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

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Abstract

Background

Obesity 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 results

Aims 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.

Conclusion

We 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.

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Data availability

All data provided as supplementary files.

Code availability

All software and packages used in this study can be seen in the methodology section. The required information to install and run these tools can be obtained from the provided references.

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Acknowledgements

We thank Assoc. Prof., M.D., Bahri Evren, MD (Inonu University Medical Faculty, Endocrinology and Diabetes Department, Malatya, Turkey), Prof., MD. Ibrahim Sahin (Inonu University Medical Faculty, Endocrinology and Diabetes Department, Malatya, Turkey), MD. Yusuf Curek (Antalya Training and Research Hospital, Pediatric Endocrinology Department, Antalya, Turkey), Prof., MD. Aysun Bideci (Gazi University Medical Faculty, Pediatric Endocrinology, and Diabetes Department, Ankara, Turkey), Prof., MD. Ayla Guven (University of Health Sciences, Goztepe Training and Research Hospital, Pediatric Endocrinology Department, Istanbul, Turkey), Assoc. Prof., MD. Erdal Eren (Uludag University Medical Faculty, Pediatric Endocrinology and Diabetes Department, Bursa, Turkey), Assoc. Prof., MD. Ozlem Sangun (Baskent University Medical Faculty, Pediatric Endocrinology and Diabetes Department, Adana, Turkey), Assoc. Prof., MD. Atilla Cayir (Erzurum Training and Research Hospital, Pediatric Endocrinology Department, Erzurum, Turkey), Prof., MD. Pelin Bilir (Ankara University Medical Faculty, Pediatric Endocrinology, and Diabetes Department, Ankara, Turkey), Prof., MD. Ayca Torel Ergur (Ufuk University Medical Faculty, Pediatric Endocrinology, and Diabetes Department, Ankara, Turkey) and Prof., MD. Oya Ercan (Istanbul University Cerrahpasa Medical Faculty, Pediatric Endocrinology, and Diabetes, İstanbul, Turkey) for providing patient and/or control samples to this study.

Funding

This study was funded by Inonu University Scientific Research Centre (Grant Number 2018-20).

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  1. Aysehan Akinci and Altan Kara have contributed equally to this work.

Authors and Affiliations

  1. Pediatric Endocrinology and Diabetes Department, Medical Faculty, Inonu University, Malatya, Turkey

    Aysehan Akinci

  2. Genetic Engineering and Bioinformatic Department, TUBITAK Marmara Research Center, Gebze, Turkey

    Altan Kara

  3. Laboratory and Veterinary Health Program, Department of Veterinary Medicine, Artova Vocational School, Tokat Gaziosmanpaşa University, Tokat, Turkey

    Aykut Özgür

  4. Pediatric Endocrinology Department, Antalya Training and Research Hospital, University of Health Sciences, Antalya, Turkey

    Doga Turkkahraman

  5. Department of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences, Istanbul Health and Technology University, İstanbul, Turkey

    Soner Aksu

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Contributions

AA took part in the design of the study, statistical analyses, evaluation of the results, and contributed to the writing of the manuscript. AK takes part in the design of the study, performed bioinformatics analyses, takes part in the evaluation of the results, generated the published figures, and contributed to the writing of the manuscript. AO takes part in the evaluating bioinformatics analysis and contributed to the writing and editing of the manuscript. SA and DT took part in evaluating the results and contributed to the writing of the manuscript.

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Correspondence to Aysehan Akinci or Altan Kara.

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Ayşehan Akinci declares that she has no conflict of interest. Altan Kara declares that he has no conflict of interest. Aykut Özgür declares that he has no conflict of interest. Doğa Türkkahraman declares that he has no conflict of interest. Soner Aksu declares that he has no conflict of interest.

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Akinci, A., Kara, A., Özgür, A. et al. Genomic analysis to screen potential genes and mutations in children with non-syndromic early onset severe obesity: a multicentre study in Turkey. Mol Biol Rep 49, 1883–1893 (2022). https://doi.org/10.1007/s11033-021-06999-2

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