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Confirmatory Results

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

Raghvendra Mall, Reda Rawi, Ehsan Ullah, Khalid Kunji, Abdelkrim Khadir, Ali Tiss, Jehad Abubaker, Mohammed Dehbi, Halima Bensmail
doi: https://doi.org/10.1101/151621
Raghvendra Mall
1Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar
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Reda Rawi
1Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar
2Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
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Ehsan Ullah
1Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar
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Khalid Kunji
1Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar
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Abdelkrim Khadir
3Dasman Diabetes Institute, Kuwait City, Kuwait
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Ali Tiss
3Dasman Diabetes Institute, Kuwait City, Kuwait
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Jehad Abubaker
3Dasman Diabetes Institute, Kuwait City, Kuwait
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Mohammed Dehbi
4Diabetes Research Centre, Qatar Biomedical Research Institute, Hamad Bin Khalifa University, Doha, Qatar
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Halima Bensmail
1Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar
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  • For correspondence: hbensmail@hbku.edu.qa
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Abstract

Background Obesity 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.

Methods Association 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.

Results For 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.

Conclusions We 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.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted June 18, 2017.
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Application of High-Dimensional Statistics and Network based Visualization techniques on Arab Diabetes and Obesity data
Raghvendra Mall, Reda Rawi, Ehsan Ullah, Khalid Kunji, Abdelkrim Khadir, Ali Tiss, Jehad Abubaker, Mohammed Dehbi, Halima Bensmail
bioRxiv 151621; doi: https://doi.org/10.1101/151621
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Application of High-Dimensional Statistics and Network based Visualization techniques on Arab Diabetes and Obesity data
Raghvendra Mall, Reda Rawi, Ehsan Ullah, Khalid Kunji, Abdelkrim Khadir, Ali Tiss, Jehad Abubaker, Mohammed Dehbi, Halima Bensmail
bioRxiv 151621; doi: https://doi.org/10.1101/151621

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