Chapter 3 Trisomy 21

Chapter 3 Trisomy 21

C H A P T E R T H R E E Trisomy 21: Causes and Consequences Jeannie Visootsak and Stephanie L. Sherman Contents 61 64 1. Introduction 2. Major Caus...

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C H A P T E R

T H R E E

Trisomy 21: Causes and Consequences Jeannie Visootsak and Stephanie L. Sherman Contents 61 64

1. Introduction 2. Major Cause of DS: Meiotic Nondisjunction in Oocytes 3. Prevalence and Survival of Individuals with DS Throughout the Life Span 4. Etiology of DS-Associated Medical Disorders 5. Neurodevelopmental Outcomes of Comorbid Medical Conditions in DS 6. Psychiatric and Neurobehavioral Issues in DS 7. Summary Acknowledgments References

72 77 82 87 89 90 90

Abstract Trisomy 21, leading to Down syndrome (DS), is the most common genetic cause of mental retardation, specific birth defects, and medical conditions. Clinical and epidemiological studies over the last 100 years have been primarily focused on infants with DS to determine the prevalence, cause, and clinical significance of the syndrome. Studies to understand the consequence of trisomy 21 with respect to the variability of specific DS-associated medical conditions and to determine how these conditions influence cognitive and behavioral outcomes are only just beginning. Here, we provide an overview of current clinical and epidemiological research that characterizes the causes of trisomy 21 and its medical consequences.

1. Introduction In this review, we will describe epidemiological approaches to understand the causes and consequences of trisomy 21, the genetic condition leading to Down syndrome (DS). To be clear, epidemiology and genetic

Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia 30033 International Review of Research in Mental Retardation, Volume 36 ISSN 0074-7750, DOI: 10.1016/S0074-7750(08)00003-7

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2008 Elsevier Inc. All rights reserved.

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epidemiology provide approaches to study the patterns and causes of healthrelated traits in defined populations, with the latter paying specific attention to potential susceptibility genes and their interaction with environmental factors. Results from such studies form a foundation for interventional medicine. These types of clinical research studies are done best in parallel with basic science approaches that use experimental model systems to uncover underlying mechanisms that cause susceptibility. Although we will not review such studies here, they show tremendous promise to delineate the biological alterations that result from the extra dosage of chromosome 21 genes (for an example of a recent review, see Reeves & Garner, 2007). For DS, observational studies began in the mid-1800s when several astute physicians described groups of patients who had mental retardation and short stature along with specific facial characteristics including upslanting palpebral fissures, epicanthal folds, flat nasal bridge, and protruding tongue (Down, 1866; Esquirol, 1838; Se´guin, 1846, 1856). J. Langdon Down, after whom DS was named, contributed significantly to the progress of the study of DS by emphasizing that this set of clinical findings constituted a distinct entity, and affected individuals could be distinguished from the heterogeneous group of all those with intellectual disabilities. In an excellent review of the history of DS, Rynders and Pueschel (1982) continued the story of the recognition of DS through the late 1800s and early 1900s. Once DS was recognized as a separate medical condition, it became possible to identify determinants that play a role in its occurrence. The first to be linked to DS was increased parental age at the birth of the infant with DS (e.g., Thurston & Jenkins, 1931; Van der Scheer, 1927). Shortly thereafter, Penrose demonstrated clearly that advanced maternal age, not paternal age or birth order, was the key determining factor for DS (Penrose, 1933, 1934). In 1954, Penrose further suggested that there could be different causes of DS: he observed that approximately one-third of cases in his series were not associated with maternal age (Penrose, 1954). Further, in families with two affected siblings, the mean maternal age was lower compared to the general sample of infants with DS. With remarkable insight, he posited several plausible causes of DS: genetic susceptibility, unbalanced chromosomes caused by translocation, and factors associated with fluctuating endocrine disturbance. The next major advance in DS, and in fact human medical genetics as a whole, came with the advent of chromosome staining and karyotyping, leading to the ability to characterize the human chromosome complement. With this technological advance, the etiology of DS was identified in 1959 as the presence of an extra chromosome 21 (Book et al., 1959; Ford et al., 1959; Jacobs et al., 1959; Lejeune, 1959). More recent studies have shown that 95% of individuals with DS have an extra chromosome 21 as a result of meiotic nondisjunction, or the abnormal segregation of chromosomes

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Meiosis I error

Meiosis II error

Homologs don’t separate

“Meiosis II” error

Homologs don’t separate

Sisters chromatids don’t separate

Sisters chromatids don’t separate

Figure 3.1 Illustration of the types of meiotic chromosomal nondisjunction errors in females. Only 1 of the 23 pairs of homologous chromosomes is shown for simplification. ‘‘MII’’ refers to meiosis [MII] errors that might be initiated in MI.

during gamete formation (Fig. 3.1). Of the remaining 5%, less than 1% is due to somatic mosaicism and the rest to chromosome 21 translocations. Interestingly, in 1964, Penrose proposed that the maternal age–dependent cases of DS could be due to meiotic nondisjunction, but succinctly stated that ‘‘The traditional explanation that the ovum becomes abnormal with age is unhelpful unless some attempt is made to link the supposed deterioration with the observed distribution curve.’’ (i.e., observed maternal age pattern) (Penrose, 1964). In summary, by the early 1960s, the syndrome hallmarks were described, the cytogenetic causes identified, and the most significant risk factor determined, namely, maternal age. DS, or trisomy 21, is now one of the most widely studied human aneuploid conditions. It is estimated that about 80% of conceptuses with an extra chromosome 21 are spontaneously lost during gestation, while some 20% are carried to term. In contrast, trisomies of other chromosomes seldom survive through gestation (for review, see Hassold & Hunt, 2001). More importantly, once medical complications at birth are appropriately treated, individuals with DS can live, on average, into their 50s or 60s, with full and productive lives if important educational, medical, and societal resources are provided. This review will survey the current field to focus attention on gaps in research. Thus, we will omit a large body of significant literature that truly pushed the field ahead to allow advances in technology and resources to make their mark. First, we will review the progress that has been made to

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understand the leading cause of trisomy 21, namely, meiotic nondisjunction. Next, we will review the aspects of mortality and morbidity among individuals with DS. We will show that the previous focus on the prevalence and survival of individuals with DS around birth has shifted to that in adults due to the significantly increased survival of individuals with DS over the years. We will outline some of the medical conditions that are prevalent among individuals with DS and finally discuss their influence on cognition, behavior, and mental health.

2. Major Cause of DS: Meiotic Nondisjunction in Oocytes As emphasized by Penrose in the early 1900s, the ability to identify the biological mechanisms and associated risk factors for trisomy 21 has benefited from studies that focus on a specific type of error. Soon after the chromosomal basis of DS became known in 1959, cytogenetic techniques allowed investigators to distinguish the underlying types of chromosome errors: (1) standard trisomy 21, (2) chromosome translocations, and (3) mosaicism (one normal cell line and one trisomic cell line). The use of chromosome heteromorphisms and DNA polymorphisms led to the ability to categorize chromosome 21 nondisjunction errors by parental origin (e.g., whether the error occurred in egg [‘‘maternal’’] or sperm [‘‘paternal’’]) and type of error (e.g., whether the error was initiated in meiosis I [MI] or meiosis II [MII] [Fig. 3.1] or postzygotic mitotic). To date, the largest study to categorize these nondisjunctional errors is the National Down Syndrome Project (NDSP), a population-based study conducted from 2000 to 2005 at six national sites representing 11% of annual births in the United States (Freeman et al., 2007). Through this population-based study, 907 infants born with DS were characterized based on the type of chromosome error. For a comparison group to examine risk factors for nondisjunction, 977 infants born without DS drawn from the same geographical areas were enrolled. Based on results from the NDSP (Table 3.1) and other population-based series (e.g., Gomez et al., 2000; Mikkelsen et al., 1995), over 90% of nondisjunction errors leading to trisomy 21 occur in the oocyte and the majority of those occur during MI. This pattern is similar to other trisomies due to chromosome nondisjunction (e.g., Hassold & Hunt, 2001). To date, most studies have focused on searching for risk factors related to maternal nondisjunction of chromosome 21 due to its frequent occurrence. We will do the same here in our review. A recent review provides an overview of our limited knowledge of paternal nondisjunction and its associated risk factors (Sherman et al., 2005).

