Implementing food-based dietary guidelines for - United Nations ...

More documents

Recommendations

Info

S110 should be anticipated in populations or population subgroups when nutrients are administered at pharmacological levels, as illustrated by the introduction of high fructose into the food supply. Other genomic consequences may also result, including permanent alterations in genome-wide methylation patterns, as observed in mouse embryos whose mothers received elevated doses of folic acid and one-carbon donors during gestation [24]. Methylation patterns that are established in utero can be metastable and influence gene expression and potentially mutation rates into adulthood [24]. The effect of diet on DNA methylation and genome programming in adult stem cells is unknown. Although antioxidants can decrease mutation rates, they also function as prooxidants in vivo [98] and may be cancer-promoting at elevated intakes by inhibiting cellular death programs in transformed cells [99]. In conclusion, elucidation of robust gene-bynutrient interactions will inform dietary approaches for individuals and for population-based interventions that prevent and/or manage rare inborn errors of metabolism as well as complex metabolic disease. Furthermore, these and other examples indicate that rigorous hazard identification is essential prior to the establishment of policies that result in pharmacological intakes of nutrients and other food components. Genomic criteria for setting requirements and toxicities Genomic technologies may provide new criteria for establishing numeric standards for adequate levels of nutrient intake by targeting the molecular antecedents of disease. Mutation increases the risks of developmental anomalies, degenerative diseases, and cancers and can be quantified in controlled experimental settings, indicating that the effects of key minerals and vitamins on DNA mutation rates should be considered when establishing RDAs (recommended dietary allowances) [30]. Marginal deficiencies in folate, vitamin B 12 , niacin, and zinc can influence genome stability, and antioxidants, including carotenoids, vitamin C, and vitamin E, may prevent damage resulting from oxidative stress. Validation of these protective effects on DNA mutation rates in controlled human trials may indicate benefits and lead to increased recommended intake levels, perhaps at levels not normally achievable from a natural food-based diet. Similarly, the use of functional genomic approaches, including expression profiling and proteomics to quantify gene expression and metabolomics to quantify metabolic pathway flux, provides a comprehensive set of quantitative and physiologically relevant “biomarkers” to model and assess nutrient efficacy in the context of optimal network function [100]. Other genomic outcomes are emerging as criteria for hazard identification and may influence the establishment of tolerable upper levels of nutrient intake during P. J. Stover pregnancy. Studies of animal models are revealing that nutrients can rescue deleterious genetic mutations, leading to the concept that “good diet hides genetic mutations” [101]. Individual nutrients can rescue severe genetic lesions in mice when administered in supraphysiologic levels during critical developmental windows. Maternal retinoic acid administration between 7.5 and 9.5 days postconception rescued deafness and inner ear development in Hoxa1 -/- mice [102], and folic acid can rescue skeletal defects associated with deletion of a Hox gene, as well as neural tube defects in mice that have no evidence of disrupted folate metabolism [101]. This rescue phenomenon is not established in humans, but animal studies indicate that nutrients can modify the viability of genomes, including genomes that confer atypical nutrient requirements on the surviving fetus [103]. There is increasing evidence that maternal nutrition can induce epigenetic changes in the fetal genome that may program increased risks of metabolic disease and nutrient requirements throughout the lifespan of the offspring. The effects of fetal glucocorticoid exposure on adult chronic disease risk provide some of the strongest evidence for the fetal origins of disease hypothesis [104–107]. Fetal glucocorticoid levels are maintained at low concentrations relative to