Volume 4: No. 2, April 2007
Addressing the Obesity Epidemic: A Genomics Perspective
Astrid Newell, MD, Amy Zlot, MPH, Kerry Silvey, MA, Kiley Ariail, MPH
Suggested citation for this article: Newell A, Zlot
A, Silvey K, Ariail K. Addressing the obesity epidemic: a genomics perspective.
Prev Chronic Dis [serial online] 2007 Apr [date cited]. Available
Genomics is the study of the entire human genome and involves not only studying the actions of single genes but also the interactions of multiple genes with each other and with the environment. This article emphasizes the multifactorial nature of
common obesity, which is caused by the interaction of genes, environment, and lifestyle. Individual variation in genes that influence behavior, satiety, and taste suggests that a one-size-fits-all approach to reducing or preventing obesity may be ineffective. Data are not yet available to allow for personalized obesity interventions based on genetic predisposition.
However, a genomics approach may provide a useful framework for addressing
the obesity epidemic. More research is needed
before specific targeted public health interventions that include genomic strategies can be effectively integrated into
addressing obesity in public health practice.
Back to top
Obesity is a multifactorial disorder that reflects complex interactions of genes, environment, and lifestyle. Considering the obesity epidemic from a genomics perspective, which takes into account the effect of all genes in the genome as well as the interactions of those genes with each other and
with the environment, has the potential to improve the effectiveness of
obesity prevention and intervention
Back to top
Evidence of Genetic Role in Weight Regulation
Numerous family studies indicate a genetic component to weight regulation. Stunkard
et al (1) show that body mass index (BMI) is highly correlated in identical
twins, even if each twin is raised in a different environment. Studies of eating
behavior in fraternal and identical twin pairs suggest that a significant
portion (45%–60%) of eating behaviors (e.g., binge eating) was due to genetic
Studies of children and their parents also point to a genetic role for obesity. Whitaker et
al (3) reported that, although not all obese children have obese parents, parental obesity is a significant predictor of children’s obesity. Parental obesity more than doubled the risk of obesity for children younger than 10 years. One prospective longitudinal study (4) found that the strongest
predictor of obesity was parental obesity, independent of diet or activity. Another study (5) found that, after controlling for environmental factors, children of obese parents had
a higher preference for fatty foods, a lower liking for vegetables, a greater tendency to overeat, and a stronger preference for sedentary activities than did children of normal-weight parents.
Back to top
How Much of Obesity is Genetic?
Separating genetic factors from other factors is difficult because genes are part of a dynamic system that is constantly in flux in response to environmental cues. Nonetheless, some researchers tried to pinpoint the proportion of obesity attributable to genetic factors as opposed to environmental factors (e.g., sidewalks,
community design) or lifestyle factors (e.g., diet, physical
Loos et al (6) reviewed genetic epidemiology studies and concluded that the heritability (proportion of a trait due to genetic factors but not necessarily single genes) of human adiposity is between 30% and 70%, with the highest heritability estimates coming from studies of twins. The risk of obesity (>90th BMI percentile) is
to three times higher for a person with a family
history of obesity than for a person without such history. This risk increases as severity of family obesity increases. Risk of extreme obesity (BMI > 45) is
to eight times higher for members of extremely obese families than for members of normal-weight families.
On the basis of their review, Loos et al suggest four levels of genetic contribution to obesity,
two of which are affected by whether one lives in an obesigenic environment
(i.e., an environment that promotes high caloric intake and low physical
activity). The four levels are 1) genetic obesity — genetic
mutation in a single gene leads to obesity despite environment (1%–5% of cases);
2) strong predisposition ― overweight in nonobesigenic environment and obese in obesigenic
environment; 3) slight predisposition ― normal weight in nonobesigenic environment and overweight in obesigenic environment; and 4) genetically resistant ― normal weight in obesigenic
Back to top
Specific Genes Associated with Obesity
Although a family history of obesity is a strong predictor of the condition, only 1%
to 5% of obesity cases can be explained by a single gene mutation (6). Common obesity (which affects most obese people) is a complex disorder with contributions from multiple genes and gene variants. However, the search for specific genes associated with obesity provides
a foundation for understanding the
effect of environmental and lifestyle factors on the development of obesity. Mounting evidence suggests that genetic factors are involved in all aspects of weight regulation, including food intake and energy expenditure. Hunger or appetite, eating behavior (e.g., binge eating), taste, satiety, spontaneous physical activity (e.g., fidgeting), metabolic rate, thermogenesis, and
motivation to exercise all appear to have genetic correlates. Most single-gene disorders identified to date are associated with mutations in genes that regulate appetite (7).
