Muhammad-Redha Abdullah-Zawawi

Diabesotension, the coexistence of diabetes mellitus, obesity, and hypertension, represents an increasingly prevalent and clinically significant cardiometabolic syndrome. Epidemiological evidence highlights strong bidirectional relationships among these conditions, which together markedly elevate the risk of cardiovascular disease, stroke, nephropathy, and premature mortality. The pathophysiology of diabesotension is multifactorial, involving insulin resistance, chronic hyperglycemia, obesity-associated inflammation, endothelial dysfunction, sympathetic overactivity, and activation of the renin–angiotensin–aldosterone system (RAAS), culminating in adverse metabolic and hemodynamic interactions. Clinically, the synergistic presence of diabetes and hypertension accelerates both microvascular and macrovascular complications, leading to poorer outcomes than either condition alone. Recognizing diabesotension as a distinct clinical entity may facilitate more comprehensive care models and improved long-term outcomes, highlighting the need for continued research to refine risk stratification and optimize individualized treatment strategies. In this review, we focus on the genes implicated in key hallmarks of diabesotension, including insulin resistance, inflammation, RAAS activation, and oxidative stress, relevant clinical management strategies, and AI-based models for risk stratification of this triad of diseases.

Diabesotension refers to the pathophysiological association between diabetes mellitus, obesity, and hypertension. Despite their frequent coexistence, the underlying molecular mechanisms driving this triad remain poorly understood, and current therapeutic strategies typically address each condition in isolation rather than targeting their shared pathophysiological pathways. To identify potential hallmark genes underlying diabesotension, we mined gene associations with the triad from the NCBI database. Our analysis revealed that AKT1 and NF-κB1 are implicated in four major hallmarks of diabesotension, such as insulin resistance, inflammation, neurohormonal regulation, and oxidative stress. Collectively, these findings highlight the PI3K/Akt and NF-κB pathways as potential molecular drivers in the pathogenesis of diabesotension. This commentary will provide a comprehensive discussion of these findings within the broader context of current knowledge on the role of PI3K/Akt and NF-κB signaling in diabesotension.

Anterior gradient protein 2 (AGR2), a member of the protein disulfide isomerase family, plays a critical role in endoplasmic reticulum proteostasis and has been implicated in breast cancer progression. However, the downstream regulatory programs and signaling pathways governed by AGR2 remain incompletely defined. Here, we employed CRISPR–Cas9-mediated knockout of AGR2 in breast cancer cells to systematically investigate the functional and transcriptional consequences of AGR2 loss. AGR2 depletion resulted in significant suppression of cell migration, invasion, and chemoresistance. Unbiased transcriptomic profiling by RNA sequencing revealed extensive differential gene expression, implicating AGR2 in receptor-mediated signaling, oxidative stress responses, and cell adhesion pathways. Protein–protein interaction network analysis identified several highly connected hub genes within the AGR2-regulated transcriptome, including estrogen receptor alpha (ESR1/ERα), cadherin 1 (CDH1), androgen receptor (AR), lymphocyte cell-specific protein-tyrosine kinase (LCK), S100 calcium binding protein P (S100P), parkin RBR E3 ubiquitin ligase (PRKN), and decay-accelerating factor (CD55). Notably, ERα emerged as a prominent node within this network, consistent with prior reports linking ERα and AGR2 biology. Integration with publicly available epigenomic datasets further supports a potential regulatory connection between ERα-associated chromatin landscapes and AGR2 expression. Together, these findings define AGR2-dependent transcriptional networks in breast cancer and identify ESR1-associated signaling as a key pathway perturbed upon AGR2 loss, providing a foundation for future mechanistic studies targeting this regulatory interaction.

Background: The Rho-associated kinase (ROCK) signaling pathway was reported to be overexpressed in cancer, as it promotes multiple hallmarks of cancer. However, the characterization of ROCK signaling pathway expression in dual-stage carcinogenesis of lung squamous cell carcinoma (LUSC) remains unclear. Therefore, this study aims to evaluate ROCK signaling pathway expression during LUSC progression in vivo . Methods: Female BALB/c mice were treated with N-nitroso-tris-chloroethylurea (NTCU) to induce pre-malignant and malignant LUSC stages. The lung tissues were subjected to immunohistochemistry and Western blot for ROCK-associated protein expression analysis. Then, differentially expressed genes (DEGs) analysis from two expression profiling datasets: GSE30219 and GSE31446, was performed to determine the mRNA expression of ROCK-associated proteins in human LUSC. Protein-protein interaction (PPI) network (analysed via Cytoscape) and correlation analysis (analysed via Gene Expression Profiling Interactive Analysis 2; GEPIA2) were also conducted to identify the relationships between each ROCK-associated protein. Results: This study found a significantly higher expression (p-value<0.05) of ROCK-associated proteins such as pFAK, RhoABC, ROCK1, ROCK2, and pMLC during LUSC progression via IHC and Western blot assays. Notably, RhoA, RhoB, and pMLC (MYL9) mRNA were significantly upregulated in human LUSC. The PPI and correlation analysis identified RhoA, ROCK1, and ROCK2 as highly correlated ROCK-associated genes encoded proteins in LUSC. Conclusion: Increased ROCK-associated proteins and genes expression in dual-stage carcinogenesis of LUSC may reflect their essential role in cancer growth. Bioinformatic analysis results verify the importance of ROCK signaling pathways in LUSC growth, making them promising targets for future LUSC treatment.

