆age (p < 2.8 × 10-6). Among them, 415 genes were validated (p < .05/481 = 1.0 × 10-4) in 2,946 participants from the Framingham Third Generation cohort (mean age 46 ± 9 years, 53% women). Many of the significant genes were involved in the ubiquitin-mediated proteolysis pathway. The replication in 414 Rotterdam Study participants (mean age 59 ± 8, 52% women) found 104 of 415 validated genes reached nominal significance (p < .05).Conclusion: We identified and validated 415 genes associated with ∆age in a community-based cohort. Future functional characterization of the biologic age-related gene network may identify targets to test for interventions to delay aging in older adults.

AB - Background: Biologic age may better reflect an individual's rate of aging than chronologic age.Methods: We conducted a transcriptome-wide association study with biologic age estimated with clinical biomarkers, which included: systolic blood pressure, forced expiratory volume at 1 second (FEV1), total cholesterol, fasting glucose, C-reactive protein, and serum creatinine. We assessed the association between the difference between biologic age and chronologic age (∆age) and gene expression in whole blood measured using the Affymetrix Human Exon 1.0st Array.Results: Our discovery sample included 2,163 participants from the Framingham Offspring cohort (mean age 67 ± 9 years, 55% women). A total of 481 genes were significantly associated with ∆age (p < 2.8 × 10-6). Among them, 415 genes were validated (p < .05/481 = 1.0 × 10-4) in 2,946 participants from the Framingham Third Generation cohort (mean age 46 ± 9 years, 53% women). Many of the significant genes were involved in the ubiquitin-mediated proteolysis pathway. The replication in 414 Rotterdam Study participants (mean age 59 ± 8, 52% women) found 104 of 415 validated genes reached nominal significance (p < .05).Conclusion: We identified and validated 415 genes associated with ∆age in a community-based cohort. Future functional characterization of the biologic age-related gene network may identify targets to test for interventions to delay aging in older adults.

KW - ARRAY

KW - Biologic aging

KW - Epidemiology

KW - Gene expression

KW - HAPLOTYPES

KW - KINASE

KW - MORTALITY

KW - PRESSURE

KW - WIDE ASSOCIATION

U2 - 10.1093/gerona/gly164

DO - 10.1093/gerona/gly164

M3 - Article

C2 - 30010802

VL - 74

SP - 81

EP - 88

JO - Journals of Gerontology Series A-Biological Sciences and Medical Sciences

JF - Journals of Gerontology Series A-Biological Sciences and Medical Sciences

SN - 1079-5006

IS - 1

ER -