Associations of galectin-3 expression and LGALS-3 (rs4652) gene variant with coronary artery disease risk in diabetics

Ibrahim, Basma A; Mohamed, Samy Hassanin; Hassaan, Mohamed M M; Sabbah, Norhan A.

doi:10.5937/jomb0-30424

Cited by 5 publications

(5 citation statements)

References 43 publications

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“…One of the studies conducted by Zhen et al (7), reported elevated expression of Galectin-3BP and positive correlation with obesity and MetS in 932 Chinese adolescents. On the other side Besma et al (21) obtained no statistically significant results regarding BMI among patients with type 2 diabetes mellitus regarding rs4644 genotype. One of the possible explanation of these results are differences in gonadal hormonal status.…”

Section: Discussionmentioning

confidence: 90%

Galectin 3 rs4644 gene polymorphism is associated with metabolic traits in Serbian adolescent population

Vidović,

Novaković,

Damnjanović

et al. 2024

J Med Biochemistry

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Background: Among many genes which have been analyzed to understand obesity and related metabolic traits among children and adolescents, not many studies are conducted on LGALS3 gene, especially in population of children. A positive correlation of circulating galectin 3 serum levels with impaired blood glucose, high blood pressure and higher values of serum lipids and was found in general population. The aim was to investigate possible association of rs4644 with body mass index, glycaemia, and lipid profile in Serbian adolescents. Methods: The study included 72 boys and 79 girls, 14-15 years of age. Among boys 51 (67.1%) had normal values of BMI, 11 (14.5%) were overweight, and 14 (18.4%) were obese. Among girls, 53 (63.9%) had normal BMI, 16 (19.3%) were overweight, and 14 (16.9%) were obese. Diabetes type 1 or 2, genetic syndromes, generalized inflammation, cardiovascular and malignant diseases were criteria for exclusion. Genotyping was performed by Real time PCR. Results: Girls carriers of CC genotype had statistically higher mean values of BMI, and triglycerides in comparison to the girls carriers of CA+AA genotypes, p=0.041, and p=0.045, respectively. The higher frequency of obese was found among group of girls who were carriers of CC genotype, p=0.049. No statistically significant association was observed among other analyzed parameters in neither examined groups. Conclusion: Our research indicates that there is an association between the CC genotype of rs4644 polymorphism with obesity and higher triglycerides level in the group of female adolescents.

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Section: Discussionmentioning

confidence: 90%

Galectin 3 rs4644 gene polymorphism is associated with metabolic traits in Serbian adolescent population

Vidović,

Novaković,

Damnjanović

et al. 2024

J Med Biochemistry

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“…Inflammation and local innate immune response are considered cornerstone pathogenic mechanisms of atherosclerotic CAD (13) . Ibrahim et al (14) concluded that Gal-3 expression level was a CAD risk factors in diabetic patients. Our aim was to assess serum Gal-3 levels among CAD cases and its role in the evaluation of CAD severity and prediction.…”

Section: Discussionmentioning

confidence: 99%

Correlation between coronary artery disease and Galectin 3 serum level: Angiographic based study

Osman,

Algamal,

Elshal

et al. 2024

Ain Shams Medical Journal

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Background: Galectin 3 (Gal-3) has great impact on initiation and progression of atherosclerosis as a cardiovascular inflammatory marker. The role of Gal-3 in coronary artery disease (CAD) remains a subject of debate. CAD and atherosclerosis are an inflammatory process. Aim of the work: to evaluate Gal-3 concentrations among patients with CAD presented with acute coronary syndrome (ACS) and chronic coronary syndrome (CCS).Patients and Methods: 252 individuals were divided into control group with normal coronary angiography and patient group with obstructive CAD which was further subdivided according to the clinical presentations into ACS and CCS subgroups. All groups were matched for age and sex.Results: significantly higher Gal-3 values were found in CAD group, ACS subgroup, and CCS subgroup versus control group. Gal-3 values were significantly higher in ACS subgroup compared with CCS subgroup. Gal-3 concentrations demonstrated a non-significant association with age and EF. Gal-3 levels showed significant positive relationship with Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) score in CAD group, CCS subgroup, and ACS subgroup. Gal-3 concentrations demonstrated significant positive relationship with the number of stenotic coronary arteries and segments in CAD group and CCS subgroup but not in ACS subgroup. Gal-3 was found to significantly predict coronary artery disease.Conclusions: Gal-3 concentrations correlated with CAD's presence and severity. We recommend the integration of Gal-3 in the diagnostic, prognostic, and predictive modules of CAD.

