Evidence map›Paper›PMID 41776309›Full record

ArticleNature aging2026

Multi-tissue transcriptomic aging atlas reveals predictive aging biomarkers in the killifish.

Emma K Costa, Jingxun Chen, Ian H Guldner, Lajoyce Mboning, Natalie Schmahl, Aleksandra Tsenter, Rahul Nagvekar, Man-Ru Wu, Patricia Moran-Losada, Louis-S Bouchard and 5 more

Abstract read
In one paragraph

Article in Nature aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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 registry

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Killiverse: an interactive multi-omics web resource for killifish.bioRxiv : the preprint server for biology · 2026
    Article
  5. Engulfment by brain macrophages in a short-lived vertebrate.bioRxiv : the preprint server for biology · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Emma K Costa *Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-9431-6852
Jingxun Chen *Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
Ian H GuldnerDepartment of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
Lajoyce MboningDepartment of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, USA.
Natalie SchmahlWu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
Aleksandra TsenterWu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
Rahul NagvekarWu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
Man-Ru WuDepartment of Ophthalmology, Mary M. and Sash A. Spencer Center for Vision Research, Byers Eye Institute, Stanford University, Stanford, CA, USA.
Patricia Moran-LosadaDepartment of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
Louis-S BouchardDepartment of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, USA.
Sui WangDepartment of Ophthalmology, Mary M. and Sash A. Spencer Center for Vision Research, Byers Eye Institute, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-1563-9117
Param Priya SinghDepartment of Anatomy, University of California, San Francisco, San Francisco, CA, USA.ORCID http://orcid.org/0000-0002-3325-8767
Matteo PellegriniDepartment of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0001-9355-9564
Anne BrunetWu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA. abrunet1@stanford.edu.ORCID http://orcid.org/0000-0002-4608-6845
Tony Wyss-CorayDepartment of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA. twc@stanford.edu.ORCID http://orcid.org/0000-0001-5893-0831

Funding

Training Program in Basic NeuroscienceT32MH020016 · NIMH · STANFORD UNIVERSITY · PI Justin L Gardner, Merritt C Maduke · 1997 to 2026
$16.2M
Training Grant in Genomic Analysis and InterpretationT32HG002536 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Valerie A Arboleda, Harold Pimentel · 2002 to 2026
$8.6M
Decoding natural protective mechanisms during diapause and longevity to counter agingDP2AG086979 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Param Priya Singh · 2023 to 2026
$2.4M
Studying Neuronal Proteostasis During Aging and AD with Novel Protein Tagging ToolsK99AG088304 · NIA · STANFORD UNIVERSITY · PI GULDNER, IAN HUNTER · 2024 to 2025
$262k
U.S. Department of Health & Human Services | National Institutes of Health (NIH) DP2AG086979U.S. Department of Health & Human Services | National Institutes of Health (NIH) K99AG088304U.S. Department of Health & Human Services | National Institutes of Health (NIH) T32HG002536U.S. Department of Health & Human Services | National Institutes of Health (NIH) T32MH020016
6 · The paper itself

Abstract

Aging is associated with progressive tissue dysfunction, leading to frailty and mortality. Characterizing aging features, such as changes in gene expression and dynamics, shared across tissues or specific to each tissue, is crucial for understanding systemic and local factors contributing to the aging process. We performed RNA sequencing on 13 tissues at six different ages in male and female African turquoise killifish, the shortest-lived vertebrate that can be raised in captivity. This comprehensive, sex-balanced 'atlas' dataset revealed varying strength of sex-age interactions across killifish tissues and age-altered genes and biological pathways that are evolutionarily conserved in mice and humans. We discovered a female-biased myeloid shift with age in the killifish hematopoietic organ, developed tissue-specific 'transcriptomic clocks' and identified biomarkers predictive of chronological age. We showed the importance of sex-specific clocks for selected tissues, validated the tissue clocks with an independent transcriptomic dataset and used them to evaluate different lifespan interventions in the killifish. Our work provides a comprehensive resource for studying aging dynamics across tissues in the killifish, a powerful vertebrate aging model.

Indexed as

AgingFundulidaeTranscriptomeAnimalsBiomarkersFemaleGene Expression ProfilingLongevityMaleBiomarkers

Identifiers

PMID41776309
PMCPMC13004697

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.