ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2019
Whole Blood Gene Expression Associated With Clinical Biological Age.
Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- Molecular markers, mechanisms and metrics of biological aging: a scoping review.Frontiers in aging · 2026Review
- Biological age prediction and NAFLD risk assessment: a machine learning model based on a multicenter population in Nanchang, Jiangxi, China.BMC gastroenterology · 2025Article
- An accurate aging clock developed from large-scale gut microbiome and human gene expression data.iScience · 2024Article
- A machine learning-based data mining in medical examination data: a biological features-based biological age prediction model.BMC bioinformatics · 2022Article
- Utilization of Host and Microbiome Features in Determination of Biological Aging.Microorganisms · 2022Review
- Article
- Correction for both common and rare cell types in blood is important to identify genes that correlate with age.BMC genomics · 2021Article
- Low muscle strength and increased arterial stiffness go hand in hand.Scientific reports · 2021Observational
- Cytotoxic lymphocytes are dysregulated in multisystem inflammatory syndrome in children.medRxiv : the preprint server for health sciences · 2020Article
- Genetic factors for short life span associated with evolution of the loss of flight ability.Ecology and evolution · 2020Article
- Allele-Specific Transcript Abundance: A Pilot Study in Healthy Centenarians.The journals of gerontology. Series A, Biological sciences and medical sciences · 2020Article
- Klotho Gene in Human Salt-Sensitive Hypertension.Clinical journal of the American Society of Nephrology : CJASN · 2020Article
- Multi-Omic Biological Age Estimation and Its Correlation With Wellness and Disease Phenotypes: A Longitudinal Study of 3,558 Individuals.The journals of gerontology. Series A, Biological sciences and medical sciences · 2019Article
- A Model of Evolutionary Selection: The Cardiovascular Protective Function of the Longevity Associated Variant of BPIFB4.International journal of molecular sciences · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
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.
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