Identification of core gene in obese type 2 diabetes patients using bioinformatics analysis

Dong, Zhiyong; Lei, Xinyi; Kujawa, Stacy; Bolu, NaciEmre; Zhao, Hong; Wang, Cunchuan

doi:10.1080/21623945.2021.1933297

Cited by 12 publications

(6 citation statements)

References 44 publications

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“…Multidimensional analysis platform development: For this paper, we used FunRich, an open-access, standalone functional enrichment and network analysis tool to perform analysis on background databases that are integrated from heterogeneous genomic and proteomic resources (>1.5 million annotations) [ 24 , 25 ] and the statistical software R version 4.1.1 (R Core Team, 2021, , accessed on 15 October 2021).…”

Section: Methodsmentioning

confidence: 99%

Replication of Integrative Data Analysis for Adipose Tissue Dysfunction, Low-Grade Inflammation, Postprandial Responses and OMICs Signatures in Symptom-Free Adults

Cabriales

Rodríguez-Ayala

Laviada-Molina

et al. 2021

Biology

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We previously reported preliminary characterization of adipose tissue (AT) dysfunction through the adiponectin/leptin ratio (ALR) and fasting/postprandial (F/P) gene expression in subcutaneous (SQ) adipose tissue (AT) biopsies obtained from participants in the GEMM study, a precision medicine research project. Here we present integrative data replication of previous findings from an increased number of GEMM symptom-free (SF) adults (N = 124) to improve characterization of early biomarkers for cardiovascular (CV)/immunometabolic risk in SF adults with AT dysfunction. We achieved this goal by taking advantage of the rich set of GEMM F/P 5 h time course data and three tissue samples collected at the same time and frequency on each adult participant (F/P blood, biopsies of SQAT and skeletal muscle (SKM)). We classified them with the presence/absence of AT dysfunction: low (<1) or high (>1) ALR. We also examined the presence of metabolically healthy (MH)/unhealthy (MUH) individuals through low-grade chronic subclinical inflammation (high sensitivity C-reactive protein (hsCRP)), whole body insulin sensitivity (Matsuda Index) and Metabolic Syndrome criteria in people with/without AT dysfunction. Molecular data directly measured from three tissues in a subset of participants allowed fine-scale multi-OMIC profiling of individual postprandial responses (RNA-seq in SKM and SQAT, miRNA from plasma exosomes and shotgun lipidomics in blood). Dynamic postprandial immunometabolic molecular endophenotypes were obtained to move towards a personalized, patient-defined medicine. This study offers an example of integrative translational research, which applies bench-to-bedside research to clinical medicine. Our F/P study design has the potential to characterize CV/immunometabolic early risk detection in support of precision medicine and discovery in SF individuals.

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Section: Methodsmentioning

confidence: 99%

Replication of Integrative Data Analysis for Adipose Tissue Dysfunction, Low-Grade Inflammation, Postprandial Responses and OMICs Signatures in Symptom-Free Adults

Cabriales

Rodríguez-Ayala

Laviada-Molina

et al. 2021

Biology

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“…COL4A2 participates in the formation of ECM and type IV collagen. Dong demonstrated that COL4A2 is highly expressed in the subcutaneous adipose tissue of obese patients with T2DM [33]. However, the relationship between the expression of COL4A2 and the pathogenesis of T2DM is yet to be elucidated.…”

Section: Disscusionmentioning

confidence: 99%

Investigation of the pathogenesis of liver cirrhosis associated with type 2 diabetes mellitus via bioinformatic analysis

