The Role of Nutrition in Cognitive Development
Anita J. Fuglestad
Raghavendra Rao, M.D.
Michael K. Georgieff, M.D.
Institute of Child Development and
Division of Neonatology, Department of Pediatrics
Center for Neurobehavioral Development
University of Minnesota
Correspondence:
Michael K. Georgieff, M.D.
Professor of Pediatrics and Child Development
Mayo Mail Code 39
420 Delaware Street, SE
Minneapolis, MN 55455
Phone: 612-626-0644
Fax: 612-624-8176
Email: mailto:[email protected]
Short title: Nutrition and Cognitive Development
Key words: nutrition, cognitive development, brain, neurodevelopment, infant
ABSTRACT
Nutrients are critical for optimal brain development and function. Although
maintenance of adequate intake of all nutrients throughout life is important for brain
health and function, certain nutrients have a more profound effect on brain development
than others. The timing of nutrient supplementation or deprivation also has an important
effect on brain development and function. Nutrient intakes may vary widely; yet, for
certain nutrients, there must be a steady flow across the blood-brain barrier to maintain
brain development and functional homeostasis. A host of transporters and regulators
ensure that the brain receives neither too much nor too little of each nutrient.
This chapter reviews the evidence for the role of nutrition in brain development,
concentrating specifically on nutrients that are important in the development of cognitive
function. A short review of nutrient categories is followed by a section on how individual
nutrients directly and indirectly affect developing brain structure and function. A detailed
analysis of the nutrients that most profoundly affect brain development ensues, with
emphasis on the importance of the timing of nutrient deprivation or supplementation.
Nutrient categories
MACRONUTRIENTS: Protein, fat, and carbohydrates are considered the three
macronutrients. Protein is typically used by the body for somatic (tissue) protein and
serum protein synthesis. Proteins also include all enzymes found within organs. Energy in
the form of fat or carbohydrates is the metabolic fuel on which the body depends. The
body preferentially uses carbohydrates (typically glucose) as the substrate for cellular
metabolism to generate adenosine triphosphate (ATP). Neuronal metabolism is
particularly dependent on glucose availability and is very sensitive to periods of
carbohydrate deprivation (Volpe, 1995). The body maintains a small storage pool of
carbohydrates in the form of glycogen that supplies glucose equivalents for a short period
of time when glucose supply is limited. Hypoglycemia (low blood sugar concentration)
has a particularly profound negative effect on the developing hippocampus (Kim, Yu,
Fredholm, and Rivkees, 2005; Yamada et al., 2004). Fat, with its higher caloric value,
provides energy for storage (as adipose tissue), but can also be utilized more slowly than
glucose to provide energy to the entire body, including the brain (e.g., as ketone bodies).
Certain fats and lipoproteins are important for normal neuronal cell membrane integrity
and myelination. For example, cholesterol, phosphatidyl choline, and certain fatty acids
are essential for cell membrane synthesis and integrity. Linolenic acid, linoleic acid,
arachidonic acid, and docosohexaenoic acid are essential for normal brain membrane
formation and myelination. During starvation or periods of illness, protein can also be
used as an energy substrate. When protein is utilized in such a manner, it is not available
for structural tissue (including brain) synthesis.
There is an extensive literature in both humans and animal models on the isolated
and combined adverse effects of protein and energy malnutrition on the developing brain
(Pollitt, 1996; Pollitt and Gorman, 1994; Pollitt, Watkins, and Husaini, 1997; Pollitt et al.,
1993, 1995; Winick and Nobel, 1966; Winick and Rosso, 1969a,b). Pollitt and Gorman
(1994) have pointed out that other nutrient deficiencies usually coexist with proteinenergy malnutrition (PEM) in free-living populations.
MICRONUTRIENTS: Minerals, trace elements and vitamins are collectively grouped as
micronutrients.
MINERALS The major minerals of the body are sodium, potassium (with their usual
accompanying dietary anion, chloride), calcium, and phosphorus. Minerals are not
classically considered essential for brain development, but deficiencies in these nutrients
will lead to abnormal brain function, mostly through altering neuronal electrical function.
TRACE ELEMENTS This class of nutrients contains elements that are required in trace
quantities by the body and are used, for the most part, in intermediary cellular
metabolism. Members of this category include magnesium, manganese, iodine, zinc,
copper, molybdenum, cobalt, selenium, fluoride, and iron. As with the major minerals,
these elements are not classically considered to be uniquely important for normal brain
development except as their deficiencies affect cellular (including neuronal) function.
Some elements in this group, however, are exceptional in their particularly profound
effect on cognitive development: iron, iodine, and zinc. Iron is required for enzymes that
regulate central nervous system cell division (ribonucleotide reductase), monoamine
synthesis (e.g., tyrosine hydroxylase), myelination (delta-9 desaturase), and oxidative
metabolism (cytochromes). The effects of iron deficiency on the growing and mature
brain are well documented. Iodine is essential for normal thyroid hormone synthesis.
Brain development is severely compromised by hypothyroidism (cretinism) with
particularly profound cognitive effects (Hetzel and Mano, 1989; Kretchmer, Beard, and
Carlson, 1996). Similarly, zinc through its role in nucleic acid synthesis plays significant
role in neurodevelopment. Both neuroanatomic and neurochemical changes have been
described in zinc deficiency. Other than the extensive literature on these trace elements,
little developmental work has been performed to assess the roles of the remaining
micronutrients on cognitive development.
VITAMINS Vitamins are categorized as water- and fat-soluble. They generally are
cofactors in intermediary metabolism, although some, like vitamin A, bind promoter
regions of genes which regulate cell differentiation and neuronal growth (Mangelsdorf,
1994). As with the trace elements, vitamin deficiencies can potentially affect total body
metabolism and consequently brain growth and development. Nevertheless, certain
vitamins [e.g., vitamin A, folic acid, pyridoxine (B6)] appear to be more critical during
certain periods of CNS development and their deficiencies present a greater risk to
neurodevelopment (for review, see Pollitt, 1996). Folic acid deficiency during early
pregnancy has been closely linked, both epidemiologically and in animal models, to
neural tube defects such as meningomyelocele and encephalocele (Copp and Bernfield,
1994). Vitamin A deficiency is an important neuroteratogenic risk factor during the
periconceptional period, but is also associated with retinal and neuronal degeneration in
the postnatal period. Pyridoxine is critical for NMDA receptor synthesis and function
(Guilarte, 1993).
The role of nutrition within the context of cognitive development
It is critical to appreciate that insufficient nutrition does not determine poor cognitive
outcome. Likewise, adequate nutrient delivery alone does not ensure normal brain growth
and development. Although adequate nutrition is essential for normal development, the
role of nutrition in cognitive development must be considered with regard to other
biological and environmental factors (Figure 1). The effect of poor nutrition on
development may be influenced by environmental factors. For instance, cognitive effects
of nutritional deficiencies (as measured by the mental development index of Bayley
Scales) are more severe for children living in homes where there is less stimulation
compared to homes with higher levels of stimulation (Grantham-McGregor, Lira,
Ashworth, Morris, and Assuncao, 1998).
Just like nutrient deficiency does not determine cognitive development, simply
providing adequate nutrition may not support normal brain growth and development.
Along with adequate nutrition, inborn errors of metabolism, growth factors, and stress
need to be considered. An example of an inborn error of metabolism is phenylketonuria
(PKU). Individuals with PKU lack the enzyme phenylalanine hydroxylase which
converts phenylalanine to tyrosine, and therefore, phenylalanine accumulates. If not
treated by limiting phenylalanine in the diet, brain development is altered, and individuals
develop mental retardation.
GROWTH FACTORS It is important to recognize that nutritional status is not
determined simply by nutrient availability. Once nutrients are ingested, they must be
absorbed and translated into useful metabolic products that promote growth and
development. This occurs through growth factors and anabolic hormones that translate
potential nutritional value into tissue synthesis and function. Nutrients for the body are
analogous to fuel for a car. Growth factors act as the transmission that “puts the car into
drive” and makes it progress forward.
Growth factors (and therefore nutrient handling) are profoundly affected by the
organism’s physiologic state. For example, starvation has a different effect than illness on
somatic and cerebral metabolism even though both are characterized by low nutrient
intakes. Typically, during starvation the body lowers its metabolic set point, thereby
requiring fewer calories for maintenance of vital functions. Although insulin levels are
low, counter-regulatory hormone concentrations that promote tissue breakdown (cortisol
and glucagon) are not typically elevated. Provision of protein and energy at a level
slightly higher than that needed for maintenance will result in some, albeit suboptimal,
growth. In the young child, the fascinating phenomenon of “head-sparing” occurs, where
somatic growth will suffer at the expense of brain growth during periods of marginal
malnutrition. The mechanism of this regional growth effect is unknown. In contrast,
illness activates cortisol and glucagon secretion to provide a ready source of glucose, and
the body is relatively insulin resistant. Thus, brain growth is severely impaired during
illness whereas it is spared during simple starvation.
The brain is dependent on a host of growth factors for normal neurogenesis,
synaptogenesis, dendritic arborization, and myelination. A complete review of these
factors and their functions is beyond the scope of this chapter (for review, see Pleasure
and Pleasure, 2003). By “growth factors” in this context, we mean small proteins that
enhance proliferation of target cells either by encouraging cell division or preventing cell
death. The brain contains growth factors that are found throughout the body, including
insulin-like growth factor-I (IGF-I), epidermal growth factor (EGF), and fibroblast
growth factor (FGF), as well as some that are specific to brain [e.g., brain-derived
neurotrophic factor (BDNF) or glial growth factor (GGF)].
The expression and function of these growth factors are influenced by nutritional
status. Malnutrition during fetal life (i.e., intrauterine growth restriction) down-regulates
IGF-I and IGF-I binding protein expression (Nishijima, 1986). IGF-I has a mitogenic and
posttranscriptional effect on oligodendrocytes, stimulates neurite outgrowth, and
promotes neuronal differentiation (Fellows, 1987). Reduction in IGF-I levels can thus
influence myelin production (McMorris and Dubois-Dalcq, 1988; Saneto et al., 1988), as
well as neuronal number and complexity. The reduction in IGF-I concentrations noted in
growth- restricted fetuses may account for the high rate of microcephaly seen in this
population.
A study of transgenic mice underscores the importance of the interaction between
IGF-I and malnutrition as they influence brain growth (Lee et al., 1999). Whole brain and
regional brain growth were assessed in well-nourished and malnourished suckling
transgenic mice that overexpress IGF-I. Transgenic overexpression of IGF-I in wellnourished mice increased whole brain weight by 20% over well-nourished controls,
predominantly due to increased myelination, a modest increase in DNA content, and
increased neuronal survival due to decreased apoptosis. Whereas generalized malnutrition
reduced brain weight by 10% in control mice, the IGF-I overexpressing mice had brain
weights comparable to well-nourished controls, implying sparing of undernutrition
effects by the IGF-I. More importantly, the malnutrition in the control group and the
ameliorating effect of IGF-I in the transgenic group were regional. The hippocampus and
cerebellum were more affected by malnutrition than the cortex, diencephalon, or
brainstem. The brain-sparing effects of IGF-I overexpression were more prominent in the
undernourished hippocampus, cortex, and diencephalon, but were not seen in the
cerebellum. This regionalization of brain effects from malnutrition may be related to the
metabolic demand of the areas at this time of development as well as variations in the
expression of IGF-I. A similar effect in terms of iron accretion has been described in
young rats (Erikson et al., 1997; deUngria et al., 2000).
STRESS AND INFLAMMATION Stress, specifically activation of the hypothalamicpituitary-adrenal (HPA) axis or administration of glucocorticoids (GCs), may alter brain
growth, targeting cognitive structures such as the hippocampus, despite adequate
nutrition. For instance, neonatal exposure to dexamethasone, a pharmaceutical synthetic
GC, has been reported to have short-term alterations on hippocampal synaptic plasticity
and memory performance in rats (Lin, Huang, and Hsu, 2006), and basal levels of the GC
cortisol is inversely related to memory performance in infancy (Gunnar and Nelson,
1994).
GCs are catabolic hormones that conteract anabolic hormones such as growth
hormones and insulin. GCs both act as insulin antagonists in carbohydrate and lipid
metabolism and act to increase the activity of counter-regulatory hormones of insulin
(e.g., glucagon) and therefore, may affect the hippocampus by inhibiting glucose
metabolism (Byrne, 2001; de Leon et al., 1997; Endo, Nishimura, Kobayashi, and
Kimura, 1997; Heffelfinger and Newcomer, 2001). GCs may also affect brain
development by inhibiting glucose transport into neurons (Horner, Packan, and Sapolsky,
1990). Furthermore, stress is related to insulin resistance and metabolic syndrome (Byrne,
2001), and may have long term effects on glucose metabolism. Therefore, despite
adequate energy intake, in the presence of GCs energy metabolism may be inadequate to
support CNS and/or hippocampal functioning.
GCs, in addition to their role in glucose metabolism, may also affect brain
development by regulating growth factors. There is evidence that cortisol (the chief GC
in humans) due to stress during late gestation may alter IGF and IGFPB-1, thereby
restricting growth (Cianfarani et al., 1998). In newborns, cortisol is inversely related to
IGF-I in cord blood (Cianfarani et al., 1998). Cell proliferation and differentiation are
also dependent on GCs through their role in IGF gene expression (Fowden and Hill,
2001). For example in osteoblasts (bone cells), GCs inhibit transcription of IGF-I (Delany
and Canalis, 1995; Swolin, Brantsing, Matejka, and Ohlsson, 1996), and it is likely that
such a relationship exists in neurons.
