Research Project: Understanding the Genetic Roots of Obesity Across Populations
Abstract
Description
Obesity is a major global health challenge, with its prevalence on the rise and severe consequences for individuals and healthcare systems. Unraveling the genetic factors that contribute to obesity is crucial for developing targeted and effective prevention and treatment strategies.Our study aims to address this challenge by developing an innovative bioinformatics pipeline to identify genetic factors linked to obesity from large-scale next-generation sequencing datasets. Our analysis pipeline, tailored to the Turkish population structure, integrates innovative techniques for sample-, variant- and gene-based annotation, filtering, and prioritization. This algorithm leverages advanced bioinformatic methods, including variant-, gene-, pathway-, and family-based rare variant aggregation analyses, alongside phenome-wide association tests (PheWAS). Our pipeline refined over 12 years through collaborations with leading experts, including, Sir Stephen O\"Rahilly, Sadaf Farooqi, Jeffrey Friedman and Richard P. Lifton.Our initial analyses have already identified promising candidates. To validate and enrich these findings, we need to test our pipeline with the UK Biobank dataset. The UK Biobank\"s extensive genomic and phenotypic data will enable robust cross-population comparisons and strengthen the reliability of our results. By comparing these two cohorts, we hope to answer a key question: Are the obesity-related genes and rare genetic variants identified in the Turkish population also associated with obesity in the UK Biobank?Our research objectives include: - Developing and implementing a powerful bioinformatics pipeline to process and analyze rare genetic variants linked to obesity traits such as BMI. - Classifying UK Biobank participants into obesity cases and controls based on BMI measurements. - Investigating the rare genetic variants and candidate genes identified in the Turkish cohort to determine their relevance in the UK Biobank.
Keywords
Bilgisayar Bilimleri, Biyoenformatik, Yaşam Bilimleri, Moleküler Biyoloji ve Genetik, Genetik Bozuklukların Moleküler Biyolojisi, Populasyon Biyolojisi, Populasyon Genetiği, Temel Bilimler, Mühendislik ve Teknoloji, Computer Sciences, bioinformatics, Life Sciences, Molecular Biology and Genetics, Genetic Disorders, Population Biology, Population Genetics, Natural Sciences, Engineering and Technology, Mühendislik Bilişim ve Teknoloji (Eng), Bilgisayar Bilimi Teori ve Yöntem, Temel Bilimler (Sci), Yaşam Bilimleri (Life), Bilgisayar Bilimi, Doğa Bilimleri Genel, Çok Disiplinli Bilimler, Gelişimsel Biyoloji, Engineering Computing & Technology (Eng), Computer Science Theory & Methods, Natural Sciences (Sci), Life Sciences (Life), Computer Science, Molecular Biology & Genetics, Natural Sciences General, Multidisciplinary Sciences, Developmental Biology, Embriyoloji, Teorik Bilgisayar Bilimi, Bilgisayar Bilimi Uygulamaları, Bilgisayar Bilimi (çeşitli), Genel Bilgisayar Bilimi, Moleküler Biyoloji, Multidisipliner, Sağlık Bilimleri, Fizik Bilimleri, Embryology, Theoretical Computer Science, Computer Science Applications, Computer Science (miscellaneous), General Computer Science, Molecular Biology, Multidisciplinary, Health Sciences, Physical Sciences