Physiol Rev 89: 887–920, 2009;
doi:10.1152/physrev.00032.2007.
Aneuploidy: From a Physiological Mechanism of Variance
to Down Syndrome
MARA DIERSSEN, YANN HERAULT, AND XAVIER ESTIVILL
Genes and Disease Program, Genomic Regulation Center-CRG, Pompeu Fabra University, Barcelona
Biomedical Research Park; CIBER de Enfermedades Raras; and Barcelona National Genotyping Center,
Barcelona, Catalonia, Spain; Morphogenesis and Molecular Embryology, University d’Orléans, UMR 6218,
IEM, CNRS, and UPS 44 TAAM, CNRS, Institut de Transgenose, Orleans France
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
I. Introduction
II. Mechanisms That Lead to Aneuploidy: From Aneusomic to Genomic Rearrangements
A. Nondisjunction and aneusomies
B. Genomic rearrangements and genomic disorders
III. Aneuploidy in the Brain: the Case of Down Syndrome as a Prototype of Extra Genomic Material
A. Neurocognitive profile in Down syndrome
B. Genetic shaping of the Down syndrome brain
C. Brain topology of the cognitive impairment in Down syndrome
D. Nature and nurture in Down syndrome: the building of a trisomic brain
IV. Modeling Down Syndrome
A. The early phase
B. Genetic tools for creating aneuploid models
C. Recent outcomes from new models for Down syndrome
D. Elucidating therapeutic pathways using mouse models
V. Future Perspective: From Phenotype to Genotype and Back
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Dierssen M, Herault Y, Estivill X. Aneuploidy: From a Physiological Mechanism of Variance to Down Syndrome.
Physiol Rev 89: 887–920, 2009; doi:10.1152/physrev.00032.2007.—Quantitative differences in gene expression emerge
as a significant source of variation in natural populations, representing an important substrate for evolution and
accounting for a considerable fraction of phenotypic diversity. However, perturbation of gene expression is also the
main factor in determining the molecular pathogenesis of numerous aneuploid disorders. In this review, we focus
on Down syndrome (DS) as the prototype of “genomic disorder” induced by copy number change. The understanding
of the pathogenicity of the extra genomic material in trisomy 21 has accelerated in the last years due to the recent
advances in genome sequencing, comparative genome analysis, functional genome exploration, and the use of model
organisms. We present recent data on the role of genome-altering processes in the generation of diversity in DS
neural phenotypes focusing on the impact of trisomy on brain structure and mental retardation and on biological
pathways and cell types in target brain regions (including prefrontal cortex, hippocampus, cerebellum, and basal
ganglia). We also review the potential that genetically engineered mouse models of DS bring into the understanding
of the molecular biology of human learning disorders.
I. INTRODUCTION
Fifty years after the discovery of the molecular basis
of Down syndrome by Lejeune et al. (214), aneuploidy,
defined as an abnormal number of copies of a genomic
region, is recognized as a common mechanism of human
genetic disease, often leading to abnormal gene expression patterns with over- or underexpression of specific
genes (59, 156). Classically, the term was restricted to the
presence of supernumerary copies of whole chromowww.prv.org
somes (trisomy) or the absence of chromosomes (monosomy). However, with the advent of high-resolution molecular tools to scan the genome, novel aneuploidy syndromes are being identified, and the definition has been
extended to include deletions or duplications of subchromosomal regions. Good examples are segmental duplications (SDs) and copy number variants (CNVs) that can
contribute to phenotypic diversity and to disease (6, 112,
137, 166, 324, 333–335), influence gene expression indirectly through positional effects, predispose to deleteri-
0031-9333/09 $18.00 Copyright © 2009 the American Physiological Society
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DIERSSEN, HERAULT, AND ESTIVILL
Physiol Rev • VOL
21q22.3), identified by studying human patients with partial segmental duplication of HSA21, is sufficient when
triplicated, to give rise to most of the DS phenotypic
traits. However, several evidences have questioned this
hypothesis. First, analysis or a large panel of human patients with segmental duplications revealed that genes
located in regions of HSA21 outside the DSCR also contribute to the DS phenotypes (202, 229), and work on
mouse models that will be described in section IV, led to a
similar conclusion showing that triplication of the region
homologous to the DSCR in mice does not recapitulate
the DS phenotypes (265).
One reason may be that increased copy number does
not always correspond with increased gene expression
level or even less with increased gene function. Even
though most of the expression studies comparing trisomic
to euploid tissues support the hypothesis of increased
mRNA levels due to gene dosage (56, 130, 185, 230),
several reports could not find increased protein levels in
trisomic brains for some specific HSA21 genes (198), and
others have shown up- or downregulation of genes located on disomic chromosomes. One possible explanation for these controversial results on expression levels
could be that regulatory mechanisms are also deregulated. One fascinating example was recently given showing that trisomy 21 gives rise to overexpression of HSA21
miRNAs that could result in turn in decreased expression
of specific target proteins and thereby contribute to features of the DS phenotype. This interesting finding was
obtained by Kuhn et al. (205) that detected overexpression of several HSA21-encoded miRNAs, namely, miR-99a,
let-7c, miR-125b-2, miR-155, and miR-802, in fetal brain
and heart specimens from individuals with DS when compared with age- and sex-matched controls. This makes
clear that to understand the impact of gene expression
alteration in DS, we will have to consider new and previously overlooked elements such as transcription factors,
noncoding RNAs (microRNAs, associated small interfering RNAs, other unclassified non-translated RNAs; 205,
239, 329), epigenetic processes (e.g., CpG dinucleotide
methylation, histone acetylation and deacetylation), and
mRNA transcript variation (e.g., alternative promoters,
alternative polyadenylation sites, differentially spliced exons and introns). In particular, the unexpected abundance
and functional significance of noncoding RNAs has to
be explored in DS. These RNAs control a remarkable
range of biological pathways and processes, all with
obvious consequences, such as initiation of translation,
mRNA abundance, transposon jumping, chromosome
architecture, stem cell maintenance, and the development of brain.
An additional problem in DS is the temporal pattern
of change and regulation of overexpressed genes along
the entire life-span, and the impossibility of separating the
effects of trisomy that disturb development from those
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ous genetic changes, or provide substrates for chromosomal changes (115, 116, 124, 228). The recently published
catalog of CNVs and SDs of the human genome in different populations has demonstrated the ubiquity and complexity of these forms of genetic variation (290; see below). Thus, to include all these possibilities, the term
aneuploidy had to be redefined. Suggested alternatives
are microaneuploidy or segmental aneuploidy, implying
that the pathogenesis of the disorder is the result of
inappropriate dosage of critical genes within a discrete
genomic segment or of changes in the expression pattern
of neighboring genes. In support of this assumption, highthroughput expression profiling in a number of organisms
has revealed that variation in gene expression levels
within and among populations is abundant, with a large
proportion of genes showing significant patterns of interindividual variation (244, 349). These new data suggest
that quantitative differences in gene expression are responsible for a significant amount of variation in natural
populations that can lead to physiological or pathological
differences among individuals (83; see next section).
The most common example of neurogenetic aneuploid disorder is Down syndrome (DS; OMIM 190685), a
neurodevelopmental disorder caused by the presence of
an extra copy of all or part of human chromosome 21
(HSA21 for Homo sapiens chromosome 21). Trisomy 21
can be divided into four categories according to the size
of triplicated genomic region: complete trisomy, partial
trisomy, microtrisomy, and single-gene duplication. The
majority of DS patients (⬎95%) have three complete copies of human chromosome 21, and others have mosaics or
translocations. The trisomic condition in DS is of particular interest for understanding how deregulated gene expression in the brain will lead to altered brain function
and specifically to subnormal intellectual functioning. In
trisomy 21, the effects of the gene-dosage imbalance on
brain phenotypes have been explained by two hypotheses: 1) the “gene-dosage effect” hypothesis claims that DS
phenotypes are determined by increased dosage of a subset of dosage-sensitive genes, and of their encoded proteins, especially during development (5, 79, 202, 229), and
2) the “amplified developmental instability” hypothesis
holds that HSA21 trisomy determines general alteration in
developmental homeostasis (for review, see Refs. 13,
303).
The gene-dosage hypothesis proposes that the 1.5fold increase in the expression of some, if not all, of the
around 430 genes that have been identified on HSA21
(http://chr21db.cudenver.edu/; Refs. 74, 131, 157, 297, 298,
302, 338) is responsible for the brain anomalies and moderate mental retardation of individuals with DS (12, 100).
According to this hypothesis, genes encoded by HSA21 in
the trisomic state are overexpressed, thus leading to an
imbalance of critical genes (79). It has been proposed that
the so-called DS-critical region (DSCR; part of 21q22.1 to
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
Physiol Rev • VOL
genes whose expression varies little between individuals
would be predicted to lead to the more penetrant phenotypes, whereas genes with high variation in expression would contribute to incompletely penetrant or
variable DS-related phenotypes. Considering the importance of allelic variation to the outcome of the DS
phenotype, the “critical region” (79) could be interpreted as a region encompassing genes with less allelic
variation, thus contributing more importantly to DS
phenotypes (265–267).
Finally, the assumption that several HSA21 genes
may be better candidates for mental retardation is tempting because it may open new therapeutic possibilities.
Should one specific gene in trisomy give rise to a specific
phenotype, its normalization would be of therapeutic
value. To understand the genotype/phenotype correlation
completely, functional information on the impact of specific subchromosomal aneuploidies is necessary because
this will give information on the molecular networks in
which candidate genes operate and on how changes in
these networks lead to changes in disease traits. However, annotation of the chromosome continues and the
functions of many genes on HSA21 remain uncertain,
making it difficult to identify good candidates. The major
challenge still remains to not only confirm that over- or
underexpressed genes are truly those involved in specific disease traits, but to elucidate the functional roles
that these genes play with respect to disease. Probably
genes with a broad impact, affecting genetic regulatory
circuits, or influencing feedback loops, buffers, and
amplifiers within these circuits will be of special interest for intervention (14).
II. MECHANISMS THAT LEAD TO ANEUPLOIDY:
FROM ANEUSOMIC TO GENOMIC
REARRANGEMENTS
According to classical cytogenetics definition, aneuploidy corresponds to the loss or gain of a complete
chromosome leading to an abnormal karyotype. When a
single chromosome is lost (2n-1), it is called a monosomy.
In these cases the daughter cell(s) with the defect will
have one chromosome missing from one of its pairs.
When a chromosome is gained, it is called trisomy, in
which the daughter cell(s) with the defect will have one
chromosome in addition to its pair. The biological consequences of loss or gain of whole chromosomes usually are
devastating and are the hallmark of numerous pathological conditions in humans. Now, with refinement of the
DNA analysis technology, the term is used to describe
changes in copy number that affect only portions, small or
large, of a chromosome.
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that alter function of mature cells. Upregulation of trisomic genes in a specific cell, in a particular time frame in
the adult period, may lead to altered function but could
also produce a developmental error that has later functional consequences (developmental versus functional effects). Thus important goals will be to determine the
relationship between microscale transcriptional temporal-spatial profiles and specific cellular phenotypes. Moreover, both cell autonomous and nonautonomous effects
may also contribute to specific DS phenotypes so that
genotypically trisomic cells can cause other cells (regardless of their genotype) to exhibit a mutant phenotype
(187). An example of cell-autonomous deficits has been
observed in response to Sonic hedgehog (SHH) in trisomic neuronal precursor cells in the cerebellum of
mouse models of DS (304 and see sect. IV).
Other differences between trisomic and euploid individuals may include presence/absence of an extra centromere, a potential trisomic maternal environment during
development, and the presence of trisomy in all or in part
of the cells (mosaicism). The centromere plays a fundamental role in accurate chromosome segregation during
mitosis and meiosis in eukaryotes. Its functions include
sister chromatid adhesion and separation, microtubule
attachment, chromosome movement, formation of the
heterochromatin structure, and mitotic control (which
correct functioning is essential for cell growth and mitotic
progression). Thus it could be proposed that an extra
centromere could have deleterious consequences and
could contribute to DS-associated phenotypes, including
the altered growth rates and decreased mitotic index and
proliferation rates described in DS patients and mouse
models.
Taken together, these data demonstrate that the elucidation of the exact nature of the genetic mechanisms
and molecular pathways that underlie the cognitive alterations in DS is still far from clear. One additional problem
in establishing a genotype-phenotype correlation in DS is
the presence of a broad phenotypic variability among DS
individuals. This directly relates to the fact that trisomy 21
can have differential pathogenicity on individual genomes. One example is syndrome-specific facial abnormalities: we can easily recognize a DS patient across
different races, but each DS individual is different and one
can see their resemblance with their family. Thus, even
though they share some morphogenetic characteristics,
these coexist with family- and ethnic/race-specific traits
(44, 362).
Studies of expression variation of HSA21 genes in
lymphoblastoid cells (282) suggested that allelic differences are likely to be important determinants of the phenotypic variability of DS. These studies have shown considerable overlap in total expression levels between cells
from normal and trisomy 21 individuals due to allelic
variation, leading to the hypothesis that overexpressed
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DIERSSEN, HERAULT, AND ESTIVILL
A. Nondisjunction and Aneusomies
B. Genomic Rearrangements and
Genomic Disorders
Genomic rearrangement is the general term for alterations of the architecture of chromosomes, which can
lead to duplications, deletions, and inversions of a given
genomic segment; to translocations, additional chromosomal material (marker chromosomes), and isochromosomes (metacentric chromosomes produced during mitosis or meiosis); or to other complex rearrangements (347).
Chromosome rearrangements have been described since
the very early use of cytogenetic and molecular tools to
study human disorders (67, 68, 106, 138, 383). The identification of recurrent genomic changes in some diseases
led to coinage of the term genomic disorders to refer to
clinical phenotypes that are due to genetic alterations that
affect a relatively large segment of the genome (227).
Genomic disorders often involve genomic rearrangements that span large deletions or duplications and affect
several genes.
Genomic rearrangements can be sporadic or recurrent (Figs. 1 and 2). Although most originate in the germ
cells, they can also be of somatic origin. Independently of
their origin, rearrangements often are produced of specific sequences or regions of the genome. Recurrent rearrangements tend to have breakpoints in specific sequences,
while most sporadic changes have different breakpoints.
Nonallelic homologous recombination (NAHR) between sequences of high level of identity (⬎90%), known as low copy
Physiol Rev • VOL
FIG. 1. Types of structural variation of the human genome. Representation of a human chromosome with the reference order of four
segments (A, B, C, and D) with respect to the annotated sequence of the
human genome. Deletions, duplications, or inversions could occur at the
sequence of reference. The finding of such events in the population can
depend on the viability of the rearrangements or the selective advantage
that they might have. Some segments can be amplified and become a
segmental duplication, which may lead to a change in copy number.
Some copy number variants (CNVs) have a complex organization with
different types of changes within the same cluster.
repeats (LCRs, also defined as duplicons and segmental
duplications), facilitates the occurrence of rearrangement
(227), whereas rearrangements that do not occur in the
same specific genomic region are the result of nonhomologous end-joining (NHEJ) rather than NAHR (335).
Over 50 genomic disorders have been identified
(Table 1). With the wide use of genomic arrays (49), we
are now able to explore the genome in a systematic way
and with exhaustive coverage. This has led to the identification of new genomic changes associated with clinical
disorders of unknown molecular basis (374), and to the
definition of clinical syndromes that were previously not
recognized (331, 334).
1. Segmental duplications and copy number variants
Segmental duplications were initially defined based
on comparison of segments sharing at least 90% identity
with known or reference genome sequence duplications
(20, 55, 332). Over 5% of the human genome is composed
of segmental duplications (20, 55, 105). These can be
divided into intra- and interchromosomal segmental duplications, although a subset of duplications occurs both
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Nondisjunction refers to the failure of chromosome
pairs to separate properly during cell division. It can be
produced by a failure of homologous chromosomes to
separate in meiosis I, or the failure of sister chromatids to
separate during meiosis II or mitosis. The result of this
error is a cell with an imbalance of chromosomes. Abnormalities arising from nondisjunction events cause cells
with aneusomy (additions or deletions of entire chromosomes). Most aneuploidy cases derive from errors in maternal meiosis I, with maternal age being a risk factor for
most human trisomies (155). It has been shown that alterations in recombination are an important contributor
to meiotic nondisjunction. In DS, the parental origin of the
extra HSA21 and the meiotic versus mitotic origin are
known. Errors in meiosis that lead to trisomy 21 are
mainly of maternal origin with an association with advanced maternal age, while ⬃5% occur during spermatogenesis. Most errors in maternal meiosis occur in meiosis
I, while maternal meiosis II errors constitute 20% of all
cases of trisomy 21. In 4.5% of the cases, the supernumerary chromosome results from an error in mitosis (11, 264,
336).
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
891
very rudimentary for the majority of CNVs, in particular
for those that have a complex organization or that are
multiple alleles. An estimate of the number and type of
CNVs that remain to be discovered indicates that the
majority of CNVs are smaller than those described so
far.
2. Copy number variants, genomic variability,
and disease
intra- and interchromosomally. These dual cases often
reflect a complex organization for some genomic sequences. Intrachromosomal segmental duplications that
are organized in tandem along the chromosome often lead
to deletion, duplication, or inversion rearrangements
(228).
Comparison of sequences from two individuals indicates that the genomic structure of the human genome
varies largely (194). Two reports in 2004 described that
the human genome varies in its sequence at several regions (177, 325). This opened the concept of CNVs, which
were originally described in 1980 in the ␣-globin gene
(138). These reports were followed by others that, either
directly (221, 332) or indirectly (59, 241), explored structural variation of the human genome (115, 194). Most of
these initial studies were not complete, as the type of
tools employed and samples that were analyzed only provided a partial view of the structural variability of the
human genome. Systematic analyses of the samples used
for the International HapMap Consortium (180) have
shown that possibly up to 12% of the human genome
varies at the structural level (394). Redon et al. (290)
showed that the human genome contains at least 1,400
CNV regions, which correspond to a much larger number
of loci. The most recent version of the Genome Diversity
web page (http://projects.tcag.ca/variation/) includes over
15,500 CNV loci (177).
The number of CNVs currently known is far from
complete, as the efforts made to elucidate their localization and characterization at the structural level are
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3. Aneuploidy syndromes and phenotypic variability
Phenotypic variability associated with aneuploidy
has mainly been attributed to variability in gene expression of the genes located in the aneuploid regions or to
the contribution of other genes of the genome (13). However, genomic imbalances involving genes of the aneuploid chromosome could also contribute to the phenotype
(26). Some genes located in the aneuploid chromosome or
the aneuploid chromosomal region could be within a CNV
region. If these genes are sensitive to gene dosage, their
copy number could have functional consequences, either
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FIG. 2. Main mechanisms that lead to CNV changes. Nonhomologous recombination between sequences with a high level of identity
(segmental duplications, low copy repeats, or duplicons) (over 90%)
might cause the duplication or deletion of genetic material. Depending
on the peculiarities of genes involved in the rearrangements, a clinical
phenotype could be observed. Inverted duplicons might cause an inversion of the genetic material, but other types of changes could occur
depending on the complexity of the duplicons, which often contain
sequences that are in a parallel orientation, in which case deletions or
duplications can result.
Variability of the human genome sequence has been
used to explore diversity, to construct genetic maps, and
to identify the genes responsible for more than 2,000
human monogenic disorders (http://www.ncbi.nlm.nih.
gov/Omim/). Single nucleotide polymorphisms (SNPs) are
the most abundant type of genetic markers with over 12
million entries deposited in public databases (http://www.
ncbi.nlm.nih.gov/SNP/). The HapMap Consortium has
genotyped nearly four million SNPs (http://www.hapmap.
org/) and has reported blocks of linkage disequilibrium
(180), which should help to define the location of genetic
changes responsible for different phenotypes in association studies of common disorders and complex traits.
Although genetic variability was initially thought to
be mainly restricted to SNPs and to small repeat amplifications, CNVs have emerged as a common and useful
source of variability. CNVs and structural variants include
deletions, duplications, inversions, and complex rearrangements (Figs. 1 and 2). They are observed variables
during genetic transmission and sometimes also during
somatic replication (279). CNVs are now considered a
common source of genomic variability in several organisms (143, 274).
The phenotypic consequences of these submicroscopic variations have only been defined for few loci.
Thus, while a typical SNP implies one single nucleotide
change, CNVs can affect between one kilobase and several megabases of DNA per event, corresponding to a
significant fraction of the genome sequence. The extensive number of CNVs in the genomes of individuals has
provided new hypotheses about phenotypic variability in
inherited disorders, aneuploidy syndromes, and common
disorders (26).
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TABLE
DIERSSEN, HERAULT, AND ESTIVILL
1.
Syndromes and disorders associated with copy number variants
Syndrome (OMIM)
Locus
End
1p36
1q21.1
1q21.1
1
5189627
144112610 144639480
144979551 146204123
1q23.3
1q23.3
1q23.3
2q32.2
2q37
3q29
4p16.3
4q22.1
5p15.33-p15.2
5q22.2
5q23.2
159741844
159741844
159741844
198190560
239619630
197156626
1
90865728
1
112129495
126045879
5q35.3
6p21.3
7q11.23
175063008 177389150
32056289 32121878
71970679 74254837
7q11.23
7q21.3
7q34
8p23.1
8q12
9q34
11p11.2
15q11.2-q13.1
15q11.2-q13.1
15q24
71970679 74254837
95369796 96619422
141595001 142195000
8156705 11803128
58300001 61356508
137934844 140238455
43924561 46080959
20197557 26896736
20197557 26896736
72158366 73949331
Mb
References
5.2 Slavotinek et al. 1999
0.2 Klopocki et al. 2007
1.2 Christiansen et al. 2004
SDs CNVs
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
No
Yes
No
No
Yes
Yes
Yes
No
Yes
Yes
Yes
No
Yes
No
No
2.3 Kurotaki et al. 2002
0.1 Yang et al. 2007
2.1 Somerville et al. 2005
Yes
Yes
Yes
Yes
Yes
Yes
2.1
1.1
0.6
3.5
2.3
2.3
2.0
5.6
5.6
1.6
BaYes et al. 2003
Scherer et al. 1994
Le Maréchal et al. 2006
Devriendt et al. 1999
Vissers et al. 2004
Kleefstra et al. 2006
Wakui et al. 2005
Sahoo et al. 2005
Chai et al. 2003
Sharp et al. 2007
Yes
No
Yes
Yes
No
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
No
Yes
No
Yes
Yes
Yes
159964557 0.2 Aitman et al. 2006
159964557 0.2 Fanciulli et al. 2007
159964557 0.2 Fanciulli et al. 2007
204915184 8.1 Van Buggenhout et al. 2004
242951149 3.1 Aldred et al. 2004
198982265 1.7 Willatt et al. 2005
2043467 1.9 Zollino et al. 2000
90975866 0.1 Singleton et al. 203
11776854 11.5 Mainardi et al. 2001
112249276 0.1 Sieber et al. 2002
126232850 0.1 Padiath et al. 2006
16p11.2-p12.2
16p13.3
17p13.3
17p12
21400001
3721465
1
14014755
30100000
3801247
2492178
15435499
8.7
0.1
2.3
1.4
Ballif et al. 2007
Bartsch et al. 2006
Cardoso et al. 2003
Boerkoel et al. 1999
Yes
No
Yes
Yes
Yes
No
Yes
Yes
17p12
14014755
15435499
1.4 Boerkoel et al. 1999
Yes
Yes
17p11.2
17p11.2
17q11.2
17q12
16529776
16526703
26082074
31430106
20286163
20422653
27337969
31889184
3.8
3.6
1.1
0.5
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
17q12
17q21.3
31799963
40988250
33389579
41565981
Yes
Yes
Yes
Yes
18q21.33-qter
21q21.3
59449684
25959827
1.6 Bellanné-Chantelot et al. 2005
0.5 Koolen et al. 2006; Shaw-Smith
et al. 2006
76117153 16.7 Katz et al. 1999
26470350 0.3 Rovelet-Lecrux et al. 2006
Yes
No
No
No
22p13-q11.21
22q11.21
1
17092539
16977306 17 Footz et al. 2001
20009525 3.0 Ryan et al. 1997
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
No
Yes
Yes
Chen et al. 1997
Potocki et al. 2007
Dorschner et al. 2000
Gonzalez et al. 2005
22q11.21
17092539 20009525 3.0 Yobb et al. 2005
22q13.33
49449104 49591432 0.1 Luciani et al. 2003
22q11-q13.33
16977306 49691432 32.5 Emmanuel et al. 2007
Xp22.33
429051
837875 0.4 Benito-Sanz et al. 2006
Xp22.31
6451572
8127696 1.7 Van Esch et al. 2005
Xq22.2
102609218 103098934 0.5 Inoue et al. 2002
Xq28
152535441 153044193 0.5 Van Esch et al. 2005
Yq11.21
12934025 13664255 0.7 Vogt et al. 1996
Yq11.221-q11.23 18449857 26569157 7.7 Yen 1998
Chromosome positions are referred to BAC clones, genes, or segmental duplications known to be involved with the syndrome or disorder (key
information about positions should be obtained from the cited and related references). Mb, estimated size in megabases; SDs, segmental
duplications; CNVs, copy number variants.