maternal concentrations primarily through the action of placental 11β-hydroxysteroid dehydrogenase type 2 (11β-HSD2), which catalyzes the oxidative inactivation of cortisol and corticosterone [108]. Elevated fetal glucocorticoid exposures during late gestation, which can result from 11β-HSD2 inhibitors, rare mutations in the human 11β-HSD2 gene, or large existing variation in placental 11β-HSD2 activity among humans, can have lifelong consequences for the fetus, including low birthweight, elevated plasma glucocorticoid, hypertension, hyperglycemia, insulin resistance, hyperinsulinemia, and anxiety [107]. Low maternal dietary protein intake during gestation causes a specific loss of placental 11β- HSD2 expression and similar outcomes resulting from elevated fetal glucocorticoid exposure [109]. Similarly, obstetric glucocorticoid therapy to accelerate lung development prior to anticipated preterm deliveries also increases the risk of reduced fetal birthweight and long-term susceptibility to hypertension, hyperglycemia, cardiovascular disease, and increased hypothalamic-pituitary-adrenal axis activity. These disorders persist not only into adulthood, but also into the next generation [110]. Lifelong consequences associated with fetal glucocorticoid exposure may result from premature glucocorticoid receptor-mediated chromatin remodeling in the hippocampus [107]. Prenatal glucocorticoid exposure decreases fetal glucocorticoid receptor expression which remains reduced through adulthood. Maternal undernutrition can elicit the same effect, presumably by decreasing placental 11β-HSD2 levels. Maternal GC exposure also affects glucose and
Human nutrition and genetic variation insulin homeostasis [111] by programming hepatic PEPCK levels through changes in PEPCK gene methylation with effects that persist into adulthood [112, 113]. The modification of glucocorticoid-mediated fetal programming by maternal folate status has not been investigated, nor have the effects of fetal programming on adult nutritional requirements. Conclusions: effects of human genetic variation on NIVs Human genetic variation is a determinant of nutrient efficacy and of tolerances and intolerances and has the potential to influence nutrient intake values (NIVs). Historically, the nature and abundance of the food supply has been one of several environmental selective pressures that governed the evolution of humans by facilitating the expansion of polymorphisms within human populations. Genetic variants that enable survival in challenging nutrient environments become enriched in populations through the process of natural selection. This process has been shown to create variation in the utilization of lactose, iron, and alcohol and the associated food intolerances. Genetic determinants of nutrient tolerances display genomic signatures of positive selection, indicating that these variants offered survival advantage in specific geographic regions. Recent history has also revealed that rapid and severe alterations in the food supply can unmask previously silent genetic variation and create new or more prevalent food intolerances, as occurred with the infusion of large quantities of fructose in the food supply [82, 114, 115]. To date, no gene variant has been demonstrated to affect nutritional requirements sufficiently to warrant genotype-specific recommendations, although the affect of the MTHFR A222V variants on folate require- References 1. Bailey LB. Folate, methyl-related nutrients, alcohol, and the MTHFR 677→T polymorphism affect cancer risk: Intake recommendations. J Nutr 2003;133(11 suppl 1):3748S–53S. 2. Bailey LB, Gregory JF 3rd. Polymorphisms of methylenetetrahydrofolate reductase and other enzymes: Metabolic significance, risks and impact on folate requirement. J Nutr 1999;129:919–22. 3. Tishkoff SA, Williams SM. Genetic analysis of African populations: Human evolution and complex disease. Nat Rev Genet 2002;3:611–21. 4. McCarthy JJ, Hilfiker R. The use of single-nucleotide polymorphism maps in pharmacogenomics. Nat Biotechnol 2000;18:505–8. 5. Weinshilboum R. Inheritance and drug response. N Engl J Med 2003;348:529–37. 