The list of genes with a possible role in weight regulation is large; more
than 400 genes or markers are associated with obesity (8). Some of the more commonly discussed genes and their
characteristics are listed in the Table.
Back to top
Some genetic research gives us a glimpse of the complex relationships between gene variants, genes and age, and genes and environment.
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).
Genes, obesity, and metabolic disorders
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).
Back to top
Genomics in the Prevention and Management of Obesity
Obesity prevention programs
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
Nutrigenomics for weight management
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.
Pharmacogenomics in the management of obesity
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).
Back to top
Obesity and Future Public Health Practices
Genomics has the potential to improve the ability of public health
professionals to address the obesity epidemic. However, additional work is
needed to improve our understanding of the role of genes in obesity and to learn
how to use that understanding to prevent or manage the condition. Below are
Surveillance and epidemiologic investigations
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
The advent of genetic technology introduced a new set of public policy
issues. Two such issues are genetic testing and population databases.
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?
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?
Ensuring access to health care
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.
Public health research
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.
Back to top
Although the list of research questions is endless, several come immediately to mind: Can a family history of obesity or genetic screening be used to identify high-risk families and target interventions to specific groups, particularly children? What are the most effective ways
of using family history to screen for obesity? What are the most effective intervention programs to prevent weight gain
and maintain healthy weight among children from obese families? Does knowing they are at increased risk for obesity (through family history or genetic testing) motivate people to change behavior?
Back to top
Obesity is almost always due to a combination of genetic predisposition, lifestyle, and environment. Individual variation in genes that influence
eating behavior, satiety, and taste are likely to affect the success of interventions,
which suggests that a one-size-fits-all approach may be ineffective in preventing or
treating obesity. In addition, because of variations in genetic predisposition, the intensity of interventions required to prevent or treat obesity is likely to vary among individuals. More research is needed to effectively incorporate genomics into public health interventions for obesity.
Back to top
This project was supported in part by a cooperative agreement from the
Centers for Disease Control and Prevention (CDC) (U58/CCU022779-04), Health Promotion Programs, Component 7, Genomics and Chronic Disease Prevention.
Back to top
Corresponding Author: Amy Zlot, Oregon Genetics
Program, Oregon Health Services, Oregon Department of Human Services,
800 NE Oregon St, Suite 825, Portland, OR 97232. Telephone:
971-673-0271. E-mail: email@example.com.
Authors' Affiliation: Astrid Newell, Amy Zlot, Kerry Silvey, Kiley Arail,
Oregon Genetics Program, Oregon Department of Human Services, Portland,
Back to top
- Stunkard AJ, Harris JR, Pedersen NL, McClearn GE.
The body-mass index of twins who have been reared apart. N Engl J Med 1990;322(21):1483-7.
- Tholin S, Rasmussen F, Tynelius P, Karlsson J.
Genetic and environmental
influences on eating behavior: the Swedish Young Male Twins Study. Am J Clin
- Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH.
Predicting obesity in young adulthood from childhood and parental obesity. N Engl J Med 1997;337(13):869-73.
- Maffeis C, Talamini G, Tato L.
Influence of diet, physical activity and parents’ obesity on children's adiposity: a four-year longitudinal study. Int J Obes Relat Metab Disord 1998;22(8):758-64.
- Wardle J, Guthrie C, Sanderson S, Birch L, Plomin R.
Food and activity preferences in children of lean and obese parents. Int J Obes Relat Metab Disord 2001;25(7):971-7.
- Loos RJ, Bouchard C.
Obesity: is it a genetic disorder? J Intern Med 2003;254(5):401-25.