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Table 3.1 Origin of trisomy 21 Origin

Maternal Meiosis I (MI) Meiosis II (MII) Stage unknowna Subtotal Paternal Meiosis I (PI) Meiosis II (PII) Stage unknowna Subtotal Postzygotic mitotic Total informative cases (all)

N

Proportion

Percent

529 179 21 729

MI/(MI þ MII) ¼ 529/708 MII/(MI þ MII) ¼ 179/708

74.7 25.3

M/All ¼ 729/782

93.2

PI/(PI þ PII) ¼ 13/31 PII/(PI þ PII) ¼ 18/31

41.9 58.1

P/all ¼ 32/782 Mitotics/All ¼ 21/782

4.1 2.7

13 18 1 32 21 782

Stage unknown ¼ DNA markers in the centromeric region were not informative. Data taken from Freeman et al. (2007).

a

2.1. Advanced maternal age Advanced maternal age is possibly, by far, the most significant factor related to chromosome 21 nondisjunction. We and others have shown that the increased age of the mother at conception exerts its influence on chromosome segregation in the egg (Sherman et al., 2005; e.g., Antonarakis et al., 1992; Ballesta et al., 1999; Muller et al., 2000). That is, advanced maternal age is not observed among mothers whose offspring received the extra chromosome 21 from a nonmaternal source. Mothers of offspring with a nondisjunction error in spermatogenesis (paternal error) do not have an increased age (Petersen et al., 1993; Sherman et al., 2005; Yoon et al., 1996). Similarly, advanced maternal age is not present among women with an offspring with DS due to a postzygotic mitotic error (e.g., Antonarakis et al., 1993; Sherman et al., 2005) or a chromosome translocation (inherited or de novo) (Hook, 1983). Interestingly, advanced maternal age is a risk factor for both MI and MII maternal nondisjunction errors (e.g., Antonarakis et al., 1992; Muller et al., 2000; Sherman et al., 2005; Yoon et al., 1996). The timeline for oogenesis compared with spermatogenesis points to possible error-prone stages of egg formation. Meiosis is initiated in oocytes during fetal life around 12 weeks of gestation. After homologous chromosomes synapse and initiate recombination, meiosis arrests and remains in this state until the oocyte is recruited for ovulation. Thus, MI spans some 10–50 years depending on when that specific oocyte is ovulated. MII only extends over the 3- to 4-day ovulation period and is completed after fertilization. This timeline differs significantly

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from that in spermatogenesis which begins at puberty; cells entering meiosis move from one stage to the other without delay. Plausible explanations for maternal age–related nondisjunction in both MI and MII include, but are not limited to (1) an accumulation of toxic effects of the environment during the arrested state of the oocyte, (2) a degradation of meiotic machinery over time while in the arrested state, leading to a suboptimal resumption of MI and MII, and/or (3) a change in ovarian functioning due to suboptimal hormonal signaling. Most likely, several processes are affected by advanced maternal age; thus, more than one or all of these hypotheses may prove to be true. Several excellent reviews of hypotheses to explain the maternal age effect are available (e.g., Eichenlaub-Ritter, 1996; Gaulden, 1992) along with a recent review of hypotheses related to biological aging of the ovary (Warburton, 2005). One potential way to understand the maternal age effect is to examine maternal health factors and environmental exposures among mothers who have had a recognized pregnancy with chromosome 21 nondisjunction. Once a risk factor for nondisjunction is identified, it can be further evaluated in the context of biological aging to provide insight into the mechanism causing the maternal age effect. For example, biological aging of the ovary is characterized by a decline in the total oocyte pool, a decline in the number of antral follicles maturing per cycle and in reproductive hormonal changes. A decrease in the number of maturing follicles has been hypothesized to decrease the probability that one of them will be at the precise stage necessary for optimal response to follicle stimulating hormone (FSH), the trigger for ovulation. Warburton (1989) put forth the ‘‘limited oocyte pool’’ hypothesis suggesting that under these circumstances, the follicle ‘‘selected’’ for ovulation may be one whose oocyte is under- or overripe and thus more susceptible to chromosome malsegregation. In an excellent review, Warburton (2005) found inconsistent results among the studies that have examined the relationship between nondisjunction and biological aging of the ovary. For example, Freeman et al. (2000) found that mothers with a maternally derived chromosome 21 nondisjunction error were more likely to have a reduced ovarian complement (congenital or surgical) compared with mothers of infants without DS (odds ratio [OR] ¼ 9.61; 95% confidence interval [CI] ¼ 1.18–46.3). Women with reduced ovarian complement have a smaller oocyte reserve and thus would ‘‘mimic’’ an older woman. However, this observation has not been confirmed. Other indirect evidence to support ovarian aging specifically for chromosome 21 nondisjunction was reported by van Montfrans et al. (1999). They examined serum FSH levels taken on menstrual days 2, 3, or 4 in three consecutive cycles from 118 women who had a child with DS to 102 women who had at least 2 children and no history of a child with DS. Women were matched for age (all under age 40 years and no difference in group means) and for menstrual cycle history. They found higher levels of FSH, an indicator of decreased ovarian reserve, among

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women with an infant with DS compared with controls. Results from their follow-up study that measured estradiol and inhibin B on this same study group suggested that the elevated FSH levels reflected early depletion of the primordial follicle pool (van Montfrans et al., 2002). A more recent case– control study compared maternal serum anti-mullerian hormone (AMH) levels, another marker for ovarian reserve. They measured AMH on banked serum collected for first trimester prenatal screening among 25 women who had a pregnancy with DS and among control samples that included women with an unaffected pregnancy and were individually matched for maternal age (within 2 years), gestational age (same completed week), and duration of storage (within a month). Although the sample size was limited, they did not find any differences in AMH levels during pregnancy between the women with a DS fetus and their controls (Seifer et al., 2007). In a recent review, Warburton (2005) concluded that much of the evidence to date suggests that, if processes of ovarian aging are related to chromosome nondisjunction, they probably involve factors other than those measured by oocyte or antral follicle pool size and reproductive hormone levels.

2.2. Recombination patterns along chromosome 21 alter the risk for maternal nondisjunction Aside from maternal age, only one additional factor has been shown to be unequivocally associated with maternal nondisjunction, that is, altered recombination patterns. Warren et al. (1987) provided the first evidence that a proportion of maternal nondisjunction errors was associated with reduced recombination along chromosome 21. In addition to the absence of an exchange, the location of an exchange along the nondisjoined chromosome is an important susceptibility factor for chromosome 21 malsegregation (Lamb et al., 2005a; Sherman et al., 2005). Briefly, examination of recombination along the maternal nondisjoined chromosome 21 has suggested three susceptibility exchange patterns: (1) no exchange leads to an increased risk of MI errors, (2) a single telomeric (i.e., end of chromosome) exchange leads to an increased risk of MI errors, and (3) a pericentromeric exchange leads to an increased risk of MII errors (Lamb et al., 1996, 1997) (Fig. 3.2). The association of maternal MII errors with a specific recombination pattern suggests that at least some proportion of MII errors are initiated in MI (e.g., Fig. 3.1). We will simply use the designation ‘‘MII’’ to indicate this suggestion. More recently, we have examined altered recombination patterns of maternal nondisjoined chromosomes 21 stratified by maternal age to gain insight into possible mechanisms of nondisjunction. The data on 400 maternal MI errors grouped by maternal ages <29 years, 29–34 years, and >34 years indicate that there are multiple causes of nondisjunction, some age dependent and others age independent (Lamb et al., 2005b). In a young

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no exchange MI error

single telomeric exchange

MI error

single peri-centromeric exchange MII error

Figure 3.2 Summary of the susceptible exchange configurations observed among maternal nondisjoined chromosomes 21 and their associated risks for MI or ‘‘MII’’ errors.

woman, meiotic machinery (spindle function, sister chromatid adhesive proteins, microtubule motor proteins, and so on) functions optimally and, as a result, can correctly segregate all but the most error-prone exchange configurations. For young women then, the most frequent risk factor for MI nondisjunction is the presence of a telomeric exchange. As a woman ages, her meiotic machinery may be exposed to an accumulation of environmental and age-related insults, becoming less efficient/more error-prone. For example, recent studies have indicated changes in gene expression in younger compared with older oocytes in both mouse (Hamatani et al., 2004; Pan et al., 2008) and human studies (Steuerwald et al., 2007). Gene profiles that were altered included those involved in cell cycle regulation, cytoskeletal structure, energy pathways, transcription control, and stress responses. Such changes could play a role in the abnormalities of meiotic spindle that have been frequently observed in oocytes of aged mothers (Battaglia et al., 1996; Eichenlaub-Ritter et al., 2004). Among these older oocytes, suboptimal exchange patterns still increase susceptibility to nondisjunction, but now even homologous chromosomes with optimally located exchanges are at risk. Over time, the proportion of nondisjunction due to normal exchange configurations increases as age-dependent risk factors exert their influence. As a result, the most prevalent exchange profile of nondisjoined oocytes shifts from susceptible to nonsusceptible patterns with increasing age of the oocyte. If ‘‘MII’’ errors are initiated in MI, exchange patterns among maternal age groups with ‘‘MII’’ errors are predicted to be similar to those observed for MI errors. Our current data contradict this hypothesis (Oliver et al., 2008). Among 58, 69, and 126 maternal MII errors grouped by maternal ages of

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<29 years, 29–34 years, and >34 years, respectively, the proportion of susceptible pericentromeric exchanges increased with age, the opposite pattern to that observed in MI. This pattern indicates that there is an interaction with the effect of the pericentromeric exchange and advanced maternal age. We suggest two alternative explanations to fit these data. First, the pericentromeric exchange may establish a suboptimal condition that exacerbates the effect of maternal age–related risk factors. Alternatively, the pericentromeric exchange protects the bivalent from maternal age–related risk factors allowing the proper segregation of homologs, but not sister chromatids. This would represent a ‘‘true’’ MII error in the classical sense (Fig. 3.1). Clearly, additional work needs to be done to distinguish these alternatives.