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1p36 microdeletion syndrome
Thrombocytopenia-absent radius syndrome (%274000)
Chromosome 1q21.1 recurrent
microdeletion/microduplication
Systemic lupus erythematosus (SLE) (#152700)
Wegener’s granulomatosis (%608710)
Microscopic polyangiitis
Chromosome 2q32.2 deletion syndrome
Chromosome 2q37 monosomy
Chromosome 3q29 microdeletion syndrome (%609425)
Wolf-Hirschhorn syndrome (#194190)
Parkinson’s disease (#168601)
Cri du Chat syndrome (5p deletion) (#123450)
Familial adenomatous polyposis (⫹175100)
Autosomal dominant leukodystrophy (ADLD)
(#169500)
Sotos syndrome (#117550)
Systemic lupus erythematosus (SLE) (#152700)
Williams-Beuren region duplication syndrome
(#609757)
Williams-Beuren syndrome (WBS) (#194050)
Split hand/foot malformation 1 (SHFM1) (%183600)
Hereditary pancreatitis (#167800)
Chromosome 8p23.1 deletion syndrome
CHARGE syndrome (#214800)
Chromosome 9q34 microdeletion syndrome
Potocki-Shaffer syndrome (#601224)
Angelman syndrome (types 1 and 2) (#105830)
Prader-Willi syndrome (types 1 and 2) (#176270)
Chromosome 15q24 recurrent microdeletion
syndrome
Chromosome 16p11.2-p12.2 microdeletion syndrome
Rubinstein-Taybi syndrome (#610543)
Miller-Dieker syndrome (MDS) (#247200)
Charcot-Marie-Tooth syndrome type 1A (CMT1A)
(#118220)
Hereditary liability to pressure palsies (HNPP)
(#162500)
Smith-Magenis syndrome (#182290)
Potocki-Lupski syndrome (#610883)
NF1-microdeletion syndrome (⫹162200)
Human immunodeficiency virus type 1 susceptibility
(#609423)
Renal cysts and diabetes (RCAD) (#137920)
Chromosome 17q21.31 microdeletion syndrome
(*610443)
Chromosome 18q deletion syndrome (#601808)
Early-onset Alzheimer’s disease with cerebral amyloid
angiopathy (#609065)
Cat-eye syndrome (type I) (#115470)
DiGeorge syndrome (DGS) (#188400), velocardiofacial
syndrome (#192430)
Chromosome 22q11 duplication syndrome (#608363)
Chromosome 22q13 deletion syndrome (#606232)
Emanuel syndrome (OMIM #609029)
Leri-Weill dyschondrostosis (LWD) (#127300)
Steroid sulphatase deficiency (STS) (%300001)
Pelizaeus-Merzbacher disease (#312080)
Xq28 (MECP2) duplication (⫹300005)
Y-linked azoospermia (AZFa) (#415000)
Y-linked azoospermia (AZFb and or AZFc) (#415000)
Start
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
Physiol Rev • VOL
schizophrenia in Caucasian population (126), and a few
CNV were shown to disrupt candidate genes in schizophrenia patients (375). CNV may also act as a susceptibility factor as has been described at the 7q11.23 segmental
duplications for the Williams-Beuren syndrome deletion
(30, 70). Microdeletions and microduplications in genes
have been associated with autism (30, 108, 116, 186, 237,
384).
The use of technologies such as sequencing or deeper
array methods, which are able to explore the genome at
higher resolution in many individuals with the development of new tools for statistical and epidemiologic analysis, should provide a more comprehensive picture of the
structural variation of the human genome (98, 201) and
will lead to a better understanding of human disease
(181).
III. ANEUPLOIDY IN THE BRAIN: THE CASE
OF DOWN SYNDROME A S A PROTOTYPE
OF EXTRA GENOMIC MATERIAL
Aneuploidy usually manifests as a highly variable
constellation of phenotypes including malformations of
different systems and organs (e.g., cardiac and gastrointestinal), morphogenetic abnormalities affecting craniofacial structure, limbs, and digits, and hematological and
metabolic abnormalities. Most aneuploidy syndromes
present a high incidence of brain phenotypes that affect
learning, language, and behavior and show increased vulnerability for psychiatric disorders. The susceptibility of
the brain to gene dosage changes probably depends on
the unprecedented degree of cellular diversity, anatomical asymmetries (laterality) and specialized regional micro domains, regional interconnections, structural and
functional plasticity, and exquisite environmental responsiveness that characterizes mammalian and in particular
primate nervous system. An increasing number of reports
of rearranged and aneuploid chromosomes in brain cells
suggest a link between developmental chromosomal instability and brain complexity (132). Aneuploidy may especially affect brain regions, such as the cerebral cortex,
in which the phenotypic properties of neuronal and nonneuronal cells are largely the result of unique combinations of gene products so that the cell pattern of gene
expression is crucial for achieving cell phenotypes and
cellular diversification. Interestingly, the assessment of
chromosome variations in normal mouse and in normal
and diseased human brain has indicated that aneuploidy
is present in a high proportion of neural cells (188, 293,
294), thus giving rise to a mosaicism of intermixed aneuploid and euploid cells. Approximately 33% of neural progenitor cells display genetic variability, manifested as
chromosomal aneuploidy that encompasses both loss and
gain of chromosomes. In the mature brain, aneuploid cells
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boosting or diminishing expression levels, with consequences to the phenotype. Thus CNVs should be considered as potential mediators of the phenotypic variability
of aneuploidies (26). Through altering gene dosage, disrupting genes, or perturbing regulation of their expression, even at long-range distances, CNVs exert their actions on numerous genes, therefore potentially having
many phenotypic consequences (244, 349). Genome-wide
efforts to uncover genomic changes involved in patients
with clinical alterations are underway (http://www.
sanger.ac.uk/PostGenomics/decipher).
CNVs have been found as events of common genetic
disorders in human and other mammalian systems (148,
212, 275, 382). Common CNVs have been detected in
subjects affected by several inherited disease. Cases of
hereditary pancreatitis are caused by duplications or triplications of the cationic trypsinogen gene (211). Somehow
the susceptibility to human immunodeficiency virus
(HIV)-1 infection may vary depending on copy numbers of
the CCL3L1 chemokine gene (137). Individuals with low
copy numbers of CCL3L1 related to their ethnic background have markedly enhanced HIV-1/acquired immunodeficiency syndrome (AIDS) susceptibility. Increase in
CCL3L1 gene dosage also influences predisposition to
autoimmune disease such as rheumatoid arthritis (242).
Similarly, a copy number polymorphism in FCGR3 has
shown to predispose to several types of systemic autoimmune disorders, such as systemic lupus erythematosus
(SLE), microscopic polyangitis, and Wegener’s granulomatosis (6, 109, 386). CNVs in complement component C4
(C4A and C4B) lead to different susceptibilities to SLE
(398). Compared with healthy subjects, patients with SLE
have lower copy numbers of C4 and C4A. Interestingly,
variability in copy number for the C4 genes and the genetic association with markers of the major histocompatibility complex (MHC) on chromosome 6p21.32 has been
known to be variable for several years, but their complex
organization and their relationship with SLE has not been
revealed until now. Variability within the ␤-defensin 2
gene (DEFB4) shows that low DEFB4 gene copy number
predisposes to Crohn’s disease, with diminished ␤-defensin expression in colon of patients with the disease (112).
Finally, the defensin locus has been found to be associated with susceptibility to psoriasis (166).
Several studies point clearly to CNV as genetic cause
of cognitive and neuropsychiatric disorders (63, 375).
Multiple cases of patients with Parkinson’s disease due to
genomic duplication or triplication of the ␣-synuclein
gene (SNCA) have been reported, suggesting that SNCA
may contribute to hereditary early-onset parkinsonism
with dementia (344). Several cases of duplication of the
amyloid precursor protein (APP) have been described in
families with early-onset Alzheimer’s dementia with cerebral amyloid angiopathy (308). On the contrary, decrease
in CNTNAP2 dosage is associated with epilepsy and
893
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DIERSSEN, HERAULT, AND ESTIVILL
Physiol Rev • VOL
358, 359), a fact that may explain the damaging effects of
gene deregulation on the integrity of the cerebral cortex.
Although this structure-function relationship at the macroscopic level is obviously important, we cannot overlook
the fact that the mammalian central nervous system, and
particularly the neocortex, contains an enormous variety
of cell types, each with unique morphology, connectivity,
physiology, and function so that each cortical region comprises a highly complicated mix of distinctive cell types.
Since functionally discrete brain regions are delineated by
gene expression patterns, probably genes with regionalized expression patterns will provide potential substrates
for functional differences across brain regions and may be
potential candidates for specific dysfunctional cognitive
patterns (34, 339).
For these reasons, to get real insight into cognitive
dysfunction, it will be necessary to reveal the contributions of genes with highly specific cortical expression
patterns restricted to discrete neuronal populations in
different cortical layers related to higher-level brain function and disease-related dysfunction. Thus the characterization of the full range of neural cell types is essential
to understand the impact of gene expression deregulation on functional neural circuit properties and their
relation to higher cognitive functions and behaviors. To
date, neural expression profiling has lacked the power
to detect effects that involve subsets of cells, since the
techniques used for expression analysis have typically
been applied to large brain regions. Such data are difficult to interpret because they do not resolve specific
brain subregions or even at a lower level, cellular diversity within those structures (184, 198, 234). To address this problem, some projects (The Allen Brain
Atlas project: http://www.brain-map.org; EurExpress:
http://www.eurexpress.org/ee/; 213) have recently taken a
global approach to understanding the genetic structural
and cellular architecture of the mouse brain by generating a genome-scale collection of cellular resolution
gene expression profiles using in situ hybridization
across 20,000 genes.
A. Neurocognitive Profile in Down Syndrome
Although the clinical presentation of DS is variable,
100% of people with trisomy 21 present with mental retardation. Mental retardation is defined as a developmental disability with onset during childhood, characterized
by significant impairment of intellectual functioning and
adaptive skills causing major limitations to living a normal, independent life [Diagnostic and Statistical Manual
of Mental Disorders (DSM-IV); Ref. 280]. In clinical practice, the limitations in intellectual functioning are defined
by an intelligence coefficient (IQ) below 70 (two standard
deviations below the average IQ of 100). In DS patients,
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that express neuronal markers are generated at least in
part by chromosomal missegregation mechanisms during
mitosis. In mouse brain, aneuploid neurons have been
shown to participate in the development of cortical circuitry and to become functionally integrated into that
circuitry (188, 293, 294, 399, 400). If we consider that the
phenotypic properties of different neuronal and nonneuronal cells in the cortex are largely the product of unique
combinations of expressed gene products, gene expression variation profiles are crucial to define cellular diversity. Thus aneuploidy with physiological consequences
exists serving to neural cell diversity or as a mechanism of
selection of specific cells. Conversely, pathogenetic aneuploidy can affect morphogenesis and function in the brain
(187) and correlates with the severity of several neurogenetic disorders (248).
Genes, brain structure, and behavior are strongly
related so that differences in genetic brain maps may be
fundamental for determining individual physiological or
pathological differences in cognition. Abilities such as
speech, consciousness, tool use, symbolic thought, cultural learning, and self-awareness are highly dependent
on the interplay between different genetic and environmental factors in spatial-temporal dimensions, leading to
individual differences in brain organization and function.
In this regard, recent studies of neural tissue from equivalent regions of different primate species suggest a general upregulation of gene expression in the human cortex
compared with the chimpanzee cortex (42, 99, 145, 365).
These upregulated genes tend to be enriched in genomic
regions that have been recently duplicated in human evolution (192, 193) and that can give rise to new genes (93).
But, what could be the mechanisms by which the
anatomical, chemical, and neurophysiological brain abnormalities underlying subnormal intelligence arise from
deregulation of gene expression? Efforts to explain the
major features of mental retardation are still mostly based
on superficial gross neuroanatomical features (e.g., size,
sulcal patterns) and on the analysis of high-level functions
that lack precise neurobiological predictions (e.g., general
intelligence, innate grammar) (for review, see Ref. 257). In
DS, high-resolution magnetic resonance imaging (MRI)
has revealed neuroanatomic abnormalities in the cerebral
cortex that correlate with the cognitive profile of DS
patients (135, 277, 278, 289), thus leading to the idea that
DS cognitive dysfunction is mainly cortical. In support of
this hypothesis, functional data exploring intellectual
functioning, impaired language ability, and impaired adaptative behavior in DS indicate possible deficits in specific corticohippocampal circuits, also involving regions
of the prefrontal and temporal cortices and the cerebellum (see next section) in the phenotypes. Interestingly, in
the last few years, imaging studies have suggested that
these brain structures, especially the frontal and temporal
cortices, are under significant genetic control (45, 134,
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
Physiol Rev • VOL
and which psychometric and functional domains are
more impaired in each DS individual (see Ref. 1). The fact
that not all skills are affected to the same extent in all
persons with DS suggests that either the impact of aneuploidy on brain structures is different among DS individuals or that the functional consequences of relatively
homogeneous structural changes may not affect all DS
patients equally (37, 57, 69, 204, 209, 273, 371). To increase
the complexity of this scenario, individuals with DS may
have additional behavioral and psychiatric problems,
such as disruptive behavior, attention deficit, hyperactivity disorder (6.1%), conduct/oppositional disorder (5.4%),
or aggressive behavior (6.5%); 25.6% of adults with DS
have a psychiatric disorder, most frequently a major depressive disorder or aggressive behavior (see Ref. 303 for
review).
B. Genetic Shaping of the Down Syndrome Brain
There are still unanswered fundamental questions
about the genetic shaping of the DS brain. How are specific structural pattern alterations under genetic control
linked to measurable differences in cognitive function?
Does aneuploidy affect cognitive phenotypes via disruptions of embryonic development or by altering function
during cognitive processing (or both)? How does genetic
variability relate to variations in cognitive profiles in people with DS? If specific genes have specific, separable
effects on specific cognitive processes, what are the longitudinal effects on cognitive profiles for DS people carrying particular risk alleles? Can the genetic information
be correlated with data from structural or functional neuroimaging? Does the genetic profile influence the response of an individual to particular behavioral interventions, and could this help to target therapies based on an
individual’s genetic information?
The main problem to answer these questions is that
during many years, it has been assumed that mental retardation was similar across different neurogenetic syndromes, with different morphometric alterations in brain.
The grounds for this generalization rest partially on the
fact that for many years the assumption was that we could
group mentally retarded people on the basis of nonspecific psychometric measurements, such as IQ (see previous section), and thus the intellectual disability of each
syndrome was considered by many researchers to be
similar. It is reasonable to expect that specific, well-defined neurobehavioral phenotypes as well as the definition of intermediate phenotypes will be good tools for
gene discovery because they will reduce phenotypic heterogeneity and help to determine the mechanistic dependence of phenotypes. At present, we have to mainly rely
on studies in DS mouse models (see sect. IV), that have
provided some cues on the molecular and cellular mech-
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mental retardation is highly diverse in terms of the severity of the cognitive disability as well as the manifestation
of additional (noncognitive) symptoms. IQ in people with
DS is usually in the severely to moderately retarded range
(IQ ⫽ 25–55) (133, 313, 370). IQ in DS is not constant
across the life (35), but it progressively decreases with
age (273, 370), although this scenario has changed in the
last years thanks to the early intervention programs and
the social integration of these persons (284). Speech and
language deficits, well documented in DS, probably contribute to the IQ decline with age. In DS adults, IQ may be
also influenced by the increased risk of early-onset dementia of the Alzheimer type, which is highly prevalent
among DS individuals (39). The intellectual disability in
DS is associated with a more or less fixed constellation of
morphogenetic and functional central nervous system
manifestations, such as craniofacial and brain malformations, and neurological or psychiatric symptoms.
Although extensively used in clinical practice, the IQ
measure is too vague to be useful for establishing a genotype/phenotype correlation, since it does not inform
about the specific functional domains affected, and thus it
does not allow predicting the structures involved in the
phenotypes or their underlying pathogenetic mechanisms.
Establishing specific diagnostic criteria and using a battery of evaluative instruments to document, for example,
verbal fluency, abstract reasoning, short- and long-term
memory, skill learning, etc. is crucial, but also an extensive and costly process, and few, if any, psychometric
studies actually attain this. The diagnosis of the specific
DS cognitive deficits is even more challenging since it
requires a combination of psychometric tests and neuropsychological paradigms, since low baseline levels of cognitive ability, impaired communication, and attention can
affect many psychometric tests (38, 77).
By definition, mental retardation implies a delay in
typical development, but in DS, this is an oversimplification of the problem. As in typically developing children,
IQ in DS is influenced by genetic and environmental factors (272) so that a positive correlation is found between
parental and DS children IQs (102). However, the behavioral phenotype is a potentially critical tool for shaping IQ
during the first years of life, and for planning education
and cognitive intervention in this population (117). In the
DS adults, the neuropsychological profile is not homogeneous, with some abilities more impaired than others. In
particular, motor function, language (specifically morphosyntax), verbal short-term memory, and explicit long-term
memory are usually more impaired, while visual-spatial
short-term memory, associative learning, and implicit
long-term memory are relatively preserved (37, 50, 57, 92,
163, 257, 289) and DS children have specific impairments
in receptive language that exceed their impairment in
other cognitive abilities (53). We still need to address the
question of which traits are specific for DS (94, 163, 164)
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DIERSSEN, HERAULT, AND ESTIVILL
C. Brain Topology of the Cognitive Impairment in
Down Syndrome
An intimate relationship exists between domains of
human cognition and functional brain architecture; thus
the neuropsychological profiles described in DS patients
are assumed to be due to altered brain structure, presumably derived from anomalous brain but also cranial development (Fig. 3). This relationship became clear when
fMRI studies enabled direct visualization of the functional
architecture of the brain networks during the performance of cognitive tasks, thus illuminating the neurophysiological underpinnings of the alteration of cognitive
functions in DS.
From the strictly structural point of view, postmortem observations and volumetric MRI studies in people
Physiol Rev • VOL
with DS have documented reduced brain weight, with
particularly small cerebellum as well as frontal and temporal lobes (390), reduced overall brain volumes and
brachycephaly, with disproportionately smaller volumes
in frontal and temporal areas (including uncus, amygdala,
hippocampus, and parahippocampal gyrus) and cerebellar regions (277, 278). In contrast, DS brains usually show
relatively preserved volumes in subcortical areas (183,
277, 278), such as lenticular nuclei (260) or the posterior
(parietal and occipital) cortical gray matter (278). The
relatively large size or preservation of these structures in
subjects with DS, in the context of significantly smaller
overall cerebral volumes, suggests that there is a dissociation of the development of cortical versus subcortical
regions.
To what extent will these structural alterations produce the functional consequences of DS? Neural network
models of the different brain structures have identified
cognitive operations that are unique to each structure
(268), thus allowing predictions on structural-functional
maps in DS. For example, the lower performances of DS
in linguistic tasks could be partially explained in terms of
impairment of the connectivity of frontocerebellar structures involved in articulation and verbal working memory
(107), whereas the reduced long-term memory capacities
may be related to the temporal lobes and, specifically, to
an hippocampal dysfunction (273). Similarly, the functional dissociation between implicit and explicit memory
in DS may be due to the severe cerebellar hypoplasia
along with normal morphology of basal ganglia that is
observed in these patients (183). Here we will focus our
review on only some of the structures that have been
shown to participate in the cognitive alterations of DS
patients.
1. Hippocampus
One important aspect of mental retardation in DS is
the specific alteration of memory patterns. The hippocampus and related structures of the medial temporal lobe
have long been linked to the ability to learn and retain
new memories for facts and events. This ability is termed
declarative memory in humans (254, 346) and relational
memory in animals (95). Evidence of the participation of
the hippocampal formation in the mnemonic process derives from studies demonstrating that damage to these
structures in adult humans and animals causes a profound
loss of declarative memory function without other sensory, motor, or cognitive impairments (246). Indeed, episodic memory is sensitive to hippocampal damage, and
the retrieval of autobiographical memories activates the
hippocampus in adults (231, 403).
The capacity for this basic, intrinsic ability to form
new memories is ultimately genetic in origin, and human
disorders that are associated with mental retardation usu-
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anisms causing developmental and/or functional alterations in neural patterning that may lead to defective
neuronal circuits responsible for the pathogenesis of
mental retardation in DS. These studies have provided
evidence that overexpression of specific genes or gene
networks leads to the disturbance of specific biological
processes, thus supporting the idea of dosage-sensitive
phenotypes. However, increased gene expression varies
for each gene and in each cell type, and cooperative
functional interaction among HSA21 genes in a signaling
pathway may result in additive or synergistic effects,
leading to signal amplification. On the other hand, the
effect of overexpression of one gene may counteract the
detrimental effects of others acting in the same pathway,
thus compensating the phenotype (76). It has been proposed that genes having a functional target that affects
information processing, such as synapses and synaptic
function, will lead to similar alterations in cognition and
adaptation (402).
Finally, an important factor may be the genetic context in which an individual’s mental retardation is taking
place and that can affect the final outcome. This is well
known in experimental models, as shown for example by
the differences in the performance on learning tasks or in
the amount of cell proliferation and neurogenesis among
different mouse strains such as C57BL/6, BALB/c, CD1
(ICR), and 129X1 mice (320, 377). In contrast, some phenotypic traits (such as motor phenotypes, or memory) are
maintained even after backcrossing to obtain a homogeneous background genotype in DS mouse models (M. Dierssen, M. Martinez de Lagrán, and G. Argué, unpublished
observations). For decades, researchers and practitioners
have attempted to find evidence for a personality stereotype
in individuals with DS that includes a pleasant, affectionate,
and passive behavior style. In fact, individuals affected with
DS present some features that are common regardless of
their particular genetic background, but other features that
may be dependent on their unique genetic background.
