Quantitative trait loci (QTL) - The Genetics of Human Obesity

QTL are loci which individually have a small but measurable influence on a continuous phenotype such as body weight rather than giving rise to discrete disease present or absent phenotypes. The principal advantage of this methodology is that interactions between loci each having only a small phenotypic effect may be investigated, particularly where the sum of more than one such effect is large.

The principle of attempting to define QTL as a tool for gene mapping relies on the fact that rodents may be selectively inbred to produce strains that differ widely in body weight and fat deposition under the influence of polygenic loci. Breeds with opposite poles of a phenotypic extreme may then be crossbred to produce F1 progeny whose phenotype will depend on the exact genotype inherited from each parental strain (Brockmann and Bevova, 2002).

The resultant F1 generation may then be back-crossed to a parent or permitted to bred with siblings to generate a back-cross or sib-mated F2 population containing a number of allele combinations (and phenotypes) not encountered in either of the parental or F1 strains. Provided the two breeds differ in one or more molecular markers associated with each locus (e.g. restriction fragment length polymorphisms, microsatellites or single nucleotide polymorphisms), the F2 generation may be genotyped and phenotyped to associate genetic markers (and thus specific allele combinations) with the resulting phenotype.

Over 165 QTL spanning the entire genome (except the Y chromosome) have been mapped in animals (mainly mice) to date (Rankinen et al., 2002). Many appear to exert rather modest effects on phenotype (as may be expected in a complex polygenic disorder) although some do appear to have more major effects. Following identification of QTL in mice, loci of interest may be mapped to the homologous (syntenic) region in man and the region further tested for association with obesity in a human population.

Thus, the many benefits of performing genetic studies in mice may be reaped whilst maintaining relevance to human populations. These advantages include stable environmental conditions, pure breeding strains, the ability to perform sibling and back-cross mating, rapid breeding (generation) times and the ability to obtain accurate phenotypical data. At present, the use of this method has identified QTL having effects on intermediary phenotypes such as thermogenesis, serum leptin levels and insulin resistance, gene–environment interactions such as susceptibility to diet-induced obesity and with time of obesity onset and gender-specific susceptibility to obesity (Brockmann and Bevova, 2002).

Because this technique examines the effects of many combinations of more than one allele, the opportunity to examine gene–gene interactions is presented.

For example, the mouse strains M. Spretus and C57BL/6 are relatively lean as are the F1 progeny resulting from crossing these parental strains. However, back-crossed progeny (with allelic combinations not found in the parental or F1 strains) vary in percentage body fat content from about 1 to 60 per cent. Significant association (LOD score >3.3) was found in the back-crossed F2 progeny between a number of intermediary phenotypes and four genomic regions (designated as mob1–4 on chromosomes 7, 6, 12 and 15, respectively). A further association with percentage body fat, accounting for some 7 per cent of the observed variance of this trait, was considered 'suggestive' rather than statistically significant (Warden et al., 1995; Warden and Fisler, 1998). These loci include a number of plausible candidate genes including IGFR-1 (mob1), ob (mob2) and GH receptor (mob4). It is of interest that M. Spretus-derived alleles appear to promote obesity at chromosomes 6, 7 and 12, whereas C57BL/6- derived alleles promote obesity only when present on chromosome 15 and then only when the loci at 6, 7, and 12 are heterozygous, providing a clear demonstration of the complexities of epistasis in the aetiology of complex polygenic disorders such as obesity.