Obesity is an important disease globally, and has resulted in significant increases in morbidity and mortality in both the developed and developing worlds. There are many proposed explanations for the current obesity epidemic, but it is clear that genetics plays a significant part in whether a person becomes obese by affecting susceptibility to the current obesogenic environment, which is characterized by easy access to high-calorie food and reduced energy expenditure owing to decreased levels of physical activity in daily life.
Although the precise physiological basis of obesity remains unclear, skewed energy balance, abnormalities of fat storage and mobilization, and disordered feeding behaviour may all play a part.
Both genome-wide linkage scans and candidate gene association studies have had limited success in identifying genes underlying non-syndromic obesity, although genes responsible for monogenic obesity have been identified.
Recently, the genome-wide association scan method has been used to successfully identify many novel SNPs associated with non-syndromic obesity. These results have significantly increased the number of obesity-related loci for which there is strong statistical evidence at the genome-wide level.
The question remains why analysis of SNPs has not identified any variants of sufficiently large genetic effect to account for the level of heritability observed in obesity. Other forms of genomic variation may account for this, for example, low frequency SNPs, copy number variants and epigenetic modifications.
Key strategies for the future of genetic studies in obesity include improving subject selection, phenotype measurement, and genome-wide study design. A systems-based approach to synthesizing genome-wide data sets is likely to be a fruitful approach to identifying obesity genes.
The last few years have seen major advances in common non-syndromic obesity research, much of it the result of genetic studies. This Review outlines the competing hypotheses about the mechanisms underlying the genetic and physiological basis of obesity, and then examines the recent explosion of genetic association studies that have yielded insights into obesity, both at the candidate gene level and the genome-wide level. With obesity genetics now entering the post-genome-wide association scan era, the obvious question is how to improve the results obtained so far using single nucleotide polymorphism markers and how to move successfully into the other areas of genomic variation that may be associated with common obesity.
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Obesity research in the authors' laborarories is funded by the Wellcome Trust and the Medical Research Council.
The authors declare no competing financial interests.
The proportion of the total phenotypic variation in a given characteristic that can be attributed to additive genetic effects. In the broad sense, heritability involves all additive and non-additive genetic variance, whereas in the narrow sense, it involves only additive genetic variance.
- Admixture mapping
Genetic mapping using individuals whose genomes are mosaics of fragments that are descended from genetically distinct populations. This method exploits differences in allele frequencies in the founders to determine ancestry at a locus in order to map traits to specific populations.
- Genome-wide association study
A hypothesis-free method of investigating the association between common genetic variation and disease. This type of analysis requires a dense set of markers (for example, SNPs) that capture a substantial proportion of common variation across the genome, and large numbers of study subjects.
A brain region located below the thalamus, forming the main portion of the ventral region of the diencephalon and functioning to regulate bodily temperature, certain metabolic processes and other autonomic activities.
A genetic locus that is identified through the statistical analysis of a quantitative trait, such as height or body weight.
- Case–control study
This is the comparison of cases (individuals with disease) with controls (otherwise similar individuals who do not have the disease) to determine whether genetic marker allele frequencies differ between the two groups, that is, are associated with susceptibility to or protection from disease.
- Minor allele frequency
The frequency of the less common allele of a biallelic genetic marker in a given population.
- Prospective cohort
This is a group of subjects initially assessed for exposure to certain risk factors and then followed over time to evaluate the progression towards specific outcomes (often disease). This forms the basis of a longitudinal study.
- Population substructure
This is the presence of hidden subgroups in a population caused by, for example, admixture, population stratification or inbreeding. If this is not accounted for it may lead to increased type 1 error and decreased statistical power.
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Walley, A., Asher, J. & Froguel, P. The genetic contribution to non-syndromic human obesity. Nat Rev Genet 10, 431–442 (2009). https://doi.org/10.1038/nrg2594
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