Evidence map›Paper›PMID 33154459›Full record

ArticleScientific reports2020

Analysis of transcriptional modules during human fibroblast ageing.

Yaelim Lee, G V Shivashankar

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Cellular Senescence of Patient-derived Fibroblasts Reveals the Mid-old Stage as a Critical Window for Transcriptomic Signatures Linked to Alzheimer's Disease Biomarkers and Classification.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2026
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Monitoring Autophagy in Human Aging: Key Cell Models and Insights.Frontiers in bioscience (Landmark edition) · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
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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

2 authors.

Yaelim LeeMechanobiology Institute, National University of Singapore, Singapore, Singapore.
G V ShivashankarMechanobiology Institute, National University of Singapore, Singapore, Singapore. shiva.gvs@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For systematic identification of transcription signatures of human cell aging, we carried out Weighted Gene Co-expression Network Analysis (WGCNA) with the RNA-sequencing data generated with young to old human dermal fibroblasts. By relating the modules to the donor's traits, we uncovered the natural aging- and premature aging disease-associated modules. The STRING functional association networks built with the core module memberships provided a systematic overview of genome-wide transcriptional changes upon aging. We validated the selected candidates via quantitative reverse transcription PCR (RT-qPCR) assay with young and aged human fibroblasts, and uncovered several genes involved in ECM, cell, and nuclear mechanics as a potential aging biomarker. Collectively, our study not only provides a snapshot of functional changes during human fibroblast aging but also presents potential aging markers that are relevant to cell mechanics.

Indexed as

Gene Regulatory NetworksAdolescentAdultAgedAged, 80 and overAgingBiomarkersCell LineCell NucleusCellular SenescenceChildChild, PreschoolExtracellular MatrixFemaleFibroblastsGene Expression ProfilingBiomarkers

Identifiers

PMID33154459
PMCPMC7645754

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.