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Charrier A, Ockunzzi J, Main L, Ghanta SV, Buchner DA. Molecular regulation of PPARγ/RXRα signaling by the novel cofactor ZFP407. PLoS One 2024; 19:e0294003. [PMID: 38781157 PMCID: PMC11115250 DOI: 10.1371/journal.pone.0294003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 02/20/2024] [Indexed: 05/25/2024] Open
Abstract
Cofactors interacting with PPARγ can regulate adipogenesis and adipocyte metabolism by modulating the transcriptional activity and selectivity of PPARγ signaling. ZFP407 was previously demonstrated to regulate PPARγ target genes such as GLUT4, and its overexpression improved glucose homeostasis in mice. Here, using a series of molecular assays, including protein-interaction studies, mutagenesis, and ChIP-seq, ZFP407 was found to interact with the PPARγ/RXRα protein complex in the nucleus of adipocytes. Consistent with this observation, ZFP407 ChIP-seq peaks significantly overlapped with PPARγ ChIP-seq peaks, with more than half of ZFP407 peaks overlapping with PPARγ peaks. Transcription factor binding motifs enriched in these overlapping sites included CTCF, RARα/RXRγ, TP73, and ELK1, which regulate cellular development and function within adipocytes. Site-directed mutagenesis of frequent PPARγ phosphorylation or SUMOylation sites did not prevent its regulation by ZFP407, while mutagenesis of ZFP407 domains potentially necessary for RXR and PPARγ binding abrogated any impact of ZFP407 on PPARγ activity. These data suggest that ZFP407 controls the activity of PPARγ, but does so independently of post-translational modifications, likely by direct binding, establishing ZFP407 as a newly identified PPARγ cofactor. In addition, ZFP407 ChIP-seq analyses identified regions that did not overlap with PPARγ peaks. These non-overlapping peaks were significantly enriched for the transcription factor binding motifs of TBX19, PAX8, HSF4, and ZKSCAN3, which may contribute to the PPARγ-independent functions of ZFP407 in adipocytes and other cell types.
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Affiliation(s)
- Alyssa Charrier
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Jeremiah Ockunzzi
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Leighanne Main
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Siddharth V. Ghanta
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - David A. Buchner
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
- Department of Biochemistry, Case Western Reserve University, Cleveland, Ohio, United States of America
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Ponomarenko I, Pasenov K, Churnosova M, Sorokina I, Aristova I, Churnosov V, Ponomarenko M, Reshetnikova Y, Reshetnikov E, Churnosov M. Obesity-Dependent Association of the rs10454142 PPP1R21 with Breast Cancer. Biomedicines 2024; 12:818. [PMID: 38672173 PMCID: PMC11048332 DOI: 10.3390/biomedicines12040818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 03/30/2024] [Accepted: 04/02/2024] [Indexed: 04/28/2024] Open
Abstract
The purpose of this work was to find a link between the breast cancer (BC)-risk effects of sex hormone-binding globulin (SHBG)-associated polymorphisms and obesity. The study was conducted on a sample of 1498 women (358 BC; 1140 controls) who, depending on the presence/absence of obesity, were divided into two groups: obese (119 BC; 253 controls) and non-obese (239 BC; 887 controls). Genotyping of nine SHBG-associated single nucleotide polymorphisms (SNP)-rs17496332 PRMT6, rs780093 GCKR, rs10454142 PPP1R21, rs3779195 BAIAP2L1, rs440837 ZBTB10, rs7910927 JMJD1C, rs4149056 SLCO1B1, rs8023580 NR2F2, and rs12150660 SHBG-was executed, and the BC-risk impact of these loci was analyzed by logistic regression separately in each group of obese/non-obese women. We found that the BC-risk effect correlated by GWAS with the SHBG-level polymorphism rs10454142 PPP1R21 depends on the presence/absence of obesity. The SHBG-lowering allele C rs10454142 PPP1R21 has a risk value for BC in obese women (allelic model: CvsT, OR = 1.52, 95%CI = 1.10-2.11, and pperm = 0.013; additive model: CCvsTCvsTT, OR = 1.71, 95%CI = 1.15-2.62, and pperm = 0.011; dominant model: CC + TCvsTT, OR = 1.95, 95%CI = 1.13-3.37, and pperm = 0.017) and is not associated with the disease in women without obesity. SNP rs10454142 PPP1R21 and 10 proxy SNPs have adipose-specific regulatory effects (epigenetic modifications of promoters/enhancers, DNA interaction with 51 transcription factors, eQTL/sQTL effects on five genes (PPP1R21, RP11-460M2.1, GTF2A1L, STON1-GTF2A1L, and STON1), etc.), can be "likely cancer driver" SNPs, and are involved in cancer-significant pathways. In conclusion, our study detected an obesity-dependent association of the rs10454142 PPP1R21 with BC in women.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (I.P.); (K.P.); (M.C.); (I.S.); (I.A.); (V.C.); (M.P.); (Y.R.); (E.R.)
