ABSTRACT
BACKGROUND: Acute myocardial infarction (AMI) and diabetic nephropathy (DN) are common clinical co-morbidities, but they are challenging to manage and have poor prognoses. There is no research on the bioinformatics mechanisms of comorbidity, and this study aims to investigate such mechanisms. METHODS: We downloaded the AMI data (GSE66360) and DN datasets (GSE30528 and GSE30529) from the Gene Expression Omnibus (GEO) platform. The GSE66360 dataset was divided into two parts: the training set and the validation set, and GSE30529 was used as the training set and GSE30528 as the validation set. After identifying the common differentially expressed genes (DEGs) in AMI and DN in the training set, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and protein-protein interaction (PPI) network construction were performed. A sub-network graph was constructed by MCODE, and 15 hub genes were screened by the Cytohubba plugin. The screened hub genes were validated, and the 15 screened hub genes were subjected to GO, KEGG, Gene MANIA analysis, and transcription factor (TF) prediction. Finally, we performed TF differential analysis, enrichment analysis, and TF and gene regulatory network construction. RESULTS: A total of 46 genes (43 up-regulated and 3 down-regulated) were identified for subsequent analysis. GO functional analysis emphasized the presence of genes mainly in the vesicle membrane and secretory granule membrane involved in antigen processing and presentation, lipopeptide binding, NAD + nucleosidase activity, and Toll-like receptor binding. The KEGG pathways analyzed were mainly in the phagosome, neutrophil extracellular trap formation, natural killer cell-mediated cytotoxicity, apoptosis, Fc gamma R-mediated phagocytosis, and Toll-like receptor signaling pathways. Eight co-expressed hub genes were identified and validated, namely TLR2, FCER1G, CD163, CTSS, CLEC4A, IGSF6, NCF2, and MS4A6A. Three transcription factors were identified and validated in AMI, namely NFKB1, HIF1A, and SPI1. CONCLUSIONS: Our study reveals the common pathogenesis of AMI and DN. These common pathways and hub genes may provide new ideas for further mechanistic studies.
Subject(s)
Diabetic Nephropathies , Myocardial Infarction , Transcription Factors , Myocardial Infarction/genetics , Humans , Diabetic Nephropathies/genetics , Transcription Factors/genetics , Transcription Factors/metabolism , Protein Interaction Maps , Computational Biology/methods , Gene Expression Profiling , Gene Regulatory Networks , Gene Ontology , Gene Expression Regulation , Databases, GeneticABSTRACT
Introduction: The retina is a highly metabolically active tissue, and there is a lack of clarity about the relationship between metabolites and diabetic retinopathy (DR). This study used two-sample bidirectional Mendelian randomization (MR) analyses to identify causal relationships between metabolites and DR. Methods: Genetic variants were selected from the open-access Genome-Wide Association Studies (GWAS) summary database as proxies for the 1400 most recently published metabolites. MR analysis was performed to examine associations between these metabolite traits and DR. Single nucleotide polymorphism (SNP) data that were significantly associated with exposure were screened through association analysis. Validated instrumental variables (IVs) were obtained by removing SNPs with linkage disequilibrium (LD) and F-statistic values below 10. MR analyses were performed using the inverse variance weighted (IVW) method as the primary approach. The robustness of the results was verified by sensitivity analyses, including assessments of heterogeneity, horizontal pleiotropy, and the leave-one-out method. Results: In the IVW approach and in the primary analysis of several sensitivity analyses, genetically determined glycolithocholate sulfate levels, androstenediol (3 beta, 17 beta) monosulfate (1) levels, 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4) levels, 1-oleoyl-2-arachidonoyl-GPE (18:1/20:4) levels, 1-oleoyl-2-linoleoyl-GPE (18:1/18:2) levels, X-26109 levels, N6-methyllysine levels, (N6,N6-dimethyllysine levels), and (N2-acetyl,N6,N6-dimethyllysine levels) were negatively associated with the risk of DR. 5-hydroxymethyl-2-furoylcarnitine levels and the glutamate-to-alanine ratio were positively associated with the risk of DR. No reverse causal association was found between DR and metabolites. Discussion: This MR study suggests that nine metabolites may have a protective effect in DR, while two metabolites may be associated with an increased risk of DR. However, further research is needed to confirm these findings. Supplementation with beneficial metabolites may reduce DR risk and could potentially be a novel therapeutic approach to DR treatment.
Subject(s)
Diabetic Retinopathy , Genome-Wide Association Study , Mendelian Randomization Analysis , Polymorphism, Single Nucleotide , Humans , Diabetic Retinopathy/genetics , Diabetic Retinopathy/bloodABSTRACT
AIM: This systematic review and meta-analysis aimed to comprehensively evaluate the impact of glucagon-like peptide 1 receptor agonists (GLP-1RAs) on visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in individuals with diabetes mellitus and non-alcoholic fatty liver disease (NAFLD) or obesity. METHODS: A search of PubMed, Embase, and Web of Science until October 2023 identified 13 Randomized Controlled Trials (RCTs) meeting the inclusion criteria. Bias risk was assessed using the Cochrane risk-of-bias instrument. Statistical analysis utilized standard mean differences (SMD) in Review Manager 5.4. Heterogeneity and publication bias were assessed. This study used the protocol registered with the Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY2023110020). RESULTS: GLP-1RA treatment significantly reduced VAT (SMD -0.55, 95 % CI [-0.90, -0.19]), SAT (SMD -0.59, 95 % CI [-0.99, -0.19]), body weight (SMD -1.07, 95 % CI [-1.67, -0.47]), and body mass index (BMI) (SMD -1.10, 95 % CI [-1.74, -0.47]) compared to controls. Heterogeneity was observed for VAT (I2 = 79 %, P < 0.01), SAT (I2 = 73 %, P < 0.01), body weight (I2 = 82 %, P < 0.01), and BMI (I2 = 82 %, P < 0.01). No publication bias was detected for VAT (P = 0.57) and SAT (P = 0.18). GLP-1RA treatment improved fasting blood glucose (FBG), postprandial glucose (PPG), hemoglobin A1c (HbA1c), Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), and fibrosis-4 (FIB-4). CONCLUSIONS: This meta-analysis highlights GLP-1RAs' potential to reduce fat accumulation, body weight, and BMI and improve glycemic control in individuals with diabetes mellitus and NAFLD or obesity. These findings supported using GLP-1RAs as promising therapeutic agents to address abnormal adipose tissue distribution and metabolic dysfunction.