Stress and activation of catabolic hormones such as GCs may reduce glucose
availability, induce insulin resistance, and likely decrease brain growth factors, resulting
in altered brain growth.
Inflammation and infection, specifically the role of cytokines, are also important to
consider in metabolism and cognitive development. Cytokines are small molecular
weight proteins which initiate tissue breakdown and are released in response to cortisol
activation by either non-infectious or infectious agents. The predominant cytokines
released are TNF-alpha (tumor necrosis factor) which promotes tissue breakdown to
provide substrates for glucose production and IL-6 (intraleukin-6) which induces the liver
to use amino acids for defense proteins rather than for tissue accretion. Thus, chronic
cytokine activation by stress results in less available amino acids for protein synthesis,
including that needed for brain structure. The roles of both stress and inflammation in the
impact of nutrition on cognition are largely theoretical, but warrant future attention.
Selected nutrients and their effect on brain development
Table 1 categorizes the components of human nutrition and their likely relationships to
central nervous system development and function. All nutrients are needed for normal
somatic development, but some play a greater role in neurodevelopment than others. The
following sections present the evidence for the nutrients that are most important to the
developing cognitive systems of the brain.
PROTEIN-ENERGY STATUS The effect of protein-energy nutritional status on brain
growth and neurodevelopment is one of the most extensively studied subjects in nutrition.
The importance of providing protein and energy to developing and mature brains has
been assessed almost exclusively through studies of protein-energy insufficiency (as
opposed to evaluating whether there is a beneficial effect of supplementing a replete
organism). Even large-scale epidemiological studies demonstrating beneficial effects of
protein and energy supplementation have been conducted in populations where proteinenergy malnutrition (PEM) is endemic (Gorman, 1995). Pollitt and Gorman (1994)
suggest that chronic energy rather than protein deficiency is responsible for most of the
neurobehavioral changes associated with PEM. Animal models, however, strongly
implicate independent roles for protein and energy in brain structural changes.
PEM can occur throughout the lifespan from fetal life through adulthood. The
likely neuropathology underlying the significant changes in brain development or
function seen with PEM has been elucidated using animal models.
Effects of prenatal PEM As with most nutritional deficiencies, the most significant
neurodevelopmental effects appear to occur when severe PEM is imposed on a rapidly
growing brain. The brain grows most rapidly during fetal and early postnatal life.
Restriction of macronutrients during fetal life results in deceleration of growth and bears
the term “intrauterine growth restriction” (IUGR). Maternal hypertension during
gestation accounts for 75% of all cases of IUGR, although maternal malnutrition,
intrauterine infections and chromosomal anomalies can alter fetal growth as well (Low
and Galbraith, 1974). In the latter two instances, the adverse neurodevelopmental
outcome associated with small brain size is not due to PEM but to the underlying
pathology of the precipitating condition (e.g., viral invasion of CNS cells). In the case of
maternal hypertension, high blood pressure causes atheromatous (plaque-like) changes in
the vessels of the placenta, which in turn restricts blood and nutrient flow to a smaller,
more calcified placenta (DeWolf, Robertson, and Brosen, 1975). Evidence of PEM
resides in the smaller weight, length, and fat and muscle content of the growth-restricted
fetus and newborn. Brain growth is compromised if the hypertensive insult is early
(second trimester), prolonged, or severe.
The neurodevelopmental effects of restricted fetal nutritional delivery and delayed
brain growth have been a subject of extensive clinical and laboratory investigation. Most
larger trials measured relatively neurologically nonspecific outcomes such as intelligence
quotient (Strauss and Dietz, 1998). Smaller studies have looked more specifically at what
areas of the brain may be preferentially affected by fetal PEM. These studies demonstrate
a fivefold higher prevalence of mild neurodevelopmental abnormalities at 2 years of age
(Spinillo et al., 1993), weak novelty preference on visual recognition memory tasks
(Gottleib, Biasini, and Bray, 1988), and reduced verbal ability (Pollitt and Gorman, 1994)
in the IUGR infants compared with appropriate-sized controls. It is important to
recognize that these effects may be due to PEM alone (based on animal models), but may
also be due to other micronutrient deficiencies (iron, zinc, selenium) or chronic
intrauterine hypoxia. A significant postnatal confounder has been the consistent finding
that fetal growth restriction occurs more frequently in women of lower socioeconomic
status who receive less prenatal care and in whom there is an increased incidence of
smoking (Strauss and Dietz, 1998).
Epidemiological studies show that poor prenatal head growth presages poor
developmental outcome (Gottleib, Biasini, and Bray, 1988; Harvey et al., 1982; Low et
al., 1982; Strauss and Dietz, 1998; Winer and Tejani, 1994). Employing a clever study
design, Strauss and Dietz (1998) matched term IUGR infants to sibling controls who
were of appropriate weight for term gestation, thus controlling for genetic and postnatal
environment; they showed a significant decrement in broad measures such as WISC IQ
and Bender-Gestalt scores at 7 years only if head growth had been compromised in the
fetal period, but found no effect if intrauterine head growth had been spared.
The biochemical and neuroanatomic bases of neurodevelopmental impairment
from early PEM can be found in human autopsy studies and in investigations using
animal models. The human studies show significant reductions in brain DNA, RNA, and
protein content (Winick and Nobel, 1966; Winick and Rosso, 1969a,b). IUGR infants
have lower brain cell number, smaller cell size, and smaller head circumferences. Certain
areas (e.g., the cerebellum, cerebral cortex, hippocampus) demonstrate more profound
effects than others, suggesting that the developing brain in some way prioritizes protein
and energy during deficiency states.
Animal models of IUGR support the human findings of lighter brain weights,
reduced neuronal DNA and RNA contents, as well as reductions in mRNAs for neuronal
and glial structural proteins, synapse number, synaptic structures, and neurotransmitter
peptide production. (Bass, Netsky, and Young, 1970; Cragg, 1972; Jones and Dyson,
1976; Wiggins, Fuller and Enna, 1984). Fatty acid profiles are profoundly altered, with
subsequent reductions in myelination, brain lipid composition, and learning ability in fatrestricted rats (Yamamoto et al., 1987). Malnutrition also downregulates CNS growth
factors critical for normal brain development (Nishijima, 1986). The study by Lee and
colleagues (1999) in transgenic mice emphasizes the importance of maintaining IGF-I
levels during periods of malnutrition in order to spare regions of the brain important for
cognition.
It will be important in future research in IUGR infants to link specific regional
neuropathologic or neurochemical findings (elucidated from controlled animal models of
PEM) with deficits in behaviors known to be based in those regions. Thus, one should be
able to relate the reduction in visual recognition memory processing in IUGR infants
(Gottleib, Biasini, and Bray, 1988) to either reduced hippocampal volume or metabolism
on MRI/NMR spectroscopy. Several studies have begun to examine such relationships
between brain and behavior in IUGR infants. For instance, IUGR infants, when compared
with matched-for-gestational-age controls, had reduced cerebral cortical gray matter, and
this reduction in gray matter was correlated with attention interaction capacity (as
measured by the APIB) (Tolsa et al., 2004). Another recent study(L. S. Black, deRegnier,
Long, Georgieff, and Nelson, 2004) assessed electrophysiological correlates to
recognition memory processing using event-related potentials (ERP); IUGR newborns,
compared with matched-for-age controls, had ERP patterns indicative of accelerated
maturation of auditory recognition memory. Continuation of such lines of research will
be principle to clarify the relationship between specific aspects of brain development and
cognition in IUGR infants.
Effects of postnatal PEM The postnatal brain grows rapidly during the first six postnatal
months and then slows considerably during the last six months of the first year. Important
regional changes that occur during this year include myelination of motor tract fibers,
rapid cerebellar development, and establishment of hippocampal-prefrontal connections.
Similar to intrauterine malnutrition, extrauterine malnutrition bodes poorly for the
developing brain. Preterm infants or those with severe illnesses during the neonatal
period are particularly vulnerable. The protein and energy needs of these infants are high,
and it is often difficult to meet the nutritional requirement of these infants due to their
illnesses. Preterm infants whose head circumference (which reflects brain growth during
typical development) fails to catch-up to the gestation-specific norm within 4 weeks have
suboptimal head growth and lower developmental quotient at 12 months corrected age
(Georgieff et al., 1985). In preterm infant with IUGR, these adverse effects are seen after
only 2 weeks of poor postnatal head growth. Similarly, a recent prospective study found
that IUGR infants had lower IQs and performed worse on measures of frontal lobe
functioning at age 9 years compared with carefully matched controls (Geva, Eshel,
Leitner, Valevski, and Harel, 2006). These findings were attenuated by postnatal catch-up
growth, such that IUGR children with incomplete catch-up growth had more cognitive
difficulties than those with complete catch-up growth.
Once infants are weaned from human milk or formula, their risk of PEM increases
because they are now dependent on the same foods as their adult food providers. A child
growing up in an area of the world where PEM is endemic will be placed at a risk
equivalent to or greater than the adult population of that area. The effects of PEM have
been extensively studied in children from age 6 months through the early teenage years in
these endemic areas. Although the studies show mixed results owing to differences in
degree, timing, type, and duration of malnutrition, it is safe to state that PEM of sufficient
degree and duration at a critical time during a growing child’s life will affect cognitive
abilities. In some cases, the negative effect on the brain is reversible with nutritional
rehabilitation, while in other cases the effects appear more “permanent”. However, as
discussed below, the assignment of nutritional causality to poorer cognitive outcomes in
free-living societies has been very difficult, given concurrent confounding variables such
as maternal mental health, maternal socioeconomic status, lack of infant mental
stimulation, and malnutrition-induced lack of infant motivation (Stein and Susser, 1985).
Until the mid-1990s, studies assessing the role of postnatal malnutrition in
cognitive development were dominated by two important theoretical concepts. The first
centered on the idea of “critical periods.” Winick and Noble’s histopathologic studies
introduced the idea that PEM during the period of rapid brain growth in the perinatal
period would cause more significant and hence more permanent perturbations in brain
structure and, ultimately, function (Winick and Nobel, 1966). The vulnerable period was
subsequently extended until at least 3 years of age as it became apparent that
synaptogenesis, dendritic pruning, programmed cell death, and myelinogenesis continued
well into the postnatal period. Dobbings’ work codified the concept of vulnerable or
critical periods in the field of nutritional neuroscience (Dobbing, 1990). Based on these
developmental neuroanatomic considerations, it was logical to expect that field studies of
PEM in 6-month-old to 3-year-old children should demonstrate significant cognitive
effects.
The other important theoretical concept centered on the role of covariates such as
maternal mental status, maternal – child interactions, and infant motivation in
determining the cognitive abilities of the malnourished infant (Lozoff et al., 1998; Pollitt
and Gorman, 1994). Theoretically, these covariates could be highly dependent on either
maternal or infant nutritional status, or they could be completely separate issues. Another
example concerns the effects of individual differences in infant motivation. An infant
could perform poorly on a set of cognitive measures as a function of what is perceived by
the investigator as “reduced motivation.” Reduced motivation could be due to depression,
decreased energy due to marginal malnutrition, or poor maternal – child stimulation
based on the mother’s (and not the infant’s) nutritional status. Lozoff has published a
diagram of these complex interactions with respect to iron deficiency (Lozoff et al., 1998;
Georgieff and Lozoff, in press), but the tenets are clearly applicable to PEM as well.
Finally, some of the impairments in developmental tests could be due to the effect of
malnutrition on the musculoskeletal system. As an example, preterm infants with
bronchopulmonary dysplasia, a condition that is associated with malnutrition (deRegnier,
Guilbert, Mills, and Georgieff, 1996) perform poorly on developmental tests, such as the
PDI component of BSID during infancy and toddlerhood (Raman, Georgieff, and Rao,
2006). With nutritional rehabilitation and improvement in physical growth, these
impairments also tend to improve.
Prior to the mid-1990s, studies in humans that attempted to associate mild to
moderate PEM with poorer cognitive outcome were so hopelessly flawed that researchers
in the field would reach diametrically opposite conclusions about the studies (see Stein
and Susser, 1985). It may not be ethically possible to separate all of the nonnutritional
confounding variables in a free-living human society, but studies published by Pollitt’s
group in the mid-1990s have given credence to the hypothesis that nutritional factors
(specifically, PEM) do influence postnatal cognitive development (Pollitt and Gorman,
1994; Pollitt et al., 1995; Pollitt, Watkins, and Husaini, 1997).
In these studies, long-term cognitive effects of early supplemental feeding in
children 0-7 years of age were examined in four Guatemalan villages from 1969 to 1977.
Seventy percent of the children were followed up in 1988 at ages 11-26 years. The
villages were in an area marked by mild to moderate PEM. Participants in two of the
villages received a high-calorie/high-protein supplement that was administered to the
mothers, infants and young children. Participants in the other two villages received a
supplement with 40% fewer calories and 20% less protein. Test scores on knowledge,
numeracy, reading, processing time, and vocabulary at follow-up (adolescence) were
significantly higher in the group receiving more robust protein-energy supplementation.