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
897
ally present functional alterations in the basic mechanisms involved in the formation of memories. This is also
the case in DS, although there have been relatively few
studies addressing hippocampal functioning in these patients. In the context of the overall cognitive dysfunction,
a common finding in DS is abnormalities in some forms of
visual-spatial memory and contextual learning that depend on the functional integrity of the hippocampus (for
review, see Refs. 128, 366). In a recent study, Carlessimo
et al. (48) described a hippocampally mediated deficit in
episodic memory, that particularly affected encoding and
retrieval, although there was a discrepancy in the performance level achieved by DS individuals in the visual and
spatial domains. Specifically, they had reduced visual but
relatively preserved spatial abilities (372). The most extensive study to date showed clear deficits in all hippocampally mediated tasks in DS patients, most strikingly
those related to long-term storage of explicit memories
(273). Similar to these findings, DS preschool children
showed deficits in a place learning and recall task, being
more severely impaired in delayed recall. This deficit in
delayed recall in DS may be explained by a specific dysfunction of the hippocampus disrupting remote informaPhysiol Rev • VOL
tion, since hippocampal memory systems show a clear
temporal gradient with a gradual strengthening of memories over time (e.g., Refs. 195, 258, 385, 403). Presumably,
once information has been processed by the hippocampus, it is transferred to neocortical association areas for
further processing and permanent storage (e.g., Refs. 258,
356). The hippocampal abnormalities described in DS
patients are suggested to be syndrome specific, since they
are more severe in individuals with DS than in other
mental retardation conditions (48, 273, 373).
Evidence for neuroanatomical abnormalities involving the hippocampus in DS derives from neuroimaging
studies. The hippocampal formation is comprised of a
group of cortical regions located in the medial temporal
lobe that includes the dentate gyrus, hippocampus, subiculum, presubiculum, parasubiculum, and entorhinal cortex. Moreover, the regional specialization of the hippocampus in the CA1, CA2, CA3, and dentate gyrus areas
reflects differential gene expression (10, 182, 223), where
a substantial proportion of neural genes (213) show region-specific expression. In individuals with DS, the volume of the hippocampus, adjusted for brain size, is
smaller than in controls, whereas amygdala volume re-
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FIG. 3. Morphometrical characteristics of Down syndrome (DS) skull and brain. A: lateral views of euploid and DS skulls. Left: the face of an
euploid young adult presents downward growth of the maxillae; therefore, the distance between the inferior orbital ridge, the nasal spine, and the
alveolar crest is considerably increased. The mandible is angled. Right: although the DS skull grows to nearly the same size as the normal adult,
it presents brachycephaly, which means “short headed,” and occurs when the right and left coronal sutures close prematurely. Brachycephaly results
in an abnormally broad head with a high forehead. It is often associated with other craniofacial abnormalities. In DS, the face is small, with
underdeveloped maxillae, and the mandible is still relatively straight. (Redrawn from Benda CE. Down’s Syndrome: Mongolism and Its Management. New York: Grune & Stratton, 1960.)
898
DIERSSEN, HERAULT, AND ESTIVILL
2. Cerebral cortex
The analysis of genetic cortical expression maps has
revealed a strong relationship between gene expression,
cortical structure, and behavior, suggesting that heritable
factors affecting the development of this brain region may
be fundamental in determining individual differences in
cognition (45, 359). As mentioned above, DS is categorized as a disease that affects the integrity of the cerebral
cortex, since trisomy of HSA21 affects more the neocortical areas, with decreased neuronal density within all
layers of cortex (178, 235, 236, 287, 353, 354, 379, 389, 392)
and functional differences in the cortices of individuals
with DS compared with euploids widely reported (84, 101,
121, 168, 216, 270, 319, 323).
The neuropsychological profiles described in DS do
reflect these neocortical alterations, but might also result
from the disrupted balance in cortical and subcortical
structures. One of the classical neocortical domains of
function is executive function, that includes planning ability, cognitive fluency, and judgment, and is attracting
attention as a basic mechanism underlying pervasive developmental disorders. Some studies have found impairment on some tests of executive function in DS individuals as shown by the greater weakness in a dual-task
processing component of executive function (197, 309).
With the use of the Complex Figure Drawing Test (296),
visual-motor (hand-eye) coordination difficulties and perceptual problems are frequently found in individuals with
DS (Fig. 4). This drawing and visual memory test examPhysiol Rev • VOL
ines the ability to construct a complex figure and remember it at later recall. It measures memory as well as
visual-motor organization. The results obtained using this
test supported the possibility of a different pattern to
drawing development in DS rather than a delayed version
of typical development (209, 210). In these studies, many
of the children with DS showed poor understanding of
spatial concepts, which was related to grammar comprehension. Those individuals with very poor understanding adopted inconsistent strategies to represent the
different spatial arrays, and children using a developmentally more advanced strategy demonstrated superior pencil control.
Frontal and parietal brain cortical regions are the
primary areas involved both in working memory and visual attention, functions that allow us to respond efficiently to the varying environmental demands of everyday
life (17, 18, 276). Several recent observations suggest that
the dorsal areas of the parietal cortex are involved in
spatial processing, whereas the ventral temporal (and
perhaps frontal) areas participate in working memory for
objects and faces and, more generally, in the processing
of visual material (65, 259). On the basis of the results of
psychometric studies, which show that persons with DS
perform better on visual-object than on visual-spatial
memory tests, it appears that the dorsal component of the
visual system in DS individuals functions closer to normal
levels than does the ventral component (371). Impairment
in verbal short-term and working memory, measured by
digit or word span, has also been documented in individuals with DS compared with mental age-matched controls
(for a review, see Ref. 373). This impairment can be
categorized as a type of working memory, defined as a
limited capacity system for the temporary storage of information held for further manipulation (17, 18).
Pinter et al. (278) showed that among individuals
with DS cerebral lobe volumes, reductions were predominant in frontal and occipital lobes. However, these effects
were not significant after adjustment for overall brain
size, suggesting that the relative preservation of temporal
lobe volume was related to a significantly larger white
matter volume. A note of caution should be taken in
interpreting these studies, since most of them used a
normal brain template that might have introduced a bias
in defining the lobe borders on the differently proportioned brains of the DS subjects.
Another important function that relates to the cortical
function and is altered in DS is language. The processing of
language information relies on a cortical network that comprises inferior frontolateral and anterior as well as posterior
temporal lobe structures in both hemispheres, and it has
been described that the grey matter density in the anatomical region that includes frontal and language-related cortices is more similar in genetically related individual. Of particular significance for language processing is the finding
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ductions do not exceed the overall reduction of brain size
(16, 203, 277). Interestingly, the volume of the parahippocampal gyrus (i.e., perirhinal and entorhinal cortices)
that appears to serve distinct and important memory functions (e.g., Refs. 96, 97, 153), such as nonrelational memory (i.e., stimulus-stimulus associations and stimulus recognition; Ref. 159), is relatively larger in DS (191, 289).
Although there is no relationship between total brain size
and the cognitive deficits, general intelligence and mastery of linguistic concepts correlated negatively with the
volume of the parahippocampal gyrus in DS patients
(289).
The reduced volumes of these regions may depend
on the reduced neuronal densities and reduced dendritic
branching, length, and spine densities that are found in
the hippocampus and parahippocampal gyrus of DS (reviewed in Refs. 29, 146, 257). Analysis of cell phenotype
showed that DS fetuses had a higher percentage of cells
with astrocytic phenotype but a smaller percentage of
cells with neuronal phenotype, along with less proliferating cells in the germinal zones of the hippocampus and
parahippocampal gyrus and higher incidence of apoptotic
cell death. Similar findings have also been reported in DS
mouse models (for a review, see Ref. 129 and sect. IV).
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
899
that the superior temporal gyrus appears to be severely
narrowed or underdeveloped in DS brains (136, 139, 390). In
this brain region, the planum temporale occupies the superior temporal plane posterior to Heschl’s gyrus, which is
generally agreed to represent auditory association cortex. In
the left hemisphere, Wernicke’s area includes part of planum
temporale and has traditionally been viewed as a language
processor. The planum temporale has been implicated in the
representation and updating of auditory speech traces that
Physiol Rev • VOL
are necessary for phonological working memory and speech
production. It is also activated by natural speech but not by
acoustically similar non-speech sounds, by deviant or unpredictable verbal and nonverbal events, or by verbal selfmonitoring (for review, see Ref. 144). In people with DS, the
planum temporale has been shown to be smaller than normal, although it has not been possible to establish a correlation across individuals between this deficiency and degree
of language deficit (123).
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FIG. 4. Executive cognitive function in DS: the Complex Figure Drawing Test. Visual-motor, hand-eye coordination difficulties, and perceptual
problems are frequently found in individuals with DS. Examples are shown of drawings of a 12-yr-old (A) and a 16-yr-old (B) DS girl of the Complex
Figure Drawing Test (296) that examines the capacity to integrate stimuli on the levels of perception, spatial organization, and planning, in a
visual-graphic modality. The subject is first instructed to copy the figure, which has been so set out that its length runs along the subject’s horizontal
plane. The examiner watches the subject’s performance closely. Each time the subject completes a section of the drawing, the examiner hands him
a different colored pencil and notes the order of colors. Time to completion is recorded, and both test figure and the subject’s drawings are removed.
This is usually followed by one or more recall trials. Children with DS show perceptual and fine motor difficulties and impaired capacity for
integration in the spontaneous first copy. The vertical drawing (A) reflects a more concrete way of perceiving the complex figure that has no realistic
meaning, similar to the way most young children draw. The poor first memory drawing shows that this tracing, copying did not produce any learning.
However, the learning phase resulted in quite accurate copy and drawing from memory. C: complete figure with configural elements, clusters, and
details. (Adapted from http://www.he.net/⬃altonweb/cs/downsyndrome/i).
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ology (110, 111, 255, 360) and are related to information
processing capacity. Minicolumns are among the structural features that are genetically regulated they may
underlie the differences in cortical function and IQ observed among DS individuals. Buxhoeveden et al. (40)
found that DS patients had larger columns with lower cell
density than normal individuals, indicating a reduction of
complexity due to abnormal development.
Even though numerous genes have been identified
with highly specific patterns of gene expression restricted
to discrete neuronal populations in different cortical layers, their specific function has not yet been elucidated.
Moreover, DS-associated behaviors are not easy to trace
to specific molecular elements or interactions in the
brain, and it is even more difficult to dissect a complex
cortically dependent cognitive function such as language
and to relate it to a particular genetic cause.
3. Cerebellum
The cerebellum has classically been related to motor
control, specifically motor learning and coordination.
However, there is increasing evidence that the cerebellum
has a role in cognition, although the observed role with
respect to changes in working memory, affect, and language production is mostly modest (see Ref. 200 for review). Motor behavior disturbances are part of the clinical
features of DS and have classically been attributed to
hypotonia in the early developmental stages. ShumwayCook and Woollacott (341) contested this hypothesis and
proved that balance difficulties were not caused by altered motoneuron function and stretch reflex mechanisms, but rather by defects within higher level postural
mechanisms mediated by the cerebellum. From the neuroanatomical point of view, reductions in cerebellar volume are a constant finding in DS individuals (183), and the
growth of the DS cerebellar field is smaller in the sagittal
and vertical directions than in normal fetuses (222). However, although cerebellar volumes are disproportionately
small in individuals with DS, they do not further diminish
significantly with age and do not undergo age-related
atrophy that is different from that of normal controls.
Volume reduction in the cerebellum does not appear to be
specifically responsible for the age-related decline in finemotor control that is observed in adults with DS (16).
However, both neuropsychological (250) and functional
neuroimaging (368) data assign a critical role to basal
ganglia and cerebellum in the implicit learning of visualmotor skills. High-resolution three-dimensional MRI revealed that the reduced cerebellar volume is a completely
penetrant phenotype that is accurately recapitulated in a
mouse model (22) bearing segmental trisomy for MMU16
(Ts65Dn; see sect. IV).
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Language deficits in individuals with DS are evident
at the onset of language use and continue through adolescence and into adulthood with some indication of
changes in language strengths throughout their life span.
Potential explanations for the specific difficulties in language include deficits in phonological working memory,
hearing sensitivity, and visual short-term memory, which
are related to comprehension and production of both
syntax and vocabulary (51, 52, 54, 210). Difficulties in oral
language skills and auditory working memory such as
those reported in DS individuals are related to phonological awareness and decoding and comprehension of
reading material (41, 210, 369). Recent brain imaging
studies on language processing (with auditory stimulation) have shown that temporal and frontal areas of
both hemispheres are involved in the processing of
connected speech, with the left hemisphere responsible
for the bulk of on-line processing of syntactic features
and prosody (125, 245). Thus the lower performances of
DS individuals in linguistic tasks may be also explained
in terms of impairment of the frontocerebellar structures involved in articulation and verbal working memory (107).
Some regions involved in language, such as the temporal lobe, may be potentially more susceptible to subtle
gene-dosage effects. Early histological analyses of DS
described a decrease in neuronal cell packing density
particularly in layer III of the cerebral cortex (58, 352,
393). Moreover, the histogenetic development of the cerebral cortex is affected, and difficulties in recognizing
cortical layers and cytoarchitectonic areas in DS brain
samples have been reported (190, 401). Wisniewski et al.
(391), in a study of the visual cortex of 60 children with
DS from birth to the age of 14 yr, reported that DS
patients had 20 –50% fewer neurons than normal children
during this period. They suggested that the neurons were
rearranged before birth, particularly in layer IV. Golden
and Hyman (136) plotted a set of reference curves for
control fetuses, reflecting cell density in the cerebral cortex throughout cortical development. They suggested that
neuronal migration is normal, but that the second phase,
after 20 –21 wk and corresponding to lamination, is both
delayed and disorganized in patients with trisomy 21. The
observed pattern of cortical maturation may also reflect
an abnormality in axonal and dendritic arborization. Normal children display expanding dendritic arborization
during childhood, whereas patients with DS display
greater dendritic branching and total dendritic length
than controls in the infantile period (up to the age of 6
mo), decreasing steadily thereafter to significantly below
normal levels in the juvenile group (over the age of 2 yr;
Refs. 23, 25). An interesting finding is the abnormal rate of
development of minicolumns in children with DS. Anatomical minicolumns represent a basic functional unit of
the cortex that have been closely associated with physi-
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
D. Nature and Nurture in Down Syndrome:
The Building of a Trisomic Brain
Physiol Rev • VOL
Obviously, the developmental aspects are very important in defining the most important part of the functional consequences of the genetic imbalance in DS at the
cognitive level. Individuals with DS have a wide range of
dysfunction in all areas of psychomotor development. As
highlighted before, in addition to the underdevelopment
typical of early infancy, the IQ of DS patients decreases in
the first decade of life, thus indicating that the activitydependent maturation of the central nervous system is
compromised. DS children present asynchronic development in functional areas different from typically developing children, as they develop with a totally different biological background, so that the organic impairments and
pathologies associated with DS can be determinant in
limiting development (257). As an example, DS children
do not appear to follow the same sequence of stages as
typically developing children with respect to certain domains, such as language development or object concept
development. This constitutes a crucial aspect that must
be taken into account when determining the developmental versus functional causes of the adult dysfunction. For
example, a deficiency in language production relative to
other areas of development often causes substantial impairments that affect other domains. Moreover, motivational aspects, derived from increased failure rates for
learning experiences, clearly have an impact on further
learning through the establishment of counterproductive learning strategies, which include avoidance strategies when faced with cognitive challenges. Finally, the
morphogenetic alteration affecting different brain regions may have a convergent impact so that difficulties
experienced when acquiring new skills will have an
impact on the success of learning in different areas
(162, 165). As an example, delayed recall deficits are
mostly caused by hippocampally related functions such
as memory acquisition or storage, but are also affected by
cortical functions, such as reduced cognitive flexibility
manifested as the persistent use of old strategies to solve
new problems (162, 165, 289, 388).
Analysis of the developmental process is even more
complicated if we consider the structural aspects. In DS
fetuses, differences in brain size become apparent as
early as 15 wk of gestation, but increase significantly after
birth. The frontothalamic distance on ultrasound scans is
5–10% lower than that of normal fetuses, and more than
50% of DS fetuses have frontothalamic distances below
the 10th percentile (19, 387). DS has a stronger negative
effect on cerebellum growth in the last part of gestation
and after birth, resulting in 30% size reduction in children
with DS compared with euploid subjects (183, 278). Studies of the weight of the infratentorial part of the brain
(including the brain stem and cerebellum) have shown
that the growth of this region is less restricted than that of
the supratentorial part of the brain, between 15 and 38 wk
of gestation (147). However, the only part of the cerebrum
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DS is a neurodevelopmental disorder that combines
genetic effects on different cells, structures, and functions
throughout development and in the adult. Normal development of the central nervous system depends on complex, dynamic mechanisms with multiple spatial and temporal components during gestation. Neurodevelopmental
disorders originate during fetal life from genetic as well as
intrauterine and extrauterine factors that affect the fetalmaternal environment, and the later can also affect the
final outcome of genetically driven disorders. Fetal neurodevelopment depends on cell genetic programs, developmental trajectories, synaptic plasticity, and maturation,
which are variously modifiable by factors such as stress,
exposure to teratogenic drugs, maternal teratogenic alleles, or premature birth. There is a clear need to expand
our understanding of how, when altered, prenatal factors
may lead to disordered development, the signs of which
may not appear until long after birth, and this is especially
important in DS, since it will define the best moment for
therapeutic intervention. The postnatal gene-environment
interaction also modifies the final structural and functional outcome so that the functional profile observed in
individuals with DS emerges as a result of the crossdomain relations between both. Moreover, during the first
years of age, more primary (cognitive, social-emotional)
aspects of the DS behavioral phenotype interact with a
general profile of delays in the development of instrumental thinking coupled with emerging relative strengths in
social-emotional functioning.
The brain is an extremely complex structure in which
different parts serve different functions and arise from
distinct cell populations across different temporal windows of development. The coordination of neurogenesis,
growth, and development of each brain component is
controlled by precisely localized patterns of gene expression (e.g., Refs. 2, 225). Many primary deficits may have
cascading effects that produce clinically observed phenotypic traits. Brains of patients with DS present specific
features that may be dependent on morphogenetic alterations, but also on a reduced remodeling potential and
impaired neural plasticity. The first include neuronal heterotopias, abnormal neuronal migration/differentiation,
and decreased neuronal density, that mainly affect specific cell populations such as granule cells in cerebral
cortices and dendritic anomalies that affect pyramidal
neurons (23, 235, 236, 355; see Ref. 120 for review). Thus
a first step in DS research is to separate developmental
effects from functional perturbations to the adult brain,
since altered functions in adults may be the consequences
of a developmental error caused by trisomy or to the
functional effects of upregulation of trisomic genes.
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program. In a relatively short time, neuroblasts permanently lose their ability to reenter the cell cycle, and they
migrate to their definitive positions and undergo major
morphological changes that establish the neuronal network. Candidate genes such as the kinase encoding
Dyrk1A gene have been related to this particular developmental stage (see Ref. 86 for review) as shown by its
transient expression in neural progenitor cells during the
transition from proliferating to neurogenic divisions in
early vertebrate embryos (149, 150).
With regard to the neuronal differentiation phase,
postmortem studies show that DS persons start their lives
with an apparently normal neuronal architecture that progressively degenerates. During the peak period of dendritic growth and differentiation (2.5-mo-old infants), no
significant differences were detected in dendritic differentiation between euploid and DS cases in layer IIIc pyramidal neurons of prefrontal cortex (prospective area 9,
376). Similarly, DS infants younger than 6 mo showed
greater dendritic branching and length than normal infants in both apical and basilar dendrites (24, 353). Thus
normal or even increased dendritic branching in the DS
fetus and newborn contrasts with the reduced number of
(especially apical) dendrites and degenerative changes in
DS children older than 2 yr (21). Similar findings of decreased values of dendritic parameters could also be observed only after the fourth postnatal month in the visual
cortex of DS brains. Finally, abnormalities of synaptic
density and length, fewer contact zones, a reduction of
dendritic spines, and shorter basilar dendrites are observed in DS (23, 123, 232, 283, 350, 353–355). When the
mechanism of these alterations is determined, the dynamic reorganization of the actin cytoskeleton turns out
to be a very good possibility, since it plays a crucial role
during every stage of neuritogenesis and structural plasticity (71, 226). Particularly, in differentiating neuroblasts,
actin rearrangements drive the extension and the path
finding of axons and dendrites and contribute to the establishment of synaptic contacts (71, 90, 226). Molecules
affecting actin cytoskeleton structural or functional properties are thus excellent candidates to explain the neuronal architecture abnormalities observed in DS. Several
candidate genes located in the HSA21 DS critical region
have been proposed to be involved in synaptic plasticity
and in particular in dendritic function and spine motility
and plasticity. The DSCR1, DYRK1A, or ITSN1 genes may
be candidates to explain the dendritic spine functional
and structural alterations. Intersectins (ITSN1 and ITSN2)
(285, 286) are multidomain scaffold proteins that interact
with several signaling proteins. A long splice variant of
intersectin, ITSN1, that contains a Dbl domain with guanine nucleotide exchange factor (GEF) activity for Cdc42,
is expressed specifically in neurons. Intersectin controls
local formation and branching of actin filaments. Dyrk1A
phosphorylates actin-binding proteins and may also have
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showing a clear decrease of magnitude is the hippocampus (27% decrease). Since the size and shape of brain
components depend on the production of different neural
and nonneuronal cells, changes in early morphogenesis of
a specific region can create a localized change in volume,
resulting in associated displacement of nearby structures,
producing both localized and global differences in shape.
Still, changes in overall brain volumes and brain shape are
not necessarily correlated across individuals, suggesting
that size and shape phenotypes provide complementary
information about the brain’s developmental history (7).
One important aspect when considering the developmental process is the proliferation of neuronal cells. In
DS, as discussed previously, the number of neurons is
significantly reduced in adult brains. This has received
special attention, since for many years the general assumption was that number of neurons was correlated
with cognitive proficiency, based on the fact that mental
retardation was frequently associated with microcephaly.
Even though we now are aware of the wide constellation of factors involved in the definition of cognitive
abilities, neuronal proliferation still deserves much attention, since proliferation of neuronal progenitor cells occurs at a significantly lower rate both in human DS fetuses
and in trisomic Ts65Dn mice than in healthy controls (62,
312; see sect. IV), suggesting an impairment of neural
precursor proliferation during early phases of brain development. The number of surviving cells is also smaller
compared with euploids, and a higher proportion of the
surviving cells in DS individuals had an astrocyte phenotype. Several studies have pointed to a defect in cell cycle
progression as a likely determinant of impaired proliferation and have highlighted some genes as possible contributors to cell cycle and replication deregulation. For
example, DS fetuses and Ts65Dn mice show a greater
proportion of cells in the G2 phase of the cell cycle and a
smaller number in the M phase, suggesting that the longer
time spent by proliferating cells in the G2 phase may
underlie their reduced proliferation rate. In Ts65Dn mice,
significant downregulation of cyclin B1 and the cell cycle
kinase Skp2, involved in the regulation of G2/M progression, and of Bmi1, a gene involved in maintenance of the
proliferative capacity of progenitors cells, has been reported. In addition, an upregulation of genes involved in
the exit from the replicative state and induction of differentiation towards either a neuronal (Mash1, NeuroD,
Neurogenin2) or a glial (Olig1, S100b) fate was found
(60, 62). These observations suggest that neurogenesis
impairment starting from the earliest stages of development may underlie the widespread brain atrophy of DS
and the delayed and disorganized emergence of lamination in the fetal DS cortex (136). The transition of neuronal precursors from a proliferating state to a completely
differentiated phenotype represents one of the most crucial events of the central nervous system developmental
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
Physiol Rev • VOL
pend on local translation and transcription of specific
genes, so that stimulation of a synapse will lead to activation of intracellular second messengers in the synapse
as well as to “synaptic tagging,” involving the recognition
of specific transcription products. In the neuronal body,
second messengers induce the synthesis of RNA and protein molecules, which are widely distributed in neuron
processes and which are inserted selectively only into
stimulation-tagged synapses, causing long-term changes
in their functional and morphological characteristics (reviewed in Ref. 262) that will affect neural plasticity and
thus adaptation to the environment.
