2022
DOI: 10.3934/mbe.2022107
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Integrative system biology and mathematical modeling of genetic networks identifies shared biomarkers for obesity and diabetes

Abstract: <abstract> <p>Obesity and type 2 and diabetes mellitus (T2D) are two dual epidemics whose shared genetic pathological mechanisms are still far from being fully understood. Therefore, this study is aimed at discovering key genes, molecular mechanisms, and new drug targets for obesity and T2D by analyzing the genome wide gene expression data with different computational biology approaches. In this study, the RNA-sequencing data of isolated primary human adipocytes from individuals who are lean, obes… Show more

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Cited by 14 publications
(13 citation statements)
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“…In this study, six tools, including Combined Annotation Dependent Depletion (CADD), Scale-invariant Feature Transform (SIFT) ( Ng and Henikoff, 2003 ), Polymorphism Phenotyping (PolyPhen) ( Adzhubei et al, 2013 ), Mendelian Clinically Applicable Pathogenicity (M-CAP) ( Jagadeesh et al, 2016 ), and Functional Analysis through Hidden Markov Models (FATHMM) ( Rogers et al, 2018 ), REVEL (rare exome variant ensemble learner) were used to evaluate the pathogenicity of variants ( Ioannidis et al, 2016 ). SIFT predicts pathogenicity based on alteration in conserved regions of the nucleotide sequence ( Shaik et al, 2020b ; Shaik et al, 2021 ; Alharthi et al, 2022 ; Bima et al, 2022 ). PolyPhen predicts the variant effects based on the nucleotide sequence and changes in protein structure.…”
Section: Methodsmentioning
confidence: 99%
“…In this study, six tools, including Combined Annotation Dependent Depletion (CADD), Scale-invariant Feature Transform (SIFT) ( Ng and Henikoff, 2003 ), Polymorphism Phenotyping (PolyPhen) ( Adzhubei et al, 2013 ), Mendelian Clinically Applicable Pathogenicity (M-CAP) ( Jagadeesh et al, 2016 ), and Functional Analysis through Hidden Markov Models (FATHMM) ( Rogers et al, 2018 ), REVEL (rare exome variant ensemble learner) were used to evaluate the pathogenicity of variants ( Ioannidis et al, 2016 ). SIFT predicts pathogenicity based on alteration in conserved regions of the nucleotide sequence ( Shaik et al, 2020b ; Shaik et al, 2021 ; Alharthi et al, 2022 ; Bima et al, 2022 ). PolyPhen predicts the variant effects based on the nucleotide sequence and changes in protein structure.…”
Section: Methodsmentioning
confidence: 99%
“…that most of the DEGs were significantly enriched in 'response to mineralocorticoid' under GO-biological processes category [37][38][39][40][41]. It is supported by the fact that, cortisol resistance in asthma conditions has been proposed and the involvement of the 11beta-HSD-2 enzyme has been suggested.…”
Section: Plos Onementioning
confidence: 72%
“…In the current work, we employed numerous bioinformatic tools to systemically analyze the gene expression data and to identify the regulatory and co-expression networks between the miRNAs and their target gene pairs in asthma. Our functional enrichment analysis showed that most of the DEGs were significantly enriched in ‘response to mineralocorticoid’ under GO- biological processes category [ 37 41 ]. It is supported by the fact that, cortisol resistance in asthma conditions has been proposed and the involvement of the 11beta-HSD-2 enzyme has been suggested.…”
Section: Discussionmentioning
confidence: 99%
“…These compounds appear to be accommodated in a similar way in the binding site of PIM1 (Xia et al, 2009;Abdelaziz et al, 2018;Ibrahim et al, 2022). The necessity of the interactions with the hinge region and Gly-loop residues (Qian et al, 2005;Pogacic et al, 2007;Tsuganezawa et al, 2012;Casuscelli et al, 2013;Fan et al, 2016;Abdelaziz et al, 2018;Bima et al, 2022;Ibrahim et al, 2022;Shaik et al, 2022) for tight binding to PIM-1 was also implicated with potent inhibitors (Xia et al, 2009;Ibrahim et al, 2022). Moreover, these four compounds can also interact with the activation loop including the Asp186 residue.…”
Section: Figurementioning
confidence: 99%