Within that group, no effect of socioeconomic status was observed. Interestingly, the
group that received less supplementation not only had lower scores on cognitive tasks,
but demonstrated a profound socioeconomic effect as well. This result suggests that
marginal nutritional status may potentiate the effects of other neurologic risk factors. A
similar effect has been described in animal models of iron deficiency (Rao et al., 1999).
Pollitt and colleagues (1995) very carefully considered potential alternative
explanations (including differences between the villages, intervening factors between the
initial intervention and the follow-up 10 years later, compliance with the dietary
supplements, and the 30% dropout rate at follow-up), and concluded that none accounted
for the observed differences in cognition. They do not claim that the study provided
definitive proof of the effect of early mild PEM on later cognitive ability, but felt that the
evidence is compelling enough to justify nutritional intervention as sound public health
policy (Pollitt and Gorman, 1994).
From a mechanistic standpoint, it would be most useful for researchers studying
postnatal PEM to assess whether the neurodevelopmental abnormalities that are observed
fit the expected pattern of vulnerable brain areas and processes predicted from human and
animal histopathologic, neurochemical, or neurophysiologic models. Although it is
laudable to demonstrate effects of mild PEM on relatively broad cognitive function, it
would be interesting to know whether neurologic circuits involved in the behaviors where
differences are observed between groups are particularly at risk specifically for protein or
energy malnutrition. For example, the reduced speed of processing could be easily
explained by nutritionally induced hypomyelination. Alternatively, the same finding at
the behavioral level could be due to reduced motivation to perform the task and may be
related to damage or dysfunction of limbic structures such as the amygdala. If no data
support amygdaloid vulnerability to PEM, the latter may be more effectively ruled out.
Newer tools that assess the structure and functions underlying certain cognitive
capabilities (e.g., fMRI, event-related potential) now allow for more precise delineation
of cause and effect of nutritional deficiencies such as early PEM).
Effects of specific macronutrients Infants in the United States and Canada are typically
fed either human milk or infant formula derived from cow’s milk or soy plant products
during this time. The significant, positive relationship between breastfeeding and
cognitive development is intriguing, since it is unclear whether the positive effect is
related to nutritional factor(s) present in human milk but not in formula, to positive
maternal-infant interactions (including the propensity of higher-IQ mothers to choose
breastfeeding), or both.
There is good reason to believe that multiple factors found in breast milk promote
normal CNS development and that deficiencies of these nutrients in cow’s milk or soybased formulas are responsible for slower rates of cognitive development (Lucas, 1997;
Morrow-Tlucak, Haude and Ernhart, 1988; Wang and Wu, 1996). These factors include
compounds such as nucleotides (DeLucchi, Pita, and Faus, 1987) oligosaccharides and
long-chain polyunsaturated fatty acids (LCPUFA) (Innis, 1992) that are simply not
synthesized by cows and soy bean plants. Because of their potential neurologic effects,
within the past few years, LCPUFAs have been added to some cow’s milk and soy-based
formulas. Other neurotrophic compounds (e.g., growth factors) have not been added
because they are destroyed in formula processing or storage (MacLean and Benson,
1989).
The oligosaccharides and lactose that are present in human milk may play a
significant role in brain development. Oligosaccharides are present only in the milks of
humans and elephants, both species with a highly developed central nervous system
which develops predominantly after birth (Kunz, Rudolf, Baier, Klein, and Strobe, 2000).
Galactose- and sialic acid-containing oligosaccharides appear be important for
myelination, synaptogenesis and learning (Kunz et al., 2000; Wang and Brand-Miller,
2003; Wang, McVeagh, Petocz, and Brand-Miller, 2003). Oral and parenteral
supplementation of sialic acid results in greater accumulation of sialic acid containing
glycolipid and glycoprotein in the cerebrum and cerebellum in rats (Carlson and House,
1986). The role of oligosaccharide supplementation has yet to be studied in human
infants.
Long-chain poly-unsaturated acids (LCPUFA) are one type of macronutrient that
have been given specific attention in neurodevelopment. LCPUFAs include
docosohexaenoic acid (DHA; 22:6n-3) and arachidonic acid (AA; 20:4n-6). Both are
transported by the placenta to the fetus (Carlson, 1997), and both accumulate in the CNS
during the third trimester (Clandinin et al., 1980). These compounds are provided
transplacentally by the mother during the last trimester. Accordingly, preterm infants are
at greater risk of deficiency due to shortened nutrient placental transfer during late
gestation. Furthermore, DHA and AA can be synthesized form the precurosors alphalinolenic acid and linoleic acid respectively; however, this synthetic pathway is immature
in neonates, with limited synthetic capacity as early as 33 weeks gestation. However, full
synthetic capacity is not thought to develop until 2 months post-term.
LCPUFAs potentially affect neurodevelopment because they are essential in all cell
membranes. They are involved in intercellular communication, signal transduction
(Carlson, 1997) and monoamine metabolism (Innis, 2003). They are critical for visual
development in primates and likely in humans (Neuringer et al, 1986; Uauy et al., 1990)
Evidence from animal studies shows that gestational DHA is necessary for normal
brain development. Gestational DHA deficiency decreases neurogenesis in the rat brain
(Coti Bertrand, O'Kusky, and Innis, 2006) and affects dopaminergic function (Levant,
Radel, and Carlson, 2004).There is evidence that prenatal LCPUFA supplementation
affects cognitive development in humans. In a double-blinded randomized
supplementation study, children born to mother’s supplemented with DHA during
pregnancy and three months of lactation performed better on cognitive tasks (mental
processing composite of the K-ABC) at 4 years of age. Furthermore, the extent of DHA
supplementation was correlated with the children’s scores (Helland, Smith, Saarem,
Saugstad, and Drevon, 2003). In another maternal supplementation study, maternal DHA
levels at birth were found to be correlated with the children’s performance on attentional
tasks at 1 year and 2 years of age (J. Colombo et al., 2004).
LCPUFAs continue to accumulate during the first 18 months postnatally
(Clandinin et al., 1980); however, postnatal supplementation of LCPUFA seems to have
different effects in preterm and term infants. Randomized trials of LCPUFA
supplementation in preterm infants show transiently improved visual acuity, faster
processing time on electroretinogram, better visual recognition memory, and higher
scores on the Mental Developmental Index of the Bayley Scales of Infant Development at
12 months of age (Birch et al., 1992; Carlson, Werkman, and Tolley, 1996). The retinal
results with respect to rod electroretinogram threshold at 36 weeks gestation and visual
acuity by forced-choice preferential looking and by visual evoked potential in preterm
infants fed supplemented formula approach the findings in breastfed infants, and are
significantly better than those of infants fed unsupplemented formula (Uauy-Dagach and
Mena, 1995). Nevertheless, most of the effects appear transient. Furthermore, the
transience of the findings is not due to withdrawal of the supplementation with
subsequent lack of synthesis by the infants, since the trials typically lasted well beyond
the age (6 months) when infants can synthesize LCPUFAs de novo. Term infants
supplemented with LCPUFAs do not demonstrate nearly the beneficial effect that
preterm infants show, perhaps because of an increased capacity to synthesize de novo AA
and DHA at an earlier postnatal age (Jensen et al., 1997).
In spite of the mixed long-term results, the data are quite convincing that
LCPUFAs (administered without the remainder of trophic factors and nutrients found in
breast milk) independently alter neurologic function and perhaps development, and these
findings provide clear evidence that nutrients can affect brain development and function.
Although they appear to be supplementation studies, they are better considered studies of
correction of deficiencies of essential nutrients in nonhuman milk formulas.
Nucleotides are nitrogenous compounds derived from the combination of a
nucleic acid base (adenine, guanine, cytosine, thymine, or uracil) with a phosphorylated
pentose sugar. Nucleotides and their precursors (nucleosides and nucleic acids) are
critical for DNA and RNA synthesis. Thus, a steady intracellular pool of nucleotides is
required to ensure cell division and protein synthesis. This de novo synthetic pathway is
immature in all newborns, but particularly in premature infants, raising the still
unresolved issue of whether dietary nucleotides are semi-essential in the newborn period.
Nucleotide supplementation of infant formula has been postulated to have an impact on
the developing brain by increasing the levels of LCPUFAs such as arachidonic and
docosohexaenoic acid (DeLucchi, Pita, and Faus, 1987; Gil et al., 1986).
IRON Iron is the second most commonly studied nutrient in relation to brain
development, after protein-energy. Iron deficiency is common worldwide; 30% of the
developing world’s population and 11% of U.S. toddlers are iron-deficient due to a lowiron diet combined (especially in the developing world) with a high rate of intestinal
blood loss. Iron deficiency is the world’s most common nutritional cause of anemia.
It is not unreasonable to study the relationship of iron to neurodevelopment and
neurologic function, given the role of iron in many brain cellular metabolic processes
(Camack, Wrigglesworth, and Baum, 1990; Larkin and Rao, 1990; Thelander, 1990;
Youdim, Ben-Sachar, and Yehuda, 1989). Iron-containing enzymes and hemeproteins are
involved in numerous neurodevelopmental processes including myelination, energy
metabolism, dendritogenesis, synaptogenesis, and monoamine metabolism (Rao, Tkac,
Townsend, Gruetter, and Georgieff, 2003). As with PEM, a convincing relationship can
be drawn between this nutrient and brain development based on deficiency states.
There are three time periods when children are at particular risk for iron
deficiency: the fetal/neonatal period, infancy and early toddlerhood (6-24 months of age),
and following the onset of menarche in girls (Bruner et al., 1996). Brain growth and
development is relatively rapid during two of these periods, while it is nearly complete
during the third. This distinction allows for studying the comparative effects of a single
nutrient deficiency on a growing versus a mature brain. Because of its intricate
involvement in cell cycle kinetics and myelination (Larkin and Rao, 1990; Thelander,
1990), one would expect profound neuroanatomic changes in a brain that is still growing,
but perhaps no structural effect in a relatively mature brain. Teenage iron deficiency
would not be expected to affect myelination since it is largely completed by that time;
however, iron deficiency prior to 3 years of age would likely result in profound and
possibly permanent myelin changes (Algarin, Peirano, Garrido, Pizarro, and Lozoff,
2003). Furthermore, areas that are growing particularly rapidly might be expected to be
most affected. Since the brain does not develop homogenously (i.e., not all parts mature
simultaneously), iron deficiency during one growth period (e.g., fetal life) may result in
very different neuroanatomic and neurobehavioral deficits than iron deficiency during
another growth period (e.g., infancy). Iron also has important effects on neurochemistry
and neurometabolism through its effects on monoamine metabolism and oxidative
phosphorylation (Cammack, Wrigglesworth, and Baum, 1990; Youdim, Ben-Sachar, and
Yehuda, 1989). Iron deficiency may affect these chemical and metabolic aspects of brain
function similarly in developing and mature brains. Therefore, neurotransmitters, such as
dopamine and glutamate (Rao et al., 2003) would be vulnerable to iron deficiency at any
age.
Iron deficiency most commonly occurs during infancy, between 6 and 24 months
of age, due to low dietary iron intake (through consumption of either low-iron formula or
cow’s milk and delayed introduction of iron-containing solid foods). It is not surprising
that this age group has been more extensively studied than any other iron-deficient group,
and animal models have focused on ID during this time. Dietary iron deficiency has been
induced in rats from weaning (21 days) to 35 days of age in order to model iron
deficiency of human infancy.
Multiple well-controlled clinical studies in this age group demonstrate significant
decrements in motor and mental achievement (Lozoff, 1990; Lozoff et al., 1982, 1987;
Nokes, van den Bosch, and Bundy, 1998; Walter, Kowalskys, and Stekel, 1983). While
the motor findings are less robust and generally reversible with iron therapy, the
significant cognitive deficits that have been documented are more resistant to reversal,
and in some studies are very long-term (Lozoff, 1990). The cognitive deficits include a
10- to 12-point reduction in the Mental Developmental Index of the Bayley Scales of
Infant Development, significantly associated with the degree of anemia (Lozoff, 1990).
These cognitive deficits appear to be irreversible with treatment. The findings are not
thought to be due to anemia itself, since rapid correction of the anemia does not affect the
neurodevelopmental test scores.
The apparent permanence of these neurobehavioral findings has three important
implications. First, there appears to be a differential regional effect of iron on the growing
brain, perhaps mediated by differences in regional blood-brain iron transport regulation.
This regionalization concept is supported by the nonhomogenous (e.g., cognitive greater
than motor) deficits induced by iron deficiency. Second, iron deficiency during this
period of brain development likely changes neuroanatomy since the deficits remain
extant over much longer periods of time than would be expected for neurochemical or
neurophysiological alterations. Third, and perhaps of greatest concern, the results
demonstrate that certain brain lesions induced by nutritional deficiencies are beyond the
reach of CNS reparative or compensatory processes which may be termed “plasticity”.