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3
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Yadalam PK, Arumuganainar D, Ronsivalle V, Di Blasio M, Badnjevic A, Marrapodi MM, Cervino G, Minervini G. Prediction of interactomic hub genes in PBMC cells in type 2 diabetes mellitus, dyslipidemia, and periodontitis. BMC Oral Health 2024; 24:385. [PMID: 38532421 DOI: 10.1186/s12903-024-04041-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 02/17/2024] [Indexed: 03/28/2024] Open
Abstract
BACKGROUND AND OBJECTIVE In recent years, the complex interplay between systemic health and oral well-being has emerged as a focal point for researchers and healthcare practitioners. Among the several important connections, the convergence of Type 2 Diabetes Mellitus (T2DM), dyslipidemia, chronic periodontitis, and peripheral blood mononuclear cells (PBMCs) is a remarkable example. These components collectively contribute to a network of interactions that extends beyond their domains, underscoring the intricate nature of human health. In the current study, bioinformatics analysis was utilized to predict the interactomic hub genes involved in type 2 diabetes mellitus (T2DM), dyslipidemia, and periodontitis and their relationships to peripheral blood mononuclear cells (PBMC) by machine learning algorithms. MATERIALS AND METHODS Gene Expression Omnibus datasets were utilized to identify the genes linked to type 2 diabetes mellitus(T2DM), dyslipidemia, and Periodontitis (GSE156993).Gene Ontology (G.O.) Enrichr, Genemania, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used for analysis for identification and functionalities of hub genes. The expression of hub D.E.G.s was confirmed, and an orange machine learning tool was used to predict the hub genes. RESULT The decision tree, AdaBoost, and Random Forest had an A.U.C. of 0.982, 1.000, and 0.991 in the R.O.C. curve. The AdaBoost model showed an accuracy of (1.000). The findings imply that the AdaBoost model showed a good predictive value and may support the clinical evaluation and assist in accurately detecting periodontitis associated with T2DM and dyslipidemia. Moreover, the genes with p-value < 0.05 and A.U.C.>0.90, which showed excellent predictive value, were thus considered hub genes. CONCLUSION The hub genes and the D.E.G.s identified in the present study contribute immensely to the fundamentals of the molecular mechanisms occurring in the PBMC associated with the progression of periodontitis in the presence of T2DM and dyslipidemia. They may be considered potential biomarkers and offer novel therapeutic strategies for chronic inflammatory diseases.
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Affiliation(s)
- Pradeep Kumar Yadalam
- Department of periodontics, Saveetha Institute Of Medical And Technical Science (SIMATS), Saveetha Dental College and Hospital, Saveetha University, Chennai, India.
| | | | - Vincenzo Ronsivalle
- Department of Biomedical and Surgical and Biomedical Sciences, Catania University, Catania, 95123, Italy
| | - Marco Di Blasio
- Department of Medicine and Surgery, University Center of Dentistry, University of Parma, Parma, 43126, Italy.
| | - Almir Badnjevic
- Verlab Research Institute for Biomedical Engineering, Medical Devices, and Artificial Intelligence, Bosnia and Herzegovina, Sarajevo, 71000, Bosnia-Herzegovina
| | - Maria Maddalena Marrapodi
- Department of Woman, Child and General and Specialist Surgery, University of Campania "Luigi Vanvitelli", Naples, 80121, Italy
| | - Gabriele Cervino
- School of Dentistry, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, via Consolare Valeria, 1, Messina, 98125, Italy
| | - Giuseppe Minervini
- Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, Tamil Nadu, India
- Multidisciplinary Department of Medical-Surgical and Dental Specialties, University of Campania "Luigi Vanvitelli", Caserta, 80121, Italy
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Bustos-Aibar M, Aguilera CM, Alcalá-Fdez J, Ruiz-Ojeda FJ, Plaza-Díaz J, Plaza-Florido A, Tofe I, Gil-Campos M, Gacto MJ, Anguita-Ruiz A. Shared gene expression signatures between visceral adipose and skeletal muscle tissues are associated with cardiometabolic traits in children with obesity. Comput Biol Med 2023; 163:107085. [PMID: 37399741 DOI: 10.1016/j.compbiomed.2023.107085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 04/28/2023] [Accepted: 05/27/2023] [Indexed: 07/05/2023]
Abstract
Obesity in children is related to the development of cardiometabolic complications later in life, where molecular changes of visceral adipose tissue (VAT) and skeletal muscle tissue (SMT) have been proven to be fundamental. The aim of this study is to unveil the gene expression architecture of both tissues in a cohort of Spanish boys with obesity, using a clustering method known as weighted gene co-expression network analysis. For this purpose, we have followed a multi-objective analytic pipeline consisting of three main approaches; identification of gene co-expression clusters associated with childhood obesity, individually in VAT and SMT (intra-tissue, approach I); identification of gene co-expression clusters associated with obesity-metabolic alterations, individually in VAT and SMT (intra-tissue, approach II); and identification of gene co-expression clusters associated with obesity-metabolic alterations simultaneously in VAT and SMT (inter-tissue, approach III). In both tissues, we identified independent and inter-tissue gene co-expression signatures associated with obesity and cardiovascular risk, some of which exceeded multiple-test correction filters. In these signatures, we could identify some central hub genes (e.g., NDUFB8, GUCY1B1, KCNMA1, NPR2, PPP3CC) participating in relevant metabolic pathways exceeding multiple-testing correction filters. We identified the central hub genes PIK3R2, PPP3C and PTPN5 associated with MAPK signaling and insulin resistance terms. This is the first time that these genes have been associated with childhood obesity in both tissues. Therefore, they could be potential novel molecular targets for drugs and health interventions, opening new lines of research on the personalized care in this pathology. This work generates interesting hypotheses about the transcriptomics alterations underlying metabolic health alterations in obesity in the pediatric population.