2.3. Environmental influences on chromosome 21 nondisjunction Over the years, a large number of potential environmental influences have been identified in epidemiological studies of DS, but almost none have been replicated. Smoking at the time of pregnancy is an excellent example of the difficulties and limitations of such studies. Previously, a number of studies reported that women who smoke around the time of conception are at decreased risk for having an infant with DS (e.g., Chen et al., 1999; Hook & Cross, 1985, 1988; Kline et al., 1983, 1993; Shiono et al., 1986). One explanation for the negative association was that trisomic conceptuses were selectively lost prenatally among women who smoke (Hook & Cross, 1985; Kline et al., 1993). However, other studies have concluded that there is no association between DS and periconceptional smoking (e.g., Cuckle et al., 1990; Kallen, 1997; Torfs & Christianson, 2000). In contrast, Yang et al. (1999) analyzed periconceptional smoking among women less than 35 years with maternal MI and ‘‘MII’’ errors separately and found an increased frequency of smoking among women with ‘‘MII’’ errors only (OR ¼ 2.98; 95% CI ¼ 1.01–8.87). The odds ratio for this group of women increased significantly if the interaction term of periconceptional smoking and oral contraceptive use (2 month around conception) was modeled (OR ¼ 7.62; 95% CI ¼ 1.63–35.6). The authors speculated that this combined risk factor may compromise the blood flow surrounding the developing follicle, depleting the follicular fluid of oxygen. The resulting hypoxic environment may cause the meiotic machinery to malfunction. The hypothesis was based on the findings of Van Blerkom et al. (1997). They examined the oxygen content of follicular fluids from 1,000 follicles of equivalent size and ultrasonographic appearance taken from 116 in vitro fertilization (IVF) patients. Oocytes from severely hypoxic follicles were associated with high frequencies of chromosome disorganization on the metaphase spindle. Such disorganization could lead to nondisjunction and resulting aneuploidy. This speculation is similar to that proposed by

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Gaulden (1992) to explain maternal age–related nondisjunction. She suggested that the follicular microcirculation may be compromised in an aging ovary because of abnormal hormone signaling. Although the study of Yang et al. must be confirmed with a larger sample size, this example illustrates the potential of using identified risk factors to help dissect the maternal age effect. Other factors such as alcohol (e.g., Kaufman, 1983), maternal irradiation (e.g., Padmanabhan et al., 2004; Strigini et al., 1990; Uchida, 1979), fertility drugs (e.g., Boue & Boue, 1973), oral contraceptives (e.g., Harlap et al., 1979; Yang et al., 1999), spermicides (e.g., Rothman, 1983; Strobino et al., 1986), parity (reviewed by Chan, 2003), and low socio economic status (Christianson et al., 2004; Torfs & Christianson, 2003) have been implicated, but not confirmed. It seems almost certain that environmental risk factors for chromosome nondisjunction exist. Studies from model organisms make it clear that a wide variety of genetic and environmental disturbances can affect aneuploidy levels. Most recently, Dr. Hunt and her team have convincingly shown that exposure of oocytes in mice to bisphenol A (BPA) has a detrimental effect on mammalian oogenesis. BPA is an estrogenic chemical that is a component of polycarbonate plastics, resins lining food containers, and additives in a variety of consumer products; thus, it is present in almost all environments. In their first series of experiments, Hunt et al. (2003) found that, in the female mouse, short-term, low-dose exposure during the final stages of oocyte growth was sufficient to cause meiotic effects and that those effects increased the risk of aneuploidy. More recently, they have shown that exposure of developing oocytes during MI prophase in vivo, at doses comparable to human exposure, leads to synaptic defects and increased levels of recombination (Susiarjo et al., 2007). In the mature female, these aberrations lead to increased rates of aneuploidy in eggs and embryos. Further work indicated that BPA acts as an estrogen antagonist and suggests that the oocyte is sensitive to estrogen during early oogenesis. Understanding the influence of BPA, as well as other endocrine disruptors, on humans is an intense area of research. Certainly, understanding important risk factors, such as BPA, helps to address a major public health concern. Identification of such factors in humans is particularly difficult as oocyte development is initiated during fetal life and continues until the oocyte is ovulated. Full evaluation requires knowledge of the grandmother’s as well as the mother’s exposures. Large population-based studies that separate individuals with DS by type of nondisjunction error will increase the power to identify risk factors that have remained elusive. New epidemiological study designs and/or large prospective cohort designs of two or more generations will be needed to capture information from women and their mothers to reliably examine environmental exposures throughout the lifecycle of the oocyte. Clearly such studies will be difficult and labor intensive.

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In this case, model systems may be more efficient to address maternal grandmother exposures.

2.4. Candidate genes for chromosome 21 nondisjunction Model organisms have been used to identify genes that are important in the proper segregation of chromosomes. Genes involved in the meiotic process (e.g., homolog pairing, assembly of the synaptonemal complex, chiasmata formation, sister chromosome cohesion, meiotic spindle formation) may predispose an organism to chromosome nondisjunction. To date, a large study to investigate the association of variants in these genes with nondisjunction of human chromosome 21 has not been conducted. Candidate gene studies of the folate pathway provide the best example of genetic epidemiological approaches being used to evaluate the association of genetic variants with nondisjunction. James et al. (1999) provided preliminary evidence that the C677T polymorphism in the methylenetetrahydrofolate reductase (MTHFR) gene increased the chance of having a child with DS (OR ¼ 2.6; 95% CI ¼ 1.2–5.8). This polymorphism is associated with an elevation in plasma homocysteine and/or low folate status. The authors hypothesized that low folate status, whether due to dietary or genetic factors, could induce centromeric DNA hypomethylation and alterations in chromatin structure. Such alterations could adversely affect DNA–protein interactions required for centromeric cohesion and meiotic segregation. Later studies of the MTHFR C677T polymorphism, as well as several other allelic variants in genes in the folate pathway (e.g., MTHFR A1298C, MTRR A66G, MTR C2756G, RFC1 A80G), generated inconsistent results, most likely due to limited sample sizes, varying population characteristics, and sampling strategies. Moreover, some studies examined single gene effects, while others included gene–gene and gene–nutrition interactions. Still others examined biomarkers such as total plasma homocysteine levels. Although a thorough review is beyond the scope of this chapter, some important findings can be highlighted. Most studies that have examined blood homocysteine levels, a broad-spectrum indicator of nutritional and/or genetic impairment in folate/B12 metabolism, have documented a significantly higher level among the mothers of children with DS compared with control mothers, irrespective of population origin (Bosco et al., 2003; da Silva et al., 2005; James et al., 1999; Martinez-Frias et al., 2006; Takamura et al., 2004; Wang et al., 2007). As studies that examined one or two variants of MTHFR provided inconsistent results, Zintzaras (2007) conducted a comprehensive meta-analysis using strict criteria to evaluate the results from 11 case–control studies that examined MTHFR C677T, MTHFR A1298C, and/or MTRR A66G variants to the maternal risk for DS. The analysis was complicated by the statistically significant heterogeneity between studies. Nevertheless, the meta-analyses using several

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approaches indicated that the pooled odds ratios were not significant for any of the variants. The cumulative meta-analysis of MTHFR C677T showed a trend toward an association as the amount of data increased. Overall, the author suggested that there was insufficient evidence for claiming or denying an association for the gene variants. More recent studies have focused on the interaction among genes in the folate pathway adjusting for covariants and continue to find intriguing correlations (e.g., Biselli et al., 2008; Bosco et al., 2003; Coppede et al., 2006; da Silva et al., 2005; Hobbs et al., 2000; Martinez-Frias et al., 2006; Rai et al., 2006; Scala et al., 2006, 2007; Wang et al., 2008). In all studies that examined multiple variants, they found that the effect was additive (e.g., Biselli et al., 2008; Hobbs et al., 2000; Martinez-Frias, 2008; Rai et al., 2006; Scala et al., 2006; Wang et al., 2008) Clearly, this story needs to be pursued. Future studies should focus on gene–gene and gene–nutrition interactions in the folate pathway using large sample sizes, appropriate controls, and genetic epidemiological methods that adjust for possible confounding due to population substructure.

