Evidence map›Paper›PMID 36458022›Full record

ArticleNAR genomics and bioinformatics2022

Gene co-expression analyses of health(span) across multiple species.

Steffen Möller, Nadine Saul, Elias Projahn, Israel Barrantes, András Gézsi, Michael Walter, Péter Antal, Georg Fuellen

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
  2. Review
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

8 authors.

Steffen MöllerRostock University Medical Center, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock, Germany.ORCID https://orcid.org/0000-0002-7187-4683
Nadine SaulHumboldt-University of Berlin, Institute of Biology, Berlin, Germany.ORCID https://orcid.org/0000-0002-6798-0918
Elias ProjahnRostock University Medical Center, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock, Germany.ORCID https://orcid.org/0000-0002-4153-4071
Israel BarrantesRostock University Medical Center, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock, Germany.ORCID https://orcid.org/0000-0002-5252-4485
András GézsiBudapest University of Technology and Economics, Department of Measurement and Information Systems, Budapest, Hungary.ORCID https://orcid.org/0000-0003-1022-6356
Michael WalterRostock University Medical Center, Institute for Clinical Chemistry and Laboratory Medicine, Rostock, Germany.ORCID https://orcid.org/0000-0002-6303-3323
Péter AntalBudapest University of Technology and Economics, Department of Measurement and Information Systems, Budapest, Hungary.ORCID https://orcid.org/0000-0002-4370-2198
Georg FuellenRostock University Medical Center, Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock, Germany.ORCID https://orcid.org/0000-0002-4994-9829

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health(span)-related gene clusters/modules were recently identified based on knowledge about the cross-species genetic basis of health, to interpret transcriptomic datasets describing health-related interventions. However, the cross-species comparison of health-related observations reveals a lot of heterogeneity, not least due to widely varying health(span) definitions and study designs, posing a challenge for the exploration of conserved healthspan modules and, specifically, their transfer across species. To improve the identification and exploration of conserved/transferable healthspan modules, here we apply an established workflow based on gene co-expression network analyses employing GEO/ArrayExpress data for human and animal models, and perform a comprehensive meta-study of the resulting modules related to health(span), yielding a small set of literature backed health(span) candidate genes. For each experiment, WGCNA (weighted gene correlation network analysis) was used to infer modules of genes which correlate in their expression with a 'health phenotype score' and to determine the most-connected (hub) genes (and their interactions) for each such module. After mapping these hub genes to their human orthologs, 12 health(span) genes were identified in at least two species (ACTN3, ANK1, MRPL18, MYL1, PAXIP1, PPP1CA, SCN3B, SDCBP, SKIV2L, TUBG1, TYROBP, WIPF1), for which enrichment analysis by g:profiler found an association with actin filament-based movement and associated organelles, as well as muscular structures. We conclude that a meta-study of hub genes from co-expression network analyses for the complex phenotype health(span), across multiple species, can yield molecular-mechanistic insights and can direct experimentalists to further investigate the contribution of individual genes and their interactions to health(span).

Identifiers

PMID36458022
PMCPMC9706456

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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.