Title:Identification of Functional Variants Associated with Obesity in Pakistani Kindred
Volume: 1
Issue: 1
Author(s): Ayesha Aftab, Syed Babar Jamal and Syeda Marriam Bakhtiar*
Affiliation:
- Genetic and Molecular Epidemiology Research Group, Department of Bioinformatics and Biosciences, Faculty of Health and Life Sciences, Capital University of Science and Technology, Islamabad,Pakistan
Keywords:
Obesity, SNPs, obesity-associated genes, functional variants, protein stability analysis, FTO, MC4R, LEPR, POMC.
Abstract:
Background: Obesity is an emerging pandemic considered to be an outcome of change in
lifestyle owing to more processed food and the use of mechanical locomotives. Obesity has not only
appeared as a problem in the esthetic appearance of an individual rather is a serious health issue due
to its associations with various chronic diseases such as coronary and cardiovascular problems, hypertension,
osteoarthritis, type-II diabetes mellitus, hyperlipidemia, and certain cancers. It is estimated
that 30 percent of the world’s population, i.e. approximately 2.1 billion people, are victims of
obesity. In addition to environmental causes, various genes and a group of genes are reported to be
increasing the suceptibility of obesity.
Objective: Pakistan is a heterogeneous population, an amalgam of various races, therefore, narrowing
down the list of obesity-associated genes and their functional variance could help molecular biologists
to select potential SNPs in the Pakistani population for molecular diagnosis and treatment.
Method: The extraction of a set of obesity-associated genes has been performed by using Polysearch2.
SNPs for each gene are retrieved from dbSNP. RegulomeDB and SNPinfo tools have been
used for the functional analysis of SNPs retrieved against the Pakistani population. For the prediction
of potential deleterious SNPs, SIFT, Polyphen-2, MUTTASTER, MUTASSESSOR, and LRT
(likelihood ratio test) are utilized. Functional analysis of potential deleterious SNPs has been performed
by studying protein stability and mapping of identified SNPs to protein structure. For the
protein stability analysis, I-Mutant and SNPs3D have been used.
Results: Four genes FTO, POMC, LEPR, and MC4R and further analysis revealed 3 deleterious
SNPs in FTO, 4 in POMC, 1 in LEPR, and 1 in MC4R.
Conclusion: This research was designed to identify obesity-associated genes and the most impactful
deleterious SNPs in these genes. These findings will be helpful for the molecular biologists and
pharmacists to design better and focused diagnosis and treatment strategies.
