Evidence map›Paper›PMID 33902539›Full record

ArticleBMC endocrine disorders2021

Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules.

G Prashanth, Basavaraj Vastrad, Anandkumar Tengli, Chanabasayya Vastrad, Iranna Kotturshetti

Open access · goldAbstract read
In one paragraph

Article in BMC endocrine disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.1field-weighted citation impact, top 14% of its field
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, 28 citations in OpenAlex.

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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 at 3 institutions in 1 country.

G PrashanthDepartment of General Medicine, Basaveshwara Medical College, Chitradurga, Karnataka, 577501, India.ORCID https://orcid.org/0000-0003-2571-5734
Basavaraj VastradDepartment of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka, 582103, India.ORCID https://orcid.org/0000-0003-2202-7637
Anandkumar TengliDepartment of Pharmaceutical Chemistry, JSS College of Pharmacy, Mysuru and JSS Academy of Higher Education & Research, Mysuru, Karnataka, 570015, India.ORCID https://orcid.org/0000-0001-8076-928X
Chanabasayya VastradBiostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad, Karnataka, 580001, India. channu.vastrad@gmail.com.ORCID https://orcid.org/0000-0003-3615-4450
Iranna KotturshettiDepartment of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka, 582209, India.ORCID https://orcid.org/0000-0003-1988-7345
JSS Academy of Higher Education and Research · INMVJ Medical College and Research Hospital · INSri Dharmasthala Manjunatheshwara College of Dental Sciences & Hospital · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus.

methodsTo screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules.

resultsA total of 820 DEGs were identified between healthy obese and metabolically unhealthy obese, among 409 up regulated and 411 down regulated genes. The GO enrichment analysis results showed that these DEGs were significantly enriched in ion transmembrane transport, intrinsic component of plasma membrane, transferase activity, transferring phosphorus-containing groups, cell adhesion, integral component of plasma membrane and signaling receptor binding, whereas, the REACTOME pathway enrichment analysis results showed that these DEGs were significantly enriched in integration of energy metabolism and extracellular matrix organization. The hub genes CEBPD, TP73, ESR2, TAB1, MAP 3K5, FN1, UBD, RUNX1, PIK3R2 and TNF, which might play an essential role in obesity associated type 2 diabetes mellitus was further screened.

conclusionsThe present study could deepen the understanding of the molecular mechanism of obesity associated type 2 diabetes mellitus, which could be useful in developing therapeutic targets for obesity associated type 2 diabetes mellitus.

Indexed as

Computational BiologyDiabetes Mellitus, Type 2ObesityAnti-Obesity AgentsDatasets as TopicDrug Evaluation, PreclinicalGene Expression ProfilingGene OntologyGene Regulatory NetworksGenetic Association StudiesHumansHypoglycemic AgentsMolecular Docking SimulationProtein Interaction MapsSmall Molecule LibrariesAnti-Obesity AgentsHypoglycemic AgentsSmall Molecule Librariesdifferentially expressed genemiRNA-target genes regulatory networkobesity associated type 2 diabetes mellituspathwayprotein-protein interaction network

Identifiers

PMID33902539
PMCPMC8074411
OpenAlexW3113255791

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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.