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Affiliation(s)
- Mireia Bustos-Aibar
- Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada, 18071, Granada, Spain.
| | - Concepción M Aguilera
- Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada, 18071, Granada, Spain; Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition, Carlos III Health Institute, 28029, Madrid, Spain.
| | - Jesús Alcalá-Fdez
- Department of Computer Science and Artificial Intelligence, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, 18071, Granada, Spain.
| | - Francisco J Ruiz-Ojeda
- Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada, 18071, Granada, Spain; RG Adipocytes and Metabolism, Institute for Diabetes and Obesity, Helmholtz Diabetes Center at the Helmholtz Zentrum München, Neuherberg, 85764, Munich, Germany.
| | - Julio Plaza-Díaz
- Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada, 18071, Granada, Spain; Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Ontario, Canada.
| | - Abel Plaza-Florido
- PROmoting FITness and Health through physical activity research group, Sport and Health University Research Institute, Department of Physical Education and Sports, University of Granada, 18071, Granada, Spain; Pediatric Exercise and Genomics Research Center, Department of Pediatrics, School of Medicine, University of California at Irvine, Irvine, 92617, CA, United States.
| | - Inés Tofe
- Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition, Carlos III Health Institute, 28029, Madrid, Spain; University Clinical Hospital, Institute Maimónides of Biomedicine Investigation of Córdoba, University of Córdoba, 14004, Córdoba, Spain.
| | - Mercedes Gil-Campos
- Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition, Carlos III Health Institute, 28029, Madrid, Spain; University Clinical Hospital, Institute Maimónides of Biomedicine Investigation of Córdoba, University of Córdoba, 14004, Córdoba, Spain.
| | - María J Gacto
- Department of Software Engineering, University of Granada, 18071, Granada, Spain.
| | - Augusto Anguita-Ruiz
- Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada, 18071, Granada, Spain; Barcelona Institute for Global Health, ISGlobal, 08003, Barcelona, Spain.
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5
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Thompson HJ, Lutsiv T, McGinley JN, Fitzgerald VK, Neil ES. Consumption of Common Bean Suppresses the Obesogenic Increase in Adipose Depot Mass: Impact of Dose and Biological Sex. Nutrients 2023; 15:2015. [PMID: 37432145 PMCID: PMC10180429 DOI: 10.3390/nu15092015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/13/2023] [Accepted: 04/19/2023] [Indexed: 07/12/2023] Open
Abstract
Obesity prevention is stated as a simple objective in the public health guidelines of most countries: avoid adult weight gain. However, the success of the global population in accomplishing this goal is limited as reflected in the persisting pandemic of overweight and obesity. While many intervention strategies have been proposed, most are directed at mitigating the consequences of obesity. Efforts intended to prevent unintentional weight gain and associated adiposity are termed anti-obesogenic. Herein, evidence is presented that a neglected category of foods, pulses, i.e., grain legumes, have anti-obesogenic activity. Using a preclinical mouse model of obesity, a dose-response study design in animals of both biological sexes, and cooked, freeze-dried, and milled common bean as a representative pulse, data are presented showing that the rate of body weight gain is slowed, and fat accumulation is suppressed when 70% of the dietary protein is provided from common bean. These anti-obesogenic effects are reduced at lower amounts of common bean (17.5% or 35%). The anti-obesogenic responsiveness is greater in female than in male mice. RNA sequence analysis indicates that the sex-related differences extend to gene expression patterns, particularly those related to immune regulation within adipose tissue. In addition, our findings indicate the potential value of a precision nutrition approach for human intervention studies that identify "pulse anti-obesogenic responders". A precision approach may reduce the concentration of pulses required in the diet for benefits, but candidate biomarkers of responsivity to pulse consumption remain to be determined.
