ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2018
Population Specific Biomarkers of Human Aging: A Big Data Study Using South Korean, Canadian, and Eastern European Patient Populations.
Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
92 citing papers in PubMed, 191 citations in OpenAlex.
- Trial
- Reverse causal relationship between periodontitis and shortened telomere length: Bidirectional two-sample Mendelian random analysis.Frontiers in immunology · 2022Trial
- Frequent Sweetened Beverage Consumption Is Associated With Accelerated Biological Aging: Evidence From a Population-Based Study and Gut Microbiota Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Artificial intelligence approaches in biological age prediction: current status and challenges.British journal of biomedical science · 2026Review
- Molecular markers, mechanisms and metrics of biological aging: a scoping review.Frontiers in aging · 2026Review
- Improving Face Age Prediction by Using Multiple-Angle Photos.Computational and structural biotechnology journal · 2026Article
- A sex-adjusted 7-biomarker clinical aging clock for translational preventative medicine.Scientific reports · 2025Article
- Biomarkers of ageing of humans and non-human primates.Nature reviews. Molecular cell biology · 2025Review
- Leveraging Artificial Intelligence and Modulation of Oxidative Stressors to Enhance Healthspan and Radical Longevity.Biomolecules · 2025Review
- How to measure and model cardiovascular aging.Cardiovascular research · 2025Review
- Age-related diseases as a testbed for anti-aging therapeutics: the case of idiopathic pulmonary fibrosis.Aging · 2025Review
- Age Estimation From Blood Test Results Using a Random Forest Model.Journal of clinical laboratory analysis · 2025Article
- Biological age prediction using a DNN model based on pathways of steroidogenesis.Science advances · 2025Article
- Biological age prediction and NAFLD risk assessment: a machine learning model based on a multicenter population in Nanchang, Jiangxi, China.BMC gastroenterology · 2025Article
- Association of clinical biomarker-based biological age and aging trajectory with cardiovascular disease and all-cause mortality in Chinese adults: a population-based cohort study.BMC public health · 2025Article
- Deep learning and generative artificial intelligence in aging research and healthy longevity medicine.Aging · 2025Review
- Histone mark age of human tissues and cell types.Science advances · 2025Article
- Development and validation of deep learning- and ensemble learning-based biological ages in the NHANES study.Frontiers in aging neuroscience · 2025Article
- The association of biological age and its trajectory with incident heart failure: a cohort study from China.Frontiers in cardiovascular medicine · 2025Article
- Prediction of biological age using machine learning.PloS one · 2025Article
32 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 5 institutions in 6 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate and physiologically meaningful biomarkers for human aging are key to assessing antiaging therapies. Given ethnic differences in health, diet, lifestyle, behavior, environmental exposures, and even average rate of biological aging, it stands to reason that aging clocks trained on datasets obtained from specific ethnic populations are more likely to account for these potential confounding factors, resulting in an enhanced capacity to predict chronological age and quantify biological age. Here, we present a deep learning-based hematological aging clock modeled using the large combined dataset of Canadian, South Korean, and Eastern European population blood samples that show increased predictive accuracy in individual populations compared to population specific hematologic aging clocks. The performance of models was also evaluated on publicly available samples of the American population from the National Health and Nutrition Examination Survey (NHANES). In addition, we explored the association between age predicted by both population specific and combined hematological clocks and all-cause mortality. Overall, this study suggests (a) the population specificity of aging patterns and (b) hematologic clocks predicts all-cause mortality. The proposed models were added to the freely-available Aging.AI system expanding the range of tools for analysis of human aging.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.