The presence of iron in the brain is critical for myelination (Larkin, Jarratt, and
Rao, 1986). Iron deficiency in immature animal models results in a predictable loss of
enzyme activity and in hypomyelination (Larkin and Rao, 1990). In animal models, early
ID affects myelin lipid synthesis and permanently alters brain lipid composition despite
repletion (Kwik-Uribe, Gietzen, German, Golub, and Keen, 2000; Ortiz et al., 2004; Rao
et al., 2003). If the same process occurs in infants, one could predict a specific
neuroanatomic effect (potentially visible with high-resolution magnetic resonance
imaging) or a neurophysiologic effect (potentially detected by electrophysiologic
assessment). Although the former has not been assessed, Roncagliolo and colleagues
(1998) have reported delayed latencies on auditory brainstem-evoked responses in irondeficient 6-month-old infants. They attributed this delay to the effects of iron deficiencyinduced hypomyelination. These effects appear to be long-lasting despite iron treatment.
At ages 3 and 4, delayed latencies in auditory brainstem responses and visual evoked
potentials have been observed in children with iron deficiency anemia despite treatment
during infancy (Algarin et al., 2003).
Iron also has important effects on neurochemistry and neurometabolism through
its effects on monoamine metabolism and oxidative phosphorylation (Cammack,
Wrigglesworth, and Baum, 1990; Youdim, Ben-Sachar, and Yehuda, 1989). Monoamine
metabolism involves iron dependent enzymes (tyrosine hydroxylase and tryptophan
hydroxylase), and animal studies which model ID in infancy show long-term monoamine
alterations (Beard and Connor, 2003; B Lozoff et al., 2006). For instance extracellular
dopamine and epinephrine increase, while monoamine transporters and dopamine
receptors D1 and D2 decrease, and such alterations occur without reductions in brain iron
concentrations (Beard and Connor, 2003; Beard et al., 2006). Decreased exploration and
increased hesitancy have been observed as a result of early ID in rodents, likely due to
altered dopaminergic function (Felt and Lozoff, 1996; Pinero, Jones, and Beard, 2001).
There is evidence for similar behaviors in infants with ID anemia. They were
observed to be more wary and hesitant, easily tired, less playful, and make less attempts
at test items (Lozoff et al., 1998). Accordingly, reduced activity and inhibited exploration
may lead to hampered cognitive abilities.
The selectivity of iron deficiency for certain areas of the brain can be similarly
assessed. Striatal development is also rapid during late gestation and early infancy and is
altered by ID during this time. The striatum contains high concentrations of both iron and
dopamine (Beard and Connor, 2003), and striatally-mediated behaviors in the rodent are
affected by ID (Felt et al, in press). There is evidence that striatal development is altered
by ID during infancy and has long-term cognitive effects. Children with severe ID during
infancy performed worse on tasks that rely on striatal-frontal connections. For instance, at
11-14 years of age, children who had severe, chronic ID during infancy had poorer
performance on tasks of spatial memory and selective attention compared with children
without severe ID during infancy (Lozoff, Jimenez, Hagen, Mollen, and Wolf, 2000).
Furthermore, at the age of 19, poor performance on tasks of executive function, primarily
those of inhibition and planning, was associated with ID during infancy (Burden, Koss
and Lozoff, 2004).
The second group of developing humans at risk for iron deficiency is late
gestation fetuses and newborns. Infants born to mothers with iron deficiency, gestational
conditions such as diabetes mellitus, IUGR and maternal smoking are at risk of fetal and
neonatal iron deficiency. The adverse effects of fetal and neonatal iron deficiency have
been studied in infants of mothers with diabetes mellitus during pregnancy and infants
who suffered IUGR. Each group has a 50% prevalence of low iron stores at birth, 25% of
which are at a risk for brain iron deficiency. Autopsy studies have documented up to a
40% decrease in brain iron in the most severely affected infants. Both groups of infants
are at increased risk for neurobehavioral abnormalities. Animal models of perinatal iron
deficiency support the concept of regional loss of iron-dependent brain metabolic
function, with the hippocampus and its prefrontal projections demonstrating particular
vulnerability (deUngria et al., 2000). Regions that are developing rapidly during a state of
ID are likely to be most affected. During late fetal and neonatal development, the
hippocampus is developing rapidly, and animal models show alterations in hippocampal
neurochemistry, structure and electrophysiology (Jorgenson, Sun, O'Connor, and
Georgieff, 2005; Rao et al., 2003; Jorgenson, Wobken, and Georgieff, 2003). Poor
performance on hippocampal-mediated memory performance (e.g., spatial memory tasks)
is associated with ID in the rodent model of early ID (Felt and Lozoff, 1996).Thus, a
putative link between perinatal iron deficiency and newborn and long-term
neurobehavioral sequelae can be proposed. Unfortunately, like all other clinical
population studies, each group has other significant neurologic risk factors (e.g.,
hypoglycemia, hypoxia, PEM) that may affect long-term outcome and confound any
attempt at causally relating perinatal iron deficiency with neurobehavioral deficits.
However, in a study of infants born to mothers with diabetes mellitus, those with iron
deficiency at birth showed delays in auditory recognition memory when tested at birth
compared with iron sufficient infants of diabetic mothers (Siddappa et al., 2004). This
finding suggests that the effects in recognition memory are due to iron rather than to
other risk factors associated with gestational diabetes.
The neurobehavioral study of iron-deficient teenage girls provides an interesting
contrast to iron-deficient infants since the brain is neuroanatomically relatively mature
and myelination is complete at this age. Iron supplementation of young women with iron
deficiency anemia improves memory and learning but has no effect on attention (Groner
et al., 1986). These findings can be contrasted with the long-term (and perhaps
permanent) deficits found in toddlers who became iron-deficient and were subsequently
treated. The reversibility of the neurobehavioral deficits with iron therapy in the teenage
population argue for an effect of iron on neurochemistry (e.g., dopamine) or
neurophysiology (oxidative metabolism) as opposed to potential structural changes in
neuroanatomy that may have occurred in the toddlers.
ZINC A strong case can be made for the essentiality of zinc for normal brain
development and function. Zinc deficiency affects neuroanatomy, neurochemistry, and
neurophysiology through a variety of mechanisms. The global effects of zinc are in part
due to the essential role that zinc plays in basic protein biochemistry and in cell
replication. Zinc has a direct effect on brain growth and morphology through its role in
enzymes that mediate protein and nucleic acid synthesis (Sandstead, 1985; Terhune and
Sandstead, 1972). Profound zinc deficiency in the growing animal results in decreased
brain DNA, RNA, and protein content (Duncan and Hurley, 1978; Sandstead, 1985). Zinc
has an indirect effect on brain growth because its presence is needed for normal insulinlike growth factor-I (IGF-I) activity (McNall, Etherton, and Fosmire, 1995). Zinc
influences brain neurochemistry (and presumably function) by inhibiting binding of
opioids to µ receptors and of magnesium to µ and δ receptors in the cerebral cortex
(Tejwani and Hanissian, 1990). Zinc also inhibits γ-aminobutyric acid (GABA)
stimulated chloride influx into hippocampal neurons (Li, Rosenberg, and Chiu, 1994).
Zinc is released into the interneuronal space from presynaptic boutons (Frederickson and
Danscher, 1990). Zinc’s effect on brain neurophysiology is evident in abnormal
electroencephalographic tracings found in zinc-deficient rats (Hesse, 1979).
The cerebellum, limbic system, and cerebral cortex are particularly rich in zinc
and demonstrate the most profound effects of zinc deprivation (Frederickson and
Danscher, 1990). These effects include truncated dendritic arborization and reduced
regional brain mass in rats. As with iron deficiency, the neuroanatomic sequelae of zinc
deficiency in young rats persist into adulthood with attendant persistent behavioral
sequelae (Frederickson and Danscher, 1990). Two-year-old rhesus monkeys fed a zincdeficient diet have reduced spontaneous motor activity and poorer short-term memory
compared with the pre-deficiency baseline period (Golub et al., 1994). Similar results
have been found in mice and rats.
Zinc is essential for growth, as it is involved in cell replication and nucleic acid
and protein synthesis. Accordingly, zinc is especially critical for infants, children,
adolescents, and pregnant women (FAO/WHO, 2004). It is likely that during times of
rapid growth and/or rapid brain growth, individuals might be vulnerable to zinc
deficiency. The rate of inadequate dietary intakes of zinc in infants and toddlers in
developing countries suggest that the rate of zinc deficiency is fairly high (FAO/WHO,
2004). Furthermore, inadequate dietary zinc intakes among middle-class and upper-class
infants and toddlers in the United States also suggest that the rate of zinc deficiency is
common among American children (Skinner et al., 1997), and according to the latest
national nutrition survey (NHANES III), young children ages 1-3 and adolescent females
are at risk for inadequate zinc intakes (Briefel et al., 2000).
Despite the evidence in animal models, zinc supplementation trials in children
have yielded inconsistent results. During infancy, there is some implication that zinc
supplementation improves motor development and promotes activity in the most severe
cases of zinc deficiency (for review, see Black, 2003). However, other findings show
zinc deficiency in humans results in significant changes in neuropsychological
performance on tests that tap the anatomical areas shown to be vulnerable in the animal
models (Sandstead et al., 1998). Six- to nine-year-old first-graders with low zinc status
were assessed biochemically and neuropsychologically before and after treatment. The
tasks included design matching to assess visual perception, delayed design matching to
assess short-term visual memory, a spatial orientation memory test, and Pollitt’s oddity
task to assess concept formation and abstract reasoning. Zinc supplementation for 10
weeks resulted in significantly better zinc status and improvement in these particular
neuropsychological assessments.
IODINE There is overwhelming evidence that iodine sufficiency is critical for normal
early CNS development. An analysis of available epidemiological studies has helped
elucidate the effect of severity, timing, and duration of iodine deficiency on brain
development and neurologic outcome. Iodine deficiency can range from severe to mild
based on the availability of iodine in the food supply (Hetzel and Mano, 1989). Endemic
areas of severe dietary iodine deficiency include parts of China, Zaire, Iran, and India
(Hetzel and Mano, 1989; Kretchmer, Beard, and Carlson, 1996), with 35% of world’s
population having insufficient iodine intake (de Benoist, Andersson, Egli, Takkouche,
and Allen, 2004). Classic older studies from these areas helped characterize the syndrome
of endemic cretinism that, in its severest neurologic manifestation, includes mental
retardation, spastic diplegia, and deaf-mutism. More recently, investigators have
concentrated on describing the neuropsychological and motor effects of moderate or mild
iodine deficiency and the effect of iodine prophylaxis or treatment in high-risk groups
(Aghini-Lombardi et al., 1995; Azizi et al., 1993). A clear dose-response effect can be
appreciated across the studies, with moderate iodine deficiency resulting in reduced
verbal IQ and subset coding ability on the Wechsler Intelligence Scale for ChildrenRevised (WISC-R) as well as motor impairments on simple reaction time tests in children
of elementary school age (Fenzi, Giusti, and Aghini-Lombardi, 1990). Mild iodine
deficiency results in reduced motor ability without any apparent effect on cognition when
children of the same age were assessed with the same tools (Azizi et al., 1993). It is
unclear whether the latter group had early cognitive findings that were “reversed” with
postnatal iodine treatment or whether they were never affected in the first place.
As with any nutrient deficiency, timing and duration are of critical importance.
Cretinism results from severe iodine deficiency during early pregnancy, rather than late
pregnancy. Moreover, developmental delays associated with prenatal iodine deficiency
appear to be specific to deficiency during the first two trimesters, but not the third (Cao et
al., 1994; O'Donnell et al., 2002). Interventional studies with iodine treatment clearly
demonstrate that prophylaxis is effective. Iodine-deficient women living in endemic areas
who were injected with iodinated oil prior to pregnancy did not produce infants with
cretinism (Hetzel, 1987). In a Chinese population at risk for iodine deficiency, iodine
supplementation before the third trimester predicted higher Bayley scores at age 2 (Cao et
al., 1994) and higher psychomotor test scores around the age of 6 (O'Donnell et al.,
2002) compared with those who received supplementation during the third trimester or
postnatally. In animal models, treatment later in pregnancy had a much less dramatic
effect, and postnatal treatment of humans and animals appeared to have little effect.
These observations lend credence to the hypothesis that the critical window for brain
responsiveness to iodine is during early fetal life. Nevertheless, it should be noted that
children and adolescents living in areas of endemic iodine deficiency will demonstrate
alterations in psychomotor development with reduced IQ, even with normal physical
growth (an indicator of less severe iodine deficiency) (Azizi et al., 1993). Although very
few studies have been performed that assess the effect of repletion of iodine status on
cognitive performance in children with mild to moderate iodine deficiency, a recent
randomized, placebo-controlled, double-blind intervention, found that iodinde
supplementation improved performance on cognitive tasks of information processing and
problem solving in children between the ages of 9 and 10. (Zimmerman et al., 2006).
There is reason to believe that late-onset iodine deficiency (hypothyroidism) affects brain
function, but not anatomy. Smith and Ain (1995), using 31P magnetic resonance
spectroscopy, demonstrated reduced oxidative metabolism in the hypothyroid brain
(Pleasure and Pleasure, 2003) that was reversible with thyroid replacement therapy.