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Affiliation(s)
- Henry J. Thompson
- Cancer Prevention Laboratory, Colorado State University, Fort Collins, CO 80523, USA
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6
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Alur V, Raju V, Vastrad B, Vastrad C, Kavatagimath S, Kotturshetti S. Bioinformatics Analysis of Next Generation Sequencing Data Identifies Molecular Biomarkers Associated With Type 2 Diabetes Mellitus. Clin Med Insights Endocrinol Diabetes 2023; 16:11795514231155635. [PMID: 36844983 PMCID: PMC9944228 DOI: 10.1177/11795514231155635] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 01/19/2023] [Indexed: 02/23/2023] Open
Abstract
Background Type 2 diabetes mellitus (T2DM) is the most common metabolic disorder. The aim of the present investigation was to identify gene signature specific to T2DM. Methods The next generation sequencing (NGS) dataset GSE81608 was retrieved from the gene expression omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) between T2DM and normal controls. Then, Gene Ontology (GO) and pathway enrichment analysis, protein-protein interaction (PPI) network, modules, miRNA (micro RNA)-hub gene regulatory network construction and TF (transcription factor)-hub gene regulatory network construction, and topological analysis were performed. Receiver operating characteristic curve (ROC) analysis was also performed to verify the prognostic value of hub genes. Results A total of 927 DEGs (461 were up regulated and 466 down regulated genes) were identified in T2DM. GO and REACTOME results showed that DEGs mainly enriched in protein metabolic process, establishment of localization, metabolism of proteins, and metabolism. The top centrality hub genes APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1 were screened out as the critical genes. ROC analysis provides prognostic value of hub genes. Conclusion The potential crucial genes, especially APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1, might be linked with risk of T2DM. Our study provided novel insights of T2DM into genetics, molecular pathogenesis, and novel therapeutic targets.
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Affiliation(s)
- Varun Alur
- Department of Endocrinology, J.J.M
Medical College, Davanagere, Karnataka, India
| | - Varshita Raju
- Department of Obstetrics and
Gynecology, J.J.M Medical College, Davanagere, Karnataka, India
| | - Basavaraj Vastrad
- Department of Pharmaceutical Chemistry,
K.L.E. College of Pharmacy, Gadag, Karnataka, India
| | - Chanabasayya Vastrad
- Biostatistics and Bioinformatics,
Chanabasava Nilaya, Dharwad, Karnataka, India,Chanabasayya Vastrad, Biostatistics and
Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad, Karnataka 580001,
India.
| | - Satish Kavatagimath
- Department of Pharmacognosy, K.L.E.
College of Pharmacy, Belagavi, Karnataka, India
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7
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Ganekal P, Vastrad B, Kavatagimath S, Vastrad C, Kotrashetti S. Bioinformatics and Next-Generation Data Analysis for Identification of Genes and Molecular Pathways Involved in Subjects with Diabetes and Obesity. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:medicina59020309. [PMID: 36837510 PMCID: PMC9967176 DOI: 10.3390/medicina59020309] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 01/19/2023] [Accepted: 01/29/2023] [Indexed: 02/10/2023]
Abstract
Background and Objectives: A subject with diabetes and obesity is a class of the metabolic disorder. The current investigation aimed to elucidate the potential biomarker and prognostic targets in subjects with diabetes and obesity. Materials and Methods: The next-generation sequencing (NGS) data of GSE132831 was downloaded from Gene Expression Omnibus (GEO) database. Functional enrichment analysis of DEGs was conducted with ToppGene. The protein-protein interactions network, module analysis, target gene-miRNA regulatory network and target gene-TF regulatory network were constructed and analyzed. Furthermore, hub genes were validated by receiver operating characteristic (ROC) analysis. A total of 872 DEGs, including 439 up-regulated genes and 433 down-regulated genes were observed. Results: Second, functional enrichment analysis showed that these DEGs are mainly involved in the axon guidance, neutrophil degranulation, plasma membrane bounded cell projection organization and cell activation. The top ten hub genes (MYH9, FLNA, DCTN1, CLTC, ERBB2, TCF4, VIM, LRRK2, IFI16 and CAV1) could be utilized as potential diagnostic indicators for subjects with diabetes and obesity. The hub genes were validated in subjects with diabetes and obesity. Conclusion: This investigation found effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting new and key therapeutic targets for subjects with diabetes and obesity.