3. Prevalence and Survival of Individuals with DS Throughout the Life Span The survival prospect of individuals with DS in developed countries has improved considerably over time with the shift from institutional care to community-based care, improved clinical interventions, and overall health of the population. For example, survival to 1 and to 10 years was estimated to be 76% and 65% in a birth cohort in the United States from the years 1950–1967 (Fabia & Drolette, 1970a). Although not directly comparable, a more recent study showed that the 1- and 10-year survival rates in another US birth cohort from the years 1979–1998 was 93% and 89%, respectively (Rasmussen et al., 2006). Significant increases in survival have been noted in other developed countries as well (reviewed in Glasson et al., 2002). Even more importantly, the overall life expectancy of an individual with DS has increased significantly and is estimated to be about 60 years in developed countries (e.g., Glasson et al., 2002). This impressive change over time should shift our research emphasis to assessing causes of morbidity and mortality throughout the life stages of an individual with DS, in addition to obtaining accurate estimates of prevalence. We will provide recent examples of both types of studies to indicate the direction of the field. An important point to reiterate is that the majority of pregnancies of fetuses with trisomy 21 are spontaneously lost prior to term. For example, the rate of fetal loss has been estimated to be about 40% between the time of chorionic villus sampling (CVS) and birth and about 25% between amniocentesis and birth, although these estimates are not straightforward to derive

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(for review, see Cuckle, 1999; Snijders, 1999). More recently, Savva et al. (2006) conducted a survival analysis on follow-up of 5,177 prenatally diagnosed cases of DS to determine if spontaneous loss depended on maternal age. They found that the rate of loss increases with increasing maternal age. The average fetal loss rate between the time of CVS and term was 32% (95% CI ¼ 26–38) and increased from 23% (95% CI ¼ 16–31) to 25–44% (33–56) for women aged 45. The average fetal loss rate between the time of amniocentesis and term was 25% (21–31) and increased from 19% (14–27) to 33% (26–45) across the same age range. Importantly, this does not include the loss prior to recognizing a pregnancy or prior to prenatal diagnosis. Thus, the estimates of the prevalence among live births not only exclude those pregnancies that were medically terminated but also those that were spontaneously lost.

3.1. Mortality and morbidity among individuals with DS Before examining trends in prevalence, it is helpful to provide an overview of the causes of mortality and morbidity over the life span of individuals with DS. A recent study has provided an excellent framework to consider these issues by dividing the lifespan into four time periods: (1) prenatal, (2) childhood, and adolescence (0–18 years), (3) adulthood (19–40 years), and (4) senescence (>40 years) (Bittles et al., 2007). We will use this study as an example of one that begins to identify increased length of survival of individuals with DS and provides a focus for future efforts. The study of Bittles et al. was based on the successful registration of individuals with DS by the Disability Services Commission of Western Australia. This commission is a primary support agency for those with intellectual disability in Western Australia since 1952. Thus, one limitation of the study is that some proportion of individuals may not get registered with the commission. Nevertheless, the study data are based on the electronic linkage of 1,332 individuals with DS in the Disability Services Commission from 1953 to 2000 with the (1) Western Australia Cancer Registry (1981 to present), (2) the Western Australia Death Registry and the state Coroner’s office, and (3) the National Death Index (1980 to present). In addition, information on overall DS survival trends for the Western Australia population from 1980 to 2004 was obtained from the Western Australia Birth Defects Registry. We will only highlight some of the findings of each period to show the value of the data collected. In the prenatal stage/birth stage, this study indicated that the overall prevalence of DS (live births, fetal deaths, and medical terminations) per 1,000 births increased from 1.1 to 2.9 per 1,000 births in 1980–2004, respectively. This increase paralleled the increase in maternal age in the population. In 1980, 4.8% of women giving birth in Western Australia were

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35 years or older compared with 18.6% in 2004. This trend has been observed in other populations as well (see below). The next stage of life, infancy to early adulthood proves to be a medically vulnerable one. About half of the 298 deaths identified among the 1,332 individuals with DS occurred before age 18 and about 36% before age 5. As in other studies, the leading causes of death between ages 0–18 years were pneumonia and other respiratory infections (33%) and congenital heart defects (CHDs) (13%). Because children with DS have a >20-fold increased risk of developing leukemia in childhood (see below), this condition was further examined during this life stage. Data from the Western Australia Cancer Registry indicated that about 54% (14/26) of cancers recorded in individuals with DS were childhood leukemia. Twelve of 14 cases were diagnosed before 5 years of age and in 4 cases it was fatal. In adulthood (19–40 years), the investigators noted that many agerelated health problems and/or medical disorders in DS begin earlier than in the general population. About 13% of the 298 deaths between 1953 and 2002 occurred in the 19–40 year age group. The main causes of death recorded were pneumonia and other respiratory infections (23%), cardiac, renal, and respiratory failure (10%), and cancers (8%). Cerebrovascular accident and coronary artery disease were recorded as causes of death in about 5% and 3% of the cases, respectively. Lastly, about 30% of individuals with DS registered in the Disability Services Commission cohort were aged >50 years at the time of death and 25% died between 57 and 62 years. Information on cause of death was available for 97 of the 111 deceased persons >40 years of age. Pneumonia and other respiratory infections were the most common causes of death (40%), followed by coronary artery disease (9.9%), cardiac, renal, and respiratory failure (9.0%) cerebrovascular accident (6.3%), and cancers (5.4%). Alzheimer’s dementia was listed as a contributory cause of death in only three cases. The above account of causes of mortality only shows a limited picture of the medical problems encountered by those with DS. The use of information from death certificates is fraught with problems as pointed out by others (e.g., Rasmussen et al., 2006; Shin et al., 2007; Yang et al., 2002), but still provides a basic overview. The age-associated morbidity patterns of DS are an area of considerable clinical research. The study of van Allen et al. (1999) indicated that significant health problems among adults with DS include untreated congenital heart anomalies (16%), acquired cardiac disease (16%), pulmonary hypertension (8%), recurrent respiratory infections/aspiration (30%), complications from presenile dementia/Alzheimer-type disease (42%), adultonset epilepsy (37%), osteoarthritic degeneration of the spine (32%), osteoporosis with resultant fractures of the long bones (55%) or vertebral bodies (30%), and untreated atlantooccipital instability (8%). In addition, they showed that acquired sensory deficits including loss of vision due to

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early onset of adult cataracts (50%), recurrent keratitis (21%), or keratoconus (16%), and measurable hearing loss (25%) were significant problems. Importantly, population-based surveillance of common medical conditions in adults with DS is infrequent. Henderson et al. (2007) found that 48% of adults with DS had not seen a doctor in the previous 12 months and 33% had not had a medical assessment in the previous 3 years. Untreated hypothyroidism, a common problem for adults with DS may lead to symptoms that mimic cognitive decline; it may also be associated with decreased energy, and weight gain (Finesilver, 2002). The causes and consequences of obesity in individuals with DS have only recently been studied (e.g., Fonseca et al., 2005; Melville et al., 2005). As Barnhart and Connolly (2007) emphasize, a shift must be made from disability prevention to the prevention of conditions that limit activity and participation of adults with DS. Consideration of exercise and healthy diet regimen will positively affect the overall health of adults with DS and, thus, will increase their quality of life.

3.2. Implication of factors that influence the prevalence of DS The recent report by Canfield et al. (2006) provides an excellent example of a large study to obtain an estimate of the birth prevalence of DS in the United States and to identify factors that may influence prevalence estimates. Eleven birth surveillance systems used active-case finding methods to identify all pregnancy outcomes with DS, including live births, fetal deaths, spontaneous and induced abortions. The national estimate for DS based on the surveillance of 22% of births in the United States and maternal age– adjusted prevalence was 13.65 (95% CI ¼ 13.22–14.09) per 10,000 live births, or 1/733. This suggests that 5,400 of the approximate 4 million infants born each year in the United States have DS. Canfield et al. further investigated the maternal age–adjusted prevalence rates among three major maternal racial/ethnic groups in the United States: non-Hispanic white, non-Hispanic black, and Hispanic. Compared with non-Hispanic white mothers, the prevalence ratio was 0.77 (95% CI ¼ 0.69–0.87) for non-Hispanic black mothers and 1.12 (95% CI ¼ 1.03–1.21) for Hispanic mothers. The causes of the increased prevalence among Hispanic and decreased prevalence among non-Hispanic black mothers are important to discern. Differences could be related to variation among surveillance systems: The authors state that each surveillance system differed in its access to prenatal records and diagnoses, spontaneous abortions, fetal deaths, and live births. If ability to ascertain information at various gestational time points varied by racial/ethnic groups, prevalence estimates would differ. Alternatively, prevalence rates could be influenced by factors that affect access to health care, such as socioeconomic status or education (e.g., Coory et al., 2007; Khoshnood et al., 2004, 2006). Differences could be due to racial/ethnic variation in use of prenatal care, prenatal diagnosis,

