ArticleAging2018
Quantitative characterization of biological age and frailty based on locomotor activity records.
Article in Aging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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
24 citing papers in PubMed.
- Molecular markers, mechanisms and metrics of biological aging: a scoping review.Frontiers in aging · 2026Review
- Recommendations for biomarker data collection in clinical trials by longevity biotechnology companies.npj aging · 2025Article
- Association of biological age acceleration with mortality in adults with diabetes or prediabetes: a mediating role of physical activity.Aging clinical and experimental research · 2025Article
- Biomarkers of aging: from molecules and surrogates to physiology and function.Physiological reviews · 2025Review
- Multimodal Transformers and Their Applications in Drug Target Discovery for Aging and Age-Related Diseases.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024Review
- Principal component-based clinical aging clocks identify signatures of healthy aging and targets for clinical intervention.Nature aging · 2024Article
- Towards Healthy Longevity: Comprehensive Insights from Molecular Targets and Biomarkers to Biological Clocks.International journal of molecular sciences · 2024Review
- Clarifying the biological and statistical assumptions of cross-sectional biological age predictors: an elaborate illustration using synthetic and real data.BMC medical research methodology · 2024Article
- Stratification of Companion Animal Life Stages from Electronic Medical Record Diagnosis Data.The journals of gerontology. Series A, Biological sciences and medical sciences · 2023Article
- Measuring biological age using omics data.Nature reviews. Genetics · 2022Review
- Interpretable machine learning for high-dimensional trajectories of aging health.PLoS computational biology · 2022Article
- LipidClock: A Lipid-Based Predictor of Biological Age.Frontiers in aging · 2022Article
- Article
- Longitudinal analysis of blood markers reveals progressive loss of resilience and predicts human lifespan limit.Nature communications · 2021Article
- Deep learning for biological age estimation.Briefings in bioinformatics · 2021Review
- Article
- Biological Age Prediction From Wearable Device Movement Data Identifies Nutritional and Pharmacological Interventions for Healthy Aging.Frontiers in aging · 2021Article
- Genetic and phenotypic analysis of the causal relationship between aging and COVID-19.Communications medicine · 2021Article
- Can Blood-Circulating Factors Unveil and Delay Your Biological Aging?Biomedicines · 2020Review
- Multidimensional phenotyping predicts lifespan and quantifies health in Caenorhabditis elegans.PLoS computational biology · 2020Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
We performed a systematic evaluation of the relationships between locomotor activity and signatures of frailty, morbidity, and mortality risks using physical activity records from the 2003-2006 National Health and Nutrition Examination Survey (NHANES) and UK BioBank (UKB). We proposed a statistical description of the locomotor activity tracks and transformed the provided time series into vectors representing physiological states for each participant. The Principal Component Analysis of the transformed data revealed a winding trajectory with distinct segments corresponding to subsequent human development stages. The extended linear phase starts from 35-40 years old and is associated with the exponential increase of mortality risks according to the Gompertz mortality law. We characterized the distance traveled along the aging trajectory as a natural measure of biological age and demonstrated its significant association with frailty and hazardous lifestyles, along with the remaining lifespan and healthspan of an individual. The biological age explained most of the variance of the log-hazard ratio that was obtained by fitting directly to mortality and the incidence of chronic diseases. Our findings highlight the intimate relationship between the supervised and unsupervised signatures of the biological age and frailty, a consequence of the low intrinsic dimensionality of the aging dynamics.
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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.