xiong

Yuan

Yao

et al. 2023

Preprint

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Background The prevalence of type 2 diabetes mellitus (T2DM) with liver cirrhosis continues to increase globally. T2DM is identified as an independent risk factor for liver cirrhosis and an important prognostic factor for clinical outcomes in patients with liver cirrhosis. However, this co-occurring mechanism has not yet been elucidated. Therefore, this study aims to investigate the mechanisms underlying the co‐pathogenesis of liver cirrhosis and T2DM and to provide reference information for future diagnoses and treatment of patients with liver cirrhosis associated with T2DM. Methods RNA-seq profile of liver cirrhosis and T2DM was downloaded from Gene Expression Omnibus (GEO) database and analyzed. Differentially expressed genes (DEGs) associated with liver cirrhosis and T2DM were identified using GEO2R. Thereafter, the co‐differentially expressed genes (co‐DEGs) associated with liver cirrhosis and T2DM were obtained from the intersection of the datasets on the DEGs. Subsequently, 175 overlapping DEGs were identified and further analyzed using a bioinformatic approach, which included Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, protein–protein interaction (PPI) network analysis, transcription factors (TFs)–gene interaction network analysis, and drug candidate prediction analysis. Results The intersection of datasets on DEGs associated with liver cirrhosis and T2DM enabled the selection of 175 co-DEGs for subsequent analyses. Functional enrichment analyses showed that these co‐DEGs are associated with inflammatory cytokine responses and positive regulation of transforming growth factor‐β1 (TGF‐β1). The KEGG analysis showed that advanced glycation end products–receptor for advanced glycation end products signaling pathway was markedly involved in liver cirrhosis associated with T2DM. Thereafter, a total of eight hub genes: SPARC, COL4A2, THBS1, LUM, TIMP3, COL3A1, IGFBP7, and FSTL1, associated with the diseases were identified using five algorithms from Cytoscape app for network centrality analysis and CytoHubba (a plug‐in in the Cytoscape software). In total, 29 TFs of the hub genes were detected by NetworkAnalyst and Drug SIGnatures DataBase, which predicted that retinoic acid is one of the promising agents that may be used for the treatment of liver cirrhosis associated with T2DM. Conclusions This study elucidated the common pathogenesis of liver cirrhosis and T2DM and predicted a potential clinical therapeutic drug. Therefore, these novel findings may contribute to the literature on the pathogenesis of liver cirrhosis associated with T2DM.

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“…Bioinformatics can help predict molecular targets that have a potential affinity for compounds or molecules of interest and identify new biomarkers for prognosis and diagnosis, identifying and analyzing differentially expressed genes (DEGs) in various diseases [ 71 , 72 ]. Moreover, this area can also contribute to the search for alternative drugs for new diseases, providing an extremely useful tool to accelerate urgent studies for the selection of these drugs, understanding and possibly helping in the treatment of new diseases, whether chronic, such as obesity, or acute and emerging, as in the case of coronavirus disease-19 (COVID-19)—since bioinformatics was and still is an essential method to perform sequencing data analysis, pandemic tracking and analysis of pandemic containment measures [ 73 , 74 , 75 ].…”

Section: Metabolic Pathways Of Inflammation In Obesity: Potential The...mentioning

confidence: 99%

Hydrolyzed Proteins and Vegetable Peptides: Anti-Inflammatory Mechanisms in Obesity and Potential Therapeutic Targets

et al. 2022

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Chronic low-grade inflammation is present in overweight and obesity, causing changes in several metabolic pathways. It impairs systemic functioning and positively feeds back the accumulation of more adipose tissue. Studies with hydrolyzed proteins and plant peptides have demonstrated a potential anti-inflammatory and immunomodulatory effect of these peptides. However, it is challenging and necessary to explore the mechanism of action of such molecules because understanding their effects depends on their structural characterizations. Furthermore, the structure might also give insights into safety, efficacy and efficiency, with a view of a possible health application. Thus, the present narrative review aimed to discuss the mechanisms of action of hydrolyzed proteins and plant peptides as anti-inflammatory agents in obesity. Keywords and related terms were inserted into databases for the search. Based on the studies evaluated, these biomolecules act by different pathways, favoring the reduction of inflammatory cytokines and adipokines and the polarization of macrophages to the M2 phenotype. Finally, as a future perspective, bioinformatics is suggested as a tool to help understand and better use these molecules considering their applicability in pre-clinical and clinical studies.

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Identification of core gene in obese type 2 diabetes patients using bioinformatics analysis

Cited by 12 publications

References 44 publications

Replication of Integrative Data Analysis for Adipose Tissue Dysfunction, Low-Grade Inflammation, Postprandial Responses and OMICs Signatures in Symptom-Free Adults

Replication of Integrative Data Analysis for Adipose Tissue Dysfunction, Low-Grade Inflammation, Postprandial Responses and OMICs Signatures in Symptom-Free Adults

Investigation of the pathogenesis of liver cirrhosis associated with type 2 diabetes mellitus via bioinformatic analysis

Hydrolyzed Proteins and Vegetable Peptides: Anti-Inflammatory Mechanisms in Obesity and Potential Therapeutic Targets

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