In this regard, research addressing early intervention
in DS showed positive effects in different developmental
domains but with unclear evidence of long-term effects,
probably reflecting an impaired structural plasticity in DS
persons, and also DS mouse models (85). These data
support the emergent recognition of the importance of the
context of child development and is already having consequences in the development of a contextualized approach to child development, particularly in relation to
the impact of early intervention on families and the longterm goals of early intervention.
IV. MODELING DOWN SYNDROME
To better understand the molecular and cellular origin of DS as well as the defects associated with the
disease, several groups developed a large panel of mouse
models. The advantages of modeling DS in mouse are
clear. First, restricting the comparison of individuals either carrying a trisomy or not, but with a similar genetic
background and that are bred in a controlled environment. Second, the impact of gene-dosage can be studied
further during embryonic and postnatal development or
in the adult, allowing easier discrimination of the effect of
gene imbalance during organogenesis from that on the
function of the adult organ, even though both events are
interconnected (78, 305). Several models developed
through transgenesis for single or multiple genes using
BAC or YAC have been already extensively described
elsewhere (13, 87). In this review, we will concentrate on
the mouse models of DS that correspond to genetically
engineered trisomy.
The laboratory mouse is a powerful model system,
with well-known biology and genetics. In addition, mouse
and human share many homologies at the genetic and
the physiological levels so that conclusions drawn in one
species can be used to approach similar issues in the
other. The sequencing of both genomes by the beginning
of the 21st century confirmed their syntenic conservation,
and ⬃80% of murine genes are homologous to human
(381). This similarity is lower for the homologous region
to the HSA21 (131, 299, 337). More than 430 genes, includ-
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a role in shaping the interaction of the spine membrane
with the actin cytoskeleton (see Ref. 86). Yang et al. (397)
showed that overexpression of a kinase-deficient form of
Dyrk1A attenuates the neurite outgrowth induced by a
neurogenic factor in immortalized hippocampal cells.
Moreover, the reduction in brain size and dendritic defects observed in mice lacking one copy of the murine
homolog Dyrk1A (Dyrk1A⫹/⫺) supports the idea that this
kinase may have a physiological role in neural differentiation (29, 122) and that deregulation of its expression may
inhibit neuritogenesis. In this regard, overexpression of
Dyrk1A in several DS models, from segmental trisomic
mice to BAC models (for review, see Refs. 4, 86), correlates with changes in size of specific regions of the brain
and with microstructural alterations at the dendritic level
(34; Dierssen et al., unpublished observations). The
DSCR1 gene is overexpressed in fetal and adult DS brains,
and many experimental data are consistent with calcineurin activity inhibition by DSCR1 overexpression
(46). Calcineurin is involved in synaptic plasticity and has
a role in the transition from short- to long-term memory
through perturbation of long-term potentiation (LTP) and
long-term depression (LTD). In addition, calcineurin-dependent induction of the gene product of DSCR1.4 may
represent an important autoregulatory mechanism for the
homeostatic control of nuclear factor of activated T cells
(NFAT) signaling in neural cells (46). Another interesting
example of synaptic-related proteins involved in DS is
drebrin, an actin-binding protein, thought to regulate assembly and disassembly of actin filaments, thereby changing the shape of spines and the synaptosomal associated
proteins SNAP and SNAP 25 (15, 158). In postmortem DS
brains, levels of drebrin are reduced in the early second
trimester. Also, overexpression of Dyrk1A is associated
with altered synaptic plasticity and learning and memory
deficits, that could also deregulate the NFAT pathway
(14). Finally, S100␤, a calcium binding protein found in
astroglial cells, has extracellular neurotrophic effects involving the neuronal cytoskeleton, and thus its overexpression may be related to the cytoskeletal abnormalities
seen in mental retardation (330). Changes in levels of
expression of these genes may lead to changes in the
timing and synaptic interaction between neurons during
development, which can lead to suboptimal functioning of
neural circuitry and signaling at that time and in later life.
After the first genetically driven developmental period, neuronal circuits are continuously modified and
shaped by experience (epigenetic development) to ensure
that the neural control of behavior is flexible in the face of
a varying environment. To this end, morphological and
physiological changes are possible at many levels, including that of the individual cells. According to current concepts, long-term memory is based on structural-functional
changes in particular synaptic connections between neurons in the brain (synapse-specific plasticity), which de-
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DIERSSEN, HERAULT, AND ESTIVILL
A. The Early Phase
In 1980, the first publication describing the linkage of
the superoxide dismutase (SOD) gene to MMU16 concluded by suggesting the opportunity of using mice trisomic for MMU16 as a model for DS (66), although this
trisomic model encompasses a large set of genes not
homologous to HSA21, and it leads to death just after
birth. Consequently, the description in the 1990s of
Ts(1716)65Dn (noted Ts65Dn) mice opened new perspectives and increased our understanding of the mechanisms
underlying DS (75, 292). Ts65Dn mice carry a translocation of the distal part of MMU16 on a small centromeric
fragment of the MMU17, which corresponds to a trisomy
FIG. 5. Genetic regions triplicated in DS mouse models. The relative
position of the mouse homologous regions on MMU16, -17, and -10 to
HSA21 are shown with the genes located at the borders of the genetic
interval. The human transchromosomic, Tc1, lines carrying a complete
HSA21, described by O’Doherty et al. (263), are indicated with two
internal deletions shown by the broken line. The other mouse models
are shown with the corresponding region that is either segmentally
duplicated [Ts1Yu (215); Ts1Rhr (265)] or translocated [Ts65Dn (292);
Ts1Cje (314)].
Physiol Rev • VOL
of 167 genes between Mrpl39 and Zfp295 (Fig. 5; Table 2).
This model has been studied extensively, and it shares
several phenotypes with human patients, including memory impairments indicative of hippocampal and cortical
dysfunction (103, 104). Learning and memory deficits
have been seen in trisomic mice using various paradigms
requiring hippocampal function such as the Morris water
maze and the radial arm maze (80, 103, 104, 140, 167, 170,
173, 176, 252, 292, 348). Accordingly, their hippocampi,
but also their cortical pyramidal layer, displayed changes
in circuitry development and structure, in synaptic plasticity, in growth, in response to signaling pathways, and in
LTP (7, 28, 32, 62, 85, 151, 342). Reduced neuronal density
and reduced excitatory synapses have been demonstrated
in specific subregions of the hippocampus (151, 179, 206,
207). In addition, LTP is not induced in their dentate
gyrus, and this defect has been linked to an enhancement
in inhibitory synaptic transmission (32, 89, 103, 199, 342).
Developmental and adult abnormalities in neurogenesis
or in plasticity have been documented in DS mouse models (220, 224, 312). Indicative of neurodegenerative disorders, these models also show the degeneration of cholinergic neurons from the basal forebrain, similar to the
defect found in Alzheimer and in trisomic patients. This
alteration was described in 12-mo-old Ts65Dn mice (61,
64, 167, 315, 328), even though when the degeneration
starts is controversial (141, 142, 169, 171).
In a way similar to human patients, Ts65Dn mice
present motor dysfunction (173), although controversial
data have been published using the rota-rod test (reviewed in Ref. 87). However, the cerebellum of Ts65Dn
mice shows clear structural and functional alterations.
The basic structure of the cerebellar cortex exhibits a
bilaterally symmetric series of sagitally oriented bands
attributable to a number of genes that are heterogeneously expressed within cerebellar granule and Purkinje
cell populations (22). Similar to DS persons, Ts65Dn show
reduced cerebellar size, and area measurements of histological sections of trisomic mice demonstrated reduced
thickness of the internal granule and molecular layers.
Moreover, the density of granule cells and Purkinje cells
is significantly lower in Ts65Dn mice (22). Defects in the
granule cell number is clearly dependent on their low
response to the SHH mitotic signal (249, 304). But the
impact of such defect on locomotor activity has so far
been detected only in a few studies (175). Nevertheless,
these cerebellar phenotypes provide quantitative end
points for future studies of gene-dosage imbalance in
mouse models with smaller, defined segmental trisomies
(see Ref. 249 for review).
Several other phenotypes that originate during development are conserved in Ts65Dn mice, including short body
length and defects in craniofacial structure, including
smaller rostrocaudal length, brachycephaly, and shorter
mandibles (161, 300, 301). In addition, a recent study reveals
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ing RNA coding genes, are identified on HSA21, and 293
homologs are found in the mouse genome, spread across
three chromosomes (www.ensembl.org; see Fig. 5). For
example, a large fragment from Lipi to Zfp295 encompassing 37 Mb and 224 genes is located on the telomeric
part of mouse chromosome 16 (MMU16; MMU for Mus
musculus). The most telomeric part of HSA21 is split
between MMU17, with 22 genes found between Umodl1
and Hsf2bp, and MMU10, where 47 genes lie in the interval between Cstb and Prmt2. Interestingly, the order and
the relative orientation of the genes known to be shared
between mice and humans have been conserved together
with 2,261 conserved nongene sequences, of which only
60% is predicted to have a function (81, 82, 357). On the
basis of this knowledge, several groups have focused on
mouse models to decode the cellular and molecular mechanisms linked to the neuropathological, cognitive, physiological, and morphological alterations found in human
DS patients.
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DOWN SYNDROME: A GENOMIC BRAIN DISORDER
TABLE
2.
Mouse models of Down syndrome with their major phenotypes
Mouse Models
Tc1
Ts1Yu
Ts65Dn
Ts1Cje
Ts1Rhr
Ms1Rhr Ts65Dn
Coding and RNA genes in 3 copies
Genetic interval
Learning and memory defect
Cerebellum defect
Craniofacial defect
Heart defect
Intestinal defect
306
HSA21
(⫹)
224
Lipi-Zfp295
167
Mrpl39-Zfp295
(⫹)
(⫹)
(⫹)
(⫹)
105
Sod1**-Zfp295
(⫹)
(⫹)
(⫹)
(⫺)
40
Cbr1-Orf9
(⫺)
(⫹)
(⫾)
(⫺)
70
Mrpl39-Cbr1* ⫹ Orf9-Zfp295
(⫺)
(⫹)
(⫹)
(⫹)
(⫹)
Physiol Rev • VOL
Both models have been extensively studied to characterize the effects of dosage imbalance on gene expression (43, 56, 72, 185, 230, 281, 316). Not surprisingly, most
of the genes with three copies were overexpressed in
various organs studied at a ratio of ⬃1.5 times disomic
controls (9, 72, 185, 230, 316). This is similar to the human
condition (119, 233, 234), even though in humans, dosage
compensation exists with a tissue-dependent specificity
(185, 230). This is referred to as the primary dosage effect
of trisomic genes, while the secondary dosage effect refers to the consequence of the overexpression of trisomic
genes on the rest of the genome (118, 249, 305). Further
transcriptome analysis looked at the consequence of trisomic genes’ overexpression at the level of the whole
genome. In a detailed series of experiments, the transcriptome analysis of Ts1Cje mice at three postnatal stages
(P0, P15, and P30) revealed that trisomic genes displayed
elevated expression and that the transcription of a panel
of disomic genes was altered. Furthermore, gene ontology
analysis showed that the differentially expressed genes
belong to the neural differentiation and migration class,
including six transcription factor genes, of which two
were from the Notch pathway (72, 281). In addition, the
secondary effect could be perturbed by stochastic mechanisms regulating a substantial set of genes (316). Thus,
even though studying the consequences of trisomy led to
a clear conclusion about the expression of trisomic genes
as a consequence of dosage imbalance (130, 351), its
impact on the global transcriptome is still under debate.
Most importantly, the origins of several phenotypes found
in trisomic models result from alterations occurring at
specific developmental time points.
Nevertheless, based on the variability in brain-regional expression of genes from various Ts65Dn individuals, Sultan et al. (351) proposed an interesting strategy to
rank the trisomic genes as candidates for phenotypes.
Obviously, measure of the impact of the trisomy in a
transcriptome analysis is dependent on the purity of the
tissue or cell type studied. A direct conclusion from these
large studies is that a few pathways have been identified
so far as altered in trisomic tissue, namely, NFAT-dependent transcription (14), the SHH signaling pathway (304),
and the Notch signaling pathway (72, 281). As occurs in
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that Ts65Dn displayed heart abnormalities (251), causing the
death of affected newborns at birth and the subsequent
lower survival of trisomic animals at weaning (251, 306).
Similar work carried out on the craniofacial defect and on
the size and cell reductions in the cerebellum and hippocampus clearly demonstrates the developmental origins of the defects (161, 224, 271). For instance, alterations in cellular proliferation during postnatal development induces a 13% decrease in granule cell numbers in
the dentate gyrus that persists until adulthood, during the
period when the cholinergic neurons from the basal forebrain have not yet begun to degenerate (224). Such analyses highlight the value of mouse models for detailed
characterization of the DS phenotype.
A second model arose in 1998 with the description of
the Ts(1216)1Cje mouse (Ts1Cje; Fig. 5; Table 2), which
carries a translocation of the Sod1-Zfp295 genetic interval to the telomeric end of the MMU12, but with disomic
Sod1 (314). Comparative analysis of these two models
allows studies of phenotype/genotype relationships in the
mouse. A first consequence of this comparison was the
reinforcement of the concept of a polygenic contribution
to the DS phenotypes. For example, Ts1Cje mice are less
severely impaired in learning and memory than are
Ts65Dn (314). Four- to five-month-old Ts1Cje mice perform normally in the novel object recognition test (110),
while 3- to 4-mo-old Ts65Dn mice show impaired performance (113) even though this defect is absent in older
Ts65Dn mice (174) . These results suggest that at least
two distinct loci, located upstream and downstream of
Sod1, are interfering with object recognition memory in
trisomic individuals. Similarly, craniofacial alterations
and cerebellar phenotypes are attenuated in Ts1Cje compared with Ts65Dn (266), while heart defect was only
found in Ts65Dn (251). In addition, the novel chromosome of the Ts1Cje is essentially transmitted in a Mendelian ratio, suggesting that at least one crucial locus for the
heart phenotype is located in the Mrpl39-Sod1 genetic
interval. Thus phenotypic analyses of these two models of
trisomy begin to lead us toward phenotype/genotype correlation using the mouse as a model system with the aim
of deciphering which genes are playing key roles in the
phenotypes associated with DS.
(⫹)
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DIERSSEN, HERAULT, AND ESTIVILL
B. Genetic Tools for Creating Aneuploid Models
Chromosomal engineering may be defined as techniques for modifying the structure or the copy number of
genomic regions or whole chromosomes. These are the
methods of choice at the moment for generating new
models of DS. Historically, generation of large chromosomal rearrangements was achieved by using x-irradiation or chemical mutagens known as clastogen or aneugen, which have the effect of inducing inversion, duplication, deletion, or chromosome loss or fusion. These
classical approaches led to the generation and study of
several valuable models of aneuploidy (73, 247, 367). Nevertheless, these random approaches still required a detailed characterization of the aneuploid condition, which
can now be more efficiently specified using technologies
for detecting copy number variation. The major breakthrough came in the mid 1990s with progress in manipulating large genomic regions or even whole chromosomes
to generate new aneuploid models. The first new strategy
took advantage of Cre/loxP-mediated chromosomal engineering and was described by the group of Bradley (for a
recent review, see Ref. 36). Basically, the insertion of two
loxP sites on either side of a region of interest (ROI) by
gene targeting in embryonic stem (ES) cells followed by
the action of CRE recombinase to select a designed chromosomal rearrangement. Thus, using two loxP sites in a
cis-configuration and in the same relative orientation will
generate either 1) a deletion if the CRE is active in the G1
phase or 2) a duplication if the CRE-mediated recombination event takes place in the G2 phase. Alternatively, a
trans-configuration of the loxP site will undoubtedly lead
to a balanced deletion and duplication of the ROI, mainPhysiol Rev • VOL
taining a pseudo-disomic state of the cell. The in vitro
strategy requires the restoration of a selectable marker,
such as the Hprt minigene in deficient ES cells to select
the new chromosomal configuration. To this end, 5⬘ and 3⬘
parts of a selectable minigene will be inserted, respectively, upstream or downstream of the loxP sites located
on each border of the interval so that the minigene sequence is restored through the action of the CRE recombinase (288). With the use of this principle, a large set of
deletions, duplications, and inversions have been engineered in the mouse genome (for a review, see Refs. 31,
33, 36, 215, 395). The strategy was used extensively to
generate models of contiguous gene syndromes or aneuploidy, such as the Smith-Magenis (228, 378, 380, 396),
Prader-Willy (363), and DiGeorge (217, 218, 318) syndromes. Following the same strategy, new models of DS
have been obtained for the DS critical region between the
Cbr1 and Orf9 genes (265) and for the entire region of
MMU16 homologous to HSA21 (215). Furthermore, additional models corresponding to the deletion of the Cbr1Orf9 interval or the Prmt2-Col6a1 region were derived
and used to ascertain the role of genes and copy number
variation on the physiology of the mouse (31, 161, 265,
267).
Complementary to the techniques described previously, X-ray Microcell-Mediated Chromosome Transfer
(XMMCT) facilitates manipulating large chromosome
fragments or whole chromosomes (for a recent review,
see Ref. 364). This strategy originates in the 1970s to
transfer into host cells single or small numbers of chromosomes by fusion with microcells (91, 243). Application
of XMMCT to the creation of models of DS was achieved
first in chimeric mice with transchromosomal ES cells
containing different parts of human chromosome 21,
ranging from ⬃50 to ⬃0.2 Mb (160, 189, 340). Those
chimeras tend to display specific phenotypes, although
with a high degree of interindividual variability (189, 340).
The major breakthrough came from the group of Fisher,
which succeeded in producing the first transchromosomic mouse line, called Tc1, that carries an almost complete extra HSA21 (263). Both techniques mentioned here
completely changed our way of thinking about genetic
dissection of DS phenotypes, allowing several groups to
develop integrated genetic strategies to dissect the contribution of HSA21 or homologous regions to the DS
phenotype.
C. Recent Outcomes From New Models
for Down Syndrome
The first hypothesis tested in the recently created DS
mouse models was that there exists a DSCR that contains
all the major genes involved in generating DS phenotypes
(79). Olson et al. (265) addressed the hypothesis using
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humans, further characterization and additional refinement will require more precise dissection of tissue or
purification of cells to limit cross-contamination. Furthermore, the identification of crucial developmental time
points will be needed to decipher the effects of genes
contributing to the secondary dosage effects, whose altered expression affects their function in the corresponding tissue (249).
Considerable knowledge was acquired using these
first trisomic mouse models, but we are still far away from
a complete picture of the syndrome. Two main features of
human patients, mental retardation and skull morphology, have been seen in trisomic mouse models. However,
several other defects, including limb and gastrointestinal
defects, hypothyroidism, increased incidence of acute
megakaryocytic leukemia, and immune defects have yet
to be explored. As a consequence, additional homologous
regions that are not in the Mrpl39-Zfp295 genetic interval
must play a role in the induction of the phenotypes associated with DS.
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
Physiol Rev • VOL
as the Ts65Dn mice, whereas they are defective in shortterm novel object recognition compared with the Ts65Dn
mice. Moreover, Tc1 mice display motor coordination
deficit (127). Interestingly, these detailed phenotypic analyses highlight more intricate phenotypes that validate the
use of the Tc1 mouse as a model system for elucidating
the complexity of DS phenotypes (291).
Further development of mouse models was recently
achieved by the description of a new model encompassing the complete region of MMU16 homologous to HSA21
that extends from the mouse homolog of the Lipi gene to
Zfp295 (Fig. 5, Table 2). The corresponding Ts1Yu mice
were described by two major phenotypes (215). One affects the heart in 37% of the embryos, with defects related
to human patients such as tetralogy of Fallot, atrial and
ventricular septal defects, cleft mitral valves, severe coarctation of the aorta, and double outlet right ventricle.
Interestingly, most of the cardiac phenotypes of the
Ts1Yu were similar to those seen in the Ts65Dn, confirming that genes from the Mrpl39 to Zfp295 region are
involved in heart abnormalities in patients. A second set
of phenotypes affects the gastrointestinal tract with annular pancreas and malrotation of the intestine, which
represents a category of rare phenotypes observed in
trisomic human patients (256, 317, 327, 361). It is obvious
that those new models represent a fantastic resource for
dissecting the genetic contributions of HSA21 mouse homologs to conserved DS phenotypes.
D. Elucidating Therapeutic Pathways Using
Mouse Models
The analysis of mouse models not only unravels the
contribution of genetic region to the DS phenotypes, but
it also highlights altered pathways that could be targeted
for therapies. One of the first discoveries came from the
study of the degeneration of the basal forebrain cholinergic neurons (BFCN) observed in 12-mo-old Ts65Dn
mice (61, 142, 167). Mobley and co-workers (64) demonstrate that BFCN reduction is due to impaired retrograde
transport of nerve growth factor (NGF) from the hippocampus to the basal forebrain starting at 6 mo of age.
Impaired transport could be restored by direct NGF infusion of BFCNs (64). The loss of BFCN is common to DS,
Alzheimer’s disease (AD), and other neurodegenerative
diseases. Similarities between both DS and AD were reinforced by the description of a duplication of App causing autosomal dominant early-onset form of the disease
(308). Evidence of the role of App in BFCN degeneration
were accumulated (172, 328), and a clear demonstration
was obtained by combining the Ts65Dn trisomy and
knock-out of the App gene (315). NGF retrograde transport was inhibited by the enlargement of early endosomes
in Ts65Dn BFCNs induced by increased level of App,
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chromosomal engineering by generating new mice trisomic for the Cbr1-Orf9 genetic interval, named Ts1Rhr
(Fig. 5; Table 2). The result of a craniofacial phenotypic
analysis was quite surprising as these mice were not as
affected as the Ts65Dn mice. Somehow, the DSCR was
not sufficient to induce similar craniofacial defects in
mice, even though distinct anomalies of rostrocaudal axis
of the skull and of the mandible were noticed. Mice
combining the deletion of the Cbr1-Orf9 region (Ms1Rhr)
with the Ts65Dn trisomy confirmed the results obtained
from the comparison between the Ts65Dn and Ts1Cje:
while genes from the DSCR may contribute to the skull
development, the genes involved in Ts65Dn craniofacial
phenotypes must be located in the Sod1-Cbr1 genetic
interval (265). Interestingly, the Tc1 mouse model does
not display the same craniofacial defects as Ts65Dn mice.