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and/or pregnancy termination (e.g., Forrester & Merz, 1999; Siffel et al., 2004). Lastly, important environmental exposures (e.g., smoking, nutrition, socioeconomic status) or genetic risk factors (e.g., variants involved in meiosis, oocyte development, or fetus survival) could vary by racial/ethnic group. Each one of these explanations is plausible and carries significant implications for future public health interventions. A significant number of important studies have been conducted that examine the birth prevalence of DS among populations using various methods of case ascertainment. Hook and his colleagues have contributed significantly to this field, not only in terms of study design and statistical methods but also in presenting results from populations with different demographics (e.g., Carothers et al., 1999, 2001; Hecht & Hook, 1996; Hook, 1981, 1983; Hook et al., 1995, 1999). In a review of 49 population groups using an index to allow comparison between studies, Carothers et al. (1999) suggested that ‘‘real’’ variation between population groups probably amounts to about 25%. Interestingly, the pattern of prevalence estimates among the racial/ethnic groups identified in this meta-analysis is the same as that observed in Canfield et al. (2006): There was an increase in the prevalence among individuals of Hispanic origin compared with those of African-American or African origin. This prevalence variation observed among groups defined by their ‘‘self-reported’’ race/ethnicity needs to be dissected. The categorization of race/ethnicity is imprecise and displays considerable in-group heterogeneity. This measure becomes more imprecise with ever-increasing numbers of individuals classified as multiethnic and multiracial. Nevertheless, there is considerable motivation to identify the underlying cause of the differences in prevalence observed among groups. The prevalence of DS among births in a specific population, of course, depends on the maternal age structure of the population, the availability of prenatal diagnosis, the option for elective terminations, and the culture’s attitude toward pregnancy terminations as well as the prospect of caring for a disabled child. Recent studies have not shown large changes in the prevalence of DS among live births over time (e.g., Bittles et al., 2007; Dolk et al., 2005; Iliyasu et al., 2002; Khoshnood et al., 2004; Rosch et al., 2000). For example, in the ethnic/racial diverse population of the fivecountry metropolitan area of Atlanta, GA, the proportion of pregnancies among women in their late 30s has increased in recent years. Interestingly, the prevalence of DS among infants of women in this age group has also shown an increase (Besser et al., 2007; Siffel et al., 2004). The reasons for this stabilization or slight increase of prevalence among births needs to be further tracked to better understand (1) the consequence of screening for trisomic conceptuses and the use of prenatal diagnosis as an intervention, (2) the decisions that families are making with respect to timing of pregnancies and use of prenatal diagnoses, and (3) the public health allocation of resources to accommodate these trends.

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As emphasized by many, it is essential to obtain accurate estimates of survival rates among individuals with DS. Survival rates differ among racial/ ethnic groups and suggest that additional studies are needed to understand such differences (e.g., Besser et al., 2007; Day et al., 2005; Rasmussen et al., 2006; Yang et al., 2002). Studies to assess prevalence of individuals with DS in adolescence and adulthood are just beginning. For example, Besser et al. (2007) recently conducted a study of children with DS born in metropolitan Atlanta, GA, from 1979 to 2003 ascertained from a population-based birth defects registry. These ascertained cases were followed using linkage to vital records and the National Death Index. The prevalence was estimated by dividing the children surviving with DS by the population obtained from the US Census estimates. They found that there were 13.0 per 10,000 live births with DS in 2003 and 8.3 per 10,000 ages 0–19 years. The prevalence of DS among 0–14 year olds increased over time, which parallels the studies outlined above that show improved medical care. Importantly, within each 5-year cohort, the prevalence decreased with age and this decrease was greater among blacks than among whites. This discrepancy between racial/ ethnic groups has also been observed using other approaches (Rasmussen et al., 2006; Yang et al., 2002). The next step is to understand the cause of the differential mortality rates to provide for those who are most at risk for childhood morbidity and mortality.

4. Etiology of DS-Associated Medical Disorders Almost universally, individuals with DS have characteristic facial features, mental retardation, and hypotonia; however, even these features vary in severity. Importantly, other features including specific birth defects and medical disorders vary considerably. They are present at a higher frequency among individuals with DS compared with the general population; however, these DS-associated conditions are not present in all individuals with an extra chromosome 21. For example, CHDs occur in about 50% of individuals with DS, gastrointestinal tract abnormalities (e.g., duodenal stenosis or atresia) occur in about 5–10%, and childhood leukemia in about 1%; these all occur at significantly higher frequencies than in the general population (for review, see Epstein, 2001). Thus, the extra chromosome 21 either (1) ‘‘sensitizes’’ the genetic background and unmasks variability in the rest of the genome and/or (2) leads to increased chromosome 21 variability, directly influencing susceptibility. Patterson (2007) reviewed possible molecular mechanisms resulting from trisomy 21 that lead to manifestations of DS. Two important epidemiological questions are (1) Among individuals with DS, what is the prevalence of a specific trait and is it increased or

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decreased compared with those without DS? and (2) What are the associated factors that explain the reduced penetrance and variable expression of DS-associated traits? There are few studies to date that have addressed these significant questions using population-based strategies (e.g., Fabia & Drolette, 1970b; Freeman et al., 1998; Kallen et al., 1996; Stoll et al., 1990; Torfs & Christianson, 1998). One example of a recent population-based study that examined both questions is that conducted by Torfs and Christianson (1998, 1999). They studied 2,894 confirmed cases of DS collected through the California Birth Defects Monitoring Program (CBDMP) between 1983 and 1993. They compared the frequencies of specific birth defects among infants with DS to those in 2.5 million newborn infants from the same population. They recorded 61 major birth defects known to be uniformly ascertained through the CBDMP, that is, those that could be diagnosed in an infant through age one or those that require early action. Forty-five defects were significantly more common in DS. For example, the chance for atrioventricular septal defects (AVSD, or sometimes called atrioventricular canal) was increased 1,000-fold over that for infants without DS. Other cardiac defects were also increased including atrial septal defects (ASD), ventricular septal defects (VSD), and defects of cardiac valves. Gastrointestinal defects were about 20 times more common in infants with DS. Duodenal atresia and annular pancreas had the highest risk ratios (265 and 430, respectively). Most defects of the primary developmental field and midline defects were either not significantly associated or not observed in infants with DS (e.g., anencephaly, spina bifida, encephalocele, and diaphragmatic hernia). In the next section, we will review two DS-associated disorders to probe further into studies that ask the second question: What factors are associated with the reduced penetrance and variable expression of DS-associated traits? CHDs will provide an example of a condition that is just beginning to be dissected with respect to etiology. Next, we will describe recent studies on DS-associated childhood leukemia. For this disorder, researchers have made some progress with respect to understanding the genes that may be involved in susceptibility. We discuss both disorders further as examples of conditions that may influence later cognitive and behavioral outcomes. We will not review another important DS-associated condition, that of Alzheimer disease. This is due to space limitations, but we point to a recent review of this significant area of focus (Zigman & Lott, 2007; also see Chapter 4).

4.1. DS-associated CHDs Most studies have shown that about 45–50% of infants with DS have CHDs with one defect, namely AVSD, being particularly common. Several recent reports have suggested that the distribution of CHDs in DS varies by race/ ethnicity (de Rubens et al., 2003; Ferencz et al., 1997; Jacobs et al., 2000;