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“…Recent studies have shown that altered expression of DDX58 [413], STAT1 [414], TLR4 [415], CYP2D6 [416], JAK2 [417], TLR2 [418], DUSP6 [419], HDAC9 [420], LATS2 [421], CA2 [150], HIPK3 [422], CCR2 [423], GAB1 [120], UFL1 [424], OGT (O-linked N-acetylglucosamine (GlcNAc) transferase) [425], PRKAR1A [265], SIRT1 [426], FGL2 [427], TET2 [428], ASCC2 [429], BIN1 [430], HSPB1 [431], IGFBP4 [432], TRPM4 [433] and LGALS3 [434] might be associated with the progression of heart failure. STAT1 [435], TLR4 [436], ABCA1 [437], PTGS2 [68], CYP2D6 [438], CR1 [439], PDK4 [440], RNF213 [441], ZDHHC17 [70], TLR8 [442], PDGFC (platelet derived growth factor C) [443], TLR2 [444], CYP1B1 [445], HDAC9 [446], IL1RN [447], GCH1 [448], EGR1 [449], ZEB2 [450], PLA2G7 [451], CCR2 [452], GCLC (glutamate-cysteine ligase catalytic subunit) [258], VEGFA (vascular endothelial growth factor A) [453], CD46 [454], NFKBIZ (NFKB inhibitor zeta) [455], LDLR (low density lipoprotein receptor) [456], TLR6 [457], SIRT1 [458], NOD2 [459], FGL2 [460], IDH1 [461], TET2 [462], PFKFB2 [463], KDM6A [464], IKZF2 [465], ZNF606 [466], PF4 [467], CCR7 [468], RUNX3 [469], TCF7 [470], PPBP (pro-platelet basic protein) [471], IGFBP4 [280], HSPG2 [472] and LGALS3 [236] expression might be regarded as an indicator of susceptibility to CAD. STAT1 [473], TLR4 [367], JAK2 [474], PDGFC (platelet derived growth factor C) […”

Section: Discussionmentioning

confidence: 99%

Identification of novel prognostic targets in coronary artery disease and related complications using bioinformatics and next generation sequencing data analysis

Vastrad¹,

Vastrad²

2023

Preprint

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Coronary artery disease (CAD) is the most common cardiovascular disorder and the leading cause of heart related deaths in world. Increasing molecular targets have been discovered for CAD and CAD - related complications prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might help the diagnosis and treatment of CAD and CAD related complications. We searched next generation sequencing (NGS) dataset (GSE202625) and identified differentially expressed genes (DEGs) by comparing CAD and normal control samples using DESeq2. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g:Profiler online database. The protein protein interaction (PPI) network was plotted with IMEx interactome and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. MiRNA hub gene regulatory network and TF hub gene regulatory network analysis was performed to identify the hub genes, miRNAs and TFs. Receiver operating characteristic (ROC) curve analysis was used to predict the diagnostic effectiveness of the hub genes. A total of 118 DEGs (479 up regulated genes and 479 down regulated genes) were detected. The GO enrichment analysis indicated that the DEGs most significantly enriched in cellular response to stimulus and biosynthetic process. The REACTOME pathway enrichment analysis revealed that the DEGs were most significantly enriched in immune system and eukaryotic translation elongation. PPI network, modules, miRNA hub gene regulatory network and TF hub gene regulatory network analysis demonstrated that EGR1, SIRT1, STAT1, LRRK2, HIF1A, CSNK2B, RPS3, RPS2, RPS4X and HDAC11 were the hub genes. On the whole, the findings of this study enhance our understanding of the potential molecular mechanisms of CAD and CAD-related complications, and provide potential targets for further research.

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Associations of galectin-3 expression and LGALS-3 (rs4652) gene variant with coronary artery disease risk in diabetics

Cited by 5 publications

References 43 publications

Galectin 3 rs4644 gene polymorphism is associated with metabolic traits in Serbian adolescent population

Galectin 3 rs4644 gene polymorphism is associated with metabolic traits in Serbian adolescent population

Correlation between coronary artery disease and Galectin 3 serum level: Angiographic based study

Identification of novel prognostic targets in coronary artery disease and related complications using bioinformatics and next generation sequencing data analysis

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