Thus the difference between the two models is dependent
either on the mosaicism of the Tc1 model, which determines that every Tc1 mouse is unique, or on additional
genes located outside of the Mrpl39-Zfp295 genetic interval that leads to the craniofacial phenotypes induced in
the Ts65Dn mice (263). Similarly, impairment in learning
and memory tasks involving the hippocampus found in
Ts65Dn is not reproduced in the Ts1Rhr, while making the
Ms1Rhr deletion in Ts65Dn mice restores normal performance in the Morris water maze (267). Thus, in this case
too, the DSCR was not sufficient to induce the brain
phenotype observed in Ts65Dn. Clearly, genes from the
Sod1-Cbr1 genetic interval also contribute in learning and
memory. On the contrary, the cerebellum and the cerebellar phenotypes observed in the three aneuploid mouse
models lines are different both in the shape and the
volume of the structure (7). These data support the hypothesis proposed by Olson et al. (265) suggesting that
the effect of a single gene might not easily be seen but
could contribute to an aneuploid phenotype in combination with other genes based on the specificity of their
actions or through interaction with other genes.
A key step in responding to the challenge of making
models of DS was achieved with the Tc1 mice (263),
displaying a pleiotropic and variable “human”-like phenotype. A large number of phenotypes including behavior,
locomotor activity, LTP, synaptic plasticity, cerebellar
neuronal number, heart development, and mandible size
were affected in these mice (127, 253, 263). Even though
the transmission of the supernumerary chromosome is
not completely achieved, leading to mosaic individuals,
the Tc1 line showed a large set of deficits comparable to
human patients. Other limitations of the model are the
additional presence of small rearrangements and the random loss of HSA21. Nevertheless, Morice et al. (253)
demonstrate that the Tc1 mice have a normal long-term
reference memory and an impaired short-term working
memory. Despite carrying the largest trisomy, Tc1 mice
are not affected in the spatial Morris water maze as much
907
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DIERSSEN, HERAULT, AND ESTIVILL
Physiol Rev • VOL
Tc1 hippocampus (253), suggest a role for the gene in the
learning and memory and LTP defects found in those DS
models. Undeniably, mouse model analysis will continue
to play a key role in the identification of target genes for
the design of new therapeutic strategies to reduce DS
deficits (311).
V. FUTURE PERSPECTIVE: FROM PHENOTYPE
TO GENOTYPE AND BACK
Identifying the molecular genetic pathogenicity and
etiology of DS mental retardation has proven arduous,
despite some recent successes. DS, like other mental
retardation disorders, is a complex polygenic disorder,
with variable penetrance. The phenotypic heterogeneity
among DS patients, and overlap with other mental retardation disorders, is not fully explored or integrated with
the genetics work carried out so far. Moreover, geneenvironment interactions and the effect of environmental
factors (epigenetic modifications, effects of stress, infections, drugs, medications) on the expression of the phenotype have not been fully considered to date.
How may deregulation/dysfunction of a myriad of
different molecules in DS affect cellular mechanisms in
the brain? The affected mechanisms include those underlying neuronal development (neurite outgrowth and neuronal morphogenesis, shaping the three-dimensional architecture of neurons, synapse formation, network formation) and synapse rearrangement, allowing long-term
memory formation and adaptation to the environment,
and functional aspects of the adult brain, combining precise, localized analysis of the phenotype and knowledge
of the genes showing dosage imbalance. However, there is
a limited set of established cellular markers that are used
in the current literature, and expression patterns of many
genes remain uncharacterized. Since gene expression patterns are brain-regionally unique, distinguishing between
localized changes in a phenotype and those affecting the
entire brain is instrumental to understanding the particular developmental perturbations that result from aneuploidy.
On the other hand, the exciting new findings demonstrating considerable plasticity of the human genome may
help to explain human traits with complex genetic patterns such as individual and pathological differences in
cognitive profiles. CNVs may provide essential clues
about complex disorders generated by gene-dosage alterations, but our current knowledge on CNVs is still very
incomplete, in particular for CNVs of small size. A final
understanding of the role of CNVs in clinical phenotypes
may need to await the development of models that mimic
the molecular consequences of gene-dosage alterations.
Presumably, in DS, the situation is even more complex, as
trisomic genes may also interact with genes located in
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leading to BFCN apoptosis. Interestingly, additional pathways might also be considered as treatment with minocycline, a semisynthetic tetracycline with anti-inflammatory properties, that reduced the decrease of BFCN in the
Ts65Dn mice, suggesting a more complex scheme for
BFCN degeneration in Ts65Dn mice (169).
A second major step was achieved by the group of
Craig Garner when they demonstrated the benefit of
GABAA receptor antagonist on the cognitive performance
of the Ts65Dn mice (114). Indeed, it was proposed that
the learning and memory deficits and impaired LTP observed in Ts65Dn mice were due to an increase of
GABAergic synaptic transmission (32, 199). Blocking the
GABAergic inhibition by using GABAA receptor antagonists, such as picrotoxin or pentylenetetrazole (PTZ; Refs.
27, 114, 199), restores cognitive performance in several
tests including Y maze, novel object recognition, and LTP.
Nevertheless, such antagonists have severe adverse effects. They can provoke epilepsy at a higher dose. Thus
caution should be taken especially in DS patients who are
already suffering from epilepsy (88). Accordingly, a second study clearly showed that chronic treatment with PTZ
induced adverse effect on locomotor function of Ts65Dn
assessed in the rotarod test without modification of the
sensory abilities, while learning and memory were improved in the Morris water maze (310).
New targets were identified via the modeling of DS
such as Dyrk1A, encoding a serine-threonine kinase
whose imbalance induces a variety of phenotypes (4, 8,
14, 47, 86, 219, 238, 240). Part of those changes could be
reverted through RNA-mediated inhibition, showing that
Dyrk1A-induced phenotypes are valuable targets for therapeutic approaches (196, 269, 326). To this end, molecules, such as Epigallocatechin-3-gallate, a major component of green tea (3), or harmine (21, 326), that could alter
directly the Dyrk1A kinase activity, or others that would
change the consequence of an hyperactive remodeling
effect of Dyrk1A on chromatin (345) are current candidates.
Other promising approaches are emerging from the
studies of mouse models. For example, the Kcnj6/Girk2,
which encodes the G protein-coupled inward rectifying
potassium channel subunit 2 (GIRK2), increased in genedosage may have a functional effect on the balance of
excitatory and inhibitory neuronal transmission perturbed in DS models (32, 152, 343). Comparing consequences on learning and memory and LTP in mouse models also pinpoint candidate genes such as Gria1 that
encodes the AMPA receptor subunit according to Schmitt
et al. (322). Gria1 is involved in CA3-CA1 LTP and controls
hippocampus-dependent spatial working memory but not
the spatial reference memory (295, 321). Changes in the
phosphorylation level of Gria1, observed in Ts65Dn hippocampal neurons (342), and reduced surface expression
of Gria1, described in the postsynaptic membrane of the
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
ACKNOWLEDGMENTS
We thank Monica Joana Do Santos and John Crabbe for
their critical reading of the manuscript.
Physiol Rev • VOL
Address for reprint requests and other correspondence: M.
Dierssen, Genes and Disease Program, Genomic Regulation
Center-CRG, Pompeu Fabra University, Barcelona Biomedical
Research Park, Dr Aiguader 88, PRBB building E, 08003 Barcelona, Catalonia, Spain (e-mail: [email protected]).
GRANTS
X. Estivill and M. Dierssen are supported by SAF-200402808, SAF2007-60827, SAF2007-31093-E, Marató TV3, Fundación R. Areces, FIS (PI082038), and “Genoma España”
(GEN2003-20651-C06-03). CIBER de Enfermedades Raras and
CIBERESP are initiatives of the ISCIII. Y. Herault is funded by
grants from the Centre National de la Recherche Scientifique,
“Region Centre,” and “Conseil Général du Loiret.” M. Dierssen,
Y. Herault, and X. Estivill are funded by the AnEUploidy project
(LSHG-CT-2006-037627) supported by European Union Sixth
Framework Program and the Fondation Jerome Lejeune.
REFERENCES
1. Abbeduto L, Warren SF, Conners FA. Language development in
Down syndrome: from the prelinguistic period to the acquisition of
literacy. Downs Syndr Res Pract 13: 247–261, 2007.
2. Abrous DN, Koehl M, Le Moal M. Adult neurogenesis: from
precursors to network and physiology. Physiol Rev 85: 523–569,
2005.
3. Adayev T, Chen-Hwang MC, Murakami N, Wegiel J, Hwang YW.
Kinetic properties of a MNB/DYRK1A mutant suitable for the elucidation of biochemical pathways. Biochemistry 45: 12011–12019, 2006.
4. Ahn KJ, Jeong HK, Choi HS, Ryoo SR, Kim YJ, Goo JS, Choi
SY, Han JS, Ha I, Song WJ. DYRK1A BAC transgenic mice show
altered synaptic plasticity with learning and memory defects. Neurobiol Dis 22: 463– 472, 2006.
5. Ait Yahya-Graison E, Aubert J, Dauphinot L, Rivals I, Prieur
M, Golfier G, Rossier J, Personnaz L, Creau N, Blehaut H,
Robin S, Delabar JM, Potier MC. Classification of human chromosome 21 gene-expression variations in Down syndrome: impact
on disease phenotypes. Am J Hum Genet 81: 475– 491, 2007.
6. Aitman TJ, Dong R, Vyse TJ, Norsworthy PJ, Johnson MD,
Smith J, Mangion J, Roberton-Lowe C, Marshall AJ, Petretto
E, Hodges MD, Bhangal G, Patel SG, Sheehan-Rooney K, Duda
M, Cook PR, Evans DJ, Domin J, Flint J, Boyle JJ, Pusey CD,
Cook HT. Copy number polymorphism in Fcgr3 predisposes to
glomerulonephritis in rats and humans. Nature 439: 851– 855, 2006.
7. Aldridge K, Reeves RH, Olson LE, Richtsmeier JT. Differential
effects of trisomy on brain shape and volume in related aneuploid
mouse models. Am J Med Genet A 143: 1060 –1070, 2007.
8. Alvarez M, Altafaj X, Aranda S, de la Luna S. DYRK1A autophosphorylation on serine residue 520 modulates its kinase activity
via 14 –3-3 binding. Mol Biol Cell 18: 1167–1178, 2007.
9. Amano K, Sago H, Uchikawa C, Suzuki T, Kotliarova SE,
Nukina N, Epstein CJ, Yamakawa K. Dosage-dependent overexpression of genes in the trisomic region of Ts1Cje mouse model
for Down syndrome. Hum Mol Genet 13: 1333–1340, 2004.
10. Amaral DG, Witter MP. The three-dimensional organization of
the hippocampal formation: a review of anatomical data. Neuroscience 31: 571–591, 1989.
11. Antonarakis SE, Avramopoulos D, Blouin JL, Talbot CC Jr,
Schinzel AA. Mitotic errors in somatic cells cause trisomy 21 in
about 4.5% of cases and are not associated with advanced maternal
age. Nat Genet 3: 146 –150, 1993.
12. Antonarakis SE, Epstein CJ. The challenge of Down syndrome.
Trends Mol Med 12: 473– 479, 2006.
13. Antonarakis SE, Lyle R, Dermitzakis ET, Reymond A, Deutsch S. Chromosome 21 and down syndrome: from genomics to
pathophysiology. Nat Rev Genet 5: 725–738, 2004.
14. Arron JR, Winslow MM, Polleri A, Chang CP, Wu H, Gao X,
Neilson JR, Chen L, Heit JJ, Kim SK, Yamasaki N, Miyakawa
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
regions showing copy number variation. Several insights
into this field have been gained over the years through the
study of aneuploidies at the chromosomal or gene level.
Thus it is of major importance to develop a complete set
of mouse models for DS. For the moment, trisomic models for the MMU17 and MMU10 regions homologous to the
telomeric part of HSA21 are still missing. Having those
models is essential to allow the generation of a model
carrying the complete trisomy of region homologous to
HSA21 and to assess more completely the genetic interactions among homologous regions. In addition, the availability in the future of a series of deletions covering
almost the entire homologous region to HSA21 could be
combined with the Tc1 mouse model to rescue the phenotypic defects and to analyze the genetic contribution
(36, 364).
At the moment, it is still not clear whether phenotypes are induced by a series of interacting genes, each
with a minimal contribution, or by major genes sensitive
to dosage combining, with epistatic relation. New steps
for DS research should thus include the following:
1) carrying out studies with groups of genes or genomic
regions that may work together, in addition to studies
with individual genes; 2) analysis of genetic association
with discrete quantitative endophenotypes (154, 261)
rather than broad mental retardation classifications
(IQ); and 3) use of gene expression studies (in human
postmortem brain or animal models), which are a direct
reflection of gene-environment interactions, in a microscale genomic approach that analyzes genetic patterns
at the cellular level.
Animal models will be useful tools in this endeavor
because 1) gene expression studies in animal models can
identify groups of genes that change together, and thus
may work together, on a relatively homogeneous genetic
background, with the signal not masked by the noise
generated from the variable genetic background present
in human studies; 2) specific phenotypes of the disorder
can be deliberately mimicked in animal models with behavioral approaches; and 3) gene-environment interactions are minimized, well-defined, and well-controlled in
animal model studies as opposed to human studies.
The elucidation of the aspects described above may
contribute to developing new strategies to induce recovery of function in the DS central nervous system. Potential therapies could result in structural changes, such as
axonal growth or synaptic reorganization in the brain or
spinal cord, with expected functional recovery. This
structural reorganization or repair will be more likely to
lead to functional recovery if adequate training is provided simultaneously with new synapse formation.
909
910
15.
16.
17.
18.
19.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
T, Francke U, Graef IA, Crabtree GR. NFAT dysregulation by
increased dosage of DSCR1 and DYRK1A on chromosome 21.
Nature 441: 595– 600, 2006.
Asada H, Uyemura K, Shirao T. Actin-binding protein, drebrin,
accumulates in submembranous regions in parallel with neuronal
differentiation. J Neurosci Res 38: 149 –159, 1994.
Aylward EH, Li Q, Honeycutt NA, Warren AC, Pulsifer MB,
Barta PE, Chan MD, Smith PD, Jerram M, Pearlson GD. MRI
volumes of the hippocampus and amygdala in adults with Down’s
syndrome with and without dementia. Am J Psychiatry 156: 564 –
568, 1999.
Baddeley A. The fractionation of human memory. Psychol Med 14:
259 –264, 1984.
Baddeley AD, Hitch G. Working memory. In: The Psychology of
Learning and Motivation: Advances in Research and Theory,
edited by Bower GH. New York: Academic, 1974, p. 47– 89.
Bahado-Singh RO, Oz AU, Gomez K, Hunter D, Copel J, Baumgarten A, Mahoney MJ. Combined ultrasound biometry, serum
markers and age for Down syndrome risk estimation. Ultrasound
Obstet Gynecol 15: 199 –204, 2000.
Bailey JA, Gu Z, Clark RA, Reinert K, Samonte RV, Schwartz
S, Adams MD, Myers EW, Li PW, Eichler EE. Recent segmental
duplications in the human genome. Science 297: 1003–1007, 2002.
Bain J, Plater L, Elliott M, Shpiro N, Hastie CJ, McLauchlan
H, Klevernic I, Arthur JS, Alessi DR, Cohen P. The selectivity
of protein kinase inhibitors: a further update. Biochem J 408:
297–315, 2007.
Baxter LL, Moran TH, Richtsmeier JT, Troncoso J, Reeves
RH. Discovery and genetic localization of Down syndrome cerebellar phenotypes using the Ts65Dn mouse. Hum Mol Genet 9:
195–202, 2000.
Becker L, Mito T, Takashima S, Onodera K. Growth and development of the brain in Down syndrome. Prog Clin Biol Res 373:
133–152, 1991.
Becker LE, Armstrong DL, Chan F. Dendritic atrophy in children
with Down’s syndrome. Ann Neurol 20: 520 –526, 1986.
Becker LE, Mito T, Takashima S, Onodera K, Friend WC.
Association of phenotypic abnormalities of Down syndrome with
an imbalance of genes on chromosome 21. APMIS Suppl 40: 57–70,
1993.
Beckmann JS, Estivill X, Antonarakis SE. Copy number variants and genetic traits: closer to the resolution of phenotypic to
genotypic variability. Nat Rev Genet 8: 639 – 646, 2007.
Belichenko PV, Kleschevnikov AM, Salehi A, Epstein CJ,
Mobley WC. Synaptic and cognitive abnormalities in mouse
models of Down syndrome: exploring genotype-phenotype relationships. J Comp Neurol 504: 329 –345, 2007.
Belichenko PV, Masliah E, Kleschevnikov AM, Villar AJ,
Epstein CJ, Salehi A, Mobley WC. Synaptic structural abnormalities in the Ts65Dn mouse model of Down Syndrome. J Comp
Neurol 480: 281–298, 2004.
Benavides-Piccione R, Dierssen M, Ballesteros-Yanez I, Martinez de Lagran M, Arbones ML, Fotaki V, DeFelipe J, Elston
GN. Alterations in the phenotype of neocortical pyramidal cells in the
Dyrk1A⫹/⫺ mouse. Neurobiol Dis 20: 115–122, 2005.
Berg JS, Brunetti-Pierri N, Peters SU, Kang SH, Fong CT,
Salamone J, Freedenberg D, Hannig VL, Prock LA, Miller
DT, Raffalli P, Harris DJ, Erickson RP, Cunniff C, Clark GD,
Blazo MA, Peiffer DA, Gunderson KL, Sahoo T, Patel A,
Lupski JR, Beaudet AL, Cheung SW. Speech delay and autism
spectrum behaviors are frequently associated with duplication of
the 7q11.23 Williams-Beuren syndrome region. Genet Med 9: 427–
441, 2007.
Besson V, Brault V, Duchon A, Togbe D, Bizot JC, Quesniaux
VF, Ryffel B, Herault Y. Modeling the monosomy for the telomeric part of human chromosome 21 reveals haploinsufficient
genes modulating the inflammatory and airway responses. Hum
Mol Genet 16: 2040 –2052, 2007.
Best TK, Siarey RJ, Galdzicki Z. Ts65Dn, a mouse model of
Down syndrome, exhibits increased GABAB-induced potassium
current. J Neurophysiol 97: 892–900, 2007.
Physiol Rev • VOL
33. Bilodeau M, Girard S, Hebert J, Sauvageau G. A retroviral
strategy that efficiently creates chromosomal deletions in mammalian cells. Nat Methods 4: 263–268, 2007.
34. Bishop DV. The role of genes in the etiology of specific language
impairment. J Commun Disord 35: 311–328, 2002.
35. Bornstein MH, Sigman MD. Continuity in mental development
from infancy. Child Dev 57: 251–274, 1986.
36. Brault V, Pereira P, Duchon A, Herault Y. Modeling chromosomes in mouse to explore the function of genes, genomic disorders, and chromosomal organization. PLoS Genet 2: e86, 2006.
37. Brown JH, Johnson MH, Paterson SJ, Gilmore R, Longhi E,
Karmiloff-Smith A. Spatial representation and attention in toddlers with Williams syndrome and Down syndrome. Neuropsychologia 41: 1037–1046, 2003.
38. Burt DB, Loveland KA, Primeaux-Hart S, Chen YW, Phillips
NB, Cleveland LA, Lewis KR, Lesser J, Cummings E. Dementia
in adults with Down syndrome: diagnostic challenges. Am J Ment
Retard 103: 130 –145, 1998.
39. Bush A, Beail N. Risk factors for dementia in people with Down
syndrome: issues in assessment and diagnosis. Am J Ment Retard
109: 83–97, 2004.
40. Buxhoeveden D, Casanova MF. Accelerated maturation in brains
of patients with Down syndrome. J Intellect Disabil Res 48: 704 –
705, 2004.
41. Byrne A, MacDonald J, Buckley S. Reading, language and memory skills: a comparative longitudinal study of children with Down
syndrome and their mainstream peers. Br J Educ Psychol 72:
513–529, 2002.
42. Caceres M, Lachuer J, Zapala MA, Redmond JC, Kudo L,
Geschwind DH, Lockhart DJ, Preuss TM, Barlow C. Elevated
gene expression levels distinguish human from non-human primate
brains. Proc Natl Acad Sci USA 100: 13030 –13035, 2003.
43. Cairns NJ. Molecular neuropathology of transgenic mouse models
of Down syndrome. J Neural Transm Suppl: 289 –301, 2001.
44. Canfield MA, Honein MA, Yuskiv N, Xing J, Mai CT, Collins
JS, Devine O, Petrini J, Ramadhani TA, Hobbs CA, Kirby RS.
National estimates and race/ethnic-specific variation of selected
birth defects in the United States, 1999 –2001. Birth Defects Res A
Clin Mol Teratol 76: 747–756, 2006.
45. Cannon TD, Thompson PM, van Erp TG, Huttunen M, Lonnqvist J, Kaprio J, Toga AW. Mapping heritability and molecular
genetic associations with cortical features using probabilistic brain
atlases: methods and applications to schizophrenia. Neuroinformatics 4: 5–19, 2006.
46. Cano E, Canellada A, Minami T, Iglesias T, Redondo JM.
Depolarization of neural cells induces transcription of the Down
syndrome critical region 1 isoform 4 via a calcineurin/nuclear
factor of activated T cells-dependent pathway. J Biol Chem 280:
29435–29443, 2005.
47. Canzonetta C, Mulligan C, Deutsch S, Ruf S, O’Doherty A,
Lyle R, Borel C, Lin-Marq N, Delom F, Groet J, Schnappauf F,
De Vita S, Averill S, Priestley JV, Martin JE, Shipley J,
Denyer G, Epstein CJ, Fillat C, Estivill X, Tybulewicz VL,
Fisher EM, Antonarakis SE, Nizetic D. DYRK1A-dosage imbalance perturbs NRSF/REST levels, deregulating pluripotency and
embryonic stem cell fate in Down syndrome. Am J Hum Genet 83:
388 – 400, 2008.
48. Carlesimo GA, Marotta L, Vicari S. Long-term memory in mental
retardation: evidence for a specific impairment in subjects with
Down’s syndrome. Neuropsychologia 35: 71–79, 1997.
49. Carter NP. Methods and strategies for analyzing copy number
variation using DNA microarrays. Nat Genet 39: S16 –S21, 2007.
50. Caycho L, Gunn P, Siegal M. Counting by children with Down
syndrome. Am J Ment Retard 95: 575–583, 1991.
51. Chapman RS. Language learning in Down syndrome: the speech
and language profile compared to adolescents with cognitive impairment of unknown origin. Downs Syndr Res Pract 10: 61– 66,
2006.
52. Chapman RS, Hesketh LJ, Kistler DJ. Predicting longitudinal
change in language production and comprehension in individuals
with Down syndrome: hierarchical linear modeling. J Speech Lang
Hear Res 45: 902–915, 2002.
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
20.
DIERSSEN, HERAULT, AND ESTIVILL
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
Physiol Rev • VOL
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83.
84.
85.
86.
87.
88.
89.
90.
91.
scriptome during postnatal development of the Ts1Cje mouse, a
segmental trisomy model for Down syndrome. Hum Mol Genet 14:
373–384, 2005.
Davisson M, Akeson E, Schmidt C, Harris B, Farley J, Handel
MA. Impact of trisomy on fertility and meiosis in male mice. Hum
Reprod 22: 468 – 476, 2007.
Davisson MT, Bechtel LJ, Akeson EC, Fortna A, Slavov D,
Gardiner K. Evolutionary breakpoints on human chromosome 21.
Genomics 78: 99 –106, 2001.
Davisson MT, Schmidt C, Akeson EC. Segmental trisomy of
murine chromosome 16: a new model system for studying Down
syndrome. Prog Clin Biol Res 360: 263–280, 1990.