SELENIUM Selenium is a micronutrient whose role in brain development is only now
being elucidated. Selenium deficiency is seen in geographical regions where there are
low selenium levels in the soil. Food crops and pasture grasses grown in these soils will
have lower selenium content; therefore, populations who depend on local food crops and
animal products are at risk for selenium deficiency. The highest rates of selenium
deficiency are in communities living in several regions throughout China with low soil
content (FAO/WHO, 2004). Several other regions with low soil content (e.g., Finland,
New Zealand, United Kingdom) have reduced the rates of selenium deficiency due to
importation of crops and animal products raised in high content regions. Finally, another
population at relatively high risk of selenium deficiency is preterm infants because of
their lower body stores and generally poorer antioxidant status.
Although direct evidence of selemium’s effect on cognitive development in
humans is lacking, its role in brain thyroid and iodine metabolism, as well as its
interaction with other micronutrients (e.g., iron, copper, zinc, lead) that affect brain
development, is important to note. Selenium is required for the synthesis of proteins
(selenoproteins) that are involved in thyroid metabolism. Thus, as with iodine, selenium
deficiency can lead to hypothyroidism and cretinism. Studies linking selenium status with
behavioral development in animal models have been published (Mitchell et al., 1998;
Watanabe and Satoh, 1994). Thus, it is likely that research on the role of this nutrient in
human brain development will be forthcoming.
CHOLINE Developing fetuses and postnatally breastfed infants may be at risk for
choline deficiency if the mother has poor choline body stores and/or poor dietary choline
intake. Formula-fed infants may also be at risk for choline deficiency depending on the
formula used as the choline concentrations range between 50% to 140% that found in
human milk. Human milk is also abundant in several choline-containing compounds, and
formulas do not contain the same composition of these compounds as human milk
(Blusztajn, 1998; Meck and Williams, 1999). Additionally, during the early postnatal
period, there is a brief spike in choline concentrations in human milk which is not
mirrored in infant formulas (Meck and Williams, 1999).
Choline serves several metabolic functions essential for neurodevelopment. The
majority of choline in the body is present in two phospholipids that are essential for both
plasma membrane and myelin synthesis (Blusztajn, 1998; Colombo, Garcia-Rodenas,
Guesry, and Rey, 2003). Choline is also involved in cholinergic neurotransmission, as it
is the precursor for acetylcholine, serves as a methyl source in single-carbon metabolism
of protein synthesis and transmethylation reactions (Blusztajn, 1998), and is involved in
transmembrane signaling during neurogenesis and synaptogenesis (Meck and Williams,
1999). During fetal development, choline is essential for stem cell proliferation and
aptoptosis (Blusztajn, 1998).
Choline has permanent effects on rodent memory and attention development. Prenatal
choline supplementation results in better spatial memory performance in the adult rat
compared with control rats and impairs memory performance in prenatally choline
deficient rats. (Meck and Williams, 1999). Prenatal choline deficiency is associated with
long-term effects on attention which may be related to the long-term effects on memory.
Gestationally deficient rats perform poorly on attention tasks compared with controls and
choline supplemented rats, showing difficulty selectively attending to stimuli and
showing an increased rate of age-related decline in attention (Meck and Williams, 2003).
Several mechanism for the effects of choline supplementation on memory
development have been identified (Meck and Williams, 2003). Prenatal choline
deficiency increases the rate of apoptosis in the hippocampus, thus potentially altering
hippocampal structure and function (Holmes-McNary, Loy, Mar, Albright, and Zeisel,
1997). Another potential mechanism involves adaptations in cholinergic transmission
(Meck and Williams, 2003); prenatal choline has long-term effects on cholinergic
transmission, altering hippocampal acetylcholine function despite repletion (Blusztajn,
Cermak, Holler, and Jackson, 1998). Yet another mechanism linking choline to memory
is through hippocampal long term potentiation LTP; the stimulus threshold for LTP is
inversely related to prenatal choline status (Pyapali, Turner, Williams, Meck, and
Swartzwelder, 1998).
Because choline supplementation of older animals does not seem to improve memory
as it does following supplementation during fetal development, it is likely that choline
during early development alters the developmental trajectory of neural circuits that
support memory, leading to long-term alterations in memory and attention (Meck and
Williams, 2003).
Despite the mounting evidence from animal research for the role of choline in
neurodevelopment and memory and attention performance, questions still exist whether
these findings translate to humans. However the evidence from animal models highly
supports the hypothesis that dietary choline during pregnancy and the early postnatal
period is necessary for normal cognitive development.
The role of timing in nutrient deprivation and subsequent repletion
A common theme in the discussion of each of the nutrients has been the roles of
timing, duration, and severity of nutrient administration or deficiency.
Clear evidence exists that brain growth and development is not an even process
and that various “circuits” come on line at different times between conception and
adolescence. Nutrient requirements are increased during a period of rapid growth for any
organ, including the brain. Human and animal model experiments also support the
concept that nutritional deprivations during a period of rapid growth result in more
profound structural, chemical, and physiological changes than if the same degree of
deprivation is imposed during a more quiescent period. What remains of great interest is
whether these early changes are reversible.
Reversibility (or amenability to nutritional rehabilitation) can be looked at in two
ways—through a large-scale population-based approach, as Pollitt has done (Pollitt and
Gorman, 1994), and through further understanding of the critical nutrients required for
normal ontogeny of brain development. Both approaches beg the question of “plasticity”
within the developing system. Pollitt’s studies clearly demonstrate that developmental
benefits of nutrient supplementation are a function of the timing of that intervention
(Pollitt et al., 1993). The earlier the timing, the greater the benefits. Yet, it is difficult to
argue that the “critical window” is ever “closed” during childhood. Studies of children
suffering from prenatal malnutrition (IUGR; Morgane et al., 1993; Strauss and Dietz,
1998) or postnatal malnutrition (Pollitt et al., 1993) clearly demonstrate recoverability of
function well beyond the period of rapid brain growth.
A similar effect is seen in the growth and development of preterm infants. Greater
than 50% of preterm infants become microcephalic during their hospital stay due to
inadequate nutrient delivery, severe illness resulting in catabolism, and a very rapid
expected rate of brain growth (Georgieff et al., 1985). Although nutritional management
of preterm infants has improved substantially during the years (Georgieff et al., 1989),
preterm infants leave the NICU with significant postnatal growth restriction and altered
body composition which remain extant until more than 1 year of life. Catch-up growth
and development has been descried well into the teenage years. The developmental
outcome of these infants far exceeds the expectations based on the number of neurologic
risk factors (including malnutrition) they encounter. A reasonable hypothesis is that the
expected developmental sequelae of this “extrauterine growth restriction” is reversed
postnatally with catch-up growth. Although it would be preferable never to have had a
nutritional deficit in the first place, it is clear that recovery is entirely possible and, in
fact, likely. Consequently, periods of rapid growth may not only confer a risk factor when
nutrients are deprived, but may also offer a window of opportunity for rapid and
complete repair when nutrients are subsequently provided. Pollitt (1996) notes that there
is evidence for recovery following PEM in all age groups, including fetuses who receive
adequate postnatal nutrition (IUGR), infants malnourished before 2 years of age who
were not supplemented until after 3 years, and infants malnourished postnatally but also
treated before 2 years of age.
A review of the nutrients that affect brain growth and development reveals
striking differences with respect to vulnerability and timing. Deficiencies of certain
nutrients, such as selenium, folate and vitamin A, exert their effects in a very narrow
post-conceptional window. Later supplementation of these nutrients will do little to alter
damage that occurred in the first 12 weeks post-conception. These nutrients play
important roles in neuronal differentiation, cell division, protein synthesis, and neuronal
migration. Other nutrients (e.g., protein, energy, iron, zinc, iodine) play a role throughout
development. Deficiencies of these nutrients at different ages result in variable
neuroanatomic, neurochemical, and neurobehavioral effects. These differences may be
regionalized within the brain, with certain areas being spared at one age and not at
another (deUngria et al., 2000; Erikson et al., 1997). In humans, nutrient deficiencies tend
to cluster and are frequently prolonged, thus exposing vulnerable brain regions to
multiple nutrient deficiencies over time. Only through careful modeling of each nutrient’s
effect on brain development combined with utilization of nutrient-specific assessments
(e.g., if hypomyelination is a distinguishing hallmark of iron deficiency, the effect in a
population could be studied electrophysiologically) (Roncagliolo et al., 1998) will it
become possible to unravel the precise effects of nutrient deficiencies at the various
stages of neurodevelopment.
Future Directions
EPIGENETIC PROCESSES Epigenetic processes are those that alter the mammalian
genome by covalently adding a methyl group to specific genomic sites (CpG sites –
cytosine followed by guanosine). This methylaton of DNA affects numerous events
including DNA repair, gene stability, and gene transcription (Robertson and Jones, 2000).
For example, addition of methyl within promoter regions inhibits genetic transcription.
Several nutrients, such as choline, folate, vitamin B12, methionine, and betaine
are involved in the metabolic pathways which supply methyl groups for all methylation
reactions (Mason, 2003), and reductions in dietary methyl sources can change genetic
expression and subsequent phenotypes (Cooney, Dave, and Wolff, 2002; Waterland and
Jirtle, 2003)
Choline is a key dietary source of methyl-groups, and there is a growing body of
evidence for choline’s role in epigenetic processes and related brain development
(Zeisel, 2004). Choline defiency in human neuroblast cell cultures decreases methylation
of the promoter region of a gene responsible for inhibition of cell proliferation.
Hypomethylation of this gene’s promoter leads to its overexpression and subsequent
reduction in cell proliferation (Niculescu, Yamamuro, and Zeisel, 2004). Choline has also
been shown to alter expression of numerous genes of neuronal precursor cells, several
which are known to be regulated by the methylation of promoter or intron regions
(Niculescu, Craciunescu, and Zeisel, 2005).
Furthermore, epigenetic process (genomic methylation) is a mechanism by which
early maternal care can affect offspring throughout life. In the rat, maternal care affects
the development of the HPA system through epigenetic processes (Weaver et al., 2004).
Although, nutrition has not been examined in the context of such epigenetic processes
which link maternal behavior to offspring development, it will be interesting in future
research to examine the potential role of nutrients required for methylation reactions in
these and other epigenetic processes involved in neurodevelopment.
FETAL ORIGINS HYPOTHESIS According to the fetal origins hypothesis, organisms
adapt to their in utero nutritional environment, and these adaptations have permanent
effects on physiology and metabolism (Barker, 1997). The in utero environment acts as a
“forecast” of the nutritional environment into which the fetus will be born; therefore,
structural, physiological, and metabolic adaptations occur during fetal development to
prepare for this “forecasted” environment (Hales and Barker, 2001). For instance,
newborns born small for gestational age (IUGR) may develop a thrifty phenotype. Fetal
undernutrition leads to physiological and structural adaptations in various tissues and
organs (such as pancreas, liver, and blood vessels) in preparation for a suboptimal
nutrition postnatal environment The initial findings have found associations between
IUGR and coronary heart disease, type 2 diabetes, and hypertension; however, it will be
important to consider brain development as well.
Physiological and metabolic adaptations to undernutrition involve regulatory
hormones of fetal growth, including insulin and growth hormones (Hales and Barker,
2001). These adaptations may alter the availability and utilization of nutrients.
Accordingly, depending on the early environment, differential programming would lead
to different nutrient metabolism throughout life, and therefore, nutrient availability to the
CNS. Thus, it will be important to consider the consequences of fetal programming of
nutrient metabolism on brain development.
COMPLEMENTARY AND SUPPLEMENTARY MEASURES The apparent
permanence of some cognitive impairments in nutrient deficiencies, suggests the need for
additional measures that complement the specific nutrient supplementation. Nutritional
and non-nutritional measures that influence disparate pathways of a specific neurological
process appear attractive for this purpose. For example, simultaneous supplementation of
LCPUFA may correct hypomyelination due to iron deficiency, since both nutrients are
involved in fatty acid metabolism (Rioux, Lindmark, and Hernell, 2006). Similarly,
environmental enrichment may have additive beneficial effects in nutritional deficiency
conditions (Fig 1). However, a thorough understanding of their mechanistic aspects is
necessary for these measures to be successful.
REFERENCES
AGHINI-LOMBARDI, F. A., A. PINCHERA, L. ANTONANGELI, T. RAGO, L.
CHIOVATO, S. BARGAGNA, B. BERTUCELLI, G. FERRETTI, B. SBRANA,
and M. MARCHESCHI, 1995. Mild iodine deficiency during fetal/neonatal life
and neuropsychological impairment in Tuscany. J. Endocrinol. Invest. 18:57-72.
ALGARIN, C., P. PEIRANO, M. GARRIDO, F. PIZARRO, and B. LOZOFF, 2003. Iron
deficiency anemia in infancy: Long-lasting effects on auditory and visual system
functioning. Pediatr Res, 5: 217-223.
AZIZI F., A. SARSHAR, M. NAFARABADI, A. GHAZI, M. KIMIAGAR, S. NOOHI,
N. RAHBAR, A. BAHRAMI, and S. KALANTARI, 1993. Impairment of
neuromotor and cognitive development in iodine-deficient schoolchildren with
normal physical growth. Acta Endocrinol. (Copenh.) 129:497-500.
BARKER, D. J. P., 1997. The long-term outcome of retarded fetal growth. Clinical
Obstetrics and Gynecology, 40: 853-863.
BASS, N. H., M. G. NETSKY, and E. YOUNG, 1970. Effects of neonatal malnutrition
on developing cerebrum. I. Microchemical and histologic study of cellular
differentiation in the rat. Arch. Neurol. 23:289-302.
