Evidence map›Paper›PMID 34850337›Full record

ArticleMolecular biology reports2022

Genomic analysis to screen potential genes and mutations in children with non-syndromic early onset severe obesity: a multicentre study in Turkey.

Aysehan Akinci, Altan Kara, Aykut Özgür, Doga Turkkahraman, Soner Aksu

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Molecular biology reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 43% 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

5 citing papers in PubMed, 5 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 5 institutions in 1 country.

Aysehan Akinci *Pediatric Endocrinology and Diabetes Department, Medical Faculty, Inonu University, Malatya, Turkey. aysehan.akinci@inonu.edu.tr.
Altan Kara *Genetic Engineering and Bioinformatic Department, TUBITAK Marmara Research Center, Gebze, Turkey. altan.kara@tubitak.gov.tr.ORCID http://orcid.org/0000-0001-7244-5031
Aykut ÖzgürLaboratory and Veterinary Health Program, Department of Veterinary Medicine, Artova Vocational School, Tokat Gaziosmanpaşa University, Tokat, Turkey.
Doga TurkkahramanPediatric Endocrinology Department, Antalya Training and Research Hospital, University of Health Sciences, Antalya, Turkey.
Soner AksuDepartment of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences, Istanbul Health and Technology University, İstanbul, Turkey.
Antalya Eğitim ve Araştırma Hastanesi · TRInonu University · TRIstanbul Health and Technology UniversityScientific and Technological Research Council of Turkey · TRTokat Gaziosmanpaşa Üniversitesi · TR

Funding

Inonu University Scientific Research Centre 2018-20
6 · The paper itself

Abstract

backgroundObesity is a complex genetic-based pediatric disorder which triggers life-threatening conditions. Therefore, the understanding the molecular mechanisms of obesity has been a significant approach in medicine. Computational methods allow rapid and comprehensive pathway analysis, which is important for generation of diagnosis and treatment of obesity. METHODS AND

resultsAims of our study are to comprehensively investigate genetic characteristics of obesity in children with non-syndromic, early-onset (< 7 years), and severe obesity (BMI-SDS > 3) through computational approaches. First, the mutational analyses of 41 of obesity-related genes in 126 children with non-syndromic early-onset severe obesity and 76 healthy non-obese controls were performed using the next generation sequencing (NGS) technique, and the NGS data analyzed by using bioinformatics methods. Then, the relationship between pathogenic variants and anthropometric/biochemical parameters was further evaluated. Obtained results demonstrated that the 15 genes (ADIPOQ, ADRB2, ADRB3, IRS1, LEPR, NPY, POMC, PPARG, PPARGC1A, PPARGC1B, PTPN1, SLC22A1, SLC2A4, SREBF1 and UCP1) which directly related to obesity found linked together via biological pathways and/or functions. Among these genes, IRS1, PPARGC1A, and SLC2A4 stand out as the most central ones. Furthermore, 12 of non-synonymous pathogenic variants, including six novels, were detected on ADIPOQ (G90S and D242G), ADRB2 (V87M), PPARGC1A (E680G, A477T, and R656H), UCP1 (Q44R), and IRS1 (R302Q, R301H, R301C, H250P, and H250N) genes.

conclusionWe propose that 12 of non-synonymous pathogenic variations detected on ADIPOQ, ADRB2, PPARGC1A, UCP1, and IRS1 genes might have a cumulative effect on the development and progression of obesity.

Indexed as

Obesity, MorbidPediatric ObesityChildGenomicsHumansMutationReceptors, Adrenergic, beta-3RNA-Binding ProteinsTurkeyADRB3 protein, humanPPARGC1B protein, humanReceptors, Adrenergic, beta-3RNA-Binding ProteinsBioinformaticsGeneticsObesityPathway analysisSNP

Identifiers

PMID34850337
OpenAlexW3215317932

What Socratic 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 Socratic graph.