Glucose-6-phosphate dehydrogenase deficiency (G6PDd) is one of the most common genetic disorders worldwide and remains highly prevalent in malaria-endemic regions. Individuals with G6PDd are at risk of severe complications, including acute haemolytic anaemia, when exposed to oxidative triggers. In Malaysia, the Proto-Malay Orang Asli (PMOA), the second largest indigenous group in Peninsular Malaysia, represents a vulnerable population. This study aimed to estimate the prevalence and mutation spectrum of G6PDd in this community. A total of 258 peripheral blood samples (91 males, 167 females) were screened using a quantitative G6PD assay (OSMMR2000-D). DNA from 73 samples was genotyped with the Hybribio G6PD GenoArray test, and 39 underwent targeted sequencing. The adjusted male median (AMM) of G6PD activity was 9.6 U/gHb (95% CI: 8.9–10.3 U/gHb), with 30% and 80% thresholds corresponding to 2.9 and 7.7 U/gHb, respectively. At the 30% cut-off threshold, the overall estimated prevalence of G6PDd was 6.8% (16/237; 12 males and 4 females). A total of 21 subjects were G6PD-intermediate (7 males and 14 females), and the remaining 221 subjects were G6PD-normal (72 males and 150 females). Genotyping identified 18 hemizygous males, 13 heterozygous females, and 3 homozygous females. Five G6PD variants were detected: G6PD Viangchan (39.5%), G6PD Coimbra (28.9%), G6PD Union (23.7%), G6PD Kaiping (5.3%), and rs782038151 (2.6%). This study demonstrates that G6PDd is common in the PMOA population, with notable molecular diversity. These findings have important implications for malaria control and the safe use of antimalarial drugs in this high-risk community.

Background: Familial hypercholesterolemia (FH) is a significant risk factor for atherosclerosis due to elevated levels of low-density lipoprotein (LDL) cholesterol in arterial walls. This study aimed to determine the key genes involved in the development of atherosclerosis among FH patients. Methods: The Affymetrix microarray dataset (GSE13985), which includes samples from five healthy controls and five FH patients, was obtained from the Gene Expression Omnibus (GEO) database. CEMiTool, an R package, was used to establish a modular gene co-expression network (mGCN) from 45,118 Affymetrix probe sets, followed by gene set enrichment analysis to determine the activity of modular gene regulation in the FH group, overrepresentation analysis to identify gene functions associated with FH, and hub gene detection. Results: A scale-free topological network of gene co-expression modules (GCM) was built, and the activity of three important modules (M2, M4, and M5) was revealed to be upregulated in FH samples compared to healthy controls with putative involvement in atherosclerosis-related biological functions and pathways as follows: regulation of cell migration, cholesterol, inflammation, innate immunity, shear stress, and lipid pathways. Based on our integrated analyses, GCMs revealed seven hub genes, RHOA, ACTB, LYN, ACTG1, BCL6, BCL2L1, and STAT3, as promising biomarkers for developing and designing effective therapeutics for atherosclerosis in FH patients. Conclusion: Seven hub genes have been identified as potential biomarkers for hypercholesterolemia, suggesting a role in the development of atherosclerosis in FH patients. These findings may aid in biomarker discovery and therapeutic targeting for FH-related atherosclerosis.

Background Diabesotension, an overlapping triad of diabetes, hypertension, and obesity, remains a diagnostic challenge due to its complex underlying molecular mechanisms. Individuals with diabesotension face twice the risk of microvascular and macrovascular complications compared to those with either condition alone. However, the complexity of diabesotension poses significant diagnostic challenges due to limited knowledge of this disease trifecta. Methods The protein network was constructed, and the DPClusOST algorithm was applied to determine the protein clusters with a density ranging from 0.1 to 1.0 and those relevant to the pathophysiology of diabesotension. The significance score (SScore) was computed using the p-value from Fisher’s exact test to evaluate each cluster, and the clusters containing proteins associated with diabesotension were classified using receiver operating characteristic (ROC) analysis. The significant density of the cluster, as indicated by the AUC, was determined and subsequently subjected to pathway enrichment analysis using ShinyGO. Results At densities of 0.6 and 0.8, 14 proteins (STX3, VAMP2, STX4, SYT1, DNAJC5, HSD17B10, DLD, AIFM1, PDHA1, PDHB, DLAT, PDHX, OGDH, and STAT5A) from clusters 13 and 53 were significantly identified as potential diabesotension-related proteins. Key pathways associated with the tripartite interplay of the three pathologies were found to involve amino acid metabolism, glycolysis/gluconeogenesis, SNARE-mediated vesicle transport, insulin and salivary secretion, and the glucagon and HIF-1 signaling pathways, thus identifying novel candidates for diabesotension biomarkers and therapeutic targets. Conclusions This study highlights the use of graph clustering to identify potential biomarkers for the comorbid triad, which could enhance personalized future treatment strategies.

