Knowledge of sex differences is essential to complement data from epidemiology in order to understand the biological factors that might be contributing to differences in risk factors, such as obesity. Nutrigenomics "examines the response of individuals to food compounds using post-genomics and related technology" (genomics, transcriptomics, proteomics, metabolomics, etc.). It can be thought of as "the study of how nutrients in food interact with our genes at the molecular and cellular levels, and the impact these reactions have on our health" (Bouwman et al., 2009). Gender-related food intake is a critical part of an individual’s environment and life history. Environment, milieu, and diet are translated into biological variability through the study of epigenetics, analyzing how environmental exposure influences, among other things, metabolism (Niewöhner, 2011). The expectation is that information about an individual's genetic make-up can be combined with knowledge about the biological impacts of environmental context to better assess "personal physical vulnerability to diet-related diseases" (Bouwman et al., 2009).
a. Sex-Specific Metabolism
Serum metabolite concentrations allow a direct readout of biological processes: and association of specific metabolomic signatures with complex diseases (such as Alzheimer’s disease), and cardiovascular and metabolic disorders has been shown. Most studies, however, have not considered the role of sexual dimorphism. Mittelstrass et al. (2011) investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. Investigators used more than 3,300 independent individuals from KORA F3 and F4 cohorts with measurement of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression revealed significant concentration differences between men and women for 102 out of 131 metabolites. Sex-Specific Genome Wide Association Studies (GWAS) showed significant differences in beta-estimates for SNPs in the CPS1 locus for glycine. This study indicates that basic metabolite profiles of men and women are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Another study analyzing micro-array data of gene expression pointed to sexually dimorphic gene expression in somatic tissue, such as kidney or brain (Isensee et al., 2007). Both studies provide new, important insights into sex-specific differences of cell regulatory processes and underscore that studies should consider sex-specific effects in design and interpretation.
b. Sex-Specific Dietary Responses
Strong mechanistic evidence in support of sex differences in response to dietary intervention comes from animal models using omic-based technologies (i.e., transcriptomics, proteomics). Studies using a rat model found sex-specific plasma protein responses to high-fat diets (Liu et al., 2012; Mukherjee et al., 2012). Another study using animal models found that a greater number of genes encoding myofibrillar proteins and glycolytic proteins were more strongly expressed in males than females when subjects were exposed to a high-fat diet (HFD), reflecting greater muscular activity and higher capacity for using glucose as an energy fuel. But a series of genes involved in oxidative metabolism and cellular defenses were more up-regulated in females than males (Oh et al., 2012). These results suggest that compared to males, females have greater fat clearing capacity in skeletal muscle through the activation of genes encoding enzymes for fat oxidation. Further clinical trials, using sex analysis, are needed to confirm these differences in women and men, but the initial findings suggest that analyzing sex could provide new insights.
c. Sex-Specific Nutrient Responses
Nutritionists using sex analysis have begun to explore—at the functional, mechanistic level—how nutrients affect gene expression and cell function in women and men. For instance, a recent study examined the interplay between inflammation-related genes and vitamin E. Data from a study in 500 elderly nursing home residents were used to examine vitamin E-gene interactions affecting the incidence of respiratory tract infections (RIs). The main finding suggested that the effect of vitamin E on reducing RIs depended on sex. Further research evaluating the effect of vitamin E on RIs should consider both genetic factors and sex, because both were found to have a significant (and interactive) bearing on the efficacy of vitamin E (Belisle et al., 2010).
Belisle, S.E., Hamer, D.H., Leka, L.S., Dallal, G.E., Delgado-Lista, J., Fine, B.C., Jacques, P.F., Ordovas, J.M., & Meydani, S.N. (2010). L-2 and IL-10 Gene Polymorphisms are Associated with Respiratory Tract Infection and may Modulate the Effect of Vitamin E on Lower Respiratory Tract Infections in Elderly Nursing Home Residents. American Journal of Clinical Nutrition, 92(1), 106-14.
Bouwman, L.I. & Molder, H. (2009). About Evidence and Beyond: A Discourse-Analytic Study of Stakeholders’ Talk on Involvement in the Early Development of Personalized Nutrition. Health Education Research, 24 ( 2), 253-269.
Brands, A. & Yach, D. (2002). NMH Reader Issue no. 1: Women and the Rapid Rise of Non-Communicable Diseases. World Health Organization.
Choi, J.W., Liu, H., Choi, D.K., Oh, T.S., Mukherjee, R., & Yun, J.W.. (2012). Profiling of Gender-specific Rat Plasma Proteins Associated with Susceptibility or Resistance to Diet-induced Obesity. Journal of Proteomics 75 (4), 1386–1400.
Darnton-Hill, I, Nishida, C., & James, W.P. (2004). A Life Course Approach to Diet, Nutrition and the Prevention of Chronic Diseases. Public Health Nutrition, 7 (1a), 101–121.
Isensee, J. & Ruiz Noppinger, P. (2007). Sexually Dimorphic Gene Expression in Mammalian Somatic Tissue. Gender Medicine 4, (Suppl B), S75-S95.
Krauss, R., Eckel, M., Howard, B., Appel, L., Daniels, S., Deckelbaum, R., & Erdman Jr., J. (2000). AHA Dietary Guidelines: Revision 2000: A Statement for Healthcare Professionals from the Nutrition Committee of the American Heart Association. Stroke: A Journal of Cerebral Circulation 31 (11), 2751–2766.
Liu, H., Choi, J.W., & Yun, J.W. (2012). Gender Differences in Rat Plasma Proteome in Response to High-fat Diet. Proteomics 12 (2), 269–283.
Mittelstrass, K., Ried, J., Yu, Z., Krumsiek, J., Gieger, C., Prehn, C., & Roemisch-Margl, W. (2011). Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarker. PLoS Genetics ,7 (8), e1002215.
Mukherjee, R., Choi, J.W., Choi, D.K., Oh, T.S., Liu, H., & Yun, J.W. (2012). Gender-Dependent Protein Expression in White Adipose Tissues of Lean and Obese Rats Fed a High Fat Diet. Cellular Physiology and Biochemistry, 29 (3-4), 617–634.
Niewöhner, Jörg. (2011). Epigenetics: Embedded Bodies and the Molecularisation of Biography and Milieu. BioSocieties 6 (3) (June 13): 279–298.
Oh, Tae Seok, & Jong Won Yun. (2012). DNA Microarray Analysis Reveals Differential Gene Expression in the Soleus Muscle Between Male and Female Rats Exposed to a High Fat Diet. Molecular Biology Reports, 39 (6) (June): 6569–6580.
Popkin B., & Gordon-Larsen, P. (2004). The Nutrition Transition: Worldwide Obesity Dynamics and their Determinants. International Journal of Obesity and Related Metabolic Disorders, 28 (3), S2-9.
World Health Organization (WHO). (2009). Interventions on Diet and Physical Activity: What Works.
World Health Organization (WHO). (2011). Noncommunicable Diseases: Country Profiles.
WHO/FAO Expert Consultation. (2003). Diet, Nutrition and the Prevention of Chronic Diseases. WHO Technical Report Series 916.