Evidence mapPaperPMID 40766611Full record

ArticlebioRxiv : the preprint server for biology2025

SkeletAge: Transcriptomics-based Aging Clock Identifies 26 New Targets in Skeletal Muscle Aging.

Muhammad Ali, Fei Li, Manpreet Katari

Abstract readPreprint
In one paragraph

Article 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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Muhammad AliDepartment of Biology, New York University, New York, NY, 10003, United States.
Fei LiDepartment of Biology, New York University, New York, NY, 10003, United States.
Manpreet KatariDepartment of Biology, New York University, New York, NY, 10003, United States.

Funding

Molecular Basis of Centromere Specification and InheritanceR35GM134920 · NIGMS · NEW YORK UNIVERSITY · 2022 to 2025
$3.4M
NIGMS NIH HHS R35 GM134920
6 · The paper itself

Abstract

Identifying the set of genes that regulate baseline healthy aging - aging that is not confounded by illness - is critical to understating aging biology. Machine learning-based age-estimators (such as epigenetic clocks) offer a robust method for capturing biomarkers that strongly correlate with age. In principle, we can use these estimators to find novel targets for aging research, which can then be used for developing drugs that can extend the healthspan. However, methylation-based clocks do not provide direct mechanistic insight into aging, limiting their utility for drug discovery. Here, we describe a method for building tissue-specific bulk RNA-seq-based age-estimators that can be used to identify the

Indexed as

AgeprintBiological AgingEpigenetic ClockLongevity Drug DiscoverySkeletal Muscle

Identifiers

PMID40766611
PMCPMC12324255

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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 Socratic graph.