BEARD, J. L., AND J. R. CONNOR, 2003. Iron status and neural functioning. Annual
Review of Nutrition, 23: 41-58.
BEARD, J. L., B. FELT, T. SCHALLERT, M. BURHANS, J. R. CONNOR, and M. K.
GEORGIEFF, 2006. Moderate iron deficiency in infancy: Biology and behavior
in young rats. Behavioural Brain Research, 170: 224-232.
BIRCH, E. E., D. G. BIRCH, D. R. HOFFMAN, and R. UAUY, 1992. Dietary essential
fatty acid supply and visual acuity development. Invest. Ophthalmol. Vis. Sci.
33:3242-3253.
BLACK, L. S., R. A. DEREGNIER, J. LONG, M. K. GEORGIEFF, and C. A. NELSON
2004. Electrographic imaging of recognition memory in 34-38 week gestation
intrauterine growth restricted newborns. Experimental Neurology, 190: 72-83.
BLACK, M. M. 2003. The evidence linking zinc deficiency with children's cognitive and
motor functioning. J. Nutr., 133: 1473S-1476S.
BLUSZTAJN, J. K. 1998. Choline, a vital amine. Science, 281, 794-795.
BLUSZTAJN, J. K., J. M. CERMAK, T. HOLLER, and D. A. JACKSON, 1998.
Imprinting of hippocampal metabolism of choline by its availability during
gestation: Implications for cholinergic transmission. J Physiology, 92: 199-203.
BRIEFEL, R. R., K. BIALOSTOSKY, J. KENNEDY-STEPHENSON, M. A.
MCDOWELL, R. B. ERVIN, and J. D. WRIGHT, 2000. Zinc intake of the U.S.
population: Findings from the third National Health and Nutrition Examination
Survey, 1988-1994. J. Nutr., 130: 1367S-1373S.
BRUNER, A. B., A. JOFFE, A. K. DUGGAN, J. F. CASELLA, and J. BRANDT, 1996.
Randomized study of cognitive effects of iron supplementation in non-anemic
iron-deficient adolescent girls. Lancet 348:992-996.
BURDEN, M., M. KOSS, and B. LOZOFF, 2004. Neurocognitive differences in 19-yearolds treated for iron deficiency in infancy. Pediatr Res, 55: 279A.
BYRNE, C. D., 2001. Programming other hormones that affect insulin. British Medical
Bulletin, 60: 153-171.
CAMMACK, R., J. M. WRIGGLESWORTH, and H. BAUM, 1990. Iron-dependent
enzymes in mammalian systems. In Iron Transport and Storage, P. Ponka, H. M.
Schulman, and R. C. Woodworth, eds. Boca Raton, Fla.: CRC Press, pp. 18-39.
CAO, X.-Y., X. M. JIANG, Z. H. DOU, M. A. RAKEMAN, M. L. ZHANG, K.
O'DONNELL, T. MA, K. AMETTE, N. DeLONG, and G. R. DeLONG, 1994.
Timing of vulnerability of the brain to iodine deficiency in endemic cretinism. N
Engl J Med, 331: 1739-1744.
CARLSON, S., and S. HOUSE, 1986. Oral and intraperitoneal administration of Nacetylneuraminic acid: effect on rat cerebral and cerebellar N-acetylneuraminic
acid. Journal of Nutrition, 116: 881-886.
CARLSON, S. E., 1997. Long-chain polyunsaturated fatty acid supplementation of
preterm infants. In Developing Brain and Behaviour, J. Dobbing, ed. London:
Academic Press, pp. 41-78.
CARLSON, S. E., S. H. WERKMAN, and E. A. TOLLEY, 1996. The effect of long
chain n-3 fatty acid supplementation on visual acuity and growth of preterm
infants with and without bronchopulmonary dysplasia. Am. J. Clin. Nutr. 63:687697.
CIANFARANI, S., D. GERMANI, L. ROSSI, G. ARGIRO, S. BOEMI, M. LEMON, J.
M. HOLLY and F. BRANCA, 1998. IGF-I and IGF-binding protein-1 are related
to cortisol in human cord blood. Eur J Endocrinol, 138: 524-529.
CLANDININ, M. T., J. E. CHAPPELL, S. LEONG, T. HEIM, P. R. SWYER, and G. W.
CHANCE, 1980. Intrauterine fatty acid accretion rates in human brain:
implications for fatty acid requirements. Early Human Development, 4: 121-129.
COLOMBO, J. P., C. GARCIA-RODENAS, P. R. GUESRY, and J. REY, 2003.
Potential effects of supplementation with amino acids, choline or sialic acid on
cognitive development in young infants. Acta Paediatrica, 92: 42-46.
COLOMBO, J., K. N. KANNASS, D. J. SHADDY, S. KUNDURTHI, J. M.
MAIKRANZ, C. J. ANDERSON, O. M. BLAGA and S. E. CARLSON, 2004.
Maternal DHA and the development of attention in infancy and toddlerhood.
Child Development, 75: 1254-1267.
COONEY, C. A., A. A. DAVE, and G. L. WOLFF, 2002. Maternal methyl supplements
in mice affect epigenetic variation and DNA methylation of offspring. J. Nutr.,
132: 2393S-2400S.
COPP, A. J., and M. BERNFIELD, 1994. Etiology and pathogenesis of human neural
tube defects. Curr. Opin. Pediatr. 6:626-631.
COTI BERTRAND, P., J. R. O'KUSKY, and S. M. INNIS, 2006. Maternal dietary (n-3)
fatty acid deficiency alters neurogenesis in the embryonic rat brain. J. Nutr., 136:
1570-1575.
CRAGG, B. G., 1972. The development of cortical synapses during starvation in the rat.
Brain 95(1): 143-150.
de BENOIST, B., M. ANDERSSON, I. EGLI, B. TAKKOUCHE, and H. ALLEN,
(Eds.), 2004. Iodine status worldwide: WHO global database on iodine
deficiency. Geneva: World Health Organization.
de LEON, M. J., T. McRAE, H. RUSINEK, A. CONVIT, S. De SANTI, C. TARSHISH,
J. GOLOMB, N. VOLKOW, K. DAISLEY, N ORENTREICH, and B.
McEWEN, 1997. Cortisol reduces hippocampal glucose metabolism in normal
elderly, but not in alzheimer's disease. J Clin Endocrinol Metab, 82: 3251-3259.
DELANY, A., and E. CANALIS, 1995. Transcriptional repression of insulin-like growth
factor I by glucocorticoids in rat bone cells. Endocrinology, 136: 4776-4781.
DELUCCHI, C., M. L. PITA, and M. J. FAUS, 1987. Effects of dietary nucleotides on
the fatty acid composition of erythrocyte membrane lipids in term infants. J. Ped.
Gastroenterol. Nutr. 6:568-574.
deREGNIER, R. A., T. W. GUILBERT, M. M. MILLS, and M. K. GEORGIEFF, 1996.
Growth failure and altered body composition are established by one month of age
in infants with bronchopulmonary dysplasia. Journal of Nutrition, 126: 168-175.
DEUNGRIA, M., R. RAO, J. D. WOBKEN, M. LUCIANA, C. A. NELSON, and M. K.
GEORGIEFF, 2000. Perinatal iron deficiency decreases cytochrome c oxidase
activity in selected regions of neonatal rat brain. Pediatr. Res. 48:169-176.
DEWOLF, F., W. B. ROBERTSON, and I. BROSEN, 1975. The ultrastructure of acute
atherosis in hypertensive pregnancy. Am. J. Obstet. Gynecol. 123:164-174.
DOBBING, J., 1990. Vulnerable periods in developing brain. In Brain, Behavior and
Iron in the Infant Diet, J. Dobbing, ed. London: Springer-Verlag, pp. 1-25.
DUNCAN, J., and L. HURLEY, 1978. Thymidine kinase and DNA polymerase activity
in normal and zinc deficient developing rat embryos. Proc. Soc. Exp. Biol. Med.
159:39-43.
ENDO, Y., J. I. NISHIMURA, S. KOBAYASHI, and F. KIMURA, 1997. Long-term
glucocorticoid treatments decrease local cerebral blood flow in the rat
hippocampus, in association with histological damage. Neuroscience, 79: 745752.
ERIKSON, K. M., D. J. PINERO, J. R. CONNOR, and J. L. BEARD, 1997. Regional
brain iron, ferritin and transferring concentrations during iron deficiency and iron
repletion in developing rats. J. Nutr. 127:2030-2038.
FAO/WHO, 2004. Vitamin and mineral requirements in human nutrition. Geneva: WHO
Press.
FELLOWS, R., 1987. 1GF-1 supports and differentiation of fetal rat brain neurons in
serum-free, hormone-free defined medium. Soc. Neurosci. Abstr. 13:1615.
FELT, B., J. BEARD, T. SCHALLERT, J. SHAO, J. W. ALDRIDGE, J.R. CONNOR,
Persistent neurochemical and behavioral abnormalities in adulthood despite early
iron supplementation for perinatal iron deficiency anemia in rats. Brain Behav
Res. in press.
FELT, B. T., and B. LOZOFF, 1996. Brain iron and behavior of rats are not
normalized by treatment of iron deficiency anemia during early development. J.
Nutr. 126: 693-701.
FENZI, G. F., L. F. GIUSTI, and F. AGHINI-LOMBARDI, 1990. Neuropsychological
assessment of schoolchildren from an area of moderate iodine deficiency. J.
Endocrinol. Invest. 13:427-432.
FOWDEN, A. L., and D. J. HILL, 2001. Intra-uterine programming of the endocrine
pancreas. Br Med Bull, 60: 123-142.
FREDERICKSON, C., and G. DANSCHER, 1990. Zinc-containing neurons in
hippocampus and related CNS structures. Prog. Brain Res. 83:71-84.
GEORGIEFF, M. K., J. S. HOFFMAN, G.R. PEREIRA, J. BERNBAUM, and M.
HOFFMAN-WILLIAMSON, 1985. Effect of neonatal caloric deprivation on head
growth and 1-year developmental status in preterm infants. J. Pediatr. 107:581587.
GEORGIEFF, M. K., and B. LOZOFF. Iron deficiency and brain development. Seminars
in Pediatric Neurology, in press.
GEORGIEFF, M. K., M. M. MILLS, L. L. LINDEKE, S. IVERSON, D. E. JOHNSON,
and T. R. THOMPSON, 1989. Changes in nutritional management and outcome
of very-low-birth-weight infants. Am. J. Dis. Child. 143:82-85.
GEVA, R., R. ESHEL, Y. LEITNER, A. F. VALEVSKI, and S. HAREL, 2006.
Neuropsychological outcome of children with intrauterine growth restriction: A 9year prospective study. Pediatrics, 118: 91-100.
GIL, A., M. PITA, A. MARTINEZ, J. A. MOLINA, and F. SANCHEZ MEDINA, 1986.
Effect of dietary nucleotides on the plasma fatty acids in at-term in neonates.
Human Nutr. Clin. Nutr. 40:185-195.
GOLUB, M. S., P. T. TAKEUCHI, C. L. KEEN, M. E. GERSHWIN, A. G.
HENDRICKS, and B. LONNERDAL, 1994. Modulation of behavioral
performance of prepubertal monkeys by moderate dietary zinc deprivation. Am. J.
Clin. Nutr. 60:238-243.
GORMAN, K. S., 1995. Malnutrition and cognitive development: Evidence from
experimental/quasi-experimental studies among the mild-moderately
malnourished. J. Nutr. 125:S2239-S2244.
GOTTLEIB, S. J., F. J. BIASINI, and N. W. BRAY, 1988. Visual recognition memory in
IUGR and normal birthweight infants. Infant Behav. Dev. 11:223-228.
GRANTHAM-MCGREGOR, S. M., P. I. C. LIRA, A. ASHWORTH, S. S. MORRIS,
and A. M. S. ASSUNCAO, 1998. The development of low birth weight term
infants and the effects of the environment in Northeast Brazil. J. Pediatr.132:
661-666.
GRONER, J. A., N. A. HOLTZMAN, E. CHARNEY, and E. D. MELLITS, 1986. A
randomized trial of oral iron on tests of short-term memory and attention span in
young pregnant women. J. Adolesc. Health Care 7:44-48.
GUILARTE, T. R., 1993. Vitamin B6 and cognitive development: recent research
findings from human and animal studies. Nutr. Rev. 51:193-198.
GUNNAR, M. R., and C. A. NELSON, 1994. Event-related potentials in year-old infants:
relations with emotionality and cortisol. Child Development, 65: 80-94.
HALES, C. N., and D. J. P. BARKER, 2001. The thrifty phenotype hypothesis. British
Medical Bulletin, 60: 5-20.
HARVEY, D., J. PRINCE, J. BUNTON, C. PARKINSON, and S. CAMPBELL, 1982.
Abilities of children who were small-for-gestational-age babies. Pediatrics 69:
296-300.
HEFFELFINGER, A. K., and J. W. NEWCOMER, 2001. Glucocorticoid effects on
memory function over the human life span. Development and Psychopathology,
13: 491-513.
HELLAND, I. B., L. SMITH, K. SAAREM, O. D. SAUGSTAD, and C. A. DREVON,
2003. Maternal supplementation with very-long-chain n-3 fatty acids during
pregnancy and lactation augments children's IQ at 4 years of age. Pediatrics, 111:
e39-44.