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Affiliation(s)
- Prashanth Ganekal
- Department of General Medicine, Basaveshwara Medical College, Chitradurga 577501, Karnataka, India
| | - Basavaraj Vastrad
- Department of Pharmaceutical Chemistry, K.L.E. College of Pharmacy, Gadag 582101, Karnataka, India
| | - Satish Kavatagimath
- Department of Pharmacognosy, K.L.E. College of Pharmacy, Belagavi 590010, Karnataka, India
| | - Chanabasayya Vastrad
- Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India
- Correspondence: ; Tel.: +91-9480073398
| | - Shivakumar Kotrashetti
- Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India
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8
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Xu J, Li J, Xu X, Chen P, Wang Q, Li A, Ren Y. IncRNA XIST Promotes Cardiac Fibrosis in Mice with Diabetic Nephropathy via Sponging miR-106a-5p to Target RUNX1. Crit Rev Eukaryot Gene Expr 2023; 33:55-66. [PMID: 36734857 DOI: 10.1615/critreveukaryotgeneexpr.2022044404] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Diabetic nephropathy (DN) accompanied by cardiac fibrosis (CF) increases the mortality rate among people with diabetes. This study sought to explore the molecular mechanism of long non-coding RNA X inactive specific transcript (lncRNA XIST) in CF in DN mice. The animal model of DN was established by streptozocin (STZ). The levels of lncRNA XIST, microRNA (miR)-106a-5p, and RUNX family transcription factor 1 (RUNX1) were determined by quantitative real-time polymerase chain reaction (qRT-PCR), followed by biochemical analysis, hematoxylin & eosin and Masson staining, echocardiography, and quantification of collagen I, collagen III, α-smooth muscle actin (α-SMA), and transforming growth factor-β1 (TGF-β1) levels through qRT-PCR and Western blot assay. The subcellular localization of lncRNA XIST was analyzed by nuclear/cytoplasmic fractionation assay and the bindings of miR-106a-5p to lncRNA XIST and RUNX1 were confirmed by RNA immunoprecipitation and dual-luciferase assays. Functional rescue experiments were performed to validate the role of miR-106a-5p/RUNX1 in CF in DN mice. lncRNA XIST and RUNX1 were elevated while miR-106a-5p was decreased in STZ mice. lncRNA XIST inhibition reduced myocardial injury and collagen deposition, along with decreased levels of fasting blood glucose, serum creatinine, blood urea nitrogen, and urinary microalbumin, collagen I, collagen III, α-SMA, and TGF-β1. lncRNA XIST competitively bound to miR-106a-5p to promote RUNX1 transcription. miR-106a-5p downregulation or RUXN1 upregulation reversed the protective role of lncRNA XIST inhibition in STZ mice. lncRNA XIST competitively bound to miR-106a-5p to promote RUNX1 transcription, thereby aggravating renal dysfunction and CF in DN mice.
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Affiliation(s)
- Jia Xu
- Department of Nephrology, Shenzhen University General Hospital, Shenzhen University, Shenzhen, Guangdong 518000, China
| | - Jinshun Li
- Department of Cardiovasology, South China Hospital, Health Science Center, Shenzhen University, Shenzhen, Guangdong 518116, China
| | - Xiaohui Xu
- Department of Nephrology, Shenzhen University General Hospital, Shenzhen University, Shenzhen, Guangdong 518000, China
| | - Peidan Chen
- Department of Nephrology, Shenzhen University General Hospital, Shenzhen University, Shenzhen, Guangdong 518000, China
| | - Qin Wang
- Department of Nephrology, Shenzhen University General Hospital, Shenzhen University, Shenzhen, Guangdong 518000, China
| | - Aiping Li
- Department of Endocrinology, Shenzhen University General Hospital, Shenzhen University, Shenzhen, Guangdong 518000, China
| | - Yeping Ren
- Department of Nephrology, Shenzhen University General Hospital, Shenzhen University, Shenzhen, Guangdong 518000, China
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9
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García-Pérez R, Ramirez JM, Ripoll-Cladellas A, Chazarra-Gil R, Oliveros W, Soldatkina O, Bosio M, Rognon PJ, Capella-Gutierrez S, Calvo M, Reverter F, Guigó R, Aguet F, Ferreira PG, Ardlie KG, Melé M. The landscape of expression and alternative splicing variation across human traits. CELL GENOMICS 2022; 3:100244. [PMID: 36777183 PMCID: PMC9903719 DOI: 10.1016/j.xgen.2022.100244] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/08/2022] [Accepted: 12/07/2022] [Indexed: 12/31/2022]
Abstract
Understanding the consequences of individual transcriptome variation is fundamental to deciphering human biology and disease. We implement a statistical framework to quantify the contributions of 21 individual traits as drivers of gene expression and alternative splicing variation across 46 human tissues and 781 individuals from the Genotype-Tissue Expression project. We demonstrate that ancestry, sex, age, and BMI make additive and tissue-specific contributions to expression variability, whereas interactions are rare. Variation in splicing is dominated by ancestry and is under genetic control in most tissues, with ribosomal proteins showing a strong enrichment of tissue-shared splicing events. Our analyses reveal a systemic contribution of types 1 and 2 diabetes to tissue transcriptome variation with the strongest signal in the nerve, where histopathology image analysis identifies novel genes related to diabetic neuropathy. Our multi-tissue and multi-trait approach provides an extensive characterization of the main drivers of human transcriptome variation in health and disease.
