Biology subjects

Abubaker, J.

Publications and source records attributed to Abubaker, J..

3 recordsLinked to original sources

bioRxiv2023

ANGPTL8 R59W variant influences inflammation through modulating NF-κB pathway under TNFα stimulation

BackgroundANGPTL8 is known to regulate lipid metabolism and inflammation. It interacts with ANGPTL3 and ANGPTL4 to regulate LPL activity, and with IKK/{beta} to modulate NF-{kappa}B activity. Further, a SNP leading to ANGPTL8 R59W variant associates with reduced LDL/HDL and increased FBG in Hispanic and Arab individuals, respectively. In this study, we investigate the impact of R59W variant on the inflammatory activity of ANGPTL8. MethodsANGPTL8 R59W variant was genotyped in a discovery cohort of 867 Arab individuals from Kuwait. Plasma levels of ANGPTL8 and inflammatory markers were measured and tested for associations with the genotype; the associations were tested for replication in an independent cohort of 278 Arab individuals. Impact of the ANGPTL8 R59W variant on NF-{kappa}B activity was examined using approaches including overexpression, luciferase assay, and structural modeling of binding dynamics. ResultsThe ANGPTL8 R59W variant was associated with increased circulatory levels of TNF and IL7. NF-{kappa}B activity, as assessed by the increased in the phosphorylation of IKK-/{beta} protein, I{kappa}B, and NF-{kappa}B p-65 in R59W variant compared to wild type, and TNF stimulation further elevated it. This finding was substantiated by increased luciferase activity of NF-{kappa}B p65 with the R59W variant. Modeled structural and binding variation due to R59W change in ANGPTL8 agreed with the observed increase in NF-{kappa}B activity. ConclusionANGPTL8 R59W is associated with increased circulatory TNF, IL7 and NF-{kappa}B p65 activity. Weak transient binding of ANGPTL8 R59W variant explains its regulatory role on the NF-{kappa}B pathway and inflammation.

biochemistry↗

bioRxiv2020

A comprehensive germline variant and expression analyses of ACE2, TMPRSS2 and SARS-CoV-2 activator FURIN genes from the Middle East: Combating SARS-CoV-2 with precision medicine

The severity of the new COVID-19 pandemic caused by the SARS-CoV-2 virus is strikingly variable in different global populations. SARS-CoV-2 uses ACE2 as a cell receptor, TMPRSS2 protease, and FURIN peptidase to invade human cells. Here, we investigated 1,378 whole-exome sequences of individuals from the Middle Eastern populations (Kuwait, Qatar, and Iran) to explore natural variations in the ACE2, TMPRSS2, and FURIN genes. We identified two activating variants (K26R and N720D) in the ACE2 gene that are more common in Europeans than in the Middle Eastern, East Asian, and African populations. We postulate that K26R can activate ACE2 and facilitate binding to S-protein RBD while N720D enhances TMPRSS2 cutting and, ultimately, viral entry. We also detected deleterious variants in FURIN that are frequent in the Middle Eastern but not in the European populations. This study highlights specific genetic variations in the ACE2 and FURIN genes that may explain SARS-CoV-2 clinical disparity. We showed structural evidence of the functionality of these activating variants that increase the SARS-CoV-2 aggressiveness. Finally, our data illustrate a significant correlation between ACE2 variants identified in people from Middle Eastern origins that can be further explored to explain the variation in COVID-19 infection and mortality rates globally.

genetics↗

bioRxiv2017

Application of High-Dimensional Statistics and Network based Visualization techniques on Arab Diabetes and Obesity data

BackgroundObesity and its co-morbidities are characterized by a chronic low-grade inflammatory state, uncontrolled expression of metabolic measurements and dis-regulation of various forms of stress response. However, the contribution and correlation of inflammation, metabolism and stress responses to the disease are not fully elucidated. In this paper a cross-sectional case study was conducted on clinical data comprising 117 human male and female subjects with and without type 2 diabetes (T2D). Characteristics such as anthropometric, clinical and bio-chemical measurements were collected.\n\nMethodsAssociation of these variables with T2D and BMI were assessed using penalized hierarchical linear and logistic regression. In particular, elastic net, hdi and glinternet were used as regularization models to distinguish between cases and controls. Differential network analysis using closed-form approach was performed to identify pairwise-interaction of variables that influence prediction of the phenotype.\n\nResultsFor the 117 participants, physical variables such as PBF, HDL and TBW had absolute coefficients 0.75, 0.65 and 0.34 using the glinternet approach, biochemical variables such as MIP, ROS and RANTES were identified as determinants of obesity with some interaction between inflammatory markers such as IL4, IL-6, MIP, CSF, Eotaxin and ROS. Diabetes was associated with a significant increase in thiobarbituric acid reactive substances (TBARS) which are considered as an index of endogenous lipid peroxidation and an increase in two inflammatory markers, MIP-1 and RANTES. Furthermore, we obtained 13 pairwise effects. The pairwise effects include pairs from and within physical, clinical and biochemical features, in particular metabolic, inflammatory, and oxidative stress markers.\n\nConclusionsWe showcase that markers of oxidative stress (derived from lipid peroxidation) such as MIP-1 and RANTES participate in the pathogenesis of diseases such as diabetes and obesity in the Arab population.

bioinformatics↗