News

The rising incidence of obesity presents one of the most disturbing and widespread public health problems for many societies. In the UK the rate of obesity has roughly doubled since the 1980s, with approx 17% of men and 21% of women now classed as obese and so at increased risk of diabetes, strokes, heart disease and cancer.

Earlier studies show that genetic predisposition is the major factor in determining whether a person becomes overweight as it accounts for 70-80% of the risk, with lifestyle playing a far smaller role. As with many other common complex conditions however, obesity doesn’t result from changes in just one gene, rather it is caused by changes in a whole series of genes, the combined effect of which is the propensity to gain weight.

In 2007 researchers scanned the genome of thousands of diabetic and obese individuals in a genome-wide association study that identified a gene called FTO, showing that individuals who possess a particular sequence variation in FTO are, on average, 3 kg heavier than those who don’t (see previous news).

However, obesity results from the interaction of many different genes in combination with different environmental effects. This complexity makes identification of each individual gene challenging using conventional techniques. In light of this, two studies published in the journal Nature have taken a different line – rather than attempting to identify individual genes, they measured gene expression levels (a measure of how much protein-coding sequence is produced by each gene) to identify networks of genes that are associated with obesity (see Reuters report).

In one study, the team measured the expression of nearly 24 000 known genes in blood and fat samples from hundreds of Icelanders in the database of the genetics company deCODE. This identified characteristic gene expression patterns in fat that correlate with body mass index (BMI, a measurement of obesity). The team used the data to identify ‘networks’ of hundreds of interacting genes that are regulated together and associated with obesity. A related study in mice indicates that many of these genes are associated with inflammation, so confirming the known link between obesity and the immune system. Furthermore, individual sub-networks associated with diabetes and atherosclerosis can be identified.

Although these reports do not necessarily identify which genes in the network are the root cause of obesity and which become altered as a consequence, they do highlight potential areas for intervention. As one author says: “We’re not just looking at one gene, that may or may not be druggable...We’re looking at what are the best nodes, or information control points. What’s the best light switch to affect the network maximally?” With this in mind, it should be noted that most genes (and the proteins they encode) might be involved in several unrelated pathways so that manipulating the ‘obesity’ network might cause harmful changes in other unrelated networks. 

Such work highlights the extraordinary complexity that lies behind genetic susceptibility to common multifactorial conditions such as obesity and associated metabolic diseases such as diabetes. The identification of individual contributory genetic factors involved adds to knowledge and understanding, and could even prove useful for the creation of therapeutic interventions to aid weight loss, ultimately, as one author states: “good diet and exercise is still probably the best treatment or way to prevent the onset of obesity".