De la Luna S, Estivill X. Cooperation to amplify gene-dosageimbalance effects. Trends Mol Med 12: 451– 454, 2006.
Deb S, Braganza J. Comparison of rating scales for the diagnosis
of dementia in adults with Down’s syndrome. J Intellect Disabil
Res 43: 400 – 407, 1999.
Delabar JM, Aflalo-Rattenbac R, Creau N. Developmental defects in trisomy 21 and mouse models. Scientific World J 6: 1945–
1964, 2006.
Delabar JM, Theophile D, Rahmani Z, Chettouh Z, Blouin JL,
Prieur M, Noel B, Sinet PM. Molecular mapping of twenty-four
features of Down syndrome on chromosome 21. Eur J Hum Genet
1: 114 –124, 1993.
Demas GE, Nelson RJ, Krueger BK, Yarowsky PJ. Spatial
memory deficits in segmental trisomic Ts65Dn mice. Behav Brain
Res 82: 85–92, 1996.
Dermitzakis ET, Kirkness E, Schwarz S, Birney E, Reymond
A, Antonarakis SE. Comparison of human chromosome 21 conserved nongenic sequences (CNGs) with the mouse and dog genomes shows that their selective constraint is independent of their
genic environment. Genome Res 14: 852– 859, 2004.
Dermitzakis ET, Reymond A, Lyle R, Scamuffa N, Ucla C,
Deutsch S, Stevenson BJ, Flegel V, Bucher P, Jongeneel CV,
Antonarakis SE. Numerous potentially functional but non-genic
conserved sequences on human chromosome 21. Nature 420: 578 –
582, 2002.
Deutsch S, Lyle R, Dermitzakis ET, Attar H, Subrahmanyan L,
Gehrig C, Parand L, Gagnebin M, Rougemont J, Jongeneel
CV, Antonarakis SE. Gene expression variation and expression
quantitative trait mapping of human chromosome 21 genes. Hum
Mol Genet 14: 3741–3749, 2005.
Devinsky O, Sato S, Conwit RA, Schapiro MB. Relation of EEG
alpha background to cognitive function, brain atrophy, and cerebral metabolism in Down’s syndrome. Age-specific changes. Arch
Neurol 47: 58 – 62, 1990.
Dierssen M, Benavides-Piccione R, Martinez-Cue C, Estivill
X, Florez J, Elston GN, DeFelipe J. Alterations of neocortical
pyramidal cell phenotype in the Ts65Dn mouse model of Down
syndrome: effects of environmental enrichment. Cereb Cortex 13:
758 –764, 2003.
Dierssen M, de Lagran MM. DYRK1A (dual-specificity tyrosinephosphorylated and -regulated kinase 1A): a gene with dosage
effect during development and neurogenesis. Scientific World J 6:
1911–1922, 2006.
Dierssen M, Fillat C, Crnic L, Arbones M, Florez J, Estivill X.
Murine models for Down syndrome. Physiol Behav 73: 859 – 871,
2001.
Dierssen M, Ortiz-Abalia J, Arque G, de Lagran MM, Fillat C.
Pitfalls and hopes in Down syndrome therapeutic approaches: in
the search for evidence-based treatments. Behav Genet 36: 454 –
468, 2006.
Dierssen M, Vallina IF, Baamonde C, Garcia-Calatayud S,
Lumbreras MA, Florez J. Alterations of central noradrenergic
transmission in Ts65Dn mouse, a model for Down syndrome. Brain
Res 749: 238 –244, 1997.
Dillon C, Goda Y. The actin cytoskeleton: integrating form and
function at the synapse. Annu Rev Neurosci 28: 25–55, 2005.
Doherty AM, Fisher EM. Microcell-mediated chromosome transfer (MMCT): small cells with huge potential. Mamm Genome 14:
583–592, 2003.
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
53. Chapman RS, Schwartz SE, Bird EK. Language skills of children
and adolescents with Down syndrome. I. Comprehension. J Speech
Hear Res 34: 1106 –1120, 1991.
54. Chapman RS, Seung HK, Schwartz SE, Bird EK. Predicting
language production in children and adolescents with Down syndrome: the role of comprehension. J Speech Lang Hear Res 43:
340 –350, 2000.
55. Cheung J, Estivill X, Khaja R, MacDonald JR, Lau K, Tsui LC,
Scherer SW. Genome-wide detection of segmental duplications
and potential assembly errors in the human genome sequence.
Genome Biol 4: R25, 2003.
56. Chrast R, Scott HS, Papasavvas MP, Rossier C, Antonarakis
ES, Barras C, Davisson MT, Schmidt C, Estivill X, Dierssen M,
Pritchard M, Antonarakis SE. The mouse brain transcriptome by
SAGE: differences in gene expression between P30 brains of the
partial trisomy 16 mouse model of Down syndrome (Ts65Dn) and
normals. Genome Res 10: 2006 –2021, 2000.
57. Clark D, Wilson GN. Behavioral assessment of children with
Down syndrome using the Reiss psychopathology scale. Am J Med
Genet A 118: 210 –216, 2003.
58. Colon EY. The structure of the cerebral cortex in Down’s syndrome: quantitative analysis. Neuropediatrics 3: 362–376, 1972.
59. Conrad DF, Andrews TD, Carter NP, Hurles ME, Pritchard
JK. A high-resolution survey of deletion polymorphism in the
human genome. Nat Genet 38: 75– 81, 2006.
60. Contestabile A, Fila T, Bartesaghi R, Ciani E. Cell cycle elongation impairs proliferation of cerebellar granule cell precursors in
the Ts65Dn mouse, an animal model for down syndrome. Brain
Pathol 19: 224 –237, 2009.
61. Contestabile A, Fila T, Bartesaghi R, Ciani E. Choline acetyltransferase activity at different ages in brain of Ts65Dn mice, an
animal model for Down’s syndrome and related neurodegenerative
diseases. J Neurochem 97: 515–526, 2006.
62. Contestabile A, Fila T, Ceccarelli C, Bonasoni P, Bonapace L,
Santini D, Bartesaghi R, Ciani E. Cell cycle alteration and decreased cell proliferation in the hippocampal dentate gyrus and in
the neocortical germinal matrix of fetuses with down syndrome
and in Ts65Dn mice. Hippocampus 17: 665– 678, 2007.
63. Cook EH Jr., Scherer SW. Copy-number variations associated
with neuropsychiatric conditions. Nature 455: 919 –923, 2008.
64. Cooper JD, Salehi A, Delcroix JD, Howe CL, Belichenko PV,
Chua-Couzens J, Kilbridge JF, Carlson EJ, Epstein CJ,
Mobley WC. Failed retrograde transport of NGF in a mouse model
of Down’s syndrome: reversal of cholinergic neurodegenerative
phenotypes following NGF infusion. Proc Natl Acad Sci USA 98:
10439 –10444, 2001.
65. Courtney SM, Ungerleider LG, Keil K, Haxby JV. Object and
spatial visual working memory activate separate neural systems in
human cortex. Cereb Cortex 6: 39 – 49, 1996.
66. Cox DR, Epstein LB, Epstein CJ. Genes coding for sensitivity to
interferon (IfRec) and soluble superoxide dismutase (SOD-1) are
linked in mouse and man and map to mouse chromosome 16. Proc
Natl Acad Sci USA 77: 2168 –2172, 1980.
67. Craig-Holmes AP, Moore FB, Shaw MW. Polymorphism of human C-band heterochromatin. I. Frequency of variants. Am J Hum
Genet 25: 181–192, 1973.
68. Craig-Holmes AP, Moore FB, Shaw MW. Polymporphism of
human C-band heterochromatin. II. Family studies with suggestive
evidence for somatic crossing over. Am J Hum Genet 27: 178 –189,
1975.
69. Crnic LS, Pennington BF. Down syndrome:neuropsychology and
animal models. Progr Infanc Res 1: 69 –111, 2000.
70. Cusco I, Corominas R, Bayes M, Flores R, Rivera-Brugues N,
Campuzano V, Perez-Jurado LA. Copy number variation at the
7q11 23 segmental duplications is a susceptibility factor for the
Williams-Beuren syndrome deletion. Genome Res 18: 683– 694,
2008.
71. Da Silva JS, Dotti CG. Breaking the neuronal sphere: regulation
of the actin cytoskeleton in neuritogenesis. Nat Rev Neurosci 3:
694 –704, 2002.
72. Dauphinot L, Lyle R, Rivals I, Dang MT, Moldrich RX, Golfier
G, Ettwiller L, Toyama K, Rossier J, Personnaz L, Antonarakis SE, Epstein CJ, Sinet PM, Potier MC. The cerebellar tran-
911
912
DIERSSEN, HERAULT, AND ESTIVILL
Physiol Rev • VOL
112. Fellermann K, Stange DE, Schaeffeler E, Schmalzl H, Wehkamp J, Bevins CL, Reinisch W, Teml A, Schwab M, Lichter P,
Radlwimmer B, Stange EF. A chromosome 8 gene-cluster polymorphism with low human beta-defensin 2 gene copy number
predisposes to Crohn disease of the colon. Am J Hum Genet 79:
439 – 448, 2006.
113. Fernandez F, Garner CC. Object recognition memory is conserved in Ts1Cje, a mouse model of Down syndrome. Neurosci Lett
30: 497–503, 2007.
114. Fernandez F, Morishita W, Zuniga E, Nguyen J, Blank M,
Malenka RC, Garner CC. Pharmacotherapy for cognitive impairment in a mouse model of Down syndrome. Nat Neurosci 10:
411– 413, 2007.
115. Feuk L, Carson AR, Scherer SW. Structural variation in the
human genome. Nat Rev Genet 7: 85–97, 2006.
116. Feuk L, Kalervo A, Lipsanen-Nyman M, Skaug J, Nakabayashi
K, Finucane B, Hartung D, Innes M, Kerem B, Nowaczyk MJ,
Rivlin J, Roberts W, Senman L, Summers A, Szatmari P, Wong
V, Vincent JB, Zeesman S, Osborne LR, Cardy JO, Kere J,
Scherer SW, Hannula-Jouppi K. Absence of a paternally inherited FOXP2 gene in developmental verbal dyspraxia. Am J Hum
Genet 79: 965–972, 2006.
117. Fidler DJ, Nadel L. Education and children with Down syndrome:
neuroscience, development, and intervention. Ment Retard Dev
Disabil Res Rev 13: 262–271, 2007.
118. FitzPatrick DR. Transcriptional consequences of autosomal trisomy: primary gene-dosage with complex downstream effects.
Trends Genet 21: 249 –253, 2005.
119. FitzPatrick DR, Ramsay J, McGill NI, Shade M, Carothers AD,
Hastie ND. Transcriptome analysis of human autosomal trisomy.
Hum Mol Genet 11: 3249 –3256, 2002.
120. Florez J. Neurologic abnormalities. In: Biomedical Concerns in
Persons With Down Syndrome, edited by Pueschel SM and
Pueschel JK. Baltimore, MD: Brookes, 1992, p. 159 –173.
121. Florez J, del Arco C, Gonzalez A, Pascual J, Pazos A. Autoradiographic studies of neurotransmitter receptors in the brain of
newborn infants with Down syndrome. Am J Med Genet Suppl 7:
301–305, 1990.
122. Fotaki V, Dierssen M, Alcantara S, Martinez S, Marti E, Casas
C, Visa J, Soriano E, Estivill X, Arbones ML. Dyrk1A haploinsufficiency affects viability and causes developmental delay and
abnormal brain morphology in mice. Mol Cell Biol 22: 6636 – 6647,
2002.
123. Frangou S, Aylward E, Warren A, Sharma T, Barta P, Pearlson
G. Small planum temporale volume in Down’s syndrome: a volumetric
MRI study. Am J Psychiatry 154: 1424 –1429, 1997.
124. Freeman JL, Perry GH, Feuk L, Redon R, McCarroll SA,
Altshuler DM, Aburatani H, Jones KW, Tyler-Smith C, Hurles
ME, Carter NP, Scherer SW, Lee C. Copy number variation: new
insights in genome diversity. Genome Res 16: 949 –961, 2006.
125. Friederici AD. The developmental cognitive neuroscience of language: a new research domain. Brain Lang 71: 65– 68, 2000.
126. Friedman JI, Vrijenhoek T, Markx S, Janssen IM, van der
Vliet WA, Faas BH, Knoers NV, Cahn W, Kahn RS, Edelmann
L, Davis KL, Silverman JM, Brunner HG, van Kessel AG,
Wijmenga C, Ophoff RA, Veltman JA. CNTNAP2 gene-dosage
variation is associated with schizophrenia and epilepsy. Mol Psychiatry 13: 261–266, 2007.
127. Galante M, Jani H, Vanes L, Daniel H, Fisher EM, Tybulewicz
VL, Bliss TV, Morice E. Impairments in motor coordination without major changes in cerebellar plasticity in the Tc1 mouse model
of Down syndrome. Hum Mol Genet 2009.
128. Galdzicki Z, Siarey R, Pearce R, Stoll J, Rapoport SI. On the
cause of mental retardation in Down syndrome: extrapolation from
full and segmental trisomy 16 mouse models. Brain Res Brain Res
Rev 35: 115–145, 2001.
129. Galdzicki Z, Siarey RJ. Understanding mental retardation in
Down’s syndrome using trisomy 16 mouse models. Genes Brain
Behav 2: 167–178, 2003.
130. Gardiner K. Gene-dosage effects in Down syndrome and trisomic
mouse models. Genome Biol 5: 244, 2004.
131. Gardiner K, Fortna A, Bechtel L, Davisson MT. Mouse models
of Down syndrome: how useful can they be? Comparison of the
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
92. Dulaney CL, Raz N, Devine C. Effortful and automatic processes
associated with Down syndrome and nonspecific mental retardation. Am J Ment Retard 100: 418 – 423, 1996.
93. Dumas L, Kim YH, Karimpour-Fard A, Cox M, Hopkins J,
Pollack JR, Sikela JM. Gene copy number variation spanning 60
million years of human and primate evolution. Genome Res 17:
1266 –1277, 2007.
94. Dykens EM, Hodapp RM. Research in mental retardation: toward
an etiologic approach. J Child Psychol Psychiatry 42: 49 –71, 2001.
95. Eichenbaum H, Otto T, Cohen NJ. The hippocampus–what does
it do? Behav Neural Biol 57: 2–36, 1992.
96. Eichenbaum H, Schoenbaum G, Young B, Bunsey M. Functional organization of the hippocampal memory system. Proc Natl
Acad Sci USA 93: 13500 –13507, 1996.
97. Eichenbaum H, Yonelinas AP, Ranganath C. The medial temporal lobe and recognition memory. Annu Rev Neurosci 30: 123–
152, 2007.
98. Eichler EE, Nickerson DA, Altshuler D, Bowcock AM, Brooks
LD, Carter NP, Church DM, Felsenfeld A, Guyer M, Lee C,
Lupski JR, Mullikin JC, Pritchard JK, Sebat J, Sherry ST,
Smith D, Valle D, Waterston RH. Completing the map of human
genetic variation. Nature 447: 161–165, 2007.
99. Enard W, Khaitovich P, Klose J, Zollner S, Heissig F, Giavalisco P, Nieselt-Struwe K, Muchmore E, Varki A, Ravid R,
Doxiadis GM, Bontrop RE, Paabo S. Intra- and interspecific
variation in primate gene expression patterns. Science 296: 340 –
343, 2002.
100. Epstein CJ. Developmental genetics. Experientia 42: 1117–1128,
1986.
101. Epstein CJ. Epilogue: toward the twenty-first century with Down
syndrome–a personal view of how far we have come and of how far
we can reasonably expect to go. Prog Clin Biol Res 393: 241–246,
1995.
102. Epstein CJ. Specificity versus nonspecificity in the pathogenesis
of aneuploid phenotypes. Am J Med Genet 29: 161–165, 1988.
103. Escorihuela RM, Fernandez-Teruel A, Vallina IF, Baamonde
C, Lumbreras MA, Dierssen M, Tobena A, Florez J. A behavioral assessment of Ts65Dn mice: a putative Down syndrome
model. Neurosci Lett 199: 143–146, 1995.
104. Escorihuela RM, Vallina IF, Martinez-Cue C, Baamonde C,
Dierssen M, Tobena A, Florez J, Fernandez-Teruel A. Impaired short- and long-term memory in Ts65Dn mice, a model for
Down syndrome. Neurosci Lett 247: 171–174, 1998.
105. Estivill X, Cheung J, Pujana MA, Nakabayashi K, Scherer SW,
Tsui LC. Chromosomal regions containing high-density and ambiguously mapped putative single nucleotide polymorphisms
(SNPs) correlate with segmental duplications in the human genome. Hum Mol Genet 11: 1987–1995, 2002.
106. Estivill X, Farrall M, Scambler PJ, Bell GM, Hawley KM,
Lench NJ, Bates GP, Kruyer HC, Frederick PA, Stanier P. A
candidate for the cystic fibrosis locus isolated by selection for
methylation-free islands. Nature 326: 840 – 845, 1987.
107. Fabbro F, Libera L, Tavano A. A callosal transfer deficit in
children with developmental language disorder. Neuropsychologia
40: 1541–1546, 2002.
108. Fan YS, Jayakar P, Zhu H, Barbouth D, Sacharow S, Morales
A, Carver V, Benke P, Mundy P, Elsas LJ. Detection of pathogenic gene copy number variations in patients with mental retardation by genomewide oligonucleotide array comparative genomic
hybridization. Hum Mutat 28: 1124 –1132, 2007.
109. Fanciulli M, Norsworthy PJ, Petretto E, Dong R, Harper L,
Kamesh L, Heward JM, Gough SC, de Smith A, Blakemore AI,
Froguel P, Owen CJ, Pearce SH, Teixeira L, Guillevin L,
Graham DS, Pusey CD, Cook HT, Vyse TJ, Aitman TJ. FCGR3B
copy number variation is associated with susceptibility to systemic,
but not organ-specific, autoimmunity. Nat Genet 39: 721–723, 2007.
110. Favorov OV, Kelly DG. Minicolumnar organization within somatosensory cortical segregates. I. Development of afferent connections. Cereb Cortex 4: 408 – 427, 1994.
111. Favorov OV, Kelly DG. Minicolumnar organization within somatosensory cortical segregates. II. Emergent functional properties. Cereb Cortex 4: 428 – 442, 1994.
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
132.
133.
134.
135.
136.
138.
139.
140.
141.
142.
143.
144.
145.
146.
147.
148.
149.
150.
151.
Physiol Rev • VOL
152. Harashima C, Jacobowitz DM, Witta J, Borke RC, Best TK,
Siarey RJ, Galdzicki Z. Abnormal expression of the G-proteinactivated inwardly rectifying potassium channel 2 (GIRK2) in hippocampus, frontal cortex, substantia nigra of Ts65Dn mouse: a
model of Down syndrome. J Comp Neurol 494: 815– 833, 2006.
153. Hartley T, Bird CM, Chan D, Cipolotti L, Husain M, VarghaKhadem F, Burgess N. The hippocampus is required for shortterm topographical memory in humans. Hippocampus 17: 34 – 48,
2007.
154. Hasler G, Drevets WC, Gould TD, Gottesman II, Manji HK.
Toward constructing an endophenotype strategy for bipolar disorders. Biol Psychiatry 60: 93–105, 2006.
155. Hassold T, Hall H, Hunt P. The origin of human aneuploidy:
where we have been, where we are going. Hum Mol Genet 16:
R203–208, 2007.
156. Hassold T, Hunt P. To err (meiotically) is human: the genesis of
human aneuploidy. Nat Rev Genet 2: 280 –291, 2001.
157. Hattori M, Fujiyama A, Taylor TD, Watanabe H, Yada T, Park
HS, Toyoda A, Ishii K, Totoki Y, Choi DK, Groner Y, Soeda E,
Ohki M, Takagi T, Sakaki Y, Taudien S, Blechschmidt K,
Polley A, Menzel U, Delabar J, Kumpf K, Lehmann R, Patterson D, Reichwald K, Rump A, Schillhabel M, Schudy A, Zimmermann W, Rosenthal A, Kudoh J, Schibuya K, Kawasaki K,
Asakawa S, Shintani A, Sasaki T, Nagamine K, Mitsuyama S,
Antonarakis SE, Minoshima S, Shimizu N, Nordsiek G, Hornischer K, Brant P, Scharfe M, Schon O, Desario A, Reichelt J,
Kauer G, Blocker H, Ramser J, Beck A, Klages S, Hennig S,
Riesselmann L, Dagand E, Haaf T, Wehrmeyer S, Borzym
K, Gardiner K, Nizetic D, Francis F, Lehrach H, Reinhardt R,
Yaspo ML. The DNA sequence of human chromosome 21. Nature
405: 311–319, 2000.
158. Hayashi K, Ishikawa R, Kawai-Hirai R, Takagi T, Taketomi A,
Shirao T. Domain analysis of the actin-binding and actin-remodeling activities of drebrin. Exp Cell Res 253: 673– 680, 1999.
159. Hayes SM, Nadel L, Ryan L. The effect of scene context on
episodic object recognition: parahippocampal cortex mediates
memory encoding and retrieval success. Hippocampus 17: 873–
889, 2007.
160. Hernandez D, Mee PJ, Martin JE, Tybulewicz VL, Fisher EM.
Transchromosomal mouse embryonic stem cell lines and chimeric
mice that contain freely segregating segments of human chromosome 21. Hum Mol Genet 8: 923–933, 1999.
161. Hill CA, Reeves RH, Richtsmeier JT. Effects of aneuploidy on
skull growth in a mouse model of Down syndrome. J Anat 210:
394 – 405, 2007.
162. Hodapp RM. Direct and indirect behavioral effects of different
genetic disorders of mental retardation. Am J Ment Retard 102:
67–79, 1997.
163. Hodapp RM, Dykens EM. Measuring behavior in genetic disorders of mental retardation. Ment Retard Dev Disabil Res Rev 11:
340 –346, 2005.
164. Hodapp RM, Dykens EM. Mental retardation’s two cultures of
behavioral research. Am J Ment Retard 98: 675– 687, 1994.
165. Hodapp RM, Dykens EM. Strengthening behavioral research on
genetic mental retardation syndromes. Am J Ment Retard 106:
4 –15, 2001.
166. Hollox EJ, Huffmeier U, Zeeuwen PL, Palla R, Lascorz J,
Rodijk-Olthuis D, van de Kerkhof PC, Traupe H, de Jongh G,
den Heijer M, Reis A, Armour JA, Schalkwijk J. Psoriasis is
associated with increased beta-defensin genomic copy number.
Nat Genet 40: 23–25, 2008.
167. Holtzman DM, Santucci D, Kilbridge J, Chua-Couzens J, Fontana DJ, Daniels SE, Johnson RM, Chen K, Sun Y, Carlson E,
Alleva E, Epstein CJ, Mobley WC. Developmental abnormalities
and age-related neurodegeneration in a mouse model of Down
syndrome. Proc Natl Acad Sci USA 93: 13333–13338, 1996.
168. Horwitz B, Schapiro MB, Grady CL, Rapoport SI. Cerebral
metabolic pattern in young adult Down’s syndrome subjects: altered intercorrelations between regional rates of glucose utilization. J Ment Defic Res 34: 237–252, 1990.
169. Hunter CL, Bachman D, Granholm AC. Minocycline prevents
cholinergic loss in a mouse model of Down’s syndrome. Ann
Neurol 56: 675– 688, 2004.