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Khoury & Erickson, 1992b; Lo et al., 1989; Marino, 1996; Torfs & Christianson, 1999), but most population-based studies have not had broad ethnic representation. We have recently analyzed data collected from the NDSP to examine variation in rates of CHD in a racially/ethnically diverse US population (Freeman et al., 2008). The noted limitations of the study can be stated first: (1) only families in which the mother spoke English or Spanish were eligible and (2) pregnancy losses, medical terminations, fetal deaths, or infants who died after birth but before the family could be enrolled were not included. First, we found that 44% of infants with DS have CHDs, a rate consistent with other studies (Freeman et al., 1998; Kallen et al., 1996; Stoll et al., 1998; Torfs & Christianson, 1998). We then estimated the proportion of cases with specific types of heart defects, knowing that infants with DS were particularly susceptible to AVSD. We found in the NDSP study population that a partial or complete AVSD was present in 17% of eligible infants (39% of those with a reported CHD), a rate similar to that found in most other studies (Calzolari et al., 2003; Fixler & Threlkeld, 1998; Freeman et al., 1998; Frid et al., 1999; Kallen et al., 1996; Rowe & Uchida, 1961; Stoll et al., 1998; Torfs & Christianson, 1998; Wells et al., 1994). In contrast to the similar estimates of AVSD among infants with DS, ASD and VSD rates vary widely among studies: 4–42% and 11–44%, respectively (Calzolari et al., 2003; Fixler & Threlkeld, 1998; Freeman et al., 1998, 2008; Frid et al., 1999; Kallen et al., 1996; Rowe & Uchida, 1961; Spahis & Wilson, 1999; Stoll et al., 1998; Torfs & Christianson, 1998; Wells et al., 1994). We then examined demographic characteristics of infants with specific types of CHD to determine if such factors provide insight into susceptibility. The NDSP was particularly useful for the analyses of race/ethnicity, as it includes three ethnic groups represented at greater than a 10% frequency: non-Hispanic white, non-Hispanic black, and Hispanic. This permitted a direct examination of possible differences in CHD rates among ethnic groups. AVSDs demonstrated the most striking ethnic differences. Specifically, black infants with DS had about twice the risk of AVSD as white infants (OR ¼ 1.98; 95% CI ¼ 1.31–2.99) whereas Hispanics had one-half the risk of whites (OR ¼ 0.60; 95% CI ¼ 0.40–0.99). Similar ethnic differences in AVSD rates at multiple sites strengthen the overall NDSP findings. In contrast, we found no significant ethnic differences in VSD rates in the NDSP as a whole or among the sites. For ASD, we noted a marginally significant increased OR for blacks compared with white infants with DS. This observed increase among black infants could be a true increase or may be due to the diagnostic misclassification of AVSD as ASD. This needs to be further examined. We also found a predominance of females among infants with AVSD (OR ¼ 2.06; 95% CI ¼ 1.55–2.75), which has been reported previously in infants with and without DS (Ferencz et al., 1997; Harris et al., 2003; Kallen et al., 1996; Park et al., 1977; Pinto et al., 1990). Interestingly, some studies

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have reported that males with DS have a significantly greater life expectancy compared with females with DS (Fabia & Drolette, 1970a; Glasson et al., 2003; Leonard et al., 2000), although not all report this difference (Day et al., 2005; Dupont et al., 1986; Malone, 1988; Mastroiacovo et al., 1992; Mulcahy, 1979; Rasmussen et al., 2006; Yang et al., 2002). If true, this observation is contrary to the male:female ratio in the general population and in most individuals with intellectual disabilities. One explanation provided for this difference may be an increased preponderance of CHD, in particular AVSDs, among females with DS (Glasson et al., 2003). Clearly more research needs to be done to understand these ethnic/racial and gender differences. Both of these parameters are surrogates for many characteristics that may prove to be susceptibility factors. One example of a study that began to further examine factors that underlie susceptibility to DS-associated birth defects is that of Torfs and Christianson (1999). They compared demographic information, pregnancy, and medical histories, and use of tobacco, alcohol, and coffee among mothers of infants with DS with and without specific birth defects in a case/control study based on 687 infants with DS. Taking CHD and tobacco use as an example, smoking was found to be associated with CHD overall (OR ¼ 2.0; 95% CI ¼ 1.2–3.2) and specifically, with AVSD, ASD, and tetralogy of Fallot. Maternal race, age, parity, income, and education did not confound the association. Others have examined smoking and DS-associated CHD and have not found a significant association; however, comparison of studies is difficult as sample sizes were smaller, the timeframe of tobacco use differed (prior to conception vs during the first trimester), and the diagnostic methods used to identify and classify CHD were older (e.g., Fixler & Threlkeld, 1998; Khoury & Erickson, 1992a). Nevertheless, the combined results suggest smoking may be a risk factor. However, as suggested by Torfs and Christianson (1999), at least in their dataset, smoking only played a small role in susceptibility for abnormal heart development among those with DS, as the frequency of periconceptional smoking was low and the association modest.

4.2. DS-associated leukemia Several studies have now documented that although the overall incidence of cancer in individuals with DS is similar to that of the general population, it shows a strikingly different profile of cancer types (e.g., Hasle et al., 2000; Patja, 2006; Sullivan et al., 2007; Yang et al., 2002). For example, in a population-based study of 2,814 individuals with DS, the incidence of solid tumors was reduced by about one-half in all age groups; however, leukemia occurred 10- to 20-fold more frequently among those with DS (Hasle et al., 2000). Importantly, the largest relative risk for leukemia was observed in children with DS under age five. In this group, acute myeloid leukemia (AML) was 153-fold more frequent than in the general population.

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Moreover, the incidence of acute megakaryoblastic leukemia (AMKL) is estimated to be 500-fold increased in children with DS compared with the general population (Zipursky et al., 1992). AMKL explains about 62–86% of AML in children with DS, a significant increase compared with the general pediatric population (Creutzig et al., 2005; Lange et al., 1998). Comparison of AML associated with and not associated with DS indicates that distinct phenotypes exist. The median age of onset is much younger—about 2 years compared with 8 years in the general population (Creutzig et al., 2005; Lange et al., 1998). Also, many times a myelodysplastic syndrome with thrombocytopenia and/or anemia and abnormal bone marrow morphology precedes AML in DS, but is usually de novo in nonsyndromic AML children (Zipursky et al., 1987, 1994). A remarkable feature of DS-associated AML is the sensitivity to therapy (e.g., Kudo et al., 2007; Lange, 2000; Ravindranath et al., 1992); disease resistance and recurrence are uncommon. In fact, children with DS have been found to be more sensitive or responsive to chemotherapy. Until treatments were altered, high rates of toxicity occurred, which sometimes led to mortality (Craze et al., 1999; Lange et al., 1998). In addition to AML, about 10% of infants with DS develop transient myeloproliferative disorder (TMD) (Hitzler & Zipursky, 2005). TMD in newborns with DS is characterized by circulating blasts with morphologic features of leukemic cells. Studies have shown that these immature megakaryoblasts are clonal and are present in the liver, bone marrow, and peripheral blood (e.g., Kurahashi et al., 1991; Miyashita et al., 1991). In a recent study of 48 newborns with DS and TMD, 25% were asymptomatic, but the others had a significant elevation of blast counts with consequences such as bruising, respiratory distress, and liver dysfunction (Massey et al., 2006). Although TMD usually resolves spontaneously within 3 months, a small percentage of neonates develops severe and sometimes fatal complications. These include hepatic fibrosis or hydrops (e.g., Dormann et al., 2004; Schwab et al., 1998). Although considered transient, recent studies have shown that 20–30% of neonates who recover from TMD develop AMKL within 3–4 years (Hitzler & Zipursky, 2005; Massey et al., 2006). There is evidence that TMD and AMKL arise from a common precursor; however, the underlying mechanism of the susceptibility of children with DS to leukemia is only beginning to be understood (reviewed in Hitzler, 2007). One of the major breakthroughs has been the discovery that nearly all of children with DS who develop either TMD or AMKL have mutations in the transcription factor GATA1 (Ahmed et al., 2004; Groet et al., 2003; Hitzler et al., 2003; Rainis et al., 2003). GATA1 is an X-linked gene that encodes a zinc-finger transcription factor. This factor is essential for normal erythroid and megakaryocytic differentiation. Although the mechanism of action is still not understood, another question comes to the forefront: How

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does the mutation in the X-linked GATA1 gene cause a leukemic condition in individuals with an extra chromosome 21? The current thinking is that such mutations interact with chromosome 21 specific genes and/or with nonchromosome 21 genes that are not regulated appropriately as a consequence of the extra chromosome 21. This interaction(s) need to explain both the variability of the presence of TMD in neonates and the conversion of TMD to AMLK in a subset of individuals. One candidate gene that is located on chromosome 21 is RUNX1. This hematopoietic transcription factor has been shown to interact physically and functionally with GATA1 (Elagib et al., 2003; Xu et al., 2006), although the mechanisms of the interaction are not well understood. Intense research is ongoing to better define the interaction between GATA1 and RUNX1, and to identify factors involved in this leukemic process.

4.3. Summary The above description provides examples of both epidemiological and molecular approaches that are being taken to begin to address the etiology of specific disorders for which individuals with DS are significantly predisposed. Additional basic epidemiological studies need to be conducted to understand these associations throughout the life span of those with DS. New bioinformatic approaches that take advantage of large, epidemiological databases and of anonymized electronic medical records, may allow new questions to be answered (e.g., Hodapp et al., 2006). In addition, these studies in concert with molecular approaches will begin to provide insight into the etiology of, for example, abnormal heart development or Alzheimer disease, in the context of trisomy 21, but may also contribute to the understanding of these conditions in general.

