Evidence map›Paper›PMID 32695266›Full record

ArticleComputational and structural biotechnology journal2020

Meta-analysis of gene expression profiles of lean and obese PCOS to identify differentially regulated pathways and risk of comorbidities.

Susan Idicula-Thomas, Ulka Gawde, Sameeksha Bhaye, Khushal Pokar, Gary D Bader

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

5 authors.

Susan Idicula-ThomasBiomedical Informatics Centre, Indian Council of Medical Research-National Institute for Research in Reproductive Health, Mumbai 400012, India.
Ulka GawdeBiomedical Informatics Centre, Indian Council of Medical Research-National Institute for Research in Reproductive Health, Mumbai 400012, India.
Sameeksha BhayeBiomedical Informatics Centre, Indian Council of Medical Research-National Institute for Research in Reproductive Health, Mumbai 400012, India.
Khushal PokarBiomedical Informatics Centre, Indian Council of Medical Research-National Institute for Research in Reproductive Health, Mumbai 400012, India.
Gary D BaderThe Donnelly Centre, University of Toronto, Toronto, ON, Canada.

Funding

TR&D 3 - Network Guided Machine LearningP41GM103504 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY · 2012 to 2024
$17.3M
NIGMS NIH HHS P41 GM103504
6 · The paper itself

Abstract

Polycystic ovary syndrome (PCOS) is a complex multigenic disorder and women with PCOS suffer from several comorbidities. Although, obesity is a known risk factor for PCOS, the incidence of lean women with PCOS is on the rise. A systematic and comparative study on lean and obese PCOS with respect to genes, pathways and comorbidity analysis has not been attempted so far. Analysis of differentially expressed genes (DEGs) across tissue types for lean and obese PCOS revealed that the majority of them were downregulated for lean and obese PCOS. Ovarian and endometrial tissues shared several commonly dysregulated genes, suggesting shared PCOS pathophysiology mechanisms exist across tissues. Several pathways for cellular homeostasis, such as inflammation and immune response, insulin signaling, steroidogenesis, hormonal and metabolic signaling, regulation of gonadotrophic hormone secretion, cell structure and signaling that are known to be affected in PCOS were found to be enriched in our gene expression analysis of lean and obese PCOS. The gene-disease network is denser for obese PCOS with a higher comorbidity score as compared to lean PCOS.

Indexed as

Comorbidity analysisDEGs, Differentially expressed genesDifferential gene expressionEnrichment analysisGEO, Gene Expression OmnibusPathway analysisPCOSPCOS, Polycystic ovary syndrome

Identifiers

PMID32695266
PMCPMC7352056

What OpenQuestion holds

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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.