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Affiliation(s)
- Raquel García-Pérez
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Jose Miguel Ramirez
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Aida Ripoll-Cladellas
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Ruben Chazarra-Gil
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Winona Oliveros
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Oleksandra Soldatkina
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Mattia Bosio
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Paul Joris Rognon
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain,Department of Economics and Business, Universitat Pompeu Fabra, Barcelona, Catalonia 08005, Spain,Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, Barcelona, Catalonia 08034, Spain
| | - Salvador Capella-Gutierrez
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Miquel Calvo
- Statistics Section, Faculty of Biology, Universitat de Barcelona (UB), Barcelona, Catalonia 08028, Spain
| | - Ferran Reverter
- Statistics Section, Faculty of Biology, Universitat de Barcelona (UB), Barcelona, Catalonia 08028, Spain
| | - Roderic Guigó
- Bioinformatics and Genomics, Center for Genomic Regulation, Barcelona, Catalonia 08003, Spain
| | | | - Pedro G. Ferreira
- Department of Computer Science, Faculty of Sciences, University of Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal,Laboratory of Artificial Intelligence and Decision Support, INESC TEC, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal,Institute of Molecular Pathology and Immunology of the University of Porto, Institute for Research and Innovation in Health (i3s), R. Alfredo Allen 208, 4200-135 Porto, Portugal
| | | | - Marta Melé
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain,Corresponding author
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Guevara-Ramírez P, Cadena-Ullauri S, Ruiz-Pozo VA, Tamayo-Trujillo R, Paz-Cruz E, Simancas-Racines D, Zambrano AK. Genetics, genomics, and diet interactions in obesity in the Latin American environment. Front Nutr 2022; 9:1063286. [PMID: 36532520 PMCID: PMC9751379 DOI: 10.3389/fnut.2022.1063286] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 10/25/2022] [Indexed: 08/25/2023] Open
Abstract
Obesity is a chronic disease characterized by abnormal or excessive fat accumulation that could impact an individual's health; moreover, the World Health Organization (WHO) has declared obesity a global epidemic since 1997. In Latin America, in 2016, reports indicated that 24.2% of the adult population was obese. The environmental factor or specific behaviors like dietary intake or physical activity have a vital role in the development of a condition like obesity, but the interaction of genes could contribute to that predisposition. Hence, it is vital to understand the relationship between genes and disease. Indeed, genetics in nutrition studies the genetic variations and their effect on dietary response; while genomics in nutrition studies the role of nutrients in gene expression. The present review represents a compendium of the dietary behaviors in the Latin American environment and the interactions of genes with their single nucleotide polymorphisms (SNPs) associated with obesity, including the risk allele frequencies in the Latin American population. Additionally, a bibliographical selection of several studies has been included; these studies examined the impact that dietary patterns in Latin American environments have on the expression of numerous genes involved in obesity-associated metabolic pathways.
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Affiliation(s)
- Patricia Guevara-Ramírez
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Santiago Cadena-Ullauri
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Viviana A. Ruiz-Pozo
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Rafael Tamayo-Trujillo
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Elius Paz-Cruz
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Daniel Simancas-Racines
- Centro de Investigación en Salud Pública y Epidemiología Clínica (CISPEC), Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Ana Karina Zambrano
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
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11
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Ding K, Zhou Z, Ma Y, Li X, Xiao H, Wu Y, Wu T, Chen D. Identification of Novel Metabolic Subtypes Using Multi-Trait Limited Mixed Regression in the Chinese Population. Biomedicines 2022; 10:biomedicines10123093. [PMID: 36551856 PMCID: PMC9775185 DOI: 10.3390/biomedicines10123093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 11/25/2022] [Accepted: 11/29/2022] [Indexed: 12/03/2022] Open
Abstract
The aggregation and interaction of metabolic risk factors leads to highly heterogeneous pathogeneses, manifestations, and outcomes, hindering risk stratification and targeted management. To deconstruct the heterogeneity, we used baseline data from phase II of the Fangshan Family-Based Ischemic Stroke Study (FISSIC), and a total of 4632 participants were included. A total of 732 individuals who did not have any component of metabolic syndrome (MetS) were set as a reference group, while 3900 individuals with metabolic abnormalities were clustered into subtypes using multi-trait limited mixed regression (MFMR). Four metabolic subtypes were identified with the dominant characteristics of abdominal obesity, hypertension, hyperglycemia, and dyslipidemia. Multivariate logistic regression showed that the hyperglycemia-dominant subtype had the highest coronary heart disease (CHD) risk (OR: 6.440, 95% CI: 3.177-13.977) and that the dyslipidemia-dominant subtype had the highest stroke risk (OR: 2.450, 95% CI: 1.250-5.265). Exome-wide association studies (EWASs) identified eight SNPs related to the dyslipidemia-dominant subtype with genome-wide significance, which were located in the genes APOA5, BUD13, ZNF259, and WNT4. Functional analysis revealed an enrichment of top genes in metabolism-related biological pathways and expression in the heart, brain, arteries, and kidneys. Our findings provide directions for future attempts at risk stratification and evidence-based management in populations with metabolic abnormalities from a systematic perspective.