- O’Rahilly S, Farooqi IS, Yeo GS, Challis BG.
Minireview: human obesity: lessons from monogenic disorders. Endocrinology 2003;144(9):3757-64.
- Snyder EE, Walts B, Perusse L, Chagnon YC, Weisnagel SJ, Rankinen T, et al.
The human obesity gene map: the 2003 update. Obes Res 2004;12(3):369-439.
- Human Genomics Laboratory. Obesity gene map database. Baton Rouge
(LA): Pennington Biomedical Research Center;2005. Available from: http://obesitygene.pbrc.edu/
* [cited 2006 Dec 5].
- Obesity and genetics: a public health perspective. Atlanta
(GA): Centers for Disease Control and Prevention; 2006. Available from:
- Ochoa MC, Marti A, Azcona C, Chueca M, Oyarzabal M, Pelach R, et al.
Gene-gene interaction between PPAR gamma 2 and ADR beta 3 increases obesity risk in children and adolescents. Int J Obes Relat Metab Disord 2004;28 Suppl 3:S37-41.
- Argyropoulos G, Rankinen T, Neufeld DR, Rice T, Province MA, Leon AS, et
A polymorphism in the human agouti-related protein is associated with late-onset obesity. J Clin Endocrinol Metab 2002;87(9):4198-202.
- Martinez JA, Corbalan MS, Sanchez-Villegas A, Forga L, Marti A, Martinez-Gonzalez MA.
Obesity risk is associated with carbohydrate intake in women carrying the Gln27Glu beta2-adrenoceptor polymorphism. J Nutr 2003;133(8):2549-54.
- Greenfield JR, Samaras K, Jenkins AB, Kelly PJ, Spector TD, Campbell LV.
Moderate alcohol consumption, dietary fat composition, and abdominal obesity in women: evidence for gene-environment interaction. J Clin Endocrinol Metab 2003;88(11):5381-6.
- Waterland RA, Garza C.
Potential mechanisms of metabolic imprinting that lead to chronic disease. Am J Clin Nutr 1999;69(2):179-97.
- Gillman MW.
Epidemiological challenges in studying the fetal origins of adult chronic disease. Int J Epidem 2002;31:294-9.
- Cassano PA, Rosner B, Vokonas PS, Weiss ST.
Obesity and body fat distribution in relation to the incidence of non-insulin-dependent diabetes mellitus: a prospective cohort study of men in the normative aging study. Am J Epidemiol 1992;136(12):1474-86.
- Olson JE, Atwood LD, Grabrick DM, Vachon CM, Sellers TA.
Evidence for a major gene influence on abdominal fat distribution: the Minnesota Breast Cancer Family Study. Genet Epidemiol 2001;20(4):458-78.
- Katz DL, O'Connell M, Yeh MC, Nawaz H, Njike V, Anderson LM, et al.
Public health strategies for preventing and controlling overweight and obesity in school and worksite settings: a report on recommendations of the Task Force on Community Preventive Services. MMWR Recomm Rep 2005;54(RR-10):1-12.
- Kaput J, Rodriguez RL.
Nutritional genomics: the next frontier in the postgenomic era. Physiol Genomics 2004;16(2):166-77.
- Arab L.
Individualized nutritional recommendations: do we have the measurements needed to assess risk and make dietary recommendations. Proc
Nutr Soc 2004;63(1);167-72.
- Chadwick R.
Nutrigenomics, individualism and public health. Proc Nutr Soc 2004;63(1):61-164.
- Ravussin E, Bouchard C.
Human genomics and obesity: finding appropriate drug targets. Eur J Pharmacol 2000;410(2-3):131-45.
- Aitman TJ.
Genetic medicine and obesity. N Engl J Med 2003;348(21):2138-9.
- Lowe MR.
Self-regulation of energy intake in the prevention and treatment of obesity: is it feasible? Obes Res 2003;11 Suppl:S44-59.
- Khoury MJ.
The case for a global human genome epidemiology initiative. Nat Genet 2004;36(10):1027-8.
- Ghosh S, Collins FS.
The geneticist's approach to complex disease. Annu Rev Med 1996;47:333-53.
Back to top