Potassium voltage-gated channel subfamily H member 2 (KCNH2) polymorphisms have been found to influence the heart-rate adjusted QT (QTc) intervals. We investigated the association between KCNH2 polymorphisms and QTc intervals among Malay opioid-dependent methadone maintenance treatment (MMT) recipients. A cross-sectional study was conducted involving 111 patients with stable methadone dosage for at least 6 months attending several methadone clinics in Kelantan, Malaysia between March 2011 and October 2012. Those with cardiac structural defects, recipients of other QTc-prolonging pharmacotherapeutic agents, had aggressive behavior or other active psychiatric illnesses, chronic medical and surgical ailments and who were unable to communicate in Malay and English were excluded. The Fridericia-corrected QTc intervals were recorded using a 12-lead electrocardiogram. DNA samples were extracted from peripheral blood leukocytes and genotyped using nested allele-specific polymerase chain reaction for these four KCNH2 polymorphisms: 1539C > T, 1956T > C, 2350C > T, and 2690A > C. Mean QTc interval is 408 ms (SD: 24). Molecular docking was performed on all four KCNH2 polymorphisms to investigate the impact of the nucleotide changes on methadone binding. Based on multiple regression analysis, only 1539T > C polymorphism (β_adjusted: 10.506 (95% CI:0.846, 20.166), p = 0.033; recessive model), serum methadone trough (β_adjusted: 0.025 (95% CI: 0.006, 0.043), p = 0.009), potassium (β_adjusted: -8.756 (95% CI: -15.938, -1.575), p = 0.017) and magnesium (β_adjusted: -106.226 (95% CI: -159.291, -53.161), p < 0.001) levels were significantly associated with mean QTc. Molecular docking analysis resulted in good binding-energy values between the 1539C > T and methadone, with the formation of hydrophobic and π–π stacking interactions, suggesting that 1539C > T was the newly discovered SNP involved in QTc prolongation. In conclusion, the 1539C > T KCNH2 polymorphism is associated with QTc prolongation in our MMT recipients, necessitating QTc monitoring to prevent methadone-associated cardiotoxicity in this Malay MMT population.

Background: Hepatocellular carcinoma is a highly encountered primary liver malignancy, currently ranked as the third major contributor to death worldwide. This research endeavoured to establish non-invasive prognostic determinants of hepatocellular carcinoma (HCC) and characterise their underpinning molecular mechanisms. Methods: Publicly available microarray data within the Gene Expression Omnibus repository were analysed to determine genetic elements that were differentially expressed. We subsequently developed a network of protein–protein interactions and established the densely interconnected clusters (core genes) underlying the network using these differentially expressed genes (DEGs). The prognostic significance of individual core gene was characterised by evaluating its impact on overall survival in HCC. The levels of expression of these core genes underwent further verification from a proteomic perspective by utilising The Human Protein Atlas (HPA) and evaluated for their link with immune cell trafficking within HCC tissues. Results: Four core genes (GTF2H1, SF3A3, FANCI, and XRCC5) were identified, which have been associated with HCC and play significant roles in immune cell trafficking through a positive correlation with neutrophils, dendritic cells, and macrophages. Furthermore, GTF2H1 exhibited positive correlations with genetic markers of M1 macrophages (IRF5), dendritic cells (NRP1), and Th1 cells (STAT1); SF3A3 with dendritic cells (NRP1) and PDL1 (CD274); FANCI with M1 macrophages (IRF5); and XRCC5 with PDL1 (CD274) and Th1 cells (STAT1), implying that these core genes might influence or be involved in immune response pathways by promoting immune cell activity. Using the HPA protein expression database, immunohistochemistry findings reaffirmed that the four genes’ expressed protein levels were more elevated in HCC than in healthy hepatocytes. Conclusion: Our prognostic signature and immune infiltration provided novel insights into prognostic indicators and potential immunotherapeutic targets for HCC. Future research endeavours are warranted to explore further the clinical importance, applicability, and therapeutic consequences of the identified biomarkers in larger cohorts.