ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2020
Biomarkers for Aging Identified in Cross-sectional Studies Tend to Be Non-causative.
Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
What it found
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Who cites it
41 citing papers in PubMed.
- Aptamer-Based Platforms for Human Aging Biomarkers: Multiplexed Proteomics, Biosensors and Translational Perspectives.International journal of molecular sciences · 2026Review
- Liver Aging Index: A Noninvasive Score for Liver Biological Aging and Liver-Related Outcomes in Multicohorts.Aging cell · 2026Article
- Proteomic aging clocks in epidemiological studies: advances, applications and prospects.Nature aging · 2026Review
- Longitudinal changes in epigenetic clocks predict survival in the InCHIANTI cohort.Nature aging · 2026Article
- A streamlined CMR-derived machine-learning model for estimating cardiovascular biological age: development and validation in the UK-biobank and multi-ethnic study of atherosclerosis.European heart journal. Cardiovascular Imaging · 2026Article
- Does leisure activity matter for epigenetic aging? Analyses of arts engagement and physical activity in the UK Household Longitudinal Study.Innovation in aging · 2026Article
- How and why does aging occur? Updating evolutionary theory to meet a new era of data.Evolution, medicine, and public health · 2026Article
- Review
- Protein Catabolites as Blood-Based Biomarkers of Aging Physiology: Findings From the Dog Aging Project.Aging cell · 2025Article
- TranslAGE: A Comprehensive Platform for Systematic Validation of Epigenetic Aging Biomarkers.bioRxiv : the preprint server for biology · 2025Article
- Does frequency or diversity of leisure activity matter more for epigenetic ageing? Analyses of arts engagement and physical activity.medRxiv : the preprint server for health sciences · 2025Article
- Systems Age: a single blood methylation test to quantify aging heterogeneity across 11 physiological systems.Nature aging · 2025Article
- Article
- Epigenetic Clocks Relate to 4 Age-related Health Outcomes Similarly Across 3 Countries.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- Article
- There Are Multiple Clocks That Time Us: Cross-Sectional and Longitudinal Associations Among 14 Alternative Indicators of Age and Aging.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- Cross-trait multivariate GWAS confirms health implications of pubertal timing.Nature communications · 2025Article
- Estimation of physiological aging based on routine clinical biomarkers: a prospective cohort study in elderly Chinese and the UK Biobank.BMC medicine · 2024Article
- Epigenetics, Microbiome and Personalized Medicine: Focus on Kidney Disease.International journal of molecular sciences · 2024Review
- Spatiotemporal transcriptomic profiling and modeling of mouse brain at single-cell resolution reveals cell proximity effects of aging and rejuvenation.bioRxiv : the preprint server for biology · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Biomarkers are important tools for diagnosis, prognosis, and identification of the causal factors of physiological conditions. Biomarkers are typically identified by correlating biological measurements with the status of a condition in a sample of subjects. Cross-sectional studies sample subjects at a single timepoint, whereas longitudinal studies follow a cohort through time. Identifying biomarkers of aging is subject to unique challenges. Individuals who age faster have intrinsically higher mortality rates and so are preferentially lost over time, in a phenomenon known as cohort selection. In this article, we use simulations to show that cohort selection biases cross-sectional analysis away from identifying causal loci of aging, to the point where cross-sectional studies are less likely to identify loci that cause aging than if loci had been chosen at random. We go on to show this bias can be corrected by incorporating correlates of mortality identified from longitudinal studies, allowing cross-sectional studies to effectively identify the causal factors of aging.
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