5. Neurodevelopmental Outcomes of Comorbid Medical Conditions in DS Despite our wealth of knowledge regarding the cognitive and behavioral phenotypes of DS, the influence of DS-associated medical problems is often not considered in neurodevelopmental outcome studies. Here, we will review the current knowledge on the relationship of several DSassociated medical conditions and neurodevelopmental outcome after providing an overview of the cognitive phenotype in DS.

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5.1. Overview of cognitive phenotype in DS DS is the most prevalent genetic cause of mental retardation with its own unique cognitive, adaptive, and behavioral profiles. Unlike other genetic conditions, individuals with DS are typically diagnosed in the newborn period based on their distinctive physical characteristics. Thus, DS should be an ideal model to study the link between infancy to aging with respect to cognitive and behavioral phenotypes. As emphasized previously, the vast majority of our current knowledge on DS focuses on the early childhood and the adult years. Research is needed to connect these two endpoints to identify how symptoms evolve and change over time, especially from the adolescent through young adult years (Dykens, 2007). To this end, in 2006, the US Congress mandated that the National Institutes of Health (NIH) establish a trans-NIH taskforce charged with creating a research plan to identify, create, and implement programs to maximize and maintain cognitive function throughout the lifespan of individuals with DS. The resulting NIH DS Working Group’s 2007 Research Plan on DS highlights the need for more research focused on identifying the cognitive phenotype of DS throughout the lifespan, especially studies on comorbid psychiatric and medical conditions. The degree of cognitive deficits in individuals with DS varies from mild to moderate mental retardation with a typical range of 40–72 (Nicham et al., 2003). Children with DS between 6.5 and 8.0 years have IQ levels between 45 and 71 (mean 55.6) compared to adolescents with DS between 12.2 and 25.9 years with IQ levels between 28 and 47 (mean 37.6) (Melyn & White, 1973). Performance strengths are recognized on visual–spatial tasks compared with short-term memory auditory and verbal tasks ( Jarrold et al., 2002; Wang & Bellugi, 1994). Indeed, the cognitive deficits in DS may further delay language learning, as cognitive abilities serve as prerequisites for acquiring certain linguistic achievement (Abbeduto et al., 2001). Age-related decline in IQ is seen in individuals with DS, typically in the third or fourth decades, which may or may not be influenced by dementia (Devenny et al., 2000). In adulthood, 70% of individuals with DS function in the moderate–severe range, 20% in the mild–moderate range, and 8% in the mild range (Devenny et al., 2000; Temple et al., 2001). The mean IQ level is 45 by adulthood with significant variability in the range of IQ levels (Carr, 1994). It is usually a challenge to distinguish between the presence of early dementia and the declines related to normal aging process and lifelong cognitive deficits (Devenny et al., 2000; Chapter 4). In a longitudinal study conducted by Devenny et al. (1996), adults with DS with suspected or possible dementia of Alzheimer type show significant decline in cognitive abilities compared to nondemented adults.

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5.2. Impact of DS-associated CHDs on neurodevelopmental outcome As reviewed previously, about half of infants with DS have CHDs, with many having to undergo surgery for repair. Several neurodevelopmental studies in typically developing children with CHDs have shown neurocognitive and psychomotor deficits (Mahle et al., 2006), yet the impact of CHD in children with DS has not been described. In a cross-sectional study design, we compared 6 children with DS and AVSD (mean age 17 months) with 11 children with DS without a CHD (mean age 16 months) and found significant developmental delay in the group with AVSD (unpublished data). Those with AVSD had a greater developmental age delay difference compared with age-matched children with DS without CHDs, as indicated by a 2.91 month delay in the cognitive domain, 3.72 months delay in expressive language, 1.91 months delay in receptive language, and 1.00 month delay in gross motor. These preliminary data emphasize the need for further study to understand why these differences occur and to identify treatment strategies that may ameliorate these delays. There are many factors that must be considered in neurodevelopmental outcome studies in children with CHD. For instance, Gaynor et al. (2007) have suggested that patient-specific factors are more important than intraoperative factors (e.g., race, birth weight) in determining neurodevelopmental outcome in children with CHDs. This finding is important because there are significant ethnic and gender differences in the prevalence of CHDs, specifically for AVSD as described above. Furthermore, abnormal brain microstructure and metabolism noted shortly after birth in newborns with CHD suggests that these newborns have impaired brain development in utero, possibly related to impaired cerebral oxygen and substrate delivery prenatally (Donofrio et al., 2003). A recent study by Miller et al. (2007) describes a high incidence of injury to white matter that resembled periventricular leukomalacia in term newborns with CHD. This morphology is similar to that seen in premature infants and is related to impaired brain development that is detected preoperatively, shortly after birth. Hence, newborns with CHD are at risk for impaired brain development in utero. Longitudinal studies are needed to understand the neurodevelopment outcome of individuals with DS and CHD, possibly beginning with fetal brain development.

5.3. Impact of DS-associated leukemia on neurodevelopmental outcome As described above, the incidence of AMKL is estimated to be 500-fold increased in children with DS compared with the general population. Although there have not been any studies that examine the neurodevelopmental

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outcome of children with DS and leukemia, some studies have investigated the neurodevelopment of typically developing children with acute lymphoblastic leukemia (ALL). In the past, cranial radiation therapy resulted in declines in intelligence among survivors of childhood ALL (Fletcher & Copeland, 1988). As a result, pediatric oncologists began to substitute intrathecal chemotherapy for CNS prophylaxis in an attempt to improve cognitive outcomes. Intrathecal chemotherapy improved survival rates and appeared to be less detrimental to a child’s neurocognitive development when compared to cranial radiation therapy. Yet, ALL survivors receiving intrathecal chemotherapy continue to demonstrate slight decline on cognitive and academic abilities (Copeland et al., 1996). Research is needed to understand the influence of leukemia treatment on the neurodevelopmental outcome in children with DS, given the increased risk of leukemia in this cohort.

5.4. Impact of DS-associated obstructive sleep apnea on neurodevelopmental outcome Children with DS are at greater risk for development of obstructive sleep apnea syndrome (OSAS), with an estimated incidence of 30–60% compared to 0.7–2.0% in the general pediatric population (Gislason & Benediktsdottir, 1995; Marcus et al., 1991; Stebbens et al., 1991). OSAS includes episodes of apnea and hypopnea, and hypoventilation with hypercarbia and episodes of sleep fragmentation with increased arousals during sleep (Shott, 2006). Predisposing factors in DS include abnormal small upper airway, mid-face, and mandibular hypoplasia, large adenoids, protruding tongue, generalized hypotonia, and obesity (Shott, 2006). Sleep fragmentation and increased sleep arousals may impair daytime functioning, resulting in learning and behavior problems (Marcus et al., 1991). Despite the high frequency of OSAS and multiple predisposing risk factors, neurodevelopmental outcome studies do not currently exist in children with DS and OSAS. In studies involving typically developing children, OSAS is correlated with lower IQ performance testing and behavioral problems, including inattention and hyperactivity (Bass et al., 2004; Chervin et al., 2002).

5.5. Impact of DS-associated seizure disorder on neurodevelopmental outcome Seizure disorder is the most common neurologic disorder associated with mental retardation, with the prevalence of 4–8 per 1,000 in individuals with mental retardation compared to 3–4 per 1,000 in the general population (Steffenburg et al., 1995). The prevalence appears to increase with decreasing cognitive abilities with 28–38% in the profound mental retardation range and 14% with mild mental retardation (Steffenburg et al., 1995). In

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individuals with DS, the prevalence of seizures is higher than the general population, but lower than among individuals with mental retardation of other etiologies (Goldberg-Stern et al., 2001). Studies have indicated the rates of epilepsy to be 8% of children and adolescents with DS and 16% in adults with DS (Goldberg-Stern et al., 2001; Prasher, 1995). The type of seizure disorders vary in children with DS with 47% partial seizures, 32% infantile spasm, and 21–69% tonic-clonic seizures (Goldberg-Stern et al., 2001; Stafstrom et al., 1991). Stafstrom et al. (1991) conducted a large, retrospective study of 737 individuals with DS and seizure disorders and hypothesized that the increased susceptibility to seizures is likely to be associated with the hypoxia caused by cardiovascular complications, including congenital heart disease, severe intracardiac shunts, infection, and neonatal hypoxia or ischemia. In addition, reduced inhibitory interneurons, altered neuronal structure, and increased excitability of membranes may play a role in epileptogenesis in DS (Stafstrom et al., 1991). There is also a bimodal distribution of seizure onset with early-onset seizures in childhood and late-onset seizures in middle-aged individuals. The late-onset seizures in older individuals may be related to the presence of underlying changes of Alzheimer’s disease (Mann, 1988). Children with both epilepsy and mental retardation are at heightened risk for behavioral problems and psychopathology. In children with mental retardation and epilepsy, 57% had at least one psychiatric diagnosis, including autistic spectrum disorder, autism-like condition, Asperger syndrome, attention/deficit hyperactivity disorder, and conduct and tic disorder (Steffenburg et al., 1996). There have been no studies to date on the impact of seizures on the intellectual outcome and behavior of children with DS. Case studies have revealed that the neurodevelopmental outcome has been poor despite relatively good seizure control in children with DS and infantile spasms (Goldberg-Stern et al., 2001). Three of five children with DS and infantile spasm displayed autistic-like features (Goldberg-Stern et al., 2001). Additional studies are needed to understand the intellectual and behavioral profile of individuals with DS and seizures in order to plan effective intervention to improve their neurodevelopmental outcome.

