Evidence map›Paper›PMID 39149379›Full record

ArticlebioRxiv : the preprint server for biology2024

Six drivers of aging identified among genes differentially expressed with age.

Ariella Coler-Reilly, Zachary Pincus, Erica L Scheller, Roberto Civitelli

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ariella Coler-ReillyDivision of Bone and Mineral Diseases, Musculoskeletal Research Center.ORCID 0000-0001-8549-6559
Zachary PincusDepartment of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA.ORCID 0000-0001-9785-5977
Erica L SchellerDivision of Bone and Mineral Diseases, Musculoskeletal Research Center.ORCID 0000-0002-1551-3816
Roberto CivitelliDivision of Bone and Mineral Diseases, Musculoskeletal Research Center.ORCID 0000-0003-4076-4315

Funding

NATIONAL RESEARCH SERVICE AWARD-MEDICAL SCIENTISTT32GM007200 · NIGMS · WASHINGTON UNIVERSITY · PI YOKOYAMA, WAYNE M. · 1985 to 2024
$59.8M
Skeletal Disorders Training ProgramT32AR060719 · NIAMS · WASHINGTON UNIVERSITY · PI Roberto Civitelli · 2011 to 2026
$4.6M
NIAMS NIH HHS T32 AR060719NIGMS NIH HHS T32 GM007200
6 · The paper itself

Abstract

Many studies have compared gene expression in young and old samples to gain insights on aging, the primary risk factor for most major chronic diseases. However, these studies only describe associations, failing to distinguish drivers of aging from compensatory geroprotective responses and incidental downstream effects. Here, we introduce a workflow to characterize the causal effects of differentially expressed genes on lifespan. First, we performed a meta-analysis of 25 gene expression datasets comprising samples of various tissues from healthy, untreated adult mammals (humans, dogs, and rodents) at two distinct ages. We ranked each gene according to the number of distinct datasets in which the gene was differentially expressed with age in a consistent direction. The top age-upregulated genes were TMEM176A, EFEMP1, CP, and HLA-A; the top age-downregulated genes were CA4, SIAH, SPARC, and UQCR10. Second, the effects of the top ranked genes on lifespan were measured by applying post-developmental RNA interference of the corresponding ortholog in the nematode C. elegans (two trials, with roughly 100 animals per genotype per trial). Out of 10 age-upregulated and 9 age-downregulated genes that were tested, two age-upregulated genes (

Identifiers

PMID39149379
PMCPMC11326176

What OpenQuestion 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 OpenQuestion graph.