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12
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Ma S, Chen L, Yan J, Shen M, Zhang R, Li M, He M, Chen K, Zhu Y, Lin H, Wang Y, Liao W, Bin J, Zheng C, Liao Y. Dapagliflozin attenuates residual cardiac remodeling after surgical ventricular reconstruction in mice with an enlarged heart after myocardial infarction. Biomed Pharmacother 2022; 156:113765. [PMID: 36228368 DOI: 10.1016/j.biopha.2022.113765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 09/14/2022] [Accepted: 09/26/2022] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Severe heart failure refractory to conventional therapy requires alternative treatment modalities. Surgical ventricular reconstruction (SVR) has been used to reverse cardiac remodeling in post-myocardial infarction (MI) patients with large left ventricular (LV) aneurysm, however, residual LV remodeling and dysfunction remain postoperatively. It is unclear whether SVR recovers response to drug treatment and whether the sodium-glucose co-transporter 2 inhibitor dapagliflozin (DAPA) reverses residual LV remodeling after SVR. METHODS Adult male C57 mice were subjected to MI or sham surgery. Four-week later, MI mice with LV aneurysm underwent modified SVR or second open-chest sham operation and were randomized to DAPA or vehicle for four-week. Cardiac remodeling, LV function, and the underlying mechanisms were evaluated by echocardiography, invasive LV hemodynamic measurements, mRNA sequencing, and bioinformatics analysis. RESULTS SVR significantly decreased LV volume; increased myocardial strain, LV pressure change rates and end-systolic elastance; and decreased heart-to-body weight ratio and myocardial fibrosis. However, significant residual cardiac remodeling remained. DAPA significantly attenuated residual cardiac remodeling and improved LV function in SVR mice but did not have curative effects in non-SVR mice. Of the 1532 genes differentially expressed in SVR and MI mice, 1037 were associated with cardiac metabolism; Src, Crebbp, Fn1, Grb2, and Mapk14 were the top 5 hub genes. Unlike sham surgery, MI upregulated those 5 genes, and treatment with SVR + DAPA normalized their expression. CONCLUSIONS SVR restores therapeutic response in the post-MI heart with large LV aneurysm, and DAPA attenuates residual cardiac remodeling after SVR by normalizing some cardiac metabolism-related hub genes.
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Affiliation(s)
- Siyuan Ma
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Lu Chen
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Junyu Yan
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Mengjia Shen
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Rui Zhang
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Mingjue Li
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Mingyuan He
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Kaitong Chen
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Yingqi Zhu
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Hairuo Lin
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Yuegang Wang
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Wangjun Liao
- Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Jianping Bin
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Cankun Zheng
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China.
| | - Yulin Liao
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Guangdong Province Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China.
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de Medeiros AF, de Queiroz JLC, Maciel BLL, de Araújo Morais AH. Hydrolyzed Proteins and Vegetable Peptides: Anti-Inflammatory Mechanisms in Obesity and Potential Therapeutic Targets. Nutrients 2022; 14:nu14030690. [PMID: 35277049 PMCID: PMC8838308 DOI: 10.3390/nu14030690] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 02/04/2022] [Accepted: 02/04/2022] [Indexed: 11/21/2022] Open
Abstract
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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Affiliation(s)
- Amanda Fernandes de Medeiros
- Postgraduate Biochemistry and Biology Molecular Program, Biosciences Center, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil; (A.F.d.M.); (J.L.C.d.Q.)
| | - Jaluza Luana Carvalho de Queiroz
- Postgraduate Biochemistry and Biology Molecular Program, Biosciences Center, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil; (A.F.d.M.); (J.L.C.d.Q.)
| | - Bruna Leal Lima Maciel
- Department of Nutrition, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil;
- Postgraduate Nutrition Program, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil
| | - Ana Heloneida de Araújo Morais
- Postgraduate Biochemistry and Biology Molecular Program, Biosciences Center, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil; (A.F.d.M.); (J.L.C.d.Q.)
