Evidence map›Paper›PMID 36061131›Full record

ArticleAvicenna journal of medical biotechnology

Prioritizing Candidate Genes for Type 2 Diabetes Mellitus using Integrated Network and Pathway Analysis.

Tejaswini Prakash, Nallur B Ramachandra

Abstract read
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Article in Avicenna journal of medical biotechnology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Tejaswini PrakashGenetics and Genomics Lab, Department of Studies in Genetics and Genomics, University of Mysore, Manasagangothri, Mysuru - 570 006, Karnataka, India.
Nallur B RamachandraGenetics and Genomics Lab, Department of Studies in Genetics and Genomics, University of Mysore, Manasagangothri, Mysuru - 570 006, Karnataka, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Type 2 Diabetes Mellitus (T2DM) has emerged as a major threat to global health that fosters life-threatening clinical complications, taking a huge toll on our society. More than 65 million Indians suffer from T2DM, making it one of the leading causes of death. T2DM and associated complications have to be constantly monitored and managed which reduces the overall quality of life and increases socioeconomic burden. Therefore, it is crucial to develop specific treatment and management strategies. In order to achieve this, it is essential to understand the underlying genetic causes and molecular mechanisms. Methods: Integrated gene network and ontology analyses facilitate prioritization of plausible candidate genes for T2DM and also aid in understanding their mechanistic pathways. In this study, T2DM-associated genes were subjected to sequential interaction network and gene set enrichment analysis. High ranking network clusters were derived and their interrelation with pathways was assessed. Results: About 23 significant candidate genes were prioritized from 615 T2DM-associated genes which were overrepresented in pathways related to insulin resistance, type 2 diabetes, signaling cascades such as insulin receptor signaling pathway, PI3K signaling, IGFR signaling pathway, ERBB signaling pathway, MAPK signaling pathway and their regulatory mechanisms. Conclusion: Of these, two tyrosine kinase receptor genes-

Indexed as

Gene ontologyHub genes identificationIn silico analysisText miningType 2 diabetes mellitus

Identifiers

PMID36061131
PMCPMC9376990

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

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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.