6. Clark AG, Glanowski S, Nielsen R, Thomas PD, Kejari- S111 ments has been considered. However, because many human populations have existed for many generations in unique, isolated, and challenging nutrient environments, relatively rare gene variants that influence NIVs may be highly prevalent in historically isolated, stable human populations. All human genetic variation is expected to be identified in the near future. Linking specific gene variants to known nutrient sensitivity in ethnic or geographic human populations, such as salt sensitivity in African Americans, may enable population-specific recommendations for genetic subgroups [116]. Because polymorphisms can confer both health benefits and risks, depending on the outcome of interest, and these outcomes may respond differentially to nutrient intake levels, it may important to consider the effects of genetic-specific recommendations on all known health outcomes. The impact of a gene variant on nutritional requirements will be dependent on its prevalence and penetrance. Penetrance, which is the probability that a gene variant will express a phenotype from a given genotype at a given time, usually varies inversely with prevalence. Recent experiences indicate that few gene variants are anticipated to be sufficiently penetrant to affect variation of an average requirement (AR) to a greater degree than environmental factors. Once highly penetrant gene variants are identified, the prevalence of the variant in that country or region will determine the feasibility and necessity of deriving more than one AR or upper limit (UL) for genetic subgroups. For example, it is unlikely that gene–gene interactions will be a major consideration in the determination of NIVs because of the very low prevalence associated with highly penetrant gene–gene interactions. Likewise, because chronic diseases are polygenic complex traits, a single SNP is unlikely to have an impact on NIVs that target long-term chronic disease prevention. wal A, Todd MA, Tanenbaum DM, Civello D, Lu F, Murphy B, Ferriera S, Wang G, Zheng X, White TJ, Sninsky JJ, Adams MD, Cargill M. Inferring nonneutral evolution from human-chimp-mouse orthologous gene trios. Science 2003;302:1960–3. 7. Vijg J, Suh Y. Genetics of longevity and aging. Annu Rev Med 2005;56:193–212. 8. Kornman KS, Martha PM, Duff GW. Genetic variations and inflammation: A practical nutrigenomics opportunity. Nutrition 2004;20:44–9. 9. Schneeman BO, Mendelson R. Dietary guidelines: Past experience and new approaches. J Am Diet Assoc 2002;102:1498–500. 10. Schneeman BO. Evolution of dietary guidelines. J Am Diet Assoc 2003;103(12 suppl 2):S5–9. 11. Enattah NS, Sahi T, Savilahti E, Terwilliger JD, Peltonen L, Jarvela I. Identification of a variant associated with
Page 1 and 2:
Contents International harmonizatio
Page 3 and 4:
Executive summary Harmonization of
Page 5 and 6:
Executive summary [11]. These are l
Page 7 and 8:
Executive summary and converted to
Page 9 and 10:
Executive summary very rapidly and
Page 11 and 12:
Executive summary References Concep
Page 13 and 14:
Introduction Janet C. King and Cutb
Page 15 and 16:
Introduction References 1. King JC,
Page 17 and 18:
Terminology and framework for nutri
Page 19 and 20:
Page 21 and 22:
Page 23 and 24:
Page 25 and 26:
Page 27 and 28:
Nutrient risk assessment: Setting u
Page 29 and 30:
Setting upper levels for nutrient r
Page 31 and 32:
Page 33 and 34:
Page 35 and 36:
Page 37 and 38:
Page 39 and 40:
Establishing nutrient intake values
Page 41 and 42:
Page 43 and 44:
Page 45 and 46:
Page 47 and 48:
Page 49 and 50:
Page 51 and 52:
Methods for using nutrient intake v
Page 53 and 54:
Using nutrient intake values to ass
Page 55 and 56:
Page 57 and 58:
Page 59 and 60: Using nutrient intake values to ass
Page 61 and 62: Determining life-stage groups and e
Page 63 and 64: Life-stage groups and nutrient inta
Page 77 and 78: The role of diet- and host-related
Page 79 and 80: Diet- and host-related factors in n
Page 101 and 102: Human nutrition and genetic variati
Page 109: Human nutrition and genetic variati
Page 117 and 118: Application of nutrient intake valu
Page 123 and 124: Trade, development, and regulatory
Page 141 and 142: Beyond recommendations: Implementin
Page 143 and 144: Dietary guidelines and nutrient int
Page 153: International Dietary Harmonization
show all

Implementing food-based dietary guidelines for - United Nations ...

Create successful ePaper yourself

Delete template?

Save as template?