- Department of Nutrition, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil;
- Postgraduate Nutrition Program, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil
- Correspondence: ; Tel.: +55-84-9910-61887
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Ahmed MM, Tazyeen S, Haque S, Alsulimani A, Ali R, Sajad M, Alam A, Ali S, Bagabir HA, Bagabir RA, Ishrat R. Network-Based Approach and IVI Methodologies, a Combined Data Investigation Identified Probable Key Genes in Cardiovascular Disease and Chronic Kidney Disease. Front Cardiovasc Med 2022; 8:755321. [PMID: 35071341 PMCID: PMC8767007 DOI: 10.3389/fcvm.2021.755321] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 11/17/2021] [Indexed: 01/28/2023] Open
Abstract
In fact, the risk of dying from CVD is significant when compared to the risk of developing end-stage renal disease (ESRD). Moreover, patients with severe CKD are often excluded from randomized controlled trials, making evidence-based therapy of comorbidities like CVD complicated. Thus, the goal of this study was to use an integrated bioinformatics approach to not only uncover Differentially Expressed Genes (DEGs), their associated functions, and pathways but also give a glimpse of how these two conditions are related at the molecular level. We started with GEO2R/R program (version 3.6.3, 64 bit) to get DEGs by comparing gene expression microarray data from CVD and CKD. Thereafter, the online STRING version 11.1 program was used to look for any correlations between all these common and/or overlapping DEGs, and the results were visualized using Cytoscape (version 3.8.0). Further, we used MCODE, a cytoscape plugin, and identified a total of 15 modules/clusters of the primary network. Interestingly, 10 of these modules contained our genes of interest (key genes). Out of these 10 modules that consist of 19 key genes (11 downregulated and 8 up-regulated), Module 1 (RPL13, RPLP0, RPS24, and RPS2) and module 5 (MYC, COX7B, and SOCS3) had the highest number of these genes. Then we used ClueGO to add a layer of GO terms with pathways to get a functionally ordered network. Finally, to identify the most influential nodes, we employed a novel technique called Integrated Value of Influence (IVI) by combining the network's most critical topological attributes. This method suggests that the nodes with many connections (calculated by hubness score) and high spreading potential (the spreader nodes are intended to have the most impact on the information flow in the network) are the most influential or essential nodes in a network. Thus, based on IVI values, hubness score, and spreading score, top 20 nodes were extracted, in which RPS27A non-seed gene and RPS2, a seed gene, came out to be the important node in the network.
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Affiliation(s)
- Mohd Murshad Ahmed
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India
| | - Safia Tazyeen
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India
| | - Shafiul Haque
- Research and Scientific Unit, College of Nursing and Allied Health Science, Jazan University, Jazan, Saudi Arabia
| | - Ahmad Alsulimani
- Department of Medical Laboratory Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arbia
| | - Rafat Ali
- Department of Bioscience, Jamia Millia Islamia, New Delhi, India
| | - Mohd Sajad
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India
| | - Aftab Alam
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India
| | - Shahnawaz Ali
- Centre for Stem Cell & Regenerative Medicine, KING' College London, Guy's Hospital, London, United Kingdom
| | - Hala Abubaker Bagabir
- Department of Medical Physiology, Faculty of Medicine, King Abdulaziz University, Rabigh, Saudi Arabia
| | - Rania Abubaker Bagabir
- Department of Hematology and Immunology, College of Medicine, Umm-Al-Qura University, Mecca, Saudi Arabia
| | - Romana Ishrat
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India,*Correspondence: Romana Ishrat ; orcid.org/0000-0001-9744-9047
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15
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Bima AIH, Elsamanoudy AZ, Albaqami WF, Khan Z, Parambath SV, Al-Rayes N, Kaipa PR, Elango R, Banaganapalli B, Shaik NA. Integrative system biology and mathematical modeling of genetic networks identifies shared biomarkers for obesity and diabetes. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:2310-2329. [PMID: 35240786 DOI: 10.3934/mbe.2022107] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
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, obese, and T2D was analyzed by an integrated framework consisting of gene expression, protein interaction network (PIN), tissue specificity, and druggability approaches. Our findings show a total of 1932 unique differentially expressed genes (DEGs) across the diabetes versus obese group comparison (p≤0.05). The PIN analysis of these 1932 DEGs identified 190 high centrality network (HCN) genes, which were annotated against 3367 GO terms and functional pathways, like response to insulin signaling, phosphorylation, lipid metabolism, glucose metabolism, etc. (p≤0.05). By applying additional PIN and topological parameters to 190 HCN genes, we further mapped 25 high confidence genes, functionally connected with diabetes and obesity traits. Interestingly, ERBB2, FN1, FYN, HSPA1A, HBA1, and ITGB1 genes were found to be tractable by small chemicals, antibodies, and/or enzyme molecules. In conclusion, our study highlights the potential of computational biology methods in correlating expression data to topological parameters, functional relationships, and druggability characteristics of the candidate genes involved in complex metabolic disorders with a common etiological basis.
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Affiliation(s)
- Abdulhadi Ibrahim H Bima
- Department of Clinical Biochemistry, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ayman Zaky Elsamanoudy
- Department of Clinical Biochemistry, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Medical Biochemistry and Molecular Biology, Faculty of Medicine, Mansoura University, Mansoura, Egypt
| | - Walaa F Albaqami
- Department of Science, Prince Sultan Military College of Health Sciences, Dhahran, Saudi Arabia
| | - Zeenath Khan
- Department of Science, Prince Sultan Military College of Health Sciences, Dhahran, Saudi Arabia
| | | | - Nuha Al-Rayes
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
- Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Prabhakar Rao Kaipa
- Department of Genetics, College of Science, Osmania University, Hyderabad, India
| | - Ramu Elango
- Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Babajan Banaganapalli
- Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Noor A Shaik
- Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
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