Evidence map›Paper›PMID 33927693›Full record

ArticleFrontiers in endocrinology2021

In-Silico Study of Immune System Associated Genes in Case of Type-2 Diabetes With Insulin Action and Resistance, and/or Obesity.

Basmah Medhat Eldakhakhny, Hadeel Al Sadoun, Hani Choudhry, Mohammad Mobashir

Abstract read
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Article in Frontiers in endocrinology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

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

17 citing papers in PubMed, 1 synthesis or guideline 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

4 authors.

Basmah Medhat EldakhakhnyDepartment of Clinical Biochemistry, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Hadeel Al SadounStem Cell Unit, Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
Hani ChoudhryCancer and Mutagenesis Unit, Department of Biochemistry, Cancer Metabolism and Epigenetic Unit, Faculty of Science, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
Mohammad MobashirSciLifeLab, Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type-2 diabetes and obesity are among the leading human diseases and highly complex in terms of diagnostic and therapeutic approaches and are among the most frequent and highly complex and heterogeneous in nature. Based on epidemiological evidence, it is known that the patients suffering from obesity are considered to be at a significantly higher risk of type-2 diabetes. There are several pieces of evidence that support the hypothesis that these diseases interlinked and obesity may aggravate the risk(s) of type-2 diabetes. Multi-level unwanted alterations such as (epi-) genetic alterations, changes at the transcriptional level, and altered signaling pathways (receptor, cytoplasmic, and nuclear level) are the major sources that promote several complex diseases, and such a heterogeneous level of complexity is considered as a major barrier in the development of therapeutics. With so many known challenges, it is critical to understand the relationships and the shared causes between type-2 diabetes and obesity, and these are difficult to unravel and understand. For this purpose, we have selected publicly available datasets of gene expression for obesity and type-2 diabetes, have unraveled the genes and the pathways associated with the immune system, and have also focused on the T-cell signaling pathway and its components. We have applied a simplified computational approach to understanding differential gene expression and patterns and the enriched pathways for obesity and type-2 diabetes. Furthermore, we have also analyzed genes by using network-level understanding. In the analysis, we observe that there are fewer genes that are commonly differentially expressed while a comparatively higher number of pathways are shared between them. There are only 4 pathways that are associated with the immune system in case of obesity and 10 immune-associated pathways in case of type-2 diabetes, and, among them, only 2 pathways are commonly altered. Furthermore, we have presented SPNS1, PTPN6, CD247, FOS, and PIK3R5 as the overexpressed genes, which are the direct components of TCR signaling.

Indexed as

Insulin ResistanceAdultAnimalsComputer SimulationDiabetes Mellitus, Type 2FemaleGene Expression ProfilingGene Expression RegulationHumansImmune SystemInsulinMiddle AgedObesityReceptors, Antigen, T-CellSignal TransductionSubcutaneous FatInsulinReceptors, Antigen, T-Celldifferentially expressed genesenriched pathwaysimmune systeminsulin action and resistancenetwork-level understandingTCR networktype-2 diabetes and obesity

Identifiers

PMID33927693
PMCPMC8078136

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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.