5.6. Impact of DS-associated hearing loss on neurodevelopmental outcome Children with DS have a three times higher likelihood of developing chronic ear disease and secondary hearing loss than children with other developmental delays (Dahle & McCollister, 1986). The higher incidence is attributed to their anatomic anomalies, including mid-face hypoplasia, easily collapsible eustachian tube, stenotic ear canals, and small external canals (Shott, 2006). Furthermore, children with DS have frequent upper respiratory infections, possibly caused by the immaturity of the immune

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system (Shott, 2006). Shott et al. (2001) has shown that with aggressive medical and surgical management of chronic middle ear effusions and chronic otitis media starting soon after birth, only 2% had hearing loss after the first year in the study. Studies have shown that even a mild hearing loss can affect a child’s articulation (Bess, 1985). Children with DS have language deficits, particularly in expressive language, vocabulary production, and speech intelligibility, which may be further complicated by their chronic ear disease and hearing loss (Shott, 2006). The small oral cavity, open mouth posture, protruding tongue, and irregular dentition may further affect their speech production. Overall, there is significant weakness in communication compared to daily living and socialization skills (Dykens et al., 2006), which may hinder independent living and inclusion in the community (Chapman & Hesketh, 2000). Thus, aggressive monitoring and management of chronic otitis media is recommended to prevent hearing loss and consequently, deficits in communication skills.

6. Psychiatric and Neurobehavioral Issues in DS In the past, neurobehavioral disorders in individuals with mental retardation were often ignored and assumed to be linked to their cognitive deficits. Clinicians may attribute these behavioral and psychiatric problems to the intellectual disability. This bias is often referred to as ‘‘diagnostic overshadowing’’ as clinicians may not consider the presence of a dual diagnosis, co-occurrence of mental retardation and a psychiatric disorder, in their evaluation (Lovell & Reiss, 1993; Reiss et al., 1982). Because this is a significant area of clinical research in DS and one that will lead to improved treatment of symptoms associated with DS, we will provide an overview of the topic. Individuals with DS are at much higher risk for having a wide array of psychiatric and behavioral disorders, yet the rate is lower compared with individuals with mental retardation of other etiology. Approximately 20–40% of individuals with DS have clinically elevated maladaptive behavior (Chapman et al., 1998; Coe et al., 1999; Dykens & Kasari, 1997; Dykens et al., 2002), which is low compared with children with other intellectual disabilities. However, comparison of these rates to typical peers and siblings of children with DS indicates that their behavioral problems are significant. In a study of children with DS between age 5 and 15 years compared with their siblings without developmental delay, children with DS exhibit more overall maladaptive behavior, including inattention and impulsivity (Cuskelly & Dadds, 1992).

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The patterns of behavioral disorders appear to change with increasing age (Chapman et al., 1998; Dykens et al., 2002; Nicham et al., 2003). For example, externalizing disorders (dominant, opposition, hyperactivity, impulsivity, inattention) are more frequent during childhood, whereas internalizing behavior problems (shyness, decreased confidence) are more common in adolescence and adulthood (Nicham et al., 2003). Dykens et al. (2006) also revealed similar patterns in a cohort of 211 individuals with DS. Increased externalizing symptoms (aggression and delinquency) is present between 4 and 19 years in contrast to older adolescents who are vulnerable to internalizing symptoms (withdrawal, somatic, anxiety). This shift in behavior from childhood to adolescence appears unique in DS because individuals in other groups with intellectual disability do not have similar age-related withdrawal (Dykens, 2003). Dykens et al. (2002) have postulated that subtle increases in internalizing symptoms over the adolescent period may increase the risk for later-onset depressive disorders, mood or behavioral changes. The risk for psychopathologies continues through adulthood, and it becomes a challenge to determine if it is influenced by age-related cognitive decline or to clinical dementia of the Alzheimer type (Holland et al., 2000). In addition to Alzheimer’s disease, adults with DS are prone to depression, with an estimated rate of 11%, compared to only 4% in adults with other mental retardation (Collacott et al., 1992). Depressed mood, crying, decreased interest, psychomotor slowing, fatigue, appetite/weight change, and sleep disturbance are symptoms observed in individuals with DS and major depression (Capone et al., 2006). Lack of interest in activities with withdrawal, mutism, psychomotor retardation, low mood, decreased appetite, weight loss, and insomnia may be present. Verbal expression of preoccupations of suicide, death, and guilt are not common in adults with DS and major depression (Myers & Pueschel, 1995). Risks for depression that are unassociated with dementia include several factors associated with the challenges in transitioning from childhood to adulthood. As children with DS become older, they become aware that they are different, with loss or changes in relationships with peers (Capone et al., 2006). Furthermore, they may not have the appropriate mechanism to cope with stress, transitions, and changes in their life. They are also prone to obesity and other medical issues, such as hypothyroidism, which may lead to a sedentary life style. As a result, withdrawal and depression may begin to emerge. In adults with DS, the early, preclinical stages of dementia include behavioral and personality changes as opposed to memory changes (Ball et al., 2006). Thus, symptoms of depression and dementia of the Alzheimer type in adults with DS may appear very similar. In adults with DS and dementia, low mood, restlessness, disturbed sleep, excessive uncooperativeness, and auditory hallucination may be present (Cooper & Prasher, 1998).

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Since the symptoms of dementia and depression are closely related, it is important to consider both conditions in the differential diagnosis in order to provide appropriate treatment. Co-occurrence of autism spectrum disorder (ASD) or pervasive developmental disorders in DS may exist. The prevalence of ASD among children with DS ranges from 1 to 13% (Capone et al., 2005; Kent et al., 1999; Myers & Pueschel, 1991). Kent et al. (1999) estimated the prevalence of ASD in children with DS to be 7% using the Childhood Autism Rating Scale, Asperger Syndrome Screening Questionnaire, and International classification of Diseases (ICD-9) criteria. Capone et al. (2005) estimated a prevalence rate of 13% from clinic population, although the ascertainment may be biased since subjects are based on referrals. In this cohort, the DS and ASD group has lower IQ levels and higher levels of lethargy, stereotypy, and hyperactivity compared to DS without ASD. Additionally, Myers et al. (1995) sampled 497 individuals with DS and reported 13% of children under age 10 with externalizing behavioral problems, 20% of those between 10 and 20 years of age, and 25% of those over 20 years of age. The most significant problems include attention, conduct/ oppositional, and aggressive behaviors in those younger than 20 years. Other findings include 1% with infantile autism, 9% with childhood psychosis, 15% conduct problems, and 3% emotional disturbances. Similar to children with DS, psychiatric disorders are not common in adults with DS compared to adults with intellectual disabilities of other etiology. In 164 adults with DS, the prevalence of a psychiatric disorder is 26% compared to other studies which revealed a 32–59% rate in adults with mental retardation (Lund, 1985; Myers & Pueschel, 1995). Symptoms of delusions and hallucinations may exist together with social isolation, bland affect, apathy, and sleep disturbance in adults with DS and psychiatric disorders, and are often mistaken for major depression (Capone et al., 2006; Myers & Pueschel, 1994). Although psychiatric disorders seem uncommon in adults with DS, there continues to be gaps in our knowledge regarding the development and course of these problems across the lifespan (Dykens, 2007). It is essential to have standardized criteria and diagnostic procedures for adults with DS in order to improve intervention and treatment for these individuals and their families.

7. Summary Importantly, the prevalence of DS at birth has the potential to increase with the trend for women to extend their reproductive life span into their late 30s and 40s. Moreover, individuals with DS now have an increased life expectancy due to community-based care and medical and health

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improvements; thus, they have the potential to live long and productive lives. In this review, we have indicated the need to conduct additional epidemiological studies to determine the prevalence, cause, and clinical significance of the syndrome throughout the lifespan. From this knowledge, we can begin to determine the influence of specific DS-associated medical conditions on cognitive and behavioral outcomes. This will lead to appropriate intervention and treatment to enhance the quality of life for individuals with DS.

ACKNOWLEDGMENTS NIH/NCRR 1KL2RR025009, National Down Syndrome Society, Emory Egleston Children’s Research Center ( JV); NIH R01 HD38979, and NIH R01 HL083300 (SLS).

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