Polygenic, or common, obesity arises when an individual's genetic makeup is susceptible to an environment that promotes energy intake over energy expenditure. Specifically, environments in most westernized societies favor weight gain rather than loss because of food abundance and lack of physical activity, thus rendering common obesity as a major epidemic currently challenging the medical and financial resources in these societies (37).
A range of polygenic mouse models have been generated through inbreeding of mouse lines or repeated selections of noninbred mice, and have enabled the identification of >408 quantitative trait loci (QTL) associated with obesity (http://obesitygene. pbrc.edu). A recent meta-analysis of ~280 QTL, from 34 mouse cross-breeding experiments involving >14,500 mice, revealed 58 QTL regions associated with body weight and adiposity (http://www.obesitygenes.org) (68). Different QTL have been associated with the age of onset and gender in obesity, while certain loci may only contribute to obesity by interacting with other loci (69).
In humans, studies of polygenic obesity are based on the analysis of single nucle-otide polymorphisms (SNPs) or repetition of bases (polyCAs or microsatellites) located within or near a candidate gene. These studies are carried out in family members (family study) or unrelated individuals (case-control study), and their objective is to determine a potential association between a gene's allelic variant and obesity-related traits (70). However, unlike monogenic obesity, many genes and chromosomal regions contribute to the common obese phenotype (7,71). For this purpose, large DNA banks have been established from different populations throughout the world and are used for the extensive investigation of large number of genes and chromosomal regions. The findings of these genetic studies are reported every year by the Human Obesity Gene Map consortium. According to their latest report, 253 QTL have been identified, in 61 genome-wide scans (7). All chromosomes, except the Y chromosome, have been found linked with an obesity-related phenotype, such as fat mass, distribution of adipose tissue, resting energy expenditure, or levels of circulating leptin and insulin. Genes associated with obesity include solute carrier family 6 (neurotransmitter transporter) member 14 (SLC6A14), glutamate decarboxylase 2 (GAD2), and ectonucleotide pyrophosphatase/ phosphodiesterase I (ENPPI) (72-74). These genes have been implicated in a variety of biological functions such as the regulation of food intake, energy expenditure, lipid and glucose metabolism, adipose tissue development, and inflammatory processes. Recent genome-wide association studies have identified genetic variants (SNPs) associated with obesity-related traits in both children and adults, in the fat mass and obesity associated (FTO) gene (75-77, 272). It has been proposed that through its catalytic activity, FTO may regulate the transcription of genes involved in metabolism (78).
In contrast to genetically identical mice, whose environments can be controlled, the genetic and environmental diversity in humans has proved problematic for data replication. To date, only 22 obesity-related genes are supported by at least five positive studies (7,37). The reasons for the lack of replication in association and linkage studies include lack of statistical power to detect modest effect, lack of control over type I error rate, and overinterpretation of marginal data (79). Thus, the use of novel approaches may provide the means to circumvent classical statistical obstacles in identifying new candidate genes and possible gene-environment interactions (see Sect. 4).
The immense ongoing research on the identification of new molecular targets for an-tiobesity drugs and the significance of the generated findings is reflected by the rapidly increasing number of patent applications. Specifically, a total of 173 US patents were issued between January 2001 and March 2004, with the word "obesity" included in the abstract (80,81). Among the molecular targets with the highest number of new patents are the serotonin receptor ligands (24 patents), neuropeptide Y receptor ligands (20 patents), and adrenergic receptor ligands (20 patents).
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