ArticleCell research2015
Three-dimensional human facial morphologies as robust aging markers.
Article in Cell research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.
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Who cites it
63 citing papers in PubMed.
- Protein profiling reveals consequences of lifestyle choices on predicted biological aging.Scientific reports · 2015Trial
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- IDEAL-Age: an interpretable deep learning framework for single-cell resolution profiling of immunological aging.Genome biology · 2026Article
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- Activating the vagus nerve-adrenal anti-inflammatory axis to delay aging: A randomized controlled trial protocol.Contemporary clinical trials communications · 2026Article
- The BHARAT study: a multi-modal, multi-omics investigation of aging signatures in the Indian population.Aging · 2026Observational
- Distinct roles of chronotype, daytime napping, and sleep duration in biological and functional aging: a univariable and multivariable Mendelian randomization study.Clinical epigenetics · 2026Article
- Body Mass Index and Facial Aging: Mendelian Randomization and Exploratory Target Prioritization.Clinical, cosmetic and investigational dermatology · 2026Article
- Improving Face Age Prediction by Using Multiple-Angle Photos.Computational and structural biotechnology journal · 2026Article
- Biomarkers of ageing of humans and non-human primates.Nature reviews. Molecular cell biology · 2025Review
- Association between the retinal age gap and systemic diseases in the Japanese population: the Nagahama study.Japanese journal of ophthalmology · 2025Article
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- Deep learning reveals diverging effects of altitude on aging.GeroScience · 2025Article
- Innovations in aging biology: highlights from the ARDD emerging science & technologies workshop.npj aging · 2025Article
- Article
- From bench to bedside: translational insights into aging research.Frontiers in aging · 2025Review
- Impact of childhood maltreatment on aging: a comprehensive Mendelian randomization analysis of multiple age-related biomarkers.Clinical epigenetics · 2024Article
- Prediagnosis recognition of acute ischemic stroke by artificial intelligence from facial images.Aging cell · 2024Article
- Coordinate-wise monotonic transformations enable privacy-preserving age estimation with 3D face point cloud.Science China. Life sciences · 2024Article
- Accurate estimation of biological age and its application in disease prediction using a multimodal image Transformer system.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
3 more citing papers are in PubMed but not listed here.
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11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aging is associated with many complex diseases. Reliable prediction of the aging process is important for assessing the risks of aging-associated diseases. However, despite intense research, so far there is no reliable aging marker. Here we addressed this problem by examining whether human 3D facial imaging features could be used as reliable aging markers. We collected > 300 3D human facial images and blood profiles well-distributed across ages of 17 to 77 years. By analyzing the morphological profiles, we generated the first comprehensive map of the aging human facial phenome. We identified quantitative facial features, such as eye slopes, highly associated with age. We constructed a robust age predictor and found that on average people of the same chronological age differ by ± 6 years in facial age, with the deviations increasing after age 40. Using this predictor, we identified slow and fast agers that are significantly supported by levels of health indicators. Despite a close relationship between facial morphological features and health indicators in the blood, facial features are more reliable aging biomarkers than blood profiles and can better reflect the general health status than chronological age.
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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.