ABSTRACT
KAI WANG, WEI-DONG LI, CLARENCE K. ZHANG, ZUOHENG WANG, JOSEPH T. GLESSNER, STRUAN F. A. GRANT, HONGYU ZHAO, HAKON HAKONARSON, and R. ARLEN PRICE
3.1 INTRODUCTION
Obesity is the sixth most important risk factor contributing to the overall burden of disease worldwide [1]. Affected subjects have reduced life expectancy, and they suffer from several adverse consequences such as cardiovascular disease, type 2 diabetes and several cancers. Many studies have shown that body weight and obesity are strongly influenced by genetic factors, with heritability estimates in the range of 65-80% [2], [3]. Genetic variants in several genes are known to influence BMI, but these mutations are rare and often cause severe monogenic syndromes with obesity [4]. With the development of high-throughput genotyping techniques and the implementation of genome-wide association studies (GWAS), common variations, such as those in FTO [5] and MC4R [6], have been associated with obesity and body mass index (BMI). Recent large-scale
meta-analysis of multiple GWAS identified additional genes harboring common SNPs that associate with BMI [7]–[10]. GWASs have also found associations with measures of body fat distribution [9], [11], [12]. By far the largest GWAS to date included almost 250 thousand individuals and 2.8 million SNPs [13]. Associations of BMI with 28 loci reached genome wide significance, including 10 that were reported previously and 18 that were newly identified. Four additional loci were associated with body fat distribution, all of which had been identified previously. However, even this major expansion of sample size has not explained much variation, 1.39% for BMI and 0.16% for body fat distribution. On the other hand, confirmation of existing BMI loci, and detailed analysis on their association with obesity as a binary trait and with other obesity-related quantitative traits, are important at the current stage to move GWAS signals forward and understand their functional consequences.