HESSE, G., 1979. Chronic zinc deficiency alters neuronal function of hippocampal
mossy fibers. Science 205:1005-1007.
HETZEL, B. S., 1987. An overview of the prevention and control of iodine deficiency
disorders. In The Prevention and Control of Iodine Deficiency Disorders, B. S.
Hetzel, J. T. Dunn, and J. B. Standbury, eds. Amsterdam: Elsevier, pp. 7-34.
HETZEL, B. S., and M. T. MANO, 1989. A review of experimental studies of iodine
deficiency during fetal development. J. Nutr. 119:145-151.
HOLMES-MCNARY, M. Q., R. LOY, M. H. MAR, C. D. ALBRIGHT, and S. H.
ZEISEL, 1997. Apoptosis is induced by choline deficiency in fetal brain and in
PC12 cells. Developmental Brain Research, 101: 9-16.
HORNER, H. C., D. R. PACKAN, and R. M. SAPOLSKY, 1990. Glucocorticoids inhibit
glucose transport in cultured hippocampal neurons and glia. Neuroendocrinolgy,
52: 57-64.
INNIS, S. M., 1992. Human milk and formula fatty acids. J. Pediatr. 120:S55-61.
INNIS, S. M., 2003. Perinatal biochemistry and physiology of long-chain
polyunsaturated fatty acids. J. Pediatr.143: S1-8.
JENSEN, C. L., T. C. PRAGER, J. K. FRALEY, H. CHEN, R. E. ANDERSON, and W.
C. HEIRD, 1997. Effects of dietary linoleic/alpha-linolenic acid ratio on growth
and visual function of term infants. J. Pediatr. 131:173-175.
JONES, D. G., and S. E. DYSON, 1981. The influence of protein restriction,
rehabilitation and changing nutritional status on synaptic development: A
quantitative study in rat brain. Brain Res. 208:97-111.
JORGENSON, L. A., M. SUN, M. O'CONNOR, and M. K. GEORGIEFF, 2005. Fetal
iron deficiency disrupts the maturation of synaptic function and efficacy in area
CA1 of the developing rat hippocampus. Hippocampus, 15: 1094-1102.
JORGENSON, L. A., J. D. WOBKEN, and M. K. GEORGIEFF, 2003. Perinatal iron
deficiency alters apical dendritic growth in hippocampal CA-1 pyramidal neurons.
Dev Neurosci, 25: 412-420.
KIM, M., Z. X. YU, B. B. FREDHOLM, and S. A. RIVKEES, 2005. Susceptibility of the
developing brain to acute hypoglycemia involving A1 adenosine receptor
activation. Am J Physiol Endocrinol Metab, 289: E562-569.
KRETCHMER, N., J. L. BEARD, and S. CARLSON, 1996. The role of nutrition in the
development of normal cognition. Am. J. Clin. Nutr. 63:997S-1001S.
KUNZ, C., S. RUDOLF, W. BAIER, N. KLEIN, and S. STROBE, 2000.
Oligosaccharides in human milk: structural, functional and metabolic aspects.
Annu Rev Nutr 20: 699-722.
KWIK-URIBE, C. L., D. GIETZEN, J. B. GERMAN, M. S. GOLUB, and C. L. KEEN,
2000. Chronic marginal iron intakes during early development in mice result in
persistent changes in dopamine metabolism and myelin composition. J. Nutr.,
130: 2821-2830.
LARKIN, E. C., B. A. JARRATT, and G. A. RAO, 1986. Reduction of relative levels of
nervonic to lignoceric acid in the brain of rat pups due to iron deficiency. Nutr.
Res. 6:309-314.
LARKIN, E. C., and G. A. RAO, 1990. Importance of fetal and neonatal iron: Adequacy
for normal development of central nervous system. In Brain, Behavior and Iron in
the Infant Diet, J. Dobbing, ed. London: Springer-Verlag, London, pp. 43-62.
LEE, K.-H., A. KALIKOGLU, P. YE, and A. J. D’ERCOLE, 1999. Insulin-like growth
factor-1 (1GF-1) ameliorates and 1GF binding protein-1 (1GFBP-1) exacerbates
the effects of undernutrition on brain growth during early postnatal life: Studies in
1GF-1 and 1GFBP-1 transgenic mice. Pediatr. Res. 45:331-336.
LEVANT, B., J. D. RADEL, and S. E. CARLSON, 2004. Decreased brain
docosahexaenoic acid during development alters dopamine-related behaviors in
adult rats that are differentially affected by dietary remediation. Behavioural
Brain Research, 152: 49-57.
LI, M., H. ROSENBERG, and T. CHIU, 1994. Zinc inhibition of GABA-stimulated Clflux in rat brain regions is unaffected by acute or chronic benzodiazepine.
Pharmacol. Biochem. Behav. 49:477-482.
LIN, H.J., C. C. HUANG, and K. S. Hsu, 2006. Effects of neonatal dexamethasone
treatment on hippocampal synaptic function. Annals of Neurology, 59: 939-951.
LOW, J. A., and R. S. GALBRAITH, 1974. Pregnancy characteristics of intrauterine
growth retardation. Obstet. Gynecol. 44:122-126.
LOW, J. A., R. S. GALBRAITH, D. MUIR, H. KILLEN, B. PATER, and J.
KARCHMAR, 1982. Intrauterine growth retardation: A study of long-term
morbidity. Am. J. Obstet. Gynecol. 142:670-677.
LOZOFF, B., 1990. Has iron deficiency been shown to cause altered behavior in infants?
In Brain, Behavior and Iron in the Infant Diet, J. Dobbing, ed. London: SpringerVerlag, pp. 107-131.
LOZOFF, B., J. L. BEARD, J. R. CONNOR, B. T. FELT, M. K. GEORGIEFF, and T.
SCHALLERT, 2006. Long-lasting neural and behavioral effects of iron
deficiency in infancy. Nutr Rev, 64: S34-S43.
LOZOFF, B., G. M. BRITTENHAM, F. E. VITERI, A. W. WOLF, and J. J. URRUTIA,
1982. The effects of short-term oral iron therapy on developmental deficits in
iron-deficient anemic infants. J. Pediatr. 100:351-357.
LOZOFF, B., G. M. BRITTEHAM, A. W. WOLF, D. K. MCCLISH, P. M. KUHNERT,
E. JIMENEZ, L. A. MORA, I. GOMEZ, and D. KRAUSKOPH, 1987. Irondeficiency anemia and iron therapy: Effects on infant developmental test
performance. Pediatrics 79:981-995.
LOZOFF, B., and M. K. GEORGIEFF. Iron deficiency and brain development. Seminars
in Pediatric Neurology, in press.
LOZOFF, B., E. JIMENEZ, J. HAGEN, E. MOLLEN, and A. W. WOLF, 2000. Poorer
behavioral and developmental outcome more than 10 years after treatment for
iron deficiency in infancy. Pediatrics, 105: e51.
LOZOFF, B., N. KLEIN, E. NELSON, D. McCLISH, M. MANUEL, and M. CHACON,
1998. Behavior of infants with iron-deficiency anemia. Child development, 69:
24-36.
LUCAS, A., 1997. Long-chain polyunsaturated fatty acids, infant feeding and cognitive
development. In Developing Brain and Behaviour, J. Dobbing, ed. London:
Academic Press, pp. 3-27.
MACLEAN, W. C., JR., and J. D. BENSON, 1989. Theory into practice: The
incorporation of new knowledge into infant formula. Sem. Perinatol. 13:104-111.
MANGELSDORF, D. J., 1994. Vitamin A receptors. Nutr. Rev. 52:S32-S37.
MASON, J. B., 2003. Biomarkers of nutrient exposure and status in one-carbon (methyl)
metabolism. J. Nutr., 133: 941S-947S.
MCMORRIS, F. A., and M. DUBOIS-DALCQ, 1988. Insulin-like growth factor 1
promotes cell proliferation and oligodendroglial commitment in rat glial
progenitor cells developing in vitro. J. Neurosci. Res. 21:199-209.
MCNALL, A., T. ETHERTON, and G. FOSMIRE, 1995. The impaired growth induced
by zinc deficiency in rats is associated with decreased expression of hepatic
insulin-like growth factor 1 and growth hormone receptor genes. J. Nutr. 124:874879.
MECK, W. H., and C. L. WILLIAMS, 1999. Choline supplementation during prenatal
development reduces proactive interference in spatial memory. Developmental
Brain Research, 118: 51-59.
MECK, W. H., and C. L. WILLIAMS, 2003. Metabolic imprinting of choline by its
availability during gestation: Implications for memory and attentional processing
across the lifespan. Neuroscience and Biobehavioral Reviews, 27: 385-399.
MITCHELL, J. H., F. NICOL, G. J. BECKETT, and J. R. ARTHUR, 1998.
Selenoprotein expression and brain development in preweanling selenium and
iodine deficient rats. J. Mol. Endocrinol. 20:203-210.
MORGANE, P. J., R. AUSTIN-LAFRANCE, J. BRONZINO, J. TONKISS, S. DIAZCINTRA, L. CINTRA, T. KEMPER, and J. R. GALLER, 1993. Prenatal
malnutrition and development of the brain. Neurosci. Biobehav. Rev. 17:91-128.
MORROW-TLUCAK, M., R. H. HAUDE, and C. B. ERNHART, 1988. Breastfeeding
and cognitive development in the first 2 years of life. Soc. Sci. Med. 26:625-639.
NEURINGER, M., W. E. CONNOR, D. S. LIN, L. BARSTAD, and S. LUCK, 1986.
Biochemical and functional effects of prenatal and postnatal omega-3-fatty acid
deficiency on retina and brain in rhesus monkeys. Proc. Natl. Acad. Sci. USA 83:
4021-4025.
NICULESCU, M. D., C. N. CRACIUNESCU, and S. H. ZEISEL, 2005. Gene expression
profiling of choline-deprived neural precursor cells isolated from mouse brain.
Molecular Brain Research, 134: 309-322.
NICULESCU, M. D., Y. YAMAMURO, and S. H. ZEISEL, 2004. Choline availability
modulates human neuroblastoma cell proliferation and alters the methylation of
the promoter region of the cyclin-dependent kinase inhibitor 3 gene. Journal of
Neurochemistry, 89: 1252-1259.
NISHIJIMA, M., 1986. Somatomedin-C as a fetal growth promoting factor and amino
acid composition of cord blood in Japanese neonates. J. Perinatol. Med. 14:163166.
NOKES, C., C. VAN DEN BOSCH, and D. A. P. BUNDY, 1998. Infants and young
children (6-24 months). In A Report of the International Anemia Consulative
Group: The Effects of Iron Deficiency and Anemia on Mental and Motor
Performance, Educational Achievement and Behavior in Children. An Annotated
Bibliography. Washington, D. C., pp. 7-22.
O'DONNELL, K., M. A. RAKEMAN, D. ZHI-HONG, C. XUE-YI, Z. Y. MEI, N.
DeLONG, G. BRENNER, M. TAI, W. DONG and G. R. DeLONG, 2002. Effects
of iodine supplementation during pregnancy on child growth and development at
school age. Developmental Medicine and Child Neurology, 44: 76-81.
ORTIZ, E., J. M. PASQUINI, K. THOMPSON, B. FELT, G. BUTKUS, J. BEARD, and
J. R. CONNOR, 2004. Effect of manipulation of iron storage, transport, or
availability on myelin composition and brain iron content in three different animal
models. Journal of Neuroscience Research, 77: 681-689.
PINERO, D. J., B. C. JONES, and J. L. BEARD, 2001. Variations in dietary iron alter
behavior in developing rats. J. Nutr., 131: 311-318.
PLEASURE, J., and D. PLEASURE, 2003. Trophic factor, and nutritional and hormonal
regulation of brain development. In Fetal and Neonatal Physiology, R. A. Polin,
W. W. Fox, and S. H. Abman, eds. Philadelphia: W. B. Saunders, pp. 1785-1792.
POLLITT, E., 1996. Timing and vulnerability in research on malnutrition and cognition.
Nutr. Rev. 54:S49-S55.
POLLITT, E., and K. S. GORMAN, 1994. Nutritional deficiencies as developmental risk
factors. In Threats to Optimal Development. The Minnesota Symposia on Child
Psychology, Vol. 27, C. A. Nelson, ed. Hillsdale, N.J.: Erlbaum Associates, pp.
121-144.
POLLITT, E., K. S. GORMAN, P. L. ENGLE, R. MARTORELL, and J. RIVERA, 1993.
Early supplementary feeding and cognition: Effects over two decades. Monogr.
Soc. Res. Child Dev. 58:1-99.
POLLITT, E., K. S. GORMAN, P. L. ENGLE, J. A. RIVERA, and R. MARTORELL,
1995. Nutrition in early life and the fulfillment of intellectual potential. J. Nutr.
125:S1111-S1118.
POLLITT, E., W. E. WATKINS, and M. A. HUSAINI, 1997. Three-month nutritional
supplementation in Indonesian infants and toddlers benefits memory function 8 Y
later. Am. J. Clin. Nutr. 66:1357-1363.
