In one paragraphArticle in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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.
2 · The registryThe 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.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
18 authors.
Spencer M GrantCenter for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-7278-0347 Mary B MakariousCenter for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-7978-1051 Abraham MollerCenter for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-7324-8678 Melissa Grant-PetersDepartment of Clinical Neurosciences, School of Clinical Medicine, The University of Cambridge, Cambridge, UK.
Amy HicksDepartment of Clinical Neurosciences, School of Clinical Medicine, The University of Cambridge, Cambridge, UK.
Ajeet MandalHuman Brain Collection Core, Division of Intramural Research, National Institute of Mental Health, NIH, Bethesda, MD, USA.
Pavan AuluckHuman Brain Collection Core, Division of Intramural Research, National Institute of Mental Health, NIH, Bethesda, MD, USA.
Hampton LeonardCenter for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0003-2390-8110 Nicole KuznetsovCenter for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.ORCID 0009-0005-9847-0282 Cory WellerCenter for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0001-6965-5599 Xylena ReedCenter for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-7563-9365 Miten JainCenter for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-4571-3982 Luigi FerrucciLongitudinal Studies Section, Translational Gerontology Branch, Intramural Research Program, National Institute.
Mark R CooksonCenter for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-1058-3831 Mina RytenDepartment of Clinical Neurosciences, School of Clinical Medicine, The University of Cambridge, Cambridge, UK.
Mike A NallsCenter for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
Kimberley J BillingsleyCenter for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-8003-4029 Funding
Procurement and Characterization of Postmortem Brain TissueZICMH002903 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI MARENCO, STEFANO · 2009 to 2025
$56.0MResearch Education ComponentP30AG019610 · NIA · SUN HEALTH RESEARCH INSTITUTE · PI REIMAN, ERIC MICHAEL · 2001 to 2020
$32.5MResearch Education ComponentP30AG072980 · NIA · BANNER HEALTH · PI ALIREZA ATRI · 2021 to 2026
$24.9MUniversity of Kentucky Alzheimer's Disease Research CenterP30AG072946 · NIA · UNIVERSITY OF KENTUCKY · PI LINDA J VAN ELDIK · 2021 to 2026
$23.5MNational Brain and Tissue Resource for Parkinson's Disease and Related DisordersU24NS072026 · NINDS · BANNER SUN HEALTH RESEARCH INSTITUTE · PI BEACH, THOMAS G · 2011 to 2015
$7.8MIntramural NIH HHS ZIC MH002903NIA NIH HHS P30 AG019610NIA NIH HHS P30 AG072946NIA NIH HHS P30 AG072980NINDS NIH HHS U24 NS072026
6 · The paper itselfAbstract
Epigenetic clocks are widely used to estimate biological aging, yet most are built from array-based data from peripheral tissues of predominantly European-ancestry individuals, limiting generalizability. Here, we present aging clocks trained using GenoML, an automated machine learning platform for clinical and multi-omics data, on DNA methylation from Oxford Nanopore long-read sequencing. These models leverage over 28 million CpG sites across individuals of African and European ancestry. Our findings highlight the power of long-read methylation data for constructing accurate, ancestry-aware aging clocks and emphasize the importance of inclusive training datasets.
Identifiers
PMID41256605
PMCPMC12621889
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