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
137.
gene content of human chromosome 21 with orthologous mouse
genomic regions. Gene 318: 137–147, 2003.
Gericke GS. An integrative view of dynamic genomic elements
influencing human brain evolution and individual neurodevelopment. Med Hypotheses 71: 360 –373, 2008.
Gibson D, Groeneweg G, Jerry P, Harris A. Age and pattern of
intellectual decline among Down syndrome and other mentally
retarded adults. Int J Rehabil Res 11: 47–55, 1988.
Glahn DC, Thompson PM, Blangero J. Neuroimaging endophenotypes: strategies for finding genes influencing brain structure and
function. Hum Brain Mapp 28: 488 –501, 2007.
Gokcora N, Atasever T, Karabacak NI, Vural G, Gucuyener K.
Tc-99m HMPAO brain perfusion imaging in young Down’s syndrome patients. Brain Dev 21: 107–112, 1999.
Golden JA, Hyman BT. Development of the superior temporal
neocortex is anomalous in trisomy 21. J Neuropathol Exp Neurol
53: 513–520, 1994.
Gonzalez E, Kulkarni H, Bolivar H, Mangano A, Sanchez R,
Catano G, Nibbs RJ, Freedman BI, Quinones MP, Bamshad
MJ, Murthy KK, Rovin BH, Bradley W, Clark RA, Anderson
SA, O’Connell RJ, Agan BK, Ahuja SS, Bologna R, Sen L,
Dolan MJ, Ahuja SK. The influence of CCL3L1 gene-containing
segmental duplications on HIV-1/AIDS susceptibility. Science 307:
1434 –1440, 2005.
Goossens M, Dozy AM, Embury SH, Zachariades Z, Hadjiminas MG, Stamatoyannopoulos G, Kan YW. Triplicated alphaglobin loci in humans. Proc Natl Acad Sci USA 77: 518 –521, 1980.
Graham D, Lantos P. Greenfield’s Neuropathology. Oxford, UK:
Oxford Univ. Press, 1997.
Granholm AC, Ford KA, Hyde LA, Bimonte HA, Hunter CL,
Nelson M, Albeck D, Sanders LA, Mufson EJ, Crnic LS. Estrogen restores cognition and cholinergic phenotype in an animal
model of Down syndrome. Physiol Behav 77: 371–385, 2002.
Granholm AC, Sanders L, Seo H, Lin L, Ford K, Isacson O.
Estrogen alters amyloid precursor protein as well as dendritic and
cholinergic markers in a mouse model of Down syndrome. Hippocampus 13: 905–914, 2003.
Granholm AC, Sanders LA, Crnic LS. Loss of cholinergic phenotype in basal forebrain coincides with cognitive decline in a
mouse model of Down’s syndrome. Exp Neurol 161: 647– 663, 2000.
Graubert TA, Cahan P, Edwin D, Selzer RR, Richmond TA, Eis
PS, Shannon WD, Li X, McLeod HL, Cheverud JM, Ley TJ. A
high-resolution map of segmental DNA copy number variation in
the mouse genome. PLoS Genet 3: e3, 2007.
Griffiths TD, Warren JD. The planum temporale as a computational hub. Trends Neurosci 25: 348 –353, 2002.
Gu J, Gu X. Induced gene expression in human brain after the split
from chimpanzee. Trends Genet 19: 63– 65, 2003.
Guidi S, Bonasoni P, Ceccarelli C, Santini D, Gualtieri F,
Ciani E, Bartesaghi R. Neurogenesis impairment and increased
cell death reduce total neuron number in the hippocampal region
of fetuses with Down syndrome. Brain Pathol 18: 180 –197, 2008.
Guihard-Costa AM, Khung S, Delbecque K, Menez F, Delezoide AL. Biometry of face and brain in fetuses with trisomy 21.
Pediatr Res 59: 33–38, 2006.
Guryev V, Saar K, Adamovic T, Verheul M, van Heesch SA,
Cook S, Pravenec M, Aitman T, Jacob H, Shull JD, Hubner N,
Cuppen E. Distribution and functional impact of DNA copy number variation in the rat. Nat Genet 40: 538 –545, 2008.
Hammerle B, Carnicero A, Elizalde C, Ceron J, Martinez S,
Tejedor FJ. Expression patterns and subcellular localization of
the Down syndrome candidate protein MNB/DYRK1A suggest a
role in late neuronal differentiation. Eur J Neurosci 17: 2277–2286,
2003.
Hammerle B, Vera-Samper E, Speicher S, Arencibia R, Martinez S, Tejedor FJ. Mnb/Dyrk1A is transiently expressed and
asymmetrically segregated in neural progenitor cells at the transition to neurogenic divisions. Dev Biol 246: 259 –273, 2002.
Hanson JE, Blank M, Valenzuela RA, Garner CC, Madison DV.
The functional nature of synaptic circuitry is altered in area CA3 of
the hippocampus in a mouse model of Down’s syndrome. J Physiol
579: 53– 67, 2007.
913
914
DIERSSEN, HERAULT, AND ESTIVILL
Physiol Rev • VOL
191. Kesslak JP, Nagata SF, Lott I, Nalcioglu O. Magnetic resonance
imaging analysis of age-related changes in the brains of individuals
with Down’s syndrome. Neurology 44: 1039 –1045, 1994.
192. Khaitovich P, Muetzel B, She X, Lachmann M, Hellmann I,
Dietzsch J, Steigele S, Do HH, Weiss G, Enard W, Heissig F,
Arendt T, Nieselt-Struwe K, Eichler EE, Paabo S. Regional
patterns of gene expression in human and chimpanzee brains.
Genome Res 14: 1462–1473, 2004.
193. Khaitovich P, Weiss G, Lachmann M, Hellmann I, Enard W,
Muetzel B, Wirkner U, Ansorge W, Paabo S. A neutral model of
transcriptome evolution. PLoS Biol 2: E132, 2004.
194. Khaja R, Zhang J, MacDonald JR, He Y, Joseph-George AM,
Wei J, Rafiq MA, Qian C, Shago M, Pantano L, Aburatani H,
Jones K, Redon R, Hurles M, Armengol L, Estivill X, Mural
RJ, Lee C, Scherer SW, Feuk L. Genome assembly comparison
identifies structural variants in the human genome. Nat Genet 38:
1413–1418, 2006.
195. Kim JJ, Fanselow MS. Modality-specific retrograde amnesia of
fear. Science 256: 675– 677, 1992.
196. Kim ND, Yoon J, Kim JH, Lee JT, Chon YS, Hwang MK, Ha I,
Song WJ. Putative therapeutic agents for the learning and memory
deficits of people with Down syndrome. Bioorg Med Chem Lett 16:
3772–3776, 2006.
197. Kittler PM, Krinsky-McHale SJ, Devenny DA. Dual-task processing as a measure of executive function: a comparison between
adults with Williams and Down syndromes. Am J Ment Retard 113:
117–132, 2008.
198. Kitzmueller E, Labudova O, Rink H, Cairns N, Lubec G. Altered gene expression in fetal Down syndrome brain as revealed by
the gene hunting technique of subtractive hybridization. J Neural
Transm Suppl 57: 99 –124, 1999.
199. Kleschevnikov AM, Belichenko PV, Villar AJ, Epstein CJ,
Malenka RC, Mobley WC. Hippocampal long-term potentiation
suppressed by increased inhibition in the Ts65Dn mouse, a genetic
model of Down syndrome. J Neurosci 24: 8153– 8160, 2004.
200. Konczak J, Timmann D. The effect of damage to the cerebellum
on sensorimotor and cognitive function in children and adolescents. Neurosci Biobehav Rev 31: 1101–1113, 2007.
201. Korbel JO, Urban AE, Affourtit JP, Godwin B, Grubert F,
Simons JF, Kim PM, Palejev D, Carriero NJ, Du L, Taillon BE,
Chen Z, Tanzer A, Saunders AC, Chi J, Yang F, Carter NP,
Hurles ME, Weissman SM, Harkins TT, Gerstein MB, Egholm
M, Snyder M. Paired-end mapping reveals extensive structural
variation in the human genome. Science 318: 420 – 426, 2007.
202. Korenberg JR, Chen XN, Schipper R, Sun Z, Gonsky R, Gerwehr
S, Carpenter N, Daumer C, Dignan P, Disteche C. Down syndrome phenotypes: the consequences of chromosomal imbalance.
Proc Natl Acad Sci USA 91: 4997–5001, 1994.
203. Krasuski JS, Alexander GE, Horwitz B, Rapoport SI, Schapiro MB. Relation of medial temporal lobe volumes to age and
memory function in nondemented adults with Down’s syndrome:
implications for the prodromal phase of Alzheimer’s disease. Am J
Psychiatry 159: 74 – 81, 2002.
204. Krinsky-McHale SJ, Devenny DA, Silverman WP. Changes in
explicit memory associated with early dementia in adults with
Down’s syndrome. J Intellect Disabil Res 46: 198 –208, 2002.
205. Kuhn DE, Nuovo GJ, Martin MM, Malana GE, Pleister AP,
Jiang J, Schmittgen TD, Terry AV Jr, Gardiner K, Head E,
Feldman DS, Elton TS. Human chromosome 21-derived miRNAs
are overexpressed in down syndrome brains and hearts. Biochem
Biophys Res Commun 370: 473– 477, 2008.
206. Kurt MA, Davies DC, Kidd M, Dierssen M, Florez J. Synaptic
deficit in the temporal cortex of partial trisomy 16 (Ts65Dn) mice.
Brain Res 858: 191–197, 2000.
207. Kurt MA, Kafa MI, Dierssen M, Davies DC. Deficits of neuronal
density in CA1 and synaptic density in the dentate gyrus, CA3 and
CA1, in a mouse model of Down syndrome. Brain Res 1022: 101–
109, 2004.
208. Larsen KB, Laursen H, Graem N, Samuelsen GB, Bogdanovic
N, Pakkenberg B. Reduced cell number in the neocortical part of
the human fetal brain in Down syndrome. Ann Anat 190: 421– 427,
2008.
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
170. Hunter CL, Bimonte HA, Granholm AC. Behavioral comparison
of 4 and 6 month-old Ts65Dn mice: age-related impairments in
working and reference memory. Behav Brain Res 138: 121–131,
2003.
171. Hunter CL, Bimonte-Nelson HA, Nelson M, Eckman CB, Granholm AC. Behavioral and neurobiological markers of Alzheimer’s
disease in Ts65Dn mice: effects of estrogen. Neurobiol Aging 25:
873– 884, 2004.
172. Hunter CL, Isacson O, Nelson M, Bimonte-Nelson H, Seo H,
Lin L, Ford K, Kindy MS, Granholm AC. Regional alterations in
amyloid precursor protein and nerve growth factor across age in a
mouse model of Down’s syndrome. Neurosci Res 45: 437– 445,
2003.
173. Hyde LA, Crnic LS. Age-related deficits in context discrimination
learning in Ts65Dn mice that model Down syndrome and Alzheimer’s disease. Behav Neurosci 115: 1239 –1246, 2001.
174. Hyde LA, Crnic LS. Reactivity to object and spatial novelty is
normal in older Ts65Dn mice that model Down syndrome and
Alzheimer’s disease. Brain Res 945: 26 –30, 2002.
175. Hyde LA, Crnic LS, Pollock A, Bickford PC. Motor learning in
Ts65Dn mice, a model for Down syndrome. Dev Psychobiol 38:
33– 45, 2001.
176. Hyde LA, Frisone DF, Crnic LS. Ts65Dn mice, a model for Down
syndrome, have deficits in context discrimination learning suggesting impaired hippocampal function. Behav Brain Res 118: 53– 60,
2001.
177. Iafrate AJ, Feuk L, Rivera MN, Listewnik ML, Donahoe PK,
Qi Y, Scherer SW, Lee C. Detection of large-scale variation in the
human genome. Nat Genet 36: 949 –951, 2004.
178. Ieshima A, Kisa T, Yoshino K, Takashima S, Takeshita K. A
morphometric CT study of Down’s syndrome showing small posterior fossa and calcification of basal ganglia. Neuroradiology 26:
493– 498, 1984.
179. Insausti AM, Megias M, Crespo D, Cruz-Orive LM, Dierssen
M, Vallina IF, Insausti R, Florez J. Hippocampal volume and
neuronal number in Ts65Dn mice: a murine model of Down syndrome. Neurosci Lett 253: 175–178, 1998.
180. International HapMap Consortium. A haplotype map of the
human genome. Nature 437: 1299 –1320, 2005.
181. Ionita-Laza I, Rogers AJ, Lange C, Raby BA, Lee C. Genetic
association analysis of copy-number variation (CNV) in human
disease pathogenesis. Genomics 93: 22–26, 2009.
182. Ishizuka N, Weber J, Amaral DG. Organization of intrahippocampal projections originating from CA3 pyramidal cells in the
rat. J Comp Neurol 295: 580 – 623, 1990.
183. Jernigan TL, Bellugi U, Sowell E, Doherty S, Hesselink JR.
Cerebral morphologic distinctions between Williams and Down
syndromes. Arch Neurol 50: 186 –191, 1993.
184. Kahlem P. Gene-dosage effect on chromosome 21 transcriptome
in trisomy 21: implication in Down syndrome cognitive disorders.
Behav Genet 36: 416 – 428, 2006.
185. Kahlem P, Sultan M, Herwig R, Steinfath M, Balzereit D,
Eppens B, Saran NG, Pletcher MT, South ST, Stetten G,
Lehrach H, Reeves RH, Yaspo ML. Transcript level alterations
reflect gene-dosage effects across multiple tissues in a mouse
model of down syndrome. Genome Res 14: 1258 –1267, 2004.
186. Kakinuma H, Ozaki M, Sato H, Takahashi H. Variation in
GABA-A subunit gene copy number in an autistic patient with
mosaic 4 p duplication (p12p16). Am J Med Genet B Neuropsychiatr Genet 147: 973–975, 2008.
187. Kalousek DK. Pathogenesis of chromosomal mosaicism and its
effect on early human development. Am J Med Genet 91: 39 – 45,
2000.
188. Kaushal D, Contos JJ, Treuner K, Yang AH, Kingsbury MA,
Rehen SK, McConnell MJ, Okabe M, Barlow C, Chun J. Alteration of gene expression by chromosome loss in the postnatal
mouse brain. J Neurosci 23: 5599 –5606, 2003.
189. Kazuki Y, Shinohara T, Tomizuka K, Katoh M, Ohguma A,
Ishida I, Oshimura M. Germline transmission of a transferred
human chromosome 21 fragment in transchromosomal mice. J
Hum Genet 46: 600 – 603, 2001.
190. Kemper TL. Anatomical basis of learning disabilities. Brain specialization. Otolaryngol Clin North Am 18: 305–314, 1985.
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
Physiol Rev • VOL
223. Lorente de No’ R. Studies on the structure of the cerebral cortex.
II. Continuation of the study of the Ammonic system. J Psychol
Neurol 46: 113–177, 1934.
224. Lorenzi HA, Reeves RH. Hippocampal hypocellularity in the
Ts65Dn mouse originates early in development. Brain Res 1104:
153–159, 2006.
225. Lukaszewicz A, Cortay V, Giroud P, Berland M, Smart I,
Kennedy H, Dehay C. The concerted modulation of proliferation
and migration contributes to the specification of the cytoarchitecture and dimensions of cortical areas. Cereb Cortex 16 Suppl 1:
i26 –34, 2006.
226. Luo L. Actin cytoskeleton regulation in neuronal morphogenesis
and structural plasticity. Annu Rev Cell Dev Biol 18: 601– 635, 2002.
227. Lupski JR. Genomic disorders: structural features of the genome
can lead to DNA rearrangements and human disease traits. Trends
Genet 14: 417– 422, 1998.
228. Lupski JR, Stankiewicz P. Genomic disorders: molecular mechanisms for rearrangements and conveyed phenotypes. PLoS Genet
1: e49, 2005.
229. Lyle R, Bena F, Gagos S, Gehrig C, Lopez G, Schinzel A,
Lespinasse J, Bottani A, Dahoun S, Taine L, Doco-Fenzy M,
Cornillet-Lefebvre P, Pelet A, Lyonnet S, Toutain A, Colleaux L, Horst J, Kennerknecht I, Wakamatsu N, Descartes
M, Franklin JC, Florentin-Arar L, Kitsiou S, Ait Yahya-Graison E, Costantine M, Sinet PM, Delabar JM, Antonarakis SE.
Genotype-phenotype correlations in Down syndrome identified by
array CGH in 30 cases of partial trisomy and partial monosomy
chromosome 21. Eur J Hum Genet 17: 454 – 466, 2009.
230. Lyle R, Gehrig C, Neergaard-Henrichsen C, Deutsch S,
Antonarakis SE. Gene expression from the aneuploid chromosome in a trisomy mouse model of down syndrome. Genome Res
14: 1268 –1274, 2004.
231. Maguire EA, Vargha-Khadem F, Mishkin M. The effects of
bilateral hippocampal damage on fMRI regional activations and
interactions during memory retrieval. Brain 124: 1156 –1170, 2001.
232. Mann DM, Yates PO, Marcyniuk B, Ravindra CR. Loss of neurones from cortical and subcortical areas in Down’s syndrome
patients at middle age. Quantitative comparisons with younger
Down’s patients and patients with Alzheimer’s disease. J Neurol
Sci 80: 79 – 89, 1987.
233. Mao R, Wang X, Spitznagel EL Jr, Frelin LP, Ting JC, Ding H,
Kim JW, Ruczinski I, Downey TJ, Pevsner J. Primary and
secondary transcriptional effects in the developing human Down
syndrome brain and heart. Genome Biol 6: R107, 2005.
234. Mao R, Zielke CL, Zielke HR, Pevsner J. Global up-regulation of
chromosome 21 gene expression in the developing Down syndrome brain. Genomics 81: 457– 467, 2003.
235. Marin-Padilla M. Pyramidal cell abnormalities in the motor cortex
of a child with Down’s syndrome. A Golgi study. J Comp Neurol
167: 63– 81, 1976.
236. Marin-Padilla M. Structural abnormalities of the cerebral cortex
in human chromosomal aberrations: a Golgi study. Brain Res 44:
625– 629, 1972.
237. Marshall CR, Noor A, Vincent JB, Lionel AC, Feuk L, Skaug J,
Shago M, Moessner R, Pinto D, Ren Y, Thiruvahindrapduram
B, Fiebig A, Schreiber S, Friedman J, Ketelaars CE, Vos YJ,
Ficicioglu C, Kirkpatrick S, Nicolson R, Sloman L, Summers
A, Gibbons CA, Teebi A, Chitayat D, Weksberg R, Thompson
A, Vardy C, Crosbie V, Luscombe S, Baatjes R, Zwaigenbaum
L, Roberts W, Fernandez B, Szatmari P, Scherer SW. Structural variation of chromosomes in autism spectrum disorder. Am J
Hum Genet 82: 477– 488, 2008.
238. Marti E, Altafaj X, Dierssen M, de la Luna S, Fotaki V, Alvarez M, Perez-Riba M, Ferrer I, Estivill X. Dyrk1A expression
pattern supports specific roles of this kinase in the adult central
nervous system. Brain Res 964: 250 –263, 2003.
239. Martin MM, Buckenberger JA, Jiang J, Malana GE, Nuovo GJ,
Chotani M, Feldman DS, Schmittgen TD, Elton TS. The human
angiotensin II type 1 receptor ⫹1166 A/C polymorphism attenuates
microRNA-155 binding. J Biol Chem 282: 24262–24269, 2007.
240. Martinez de Lagran M, Altafaj X, Gallego X, Marti E, Estivill
X, Sahun I, Fillat C, Dierssen M. Motor phenotypic alterations in
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
209. Laws G. Working memory in children and adolescents with Down
syndrome: evidence from a colour memory experiment. J Child
Psychol Psychiatry 43: 353–364, 2002.
210. Laws G, Gunn D. Relationships between reading, phonological
skills and language development in individuals with Down syndrome: a five year follow up study. Reading Writing 15: 127–148,
2002.
211. Le Marechal C, Masson E, Chen JM, Morel F, Ruszniewski P,
Levy P, Ferec C. Hereditary pancreatitis caused by triplication of
the trypsinogen locus. Nat Genet 38: 1372–1374, 2006.
212. Lee AS, Gutierrez-Arcelus M, Perry GH, Vallender EJ, Johnson WE, Miller GM, Korbel JO, Lee C. Analysis of copy number
variation in the rhesus macaque genome identifies candidate loci
for evolutionary and human disease studies. Hum Mol Genet 17:
1127–1136, 2008.
213. Lein ES, Hawrylycz MJ, Ao N, Ayres M, Bensinger A, Bernard
A, Boe AF, Boguski MS, Brockway KS, Byrnes EJ, Chen L,
Chen TM, Chin MC, Chong J, Crook BE, Czaplinska A, Dang
CN, Datta S, Dee NR, Desaki AL, Desta T, Diep E, Dolbeare
TA, Donelan MJ, Dong HW, Dougherty JG, Duncan BJ, Ebbert
AJ, Eichele G, Estin LK, Faber C, Facer BA, Fields R, Fischer
SR, Fliss TP, Frensley C, Gates SN, Glattfelder KJ, Halverson
KR, Hart MR, Hohmann JG, Howell MP, Jeung DP, Johnson
RA, Karr PT, Kawal R, Kidney JM, Knapik RH, Kuan CL, Lake
JH, Laramee AR, Larsen KD, Lau C, Lemon TA, Liang AJ, Liu
Y, Luong LT, Michaels J, Morgan JJ, Morgan RJ, Mortrud MT,
Mosqueda NF, Ng LL, Ng R, Orta GJ, Overly CC, Pak TH,
Parry SE, Pathak SD, Pearson OC, Puchalski RB, Riley
ZL, Rockett HR, Rowland SA, Royall JJ, Ruiz MJ, Sarno NR,
Schaffnit K, Shapovalova NV, Sivisay T, Slaughterbeck CR,
Smith SC, Smith KA, Smith BI, Sodt AJ, Stewart NN, Stumpf
KR, Sunkin SM, Sutram M, Tam A, Teemer CD, Thaller C,
Thompson CL, Varnam LR, Visel A, Whitlock RM, Wohnoutka
PE, Wolkey CK, Wong VY, Wood M. Genome-wide atlas of gene
expression in the adult mouse brain. Nature 445: 168 –176, 2007.
214. Lejeune J, Gauthier M, Turpin R. Etude des chromosomes
somatiques de neuf enfants mongoliens. C R Acad Sci 248: 1721,
1959.
215. Li Z, Yu T, Morishima M, Pao A, Laduca J, Conroy J, Nowak N,
Matsui S, Shiraishi I, Yu YE. Duplication of the entire 22.9 Mb
human chromosome 21 syntenic region on mouse chromosome 16
causes cardiovascular and gastrointestinal abnormalities. Hum Mol
Genet 16: 1359 –1366, 2007.
216. Lincoln AJ, Courchesne E, Kilman BA, Galambos R. Neuropsychological correlates of information-processing by children
with Down syndrome. Am J Ment Defic 89: 403– 414, 1985.
217. Lindsay EA, Botta A, Jurecic V, Carattini-Rivera S, Cheah YC,
Rosenblatt HM, Bradley A, Baldini A. Congenital heart disease
in mice deficient for the DiGeorge syndrome region. Nature 401:
379 –383, 1999.
