ArticleNature aging2024
Longitudinal machine learning uncouples healthy aging factors from chronic disease risks.
Article in Nature aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 15 citations in OpenAlex.
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- Subtle Laboratory and Clinical Precursors of Celiac Disease in Young Adults: A Large-Scale Retrospective Cohort Study.Journal of general internal medicine · 2026Article
- Isolated ventricular septal defect is not a risk factor for celiac disease: evidence from a large real-world data cohort of 493,382 children.Frontiers in pediatrics · 2026Article
- Nurses as guardians of time: the hidden clinical value of continuous care in geriatrics.Frontiers in public health · 2026Review
- Autophagy in kidney physiology: from cellular quality control to organ metabolism.Autophagy reports · 2026Review
- Low serum IgE is associated with an increased risk of chronic lymphocytic leukemia: a large retrospective cohort study.Frontiers in immunology · 2026Observational
- Immunosenescence in aging and neurodegenerative diseases: evidence, key hallmarks, and therapeutic implications.Translational neurodegeneration · 2025Review
- Pregnancy and postpartum dynamics revealed by millions of lab tests.Science advances · 2025Article
- High-dimensional mediation analysis reveals the mediating role of physical activity patterns in genetic pathways leading to AD-like brain atrophy.BioData mining · 2025Article
- Pathological mechanisms of kidney disease in ageing.Nature reviews. Nephrology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
To understand human longevity, inherent aging processes must be distinguished from known etiologies leading to age-related chronic diseases. Such deconvolution is difficult to achieve because it requires tracking patients throughout their entire lives. Here, we used machine learning to infer health trajectories over the entire adulthood age range using extrapolation from electronic medical records with partial longitudinal coverage. Using this approach, our model tracked the state of patients who were healthy and free from known chronic disease risk and distinguished individuals with higher or lower longevity potential using a multivariate score. We showed that the model and the markers it uses performed consistently on data from Israeli, British and US populations. For example, mildly low neutrophil counts and alkaline phosphatase levels serve as early indicators of healthy aging that are independent of risk for major chronic diseases. We characterize the heritability and genetic associations of our longevity score and demonstrate at least 1 year of extended lifespan for parents of high-scoring patients compared to matched controls. Longitudinal modeling of healthy individuals is thereby established as a tool for understanding healthy aging and longevity.
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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.