ArticleAging cell2021
BiT age: A transcriptome-based aging clock near the theoretical limit of accuracy.
Article in Aging cell, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers.
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Who cites it
97 citing papers in PubMed, 160 citations in OpenAlex.
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- Enteric viral infections promote systemic accelerated aging inScience advances · 2026Article
- Collagen gene expression is linked to aging and lifespan extension inMatrix biology plus · 2026Article
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- The Evolving Landscape of Clinical Aging Clocks: From Epigenetic to Multi-Omics Integration.Aging cell · 2026Review
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- The BHARAT study: a multi-modal, multi-omics investigation of aging signatures in the Indian population.Aging · 2026Observational
- An snRNA-seq aging clock for the fruit fly head sheds light on sex-biased aging.Scientific reports · 2026Article
- Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes.npj aging · 2026Article
- Aging clocks delineate neuron types vulnerable or resilient to neurodegeneration and identify neuroprotective interventions.Nature aging · 2026Article
- Histone modification clocks for robust cross-species biological age prediction and elucidating senescence regulation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
37 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aging clocks dissociate biological from chronological age. The estimation of biological age is important for identifying gerontogenes and assessing environmental, nutritional, or therapeutic impacts on the aging process. Recently, methylation markers were shown to allow estimation of biological age based on age-dependent somatic epigenetic alterations. However, DNA methylation is absent in some species such as Caenorhabditis elegans and it remains unclear whether and how the epigenetic clocks affect gene expression. Aging clocks based on transcriptomes have suffered from considerable variation in the data and relatively low accuracy. Here, we devised an approach that uses temporal scaling and binarization of C. elegans transcriptomes to define a gene set that predicts biological age with an accuracy that is close to the theoretical limit. Our model accurately predicts the longevity effects of diverse strains, treatments, and conditions. The involved genes support a role of specific transcription factors as well as innate immunity and neuronal signaling in the regulation of the aging process. We show that this binarized transcriptomic aging (BiT age) clock can also be applied to human age prediction with high accuracy. The BiT age clock could therefore find wide application in genetic, nutritional, environmental, and therapeutic interventions in the aging process.
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