PYAPALI, G. K., D. A. TURNER, C. L. WILLIAMS, W. H. MECK, and H. S.
SWARTZWELDER, 1998. Prenatal dietary choline supplementation decreases
the threshold for induction of long-term potentiation in young adult rats. J
Neurophysiol, 79: 1790-1796.
RAMAN, L., M. K. GEORGIEFF, and R. RAO, 2006. The role of chronic hypoxia in the
development of neurocognitive abnormalities in preterm infants with
bronchopulmonary dysplasia. Developmental Science, 9: 359-367.
RAO, R., M. DEUNGRIA, D. SULLIVAN, P. WU, J. D. WOBKEN, C. A. NELSON,
and M. K. GEORGIEFF, 1999. Perinatal brain iron deficiency increases the
vulnerability of rat hippocampus to hypoxic ischemic insult. J. Nutr. 129:199-206.
RAO, R., I. TKAC, E. L. TOWNSEND, R. GRUETTER, and M. K. GEORGIEFF, 2003.
Perinatal iron deficiency alters the neurochemical profile of the developing rat
hippocampus. J. Nutr., 133: 3215-3221.
RIOUX, F. M., G. LINDMARK, and O. HERNELL, 2006. Does inadequate maternal
iron or DHA status have a negative impact on an infant's functional outcomes?
Acta Paediatrica, 95: 137-144.
ROBERTSON, K. D., and P. A. JONES, 2000. DNA methylation: past, present and
future directions. Carcinogenesis, 21: 461-467.
RONCAGLIOLO, M., M. GARRIDO, T. WALTER, P. PEIRANO, and B. LOZOFF,
1998. Evidence of altered central nervous system development in infants with iron
deficiency anemia at 6 mo: Delayed maturation of auditory brainstem responses.
Am. J. Clin. Nutr. 68:683-690.
SANDSTEAD, H. H., 1985. Zinc: Essentiality for brain development and function. Nutr.
Rev. 43:129-137.
SANDSTEAD, H. H., J. G. PENLAND, N. W. ALCOCK, and H. H. DAYAL, 1998.
Effects of repletion with zinc and other micronutrients on neuropsychologic
performance and growth of Chinese children. Am. J. Clin. Nutr. 68:470S-475S.
SANETO, R. P., K. G. LOW, M. H. MELNER, and J. DE VELLIS, 1988. Insulin/insulinlike growth factor 1 and other epigenetic modulators of myelin basic protein
expression in isolated oligodendrocyte progenitor cells. J. Neurosci. Res. 21:210219.
SIDDAPPA, A. M., M. K. GEORGIEFF, S. WEWERKA, C. WORWA, C. A. NELSON,
and R. A. DEREGNIER, 2004. Iron deficiency alters auditory recognition
memory in newborn infants of diabetic mothers. Pediatr Res, 55: 1034-1041.
SKINNER, J. D., B. R. CARRUTH, K. S. HOUCK, F. COLETTA, R. COTTER, D.
OTT, and M. McLEOD, 1997. Longitudinal study of nutrient and food intakes of
infants aged 2 to 24 months. Journal of the American Dietetic Association, 97:
496-504.
SMITH, C. D., and K. B. AIN, 1995. Brain metabolism in hypothyroidism studied with
31
P magnetic-resonance spectroscopy. Lancet 345:619-620.
SPINILLO, A., M. STRONATI, A. OMETTO, E. FAZZI, G. LANZI, and S.
GUASCHINO, 1993. Infant neurodevelopmental outcome in pregnancies
complicated by gestational hypertension and intrauterine growth retardation. J.
Perinatol. Med. 21:195-203.
STEIN, Z., and M. SUSSER, 1985. Effects of early nutrition on neurological and mental
competence in human beings. Psychol. Med. 15:717-726.
STRAUSS, R. S., and W. H. DIETZ, 1998. Growth and development of term children
born with low birth weight: Effects of genetic and environmental factors. J.
Pediatr. 133:67-72.
SWOLIN, D., C. BRANTSING, G. MATEJKA, and C. OHLSSON, 1996. Cortisol
decreases IGF-I mRNA levels in human osteoblast-like cells. J Endocrinol, 149:
397-403.
TEJWANI, G., and S. HANISSIAN, 1990. Modulation of mu, delta and kappa opioid
receptors in rat brain by metal ions and histidine. Neuropharmacology 29:445452.
TERHUNE, M. W., and H. H. SANDSTEAD, 1972. Decreased RNA polymerase activity
in mammalian zinc deficiency. Science 177:68-69.
THELANDER, L., 1990. Ribonucleotide reductase. In Iron Transport and Storage, P.
Ponka, H. M. Schulman, and R. C. Woodworth, eds. Boca Raton, Fla.: CRC
Press, pp. 193-200.
TOLSA, C. B., S. ZIMINE, S. K. WARFIELD, M. FRESCHI, A. SANCHO
ROSSIGNOL, F. LAZEYRAS, S. HANQUINET, M. PFIZENMAIER and P. S.
HUPPI, 2004. Early alteration of structural and functional brain development in
premature infants born with intrauterine growth restriction. Pediatr Res, 56: 132138.
UAUY, R. D., D. G. BIRCH, E. E. BIRCH, J. E. TYSON, and D. R. HOFFMAN, 1990.
Effect of dietary omega-3 fatty acids on retinal function of very-low-birth-weight
neonates. Pediatr. Res. 28:485-492.
UAUY-DAGACH, R., and P. MENA, 1995. Nutritional role of omega-3 fatty acids
during the perinatal period. Clin. Perinatol. 22:157-176.
VOLPE, J. J., 1995. Hypoglycemia and brain injury. In Neurology of the Newborn, 3rd
ed., J. J. Volpe, ed. Philadelphia: W. B. Saunders, pp. 467-489.
WALTER, T., J. KOWALSKYS, and A. STEKEL, 1983. Effect of mild iron deficiency
on infant mental developmental scores. J. Pediatr. 102:519-522.
WANG, B., and J. BRAND-MILLER, 2003. The role and potential of sialic acid in
human nutrition. European Journal of Clinical Nutrition, 57: 1351-1369.
WANG, B., P. MCVEAGH, P. PETOCZ, and J. BRAND-MILLER, 2003. Brain
ganglioside and glycoprotein sialic acid in breastfed compared with formula-fed
infants. Am J Clin Nutr, 78: 1024-1029.
WANG, Y. S. and S. Y. WU, 1996. The effect of exclusive breast-feeding on
development and incidence of infection in infants. J. Hum. Lactation 12:27-30.
WATANABE, C., and H. SATOH, 1994. Brain selenium status and behavioral
development in selenium-deficient preweanling mice. Physiol. Behav. 56:927932.
WATERLAND, R. A., and R. L. JIRTLE, 2003. Transposable elements: targets for early
nutritional effects on epigenetic gene regulation. Mol. Cell. Biol., 23: 5293-5300.
WEAVER, I. C., N. CERVONI, F. A. CHAMPAGNE, A. C. D. ALESSIO, S.
SHARMA, J. R. SECKL, S. DYMOV, M. SZYF, and M. J. MEANEY, (2004).
Epigenetic programming by maternal behavior. Nature Neuroscience, 7: 847-854.
WIGGINS, R. C., G. FULLER, and S. J. ENNA, 1984. Undernutrition and the
development of brain neurotransmitter systems. Life Sci. 35:2085-2094.
WINER, E. K., and N. TEJANI, 1994. Four- to seven-year evaluation in two groups of
small-for-gestational-age infants. In Obstetrical Events and Developmental
Sequelae, 2nd ed., N. Tejani, ed. Boca Raton, Fla.: CRC Press, pp. 77-94.
WINICK, M., and A. NOBEL, 1966. Cellular responses in rats during malnutrition at
various ages. J. Nutr. 89:300-306.
WINICK, M., and P. ROSSO, 1969a. Head circumference and cellular growth of the
brain in normal and marasmic children. J. Pediatr. 74:774-778.
WINICK, M., and P. ROSSO, 1969b. The effect of severe early malnutrition on cellular
growth of the human brain. Pediatr. Res. 3:181-184.
YAMADA, K. A., N. RENSING, Y. IZUMI, G. A. De ERAUSQUIN, V. GAZIT, D. A.
DORSEY, and D. G. HERRERA, 2004. Repetitive hypoglycemia in young rats
impairs hippocampal long-term potentiation. Pediatr Res, 55: 372-379.
YAMAMOTO, N., M. SAITOH, A. MORIUCHI, M. NOMURA, and H. OKUYAMA,
1987. Effect of dietary alpha-linolenate/linoleate balance on brain lipid
compositions and learning ability of rats. J. Lipid Res. 28:144-151.
YOUDIM, M. B. H., D. BEN-SACHAR, and S. YEHUDA, 1989. Putative biological
mechanisms of the effect of iron deficiency on brain biochemistry and behavior.
Am. J. Clin. Nutr. 50:607-612.
ZEISEL, S. H., 2004. Nutritional importance of choline for brain development. Journal
of the American College of Nutrition, 23: 621S-626S.
ZIMMERMANN, M. B., K. CONNOLLY, M. BOZO, J. BRIDSON, F. ROHNER, and
L. GRIMCI, 2006. Iodine supplementation improves cognition in iodine-deficient
schoolchildren in Albania: a randomized, controlled, double-blind study. Am J
Clin Nutr, 83: 108-114.
NUTRIENT
Protein-energy
Iron
Zinc
EFFECT OF DEFICIT
(1) ↓ Total DNA, RNA, protein
content
(2) ↓ mRNA for neuronal, glial
proteins
↓ Neurotransmitter production
↓ Altered fatty acid profile
↓ Growth factor synthesis
(3) ↓ Synapse number
↓ Myelin
↓ Brain-weight
(4) ↓ IQ
↓ Bender-Gestalt scores
Weak visual recognition memory
Weak verbal ability/reduced
vocabulary
Decreased speed of processing
(1) ↓ Brain DNA, RNA protein
content
↓ Ribonucleotide reductase
activity
(2) ↓ Tyrosine hydroxylase
activity
↓ Cytochrome c and c oxidase
activity
↓ Delta-9 desaturase activity
(3) ↓ Dopamine activity
↓ Neuronal oxidative metabolism
↓ Myelination
(4) ↓ Bayley MDI
↓ Bayley PDI
↓ Spontaneous movement
Delayed latency on evoked
responses
↓ Spatial working memory
↓ Memory and learning
(1) ↓ DNA, RNA, and protein
content
↓ Cell replication
(2) ↓ IGF-I activity
↓ Synaptic Zn release
Altered neurotransmitter receptor
binding
(3) Truncated dendritic
arborization
TARGETED BRAIN REGION
Whole brain
Cerebellar cortex
Cerebral cortex
Hippocampus
Variable, based on age of insult
(see text for details)
Hippocampus targeted at young
ages
Cerebellum, limbic system,
cerebral cortex
Many effects are
neurochemical/neurophysiological,
given their reversibility with
treatment
IodineC
Selenium‡
Choline
Reduced regional brain mass
↓ Inhibition of GABA
↓ Binding to receptors
(4) ↓ Spontaneous motor activity
↓ Short-term visual memory
↓ Concept formation and abstract
reasoning
(1) ↓ Brain DNA, stable
protein:DNA ratio
↓ Membrane signaling proteins
↓ mRNA for microtubule proteins
↓ Binding of gene promoter
regions for stem cell
differentiation
(2) Abnormal fatty acid synthesis
↓ Axonal and dendritic
microtubule protein
↓ Neuronal oxidative metabolism
(3) ↓ Brain weight
↓ Dendritic arborization
Migration defects
↓ Neuropil
Hypomyelination
(4) ↓ Verbal IQ
↓ Subset coding ability (WISC-R)
Motor impairment (reaction time)
Spastic diplegia
Mental retardation
(1) Down-regulation of myelin
genes in oligodendrocytes
(2) Biochemical findings of
hypothyroidism (see iodine
deficiency)
(3) Increased dopamine turnover
Hypomyelination (↓ myelin
basic protein)
(4) ↓ Thermoregulation
Impaired motor ability
(1) ↑ Apoptosis
↓ Transmethylation reactions
(2) ↓ decreased acetylcholine
concentrations.
(4) Impaired memory & attention
All areas, but primarily cerebellar
cortex, prefrontal cortex, and
hippocampus
Hippocampus
Table 1. Selected nutrient effects on cognitive development at the (1) molecular, (2)
biochemical, (3) structural, and (4) behavioral level*
*The model portrayed is based on integrated human and animal behavioral, histological,
and cell culture data.
C
Iodine’s effect on the CNS is strictly through its role in thyroid hormone, not elemental
iodine deficiency.
‡ Selenium’s primary effects are through interaction with iodine and thyroid status.
Growth factors
Inborn Errors of Metabolism
Genetic Factors
Brain microarchitecture
Nutrients
Developing
Brain
Environmental
Enrichment
MaternalInfant bonding
Figure Legend
The role of nutrition in the developing brain. Genetic factors, nutrients and environmental
factors play major roles in neurodevelopment. In addition to their direct involvements
(thin arrows) in neurological processes such as myelination, cell proliferation,
synaptogenesis and neurotransmission, these factors interact with each other (thick
arrows) in shaping the developing brain. Curved arrows indicate interaction within a
major group (e.g. nutrient-nutrient interaction).