Ochoa et al (11) found a significant interaction between two gene variants, PPAR λ 2 and ADR β 3, in the risk of obesity in children and adolescents. After adjusting for family history of obesity, the researchers found that carriers of both gene variants were almost 20 times more likely to be obese than noncarriers (odds ration [OR] 19.5; 95% confidence interval [CI], 2.4–146.8), suggesting a synergistic effect between the two genes.

The effects of genes may vary depending on a person's age. Argyropoulos et al (12) reported an association between a mutation in the gene for agouti-related protein (a strong appetite stimulator) and obesity in older adults. The mutation was not associated with obesity in study subjects with a mean age of 25 years but was significantly associated with fat and abdominal adiposity in the subjects' parents, whose mean age was 53 years.

Numerous studies explored gene–environment–lifestyle interactions. Martinez et al (13) found that an interaction between diet and specific genes may affect obesity risk. They found an increased obesity risk for women with a Glu27 variant and a diet with more than 49% of calories coming from carbohydrates. An alternate variant of that same gene was not associated with an increased obesity risk in relation to carbohydrate intake, given the same number of calories consumed. Another study (14) found that moderate alcohol intake was associated with reduced abdominal fat among middle-aged women genetically predisposed to obesity, whereas abstinence or light alcohol intake was not. The study also found that among people with high polyunsaturated fat intake, those with low genetic risk for obesity have lower levels of abdominal fat than those with high genetic risk for obesity. This finding suggests that the effect of diet on obesity depends on genetic factors.

Changes in gene expression that result from epigenetic influences (modifications of DNA structure rather than DNA sequence) were also explored because of their potential role in obesity and associated chronic diseases. Associations between fetal environment (undernutrition or exposure to maternal hyperglycemia) and adult-onset obesity may be due to epigenetic influences that promote fat storage, but possible mechanisms are not well understood (15,16).

Distribution of fat, rather than amount of total body fat, appears to play a key role in metabolic consequences associated with obesity. Excess central abdominal fat is particularly associated with adverse consequences. People with fat concentrated in the abdomen are more likely to develop diabetes than are people with the same amount of fat distributed throughout the body (17). A study of postmenopausal women also suggests that genetics has a role in abdominal fat deposition (18).

Although many researchers and policy makers recognize the need to mitigate the increasing rate of obesity, studies indicate that the effectiveness of prevention strategies is limited (19). Understanding the biology of weight regulation, including the effect of an obesigenic environment on gene expression, is essential to the development of effective interventions. For instance, if obesity is related to genetic changes caused by fetal exposures in utero or shortly after birth, more emphasis on maternal and infant nutrition will be needed.

As discussed earlier, children with obese parents are at particular risk of becoming obese. Studies are needed to determine the effectiveness of obesity screening and prevention strategies based on family history. Also needed is an evaluation of the effectiveness of identifying children at risk for obesity at an early age (or even prenatally) and of intervening with families to prevent those children from gaining excess weight.

The premise of nutrigenomics is that a person's optimal diet is determined by genetic makeup. Nutrigenomics proponents maintain that dietary intervention based on individual genotype can prevent or treat chronic disease and manage weight (20). Although nutrigenomic profiling combined with personalized interventions based on those profiles may help prevent and manage obesity in the future, data to support the efficacy of this approach are not available now (21,22). Unfortunately, lack of data has not stopped companies from marketing genetic tests directly to the public and from making claims about the efficacy of basing nutritional advice on the results of those tests.

Although development of drugs for obesity may have little appeal for those who primarily advocate environmental and lifestyle change, effective medications may be the best hope for some individuals struggling to maintain a healthy weight. Studies to identify the genomics of obesity and use the results to develop drug treatments are under way (23). Aitman (24) suggests that gene expression patterns may help define particular subtypes of obesity and may help in developing antiobesity drugs.

Although gene-based approaches (e.g., nutrigenomics, pharmacogenomics) are not yet ready for widespread application, information from genomic studies gives us clues about how to manage obesity. In 2003, Lowe (25) reported that people with a genetic predisposition to obesity have difficulty self-regulating food intake to maintain weight loss or prevent weight gain, even if they had extensive education in how to do so. Lowe concluded that weight control programs that focus on lifestyle modifications based primarily on cognitive–behavioral change are not effective because they do not consider that availability of food is a biological stimulus to eating, particularly for those genetically prone to obesity. Programs that provide portion-controlled, nutrient-dense meals may be more effective than other programs because they limit opportunities for participants to consume energy-dense foods. Lowe argues that, to stem the tide of obesity, individuals and communities need to eliminate many food stimuli (e.g., overabundance of food, large portion sizes, high-calorie foods).

Baseline data are needed to understand familial risk for obesity and to monitor changes in eating behavior. Using family history information to estimate population risk for obesity is a promising concept because family history reflects genetic predisposition, behavioral factors, and shared environmental factors that may contribute to obesity. Identifying population subgroups at greater than average risk of obesity because of familial factors may provide a basis for targeted intervention. More data are also needed on the interactions between genetic risks and environmental and lifestyle risks. Valuable information could be gleaned by adding questions about family history of obesity to population surveys (e.g., Behavioral Risk Factor Surveillance System) and by cross-tabulating family history factors with lifestyle and environmental factors.

The advent of genetic technology introduced a new set of public policy issues. Two such issues are genetic testing and population databases.

Genetic testing

Direct-to-consumer marketing of genetic profiling raises many questions about public policy: Should genetic testing be regulated and by whom? Are there potential or real harms to the public from not regulating genetic testing? In the absence of regulation, should public health agencies monitor genetic testing to ensure that public health is not jeopardized?

Databases

Large-scale databases containing genetic information could provide information about links between gene variants and health conditions such as obesity. Although the potential benefits to various populations are great, the associated risks for individuals with deleterious genetic variants may also be great. The question is this: how do we protect information in databases so as to prevent discrimination against individuals?

A key public health function is to ensure that everyone has access to the services needed to achieve optimal health. The potential for developing genetic tests with results that can be used to decide which drugs are most effective for treating obesity and other conditions holds promise. Pharmacogenomics is already used to treat some diseases (e.g., cancer). However, advances in pharmacogenomics could also aggravate health disparities. As new treatments emerge, public health will have an important role in ensuring fair distribution of services to the entire population (23,24).

Despite increasing exposure to genetic information through the media and in schools, the public's genetic literacy remains low. Misperceptions (e.g., genes equal destiny) are common. Public health has an important role in demystifying genetics and clarifying genetic concepts, not only as they apply to obesity but also as they apply to other health conditions. Studies to determine the value of incorporating genomic information into obesity prevention and education programs are needed.

Although health care and public health professionals are working to increase their understanding of genomics, many have limited knowledge of genomic concepts. To use genomics effectively in developing and implementing obesity interventions, public health professionals must increase their understanding of the role of genes in health and disease.

Further research is needed to identify effective individual and population approaches to weight management that incorporate genomic information, and large longitudinal studies are needed to examine gene–environment–lifestyle interactions on a population level (26,27). Such studies must include both sexes, all races and ethnic groups, and people of various ages. Well-executed studies of prenatal subjects and public health populations (e.g., women enrolled in WIC, the U.S. Department of Agriculture's supplemental food program for women, infants, and children) would contribute much to our understanding of genetic risk and its role in preventing or managing obesity. Although scientists hope that personalized health care based on genetic profiling will help people recognize their risk and improve their behavior, additional evidence is needed to support this possibility.