Evidence map›Paper›PMID 41723297›Full record

ArticleGeroScience2026

Whole blood transcriptional signatures of age and survival identified in long life family and integrative longevity omics studies.

Mengze Li, Zeyuan Song, Eric Reed, Tanya T Karagiannis, Stacy Andersen, Michael Brent, Chase Mateusiak, Sandeep Acharya, Wooseok J Jung, Shu Liao and 11 more

Abstract read
PubMed Publisher
In one paragraph

Article in GeroScience, 2026. 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

5 · Who and what money

Authors and funding

21 authors.

Mengze LiBioinformatics Program, Boston University, Boston, MA, 02215, USA.
Zeyuan SongInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, 02111, USA.
Eric ReedDepartment of Medicine, Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, 10461, USA.
Tanya T KaragiannisInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, 02111, USA.
Stacy AndersenDepartment of Medicine, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA, 02118, USA.
Michael BrentDepartment of Computer Science and Engineering, Washington University, St Louis, MO, 63130, USA.
Chase MateusiakDepartment of Computer Science and Engineering, Washington University, St Louis, MO, 63130, USA.
Sandeep AcharyaDepartment of Computer Science and Engineering, Washington University, St Louis, MO, 63130, USA.
Wooseok J JungDepartment of Computer Science and Engineering, Washington University, St Louis, MO, 63130, USA.
Shu LiaoDepartment of Computer Science and Engineering, Washington University, St Louis, MO, 63130, USA.
Mary K WojczynskiDepartment of Genetics, Washington University School of Medicine, St. Louis, MO, 63130, USA. mwojczynski@wustl.edu.
Mary F FeitosaDepartment of Genetics, Washington University School of Medicine, St. Louis, MO, 63130, USA.
Jeffrey R O'ConnellDepartment of Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
May E MontasserDepartment of Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
Roland J ThorpeProgram for Research on Men's Health, Hopkins Center for Health Disparities Solutions, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA.
Konstantin ArbeevSocial Science Research Institute, Duke University, Durham, NC, 27708, USA.
Sofiya MilmanDepartment of Medicine, Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, 10461, USA.
Albert TaiDepartment of Medicine, School of Medicine, Tufts University, Boston, MA, 02111, USA.
Thomas T PerlsDepartment of Medicine, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA, 02118, USA.
Paola SebastianiInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, 02111, USA. Paola.Sebastiani@tuftsmedicine.org.
Stefano MontiBioinformatics Program, Boston University, Boston, MA, 02215, USA. smonti@bu.edu.ORCID http://orcid.org/0000-0002-9376-0660

Funding

The Long Life Family StudyU19AG063893 · NIA · WASHINGTON UNIVERSITY · PI PAOLA SEBASTIANI · 2019 to 2026
$125.4M
Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategiesUH2AG064704 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI PERLS, THOMAS T, SEBASTIANI, PAOLA · 2019 to 2021
$9.4M
NIA NIH HHS U19 AG063893NIA NIH HHS UH2 AG064704NIA NIH HHS UH2/UH3 AG064704
6 · The paper itself

Abstract

Although aging is a universal event, some individuals are able to achieve extreme longevity. The Long-Life Family Study (LLFS) enrolls participants from families enriched with long-lived individuals, serves as a valuable dataset for studying ageing phenotypes and identify potential intervention targets. We analyzed the association between age at blood draw and 16,284 RNAseq-based blood transcriptomic data from 2,167 LLFS participants with ages ranging from 18 to 107, replicated the results in the Integrative Longevity Omics Study (ILO) dataset of 20,884 RNAseq-based blood transcriptomic data from 419 participants, with ages ranging from 60 to 108, and further compared our findings to a published reference aging signature. We identified 4,227 transcripts increasing and 4,044 transcripts decreasing with age, and enrichment analysis revealed age-related upregulation of inflammatory and senescence-related pathways, and downregulation of MYC and Wnt/β-catenin targets, among others. Further, a subset of transcripts showed age associations unique to the longevity-enriched cohorts (LLFS and ILO). We also identified 314 transcripts significantly associated with mortality risk and found that pro-survival gene sets included NK cell-mediated cytotoxicity and GPCR signaling. Finally, increased transcriptomic age predicted using transcriptomic clock was strongly associated with increased mortality. In summary, this study identified robust transcriptomic signatures of aging and mortality in a longevity-enriched population, highlighting key biological pathways such as immune modulation, inflammation, and senescence.

Indexed as

AgingAging clockLongevity-enriched populationMortality riskTranscriptomicsWhole blood

Identifiers

PMID41723297

What Socratic holds

Textmetadata
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.