Balkan Journal of Medical Genetics

COMPARATIVE ANALYSIS OF GENES ASSOCIATED WITH OBESITY IN HUMANS USING BIOINFORMATIC DATA AND TOOLS
Musliji ZS1, Pollozhani AK1, Lisichkov K2, Deligios M3, Popovski ZT2,4,*
*Corresponding Author: Professor Zoran T. Popovski, Ph.D., Department of Biochemistry and Genetic Engineering, Faculty of Agriculture and Food Sciences, Bld “Aleksandar Makedonski,” bb PB 297, 1000 Skopje, Republic of North Macedonia. Tel: +389-70-252-731. Fax: +389-2-3134-310. E-mail: zoran_ popovski@yahoo.com
page: 35

INTRODUCTION

Obesity is becoming a major global challenge for humanity. It is expected that in one decade, 38.0% of adults around the world will be overweight, if the current growth rate continues [1]. Obesity occurs because of an unbalanced intake of energy. This imbalance contributes to the occurrence of many chronic diseases such as cardiovascular, diabetes, musculoskeletal disorders, and several types of malignant diseases [2-4]. Obesity is multifactorial. In addition to the non genetic factors, such as nutritional habits and physical inactivity, genetic factors and genetic predisposition play a significant role [2,5,6]. So far, 127 genetic loci have been studied that have a potential link to overweight and obesity [1,4]. Despite many attempts to find a solution to this phenomenon and to reduce the number of people suffering from these diseases, the long-term solution is still being investigated. The development of obesity as a phenomenon is complex [7] and has not been fully understood. Prevention, as a promising strategy for dealing with this disease, can be achieved by better understanding and controlling of the factors that lead to its manifestation. The analysis and characterization of genetic factors associated with obesity is therefore particularly important. In the last two decades, various tools have been developed to research, collect data, analyze, and better understand genetic factors. One way of gene analysis is through bioinformatic tools. Bioinformatics is a modern scientific discipline that combines computer science and molecular biology. Bioinformatic tools analyze proteins and nucleic acids, i.e., genes and gene products using computer algorithms and appropriate databases [8]. Due to the ability to quickly analyze biological data, bioinformatics has become an immensely popular and useful field. Specifically, it enables the analysis of biological data such as DNA, RNA, amino acid sequence of proteins, identification of various characteristics and molecular interactions, prediction of 3D structures, etc. All this can be done with tools that are widely available to potential users [9]. Osman et al. [4] has recently performed a bioinformatic analysis of the single nucleotide polymorphisms (SNP) of the human FTO gene (fat and obesity gene) and suggested that the use of in silico analysis may be a good approach to targeting SNPs in other genes associated with the appearance of overweight and obesity. Appa Rao et al. [7] has also used bioinformatic tools to analyze the genes involved in diabetes-related obesity. A similar study was conducted by Abdella [10], which concluded that this method of analysis was useful for further studies related to therapeutic and preventive findings for certain diseases. In this study, using online bioinformatic tools, data related to the FTO, PPARG (peroxisome proliferator activated receptor γ), ADRB3 (adrenergic receptor β 3) and FABP2 (fatty acid binding protein 2) genes, which have been associated with obesity in humans, were collected and analyzed.

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