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

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ethanol to acetaldehyde; acetaldehyde is subsequently
oxidized to acetic acid by the enzyme aldehyde dehydrogenase
encoded by ALDH2. Seven ADH genes
have been identified and cluster on chromosome 4;
all encoded proteins display distinct catalytic properties
and tissue-specific expression patterns. Two
of the genes encoding class I enzymes (ADH1B and
ADH1C) are expressed in liver, function in systemic
ethanol clearance, and display functional polymorphism.
A variant ADH1B* 47His allele predominates
in Japanese and Chinese populations but is rare in
European and northern African populations [59].
The variant allele encodes an enzyme with elevated
enzyme activity leading to more rapid formation of
acetaldehyde. The ADH1C*349Ile variant is found in
Europeans, whereas the ADH1B*369Arg variant is
mostly restricted to individuals of African descent.
ALDH2 is also highly polymorphic; members of Asian
populations carry a common dominant null allelic
variant (E487K) and when consuming alcohol develop
a characteristic “flush” reaction resulting from acetaldehyde
accumulation [60]. ADH and ALDH alleles
that predominate in east Asian populations display
signatures of positive selection, and the expression of
these variant alleles results in elevated acetaldehyde
concentrations following alcohol consumption, which
may have conferred advantage by protecting against
parasite infection [61].
Energy metabolism
The “thrifty gene” hypothesis was first proposed over 40
years ago to account for the epidemic of type 2 diabetes
observed in non-Western cultures that adopt Westernstyle
diets and lifestyles [62, 63]. The hypothesis states
that exposure to frequent famine selected for gene
variants that enabled the more efficient conversion of
food into energy and fat deposition during periods of
unpredictable and sometimes scant food supplies. The
putative adaptations also may have resulted in more
efficient adaptations to fasting conditions (e.g., more
rapid decreases in basal metabolism) and/or physiological
responses that facilitate excessive intakes in
times of plenty. Conclusive genomic data have not yet
supported this hypothesis [63, 64].
Oxidative metabolism
Variations that impact human nutrition and metabolism
may have arisen independently of direct nutritional
challenges. The enzyme glucose-6-phosphate
dehydrogenase is solely responsible for the generation
of reduced nicotinamide adenine dinucleotide phosphate
(NADPH) in red blood cells and therefore is
required to prevent oxidative damage. Variants with
low activity resulting from amino acid substitutions,
including the G6PD-202A allele, are enriched in sub-
Saharan African populations and arose 2,500 to 6,500
years ago [65]. Presumably, this allelic variant became
P. J. Stover
enriched in populations as a result of balancing selection
because it conferred resistance to malarial disease
in heterozygous females and hemizygous males
[66, 67].
These examples illustrate the role of environmental
exposures, including pathogens and dietary components,
as selective forces that facilitated the fixation
of alleles that alter the utilization and metabolism of
dietary components. Adaptive alleles may become
recessive disease alleles, or disease alleles even in
heterozygote individuals, when the environmental
conditions change profoundly, such as those brought
about by the advent of civilization and agriculture,
including alterations in the nature and abundance of
the food supply [6, 37, 41, 43, 68–72]. Adaptive alleles
may be responsible for the generation of metabolic
disease alleles both within and across ethnically diverse
human populations and therefore are strong, nonbiased
candidate genes for disease association studies; the
interacting and modifying environmental factors can
be inferred from the nutrients and/or metabolites that
are known to interact with the gene product [12].
Functional consequences of human genetic
variation
Polymorphisms that affect nutrient utilization or
metabolism probably arose from historical adaptation
and can be identified now by “blinded” computational
approaches. However, prior to the advent of whole
genome approaches, most functional polymorphisms
were identified as highly penetrant disease alleles
from epidemiologic or clinical studies. Candidate
genes were selected for analyses of variation based on
knowledge of metabolic pathways and predictions that
their impairment could result in metabolic phenotypes
that either mirror a particular disease state or affect
the concentration of a biomarker associated with the
disease. Genetically modifiable organisms, including
yeast, Drosophila, Caenorhabditis elegans, and mice, are
also excellent resources to identify candidate genes and
serve as models to confirm gene function. Candidate
gene approaches have been successful in identifying
many disease susceptibility alleles (table 2) [73, 74],
but they are limited by incomplete knowledge of gene
function, incomplete knowledge of transcriptional and
metabolic networks that suggest candidate genes for
analyses, and inconsistent findings among epidemiologic
studies, especially for low-penetrant alleles. Once
candidate genes are identified, establishing alleles as
disease-causing is equally challenging. Because many
SNPs are in linkage disequilibrium, it is not always possible
to determine with certainty whether an individual
SNP or allele is functional. Furthermore, SNP penetrance
cannot always be inferred from in vitro studies
of proteins or studies of model organisms. Metabolic