218. Lindsay EA, Vitelli F, Su H, Morishima M, Huynh T, Pramparo
T, Jurecic V, Ogunrinu G, Sutherland HF, Scambler PJ, Bradley A, Baldini A. Tbx1 haploinsufficieny in the DiGeorge syndrome region causes aortic arch defects in mice. Nature 410:
97–101, 2001.
219. Liu F, Liang Z, Wegiel J, Hwang YW, Iqbal K, Grundke-Iqbal I,
Ramakrishna N, Gong CX. Overexpression of Dyrk1A contributes to neurofibrillary degeneration in Down syndrome. FASEB J
22: 3224 –3233, 2008.
220. Llorens-Martin MV, Rueda N, Martinez-Cue C, Torres-Aleman I, Florez J, Trejo JL. Both increases in immature dentate
neuron number and decreases of immobility time in the forced
swim test occurred in parallel after environmental enrichment of
mice. Neuroscience 147: 631– 638, 2007.
221. Locke DP, Sharp AJ, McCarroll SA, McGrath SD, Newman TL,
Cheng Z, Schwartz S, Albertson DG, Pinkel D, Altshuler DM,
Eichler EE. Linkage disequilibrium and heritability of copy-number polymorphisms within duplicated regions of the human genome. Am J Hum Genet 79: 275–290, 2006.
222. Lomholt JF, Keeling JW, Hansen BF, Ono T, Stoltze K, Kjaer
I. The prenatal development of the human cerebellar field in Down
syndrome. Orthod Craniofac Res 6: 220 –226, 2003.
915
916
241.
242.
243.
244.
246.
247.
248.
249.
250.
251.
252.
253.
254.
255.
256.
257.
258.
259.
260.
261.
TgDyrk1A transgenic mice implicate DYRK1A in Down syndrome
motor dysfunction. Neurobiol Dis 15: 132–142, 2004.
McCarroll SA, Hadnott TN, Perry GH, Sabeti PC, Zody MC,
Barrett JC, Dallaire S, Gabriel SB, Lee C, Daly MJ, Altshuler
DM. Common deletion polymorphisms in the human genome. Nat
Genet 38: 86 –92, 2006.
McKinney C, Merriman ME, Chapman PT, Gow PJ, Harrison
AA, Highton J, Jones PB, McLean L, O’Donnell JL, Pokorny V,
Spellerberg M, Stamp LK, Willis J, Steer S, Merriman TR.
Evidence for an influence of chemokine ligand 3-like 1 (CCL3L1)
gene copy number on susceptibility to rheumatoid arthritis. Ann
Rheum Dis 67: 409 – 413, 2008.
Meaburn KJ, Parris CN, Bridger JM. The manipulation of chromosomes by mankind: the uses of microcell-mediated chromosome
transfer. Chromosoma 114: 263–274, 2005.
Merla G, Howald C, Henrichsen CN, Lyle R, Wyss C, Zabot
MT, Antonarakis SE, Reymond A. Submicroscopic deletion in
patients with Williams-Beuren syndrome influences expression levels of the nonhemizygous flanking genes. Am J Hum Genet 79:
332–341, 2006.
Meyer M, Alter K, Friederici AD, Lohmann G, von Cramon
DY. FMRI reveals brain regions mediating slow prosodic modulations in spoken sentences. Hum Brain Mapp 17: 73– 88, 2002.
Milner B. Visual recognition and recall after right temporal-lobe
excision in man. Epilepsy Behav 4: 799 – 812, 2003.
Miyabara S, Gropp A, Winking H. Trisomy 16 in the mouse fetus
associated with generalized edema and cardiovascular and urinary
tract anomalies. Teratology 25: 369 –380, 1982.
Modi D, Berde P, Bhartiya D. Down syndrome: a study of chromosomal mosaicism. Reprod Biomed Online 6: 499 –503, 2003.
Moldrich RX, Dauphinot L, Laffaire J, Rossier J, Potier MC.
Down syndrome gene-dosage imbalance on cerebellum development. Prog Neurobiol 82: 87–94, 2007.
Molinari M, Grammaldo LG, Petrosini L. Cerebellar contribution to spatial event processing: right/left discrimination abilities in
rats. Eur J Neurosci 9: 1986 –1992, 1997.
Moore CS. Postnatal lethality and cardiac anomalies in the Ts65Dn
Down syndrome mouse model. Mamm Genome 17: 1005–1012,
2006.
Moran TH, Capone GT, Knipp S, Davisson MT, Reeves RH,
Gearhart JD. The effects of piracetam on cognitive performance
in a mouse model of Down’s syndrome. Physiol Behav 77: 403– 409,
2002.
Morice E, Andreae LC, Cooke SF, Vanes L, Fisher EM, Tybulewicz VL, Bliss TV. Preservation of long-term memory and
synaptic plasticity despite short-term impairments in the Tc1
mouse model of Down syndrome. Learn Mem 15: 492–500, 2008.
Moscovitch M, Nadel L, Winocur G, Gilboa A, Rosenbaum RS.
The cognitive neuroscience of remote episodic, semantic and spatial memory. Curr Opin Neurobiol 16: 179 –190, 2006.
Mountcastle VB. Introduction. Computation in cortical columns.
Cereb Cortex 13: 2– 4, 2003.
Muraoka I, Ohno Y, Kobayashi K, Honda R, Kubo T, Kanematsu T. Preduodenal position of the common bile duct associated with annular pancreas: case report and literature review.
Pancreas 31: 283–285, 2005.
Nadel L. Down’s syndrome: a genetic disorder in biobehavioral
perspective. Genes Brain Behav 2: 156 –166, 2003.
Nadel L, Moscovitch M. Memory consolidation, retrograde amnesia and the hippocampal complex. Curr Opin Neurobiol 7: 217–
227, 1997.
Nelson CA, Monk CS, Lin J, Carver LJ, Thomas KM, Truwit
CL. Functional neuroanatomy of spatial working memory in children. Dev Psychol 36: 109 –116, 2000.
Nichols S, Jones W, Roman MJ, Wulfeck B, Delis DC, Reilly J,
Bellugi U. Mechanisms of verbal memory impairment in four
neurodevelopmental disorders. Brain Lang 88: 180 –189, 2004.
Niculescu AB, Lulow LL, Ogden CA, Le-Niculescu H, Salomon
DR, Schork NJ, Caligiuri MP, Lohr JB. PhenoChipping of psychotic disorders: a novel approach for deconstructing and quantitating psychiatric phenotypes. Am J Med Genet B Neuropsychiatr
Genet 141: 653– 662, 2006.
Physiol Rev • VOL
262. Nitkin RM. Dendritic mechanisms in brain function and developmental disabilities. Cereb Cortex 10: 925–926, 2000.
263. O’Doherty A, Ruf S, Mulligan C, Hildreth V, Errington ML,
Cooke S, Sesay A, Modino S, Vanes L, Hernandez D, Linehan
JM, Sharpe PT, Brandner S, Bliss TV, Henderson DJ, Nizetic
D, Tybulewicz VL, Fisher EM. An aneuploid mouse strain carrying human chromosome 21 with Down syndrome phenotypes. Science 309: 2033–2037, 2005.
264. Oliver TR, Feingold E, Yu K, Cheung V, Tinker S, Yadav-Shah
M, Masse N, Sherman SL. New insights into human nondisjunction of chromosome 21 in oocytes. PLoS Genet 4: e1000033, 2008.
265. Olson LE, Richtsmeier JT, Leszl J, Reeves RH. A chromosome
21 critical region does not cause specific Down syndrome phenotypes. Science 306: 687– 690, 2004.
266. Olson LE, Roper RJ, Baxter LL, Carlson EJ, Epstein CJ,
Reeves RH. Down syndrome mouse models Ts65Dn, Ts1Cje,
Ms1Cje/Ts65Dn exhibit variable severity of cerebellar phenotypes.
Dev Dyn 230: 581–589, 2004.
267. Olson LE, Roper RJ, Sengstaken CL, Peterson EA, Aquino V,
Galdzicki Z, Siarey R, Pletnikov M, Moran TH, Reeves RH.
Trisomy for the Down syndrome “critical region” is necessary but
not sufficient for brain phenotypes of trisomic mice. Hum Mol
Genet 16: 774 –782, 2007.
268. O’Reilly R, Munakata Y. Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the
Brain. Cambridge, MA: MIT Press, 2000.
269. Ortiz-Abalia J, Sahun I, Altafaj X, Andreu N, Estivill X, Dierssen M, Fillat C. Targeting Dyrk1A with AAVshRNA attenuates
motor alterations in TgDyrk1A, a mouse model of Down syndrome.
Am J Hum Genet 83: 479 – 488, 2008.
270. Oster-Granite ML. The neurobiologic consequences of autosomal
trisomy in mice and men. Brain Res Bull 16: 767–771, 1986.
271. Parsons T, Ryan TM, Reeves RH, Richtsmeier JT. Microstructure of trabecular bone in a mouse model for Down syndrome.
Anat Rec 290: 414 – 421, 2007.
272. Pennington BF. From single to multiple deficit models of developmental disorders. Cognition 101: 385– 413, 2006.
273. Pennington BF, Moon J, Edgin J, Stedron J, Nadel L. The
neuropsychology of Down syndrome: evidence for hippocampal
dysfunction. Child Dev 74: 75–93, 2003.
274. Perry GH, Tchinda J, McGrath SD, Zhang J, Picker SR, Caceres AM, Iafrate AJ, Tyler-Smith C, Scherer SW, Eichler EE,
Stone AC, Lee C. Hotspots for copy number variation in chimpanzees and humans. Proc Natl Acad Sci USA 103: 8006 – 8011,
2006.
275. Perry GH, Yang F, Marques-Bonet T, Murphy C, Fitzgerald T,
Lee AS, Hyland C, Stone AC, Hurles ME, Tyler-Smith C,
Eichler EE, Carter NP, Lee C, Redon R. Copy number variation
and evolution in humans and chimpanzees. Genome Res 18: 1698 –
1710, 2008.
276. Pessoa L, Ungerleider LG. Top-down mechanisms for working
memory and attentional processes. In: The New Cognitive Neurosciences (3rd ed.), edited by Gazzaniga MS. Cambridge, MA: MIT
Press, 2004, p. 919 –930.
277. Pinter JD, Brown WE, Eliez S, Schmitt JE, Capone GT, Reiss
AL. Amygdala and hippocampal volumes in children with Down
syndrome: a high-resolution MRI study. Neurology 56: 972–974,
2001.
278. Pinter JD, Eliez S, Schmitt JE, Capone GT, Reiss AL. Neuroanatomy of Down’s syndrome: a high-resolution MRI study. Am J
Psychiatry 158: 1659 –1665, 2001.
279. Piotrowski A, Bruder CE, Andersson R, de Stahl TD, Menzel
U, Sandgren J, Poplawski A, von Tell D, Crasto C, Bogdan A,
Bartoszewski R, Bebok Z, Krzyzanowski M, Jankowski Z,
Partridge EC, Komorowski J, Dumanski JP. Somatic mosaicism for copy number variation in differentiated human tissues.
Hum Mutat 29: 1118 –1124, 2008.
280. Pope AM, Tarlov AR. Disability in America: Toward a National
Agenda for Prevention. Washington, DC: National Academic, 1991.
281. Potier MC, Rivals I, Mercier G, Ettwiller L, Moldrich RX,
Laffaire J, Personnaz L, Rossier J, Dauphinot L. Transcriptional disruptions in Down syndrome: a case study in the Ts1Cje
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
245.
DIERSSEN, HERAULT, AND ESTIVILL
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
282.
283.
284.
286.
287.
288.
289.
290.
291.
292.
293.
294.
295.
296.
297.
298.
Physiol Rev • VOL
299.
300.
301.
302.
303.
304.
305.
306.
307.
308.
309.
310.
311.
312.
313.
314.
315.
316.
317.
318.
319.
human chromosome 21 transcription map. Genomics 78: 46 –54,
2001.
Reymond A, Marigo V, Yaylaoglu MB, Leoni A, Ucla C, Scamuffa N, Caccioppoli C, Dermitzakis ET, Lyle R, Banfi S,
Eichele G, Antonarakis SE, Ballabio A. Human chromosome 21
gene expression atlas in the mouse. Nature 420: 582–586, 2002.
Richtsmeier JT, Baxter LL, Reeves RH. Parallels of craniofacial
maldevelopment in Down syndrome and Ts65Dn mice. Dev Dyn
217: 137–145, 2000.
Richtsmeier JT, Zumwalt A, Carlson EJ, Epstein CJ, Reeves
RH. Craniofacial phenotypes in segmentally trisomic mouse models for Down syndrome. Am J Med Genet 107: 317–324, 2002.
Rogers MA, Langbein L, Winter H, Beckmann I, Praetzel S,
Schweizer J. Hair keratin associated proteins: characterization of
a second high sulfur KAP gene domain on human chromosome 21.
J Invest Dermatol 122: 147–158, 2004.
Roizen NJ, Patterson D. Down’s syndrome. Lancet 361: 1281–
1289, 2003.
Roper RJ, Baxter LL, Saran NG, Klinedinst DK, Beachy PA,
Reeves RH. Defective cerebellar response to mitogenic Hedgehog
signaling in Down syndrome mice. Proc Natl Acad Sci USA 103:
1452–1456, 2006.
Roper RJ, Reeves RH. Understanding the basis for Down syndrome phenotypes. PLoS Genet 2: e50, 2006.
Roper RJ, St John HK, Philip J, Lawler A, Reeves RH. Perinatal loss of Ts65Dn Down syndrome mice. Genetics 172: 437– 443,
2006.
Ross MH, Galaburda AM, Kemper TL. Down’s syndrome: is
there a decreased population of neurons? Neurology 34: 909 –916,
1984.
Rovelet-Lecrux A, Hannequin D, Raux G, Le Meur N, Laquerriere A, Vital A, Dumanchin C, Feuillette S, Brice A, Vercelletto M, Dubas F, Frebourg T, Campion D. APP locus duplication causes autosomal dominant early-onset Alzheimer disease
with cerebral amyloid angiopathy. Nat Genet 38: 24 –26, 2006.
Rowe J, Lavender A, Turk V. Cognitive executive function in
Down’s syndrome. Br J Clin Psychol 45: 5–17, 2006.
Rueda N, Florez J, Martinez-Cue C. Chronic pentylenetetrazole
but not donepezil treatment rescues spatial cognition in Ts65Dn
mice, a model for Down syndrome. Neurosci Lett 433: 22–27, 2008.
Rueda N, Florez J, Martinez-Cue C. Effects of chronic administration of SGS-111 during adulthood and during the pre- and
post-natal periods on the cognitive deficits of Ts65Dn mice, a
model of Down syndrome. Behav Brain Res 188: 355–367, 2008.
Rueda N, Mostany R, Pazos A, Florez J, Martinez-Cue C. Cell
proliferation is reduced in the dentate gyrus of aged but not young
Ts65Dn mice, a model of Down syndrome. Neurosci Lett 380:
197–201, 2005.
Rynders JE, Spiker D, Horrobin JM. Underestimating the educability of Down’s syndrome children: examination of methodological problems in recent literature. Am J Ment Defic 82: 440 – 448,
1978.
Sago H, Carlson EJ, Smith DJ, Kilbridge J, Rubin EM, Mobley
WC, Epstein CJ, Huang TT. Ts1Cje, a partial trisomy 16 mouse
model for Down syndrome, exhibits learning and behavioral abnormalities. Proc Natl Acad Sci USA 95: 6256 – 6261, 1998.
Salehi A, Delcroix JD, Belichenko PV, Zhan K, Wu C, Valletta
JS, Takimoto-Kimura R, Kleschevnikov AM, Sambamurti K,
Chung PP, Xia W, Villar A, Campbell WA, Kulnane LS, Nixon
RA, Lamb BT, Epstein CJ, Stokin GB, Goldstein LS, Mobley
WC. Increased App expression in a mouse model of Down’s syndrome disrupts NGF transport and causes cholinergic neuron degeneration. Neuron 51: 29 – 42, 2006.
Saran NG, Pletcher MT, Natale JE, Cheng Y, Reeves RH.
Global disruption of the cerebellar transcriptome in a Down syndrome mouse model. Hum Mol Genet 12: 2013–2019, 2003.
Savino A, Rollo V, Chiarelli F. Congenital duodenal stenosis and
annular pancreas: a delayed diagnosis in an adolescent patient with
Down syndrome. Eur J Pediatr 166: 379 –380, 2007.
Scambler PJ. The 22q11 deletion syndromes. Hum Mol Genet 9:
2421–2426, 2000.
Schapiro MB, Berman KF, Alexander GE, Weinberger DR,
Rapoport SI. Regional cerebral blood flow in Down syndrome
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
285.
mouse cerebellum during post-natal development. J Neurochem 97
Suppl 1: 104 –109, 2006.
Prandini P, Deutsch S, Lyle R, Gagnebin M, Delucinge Vivier
C, Delorenzi M, Gehrig C, Descombes P, Sherman S, Dagna
Bricarelli F, Baldo C, Novelli A, Dallapiccola B, Antonarakis
SE. Natural gene-expression variation in Down syndrome modulates the outcome of gene-dosage imbalance. Am J Hum Genet 81:
252–263, 2007.
Prinz M, Prinz B, Schulz E. The growth of non-pyramidal neurons
in the primary motor cortex of man: a Golgi study. Histol Histopathol 12: 895–900, 1997.
Pritchard M, Reeves RH, Dierssen M, Patterson D, Gardiner
KJ. Down syndrome and the genes of human chromosome 21:
current knowledge and future potentials. Report on the Expert
workshop on the biology of chromosome 21 genes: towards genephenotype correlations in Down syndrome Washington D C, September 28-October 1, 2007. Cytogenet Genome Res 121: 67–77, 2008.
Pucharcos C, Estivill X, de la Luna S. Intersectin 2, a new
multimodular protein involved in clathrin-mediated endocytosis.
FEBS Lett 478: 43–51, 2000.
Pucharcos C, Fuentes JJ, Casas C, de la Luna S, Alcantara S,
Arbones ML, Soriano E, Estivill X, Pritchard M. Alu-splice
cloning of human Intersectin (ITSN), a putative multivalent binding
protein expressed in proliferating and differentiating neurons and
overexpressed in Down syndrome. Eur J Hum Genet 7: 704 –712,
1999.
Purpura DP. Dendritic spine “dysgenesis” and mental retardation.
Science 186: 1126 –1128, 1974.
Ramirez-Solis R, Liu P, Bradley A. Chromosome engineering in
mice. Nature 378: 720 –724, 1995.
Raz N, Torres IJ, Briggs SD, Spencer WD, Thornton AE,
Loken WJ, Gunning FM, McQuain JD, Driesen NR, Acker JD.
Selective neuroanatomic abnormalities in Down’s syndrome and
their cognitive correlates: evidence from MRI morphometry. Neurology 45: 356 –366, 1995.
Redon R, Ishikawa S, Fitch KR, Feuk L, Perry GH, Andrews
TD, Fiegler H, Shapero MH, Carson AR, Chen W, Cho EK,
Dallaire S, Freeman JL, Gonzalez JR, Gratacos M, Huang J,
Kalaitzopoulos D, Komura D, MacDonald JR, Marshall CR,
Mei R, Montgomery L, Nishimura K, Okamura K, Shen F,
Somerville MJ, Tchinda J, Valsesia A, Woodwark C, Yang F,
Zhang J, Zerjal T, Armengol L, Conrad DF, Estivill X, TylerSmith C, Carter NP, Aburatani H, Lee C, Jones KW, Scherer
SW, Hurles ME. Global variation in copy number in the human
genome. Nature 444: 444 – 454, 2006.
Reeves RH. Down syndrome mouse models are looking up.
Trends Mol Med 12: 237–240, 2006.
Reeves RH, Irving NG, Moran TH, Wohn A, Kitt C, Sisodia SS,
Schmidt C, Bronson RT, Davisson MT. A mouse model for
Down syndrome exhibits learning and behaviour deficits. Nat
Genet 11: 177–184, 1995.
Rehen SK, McConnell MJ, Kaushal D, Kingsbury MA, Yang
AH, Chun J. Chromosomal variation in neurons of the developing
and adult mammalian nervous system. Proc Natl Acad Sci USA 98:
13361–13366, 2001.
Rehen SK, Yung YC, McCreight MP, Kaushal D, Yang AH,
Almeida BS, Kingsbury MA, Cabral KM, McConnell MJ,
Anliker B, Fontanoz M, Chun J. Constitutional aneuploidy in the
normal human brain. J Neurosci 25: 2176 –2180, 2005.
Reisel D, Bannerman DM, Schmitt WB, Deacon RM, Flint J,
Borchardt T, Seeburg PH, Rawlins JN. Spatial memory dissociations in mice lacking GluR1. Nat Neurosci 5: 868 – 873, 2002.
Rey A. Test de copie et de reproduction de mémoire de figures
géométriques complexes. Paris: les éditions du Centre de Psychologie Appliquée, 1959.
Reymond A, Camargo AA, Deutsch S, Stevenson BJ, Parmigiani RB, Ucla C, Bettoni F, Rossier C, Lyle R, Guipponi M, de
Souza S, Iseli C, Jongeneel CV, Bucher P, Simpson AJ, Antonarakis SE. Nineteen additional unpredicted transcripts from
human chromosome 21. Genomics 79: 824 – 832, 2002.
Reymond A, Friedli M, Henrichsen CN, Chapot F, Deutsch S,
Ucla C, Rossier C, Lyle R, Guipponi M, Antonarakis SE. From
PREDs and open reading frames to cDNA isolation: revisiting the
917
918
320.
321.
322.
323.
325.
326.
327.
328.
329.
330.
331.
332.
333.
334.
adults during the Wisconsin Card Sorting Test: exploring cognitive
activation in the context of poor performance. Biol Psychiatry 45:
1190 –1196, 1999.
Schauwecker PE. Genetic influence on neurogenesis in the dentate gyrus of two strains of adult mice. Brain Res 1120: 83–92, 2006.
Schmitt WB, Deacon RM, Seeburg PH, Rawlins JN, Bannerman DM. A within-subjects, within-task demonstration of intact
spatial reference memory and impaired spatial working memory in
glutamate receptor-A-deficient mice. J Neurosci 23: 3953–3959,
2003.
Schmitt WB, Sprengel R, Mack V, Draft RW, Seeburg PH,
Deacon RM, Rawlins JN, Bannerman DM. Restoration of spatial
working memory by genetic rescue of GluR-A-deficient mice. Nat
Neurosci 8: 270 –272, 2005.
Scott BS, Petit TL, Becker LE, Edwards BA. Abnormal electric
membrane properties of Down’s syndrome DRG neurons in cell
culture. Brain Res 254: 257–270, 1981.
Sebat J, Lakshmi B, Malhotra D, Troge J, Lese-Martin C,
Walsh T, Yamrom B, Yoon S, Krasnitz A, Kendall J, Leotta A,
Pai D, Zhang R, Lee YH, Hicks J, Spence SJ, Lee AT, Puura K,
Lehtimaki T, Ledbetter D, Gregersen PK, Bregman J, Sutcliffe JS, Jobanputra V, Chung W, Warburton D, King MC,
Skuse D, Geschwind DH, Gilliam TC, Ye K, Wigler M. Strong
association of de novo copy number mutations with autism. Science 316: 445– 449, 2007.
Sebat J, Lakshmi B, Troge J, Alexander J, Young J, Lundin P,
Maner S, Massa H, Walker M, Chi M, Navin N, Lucito R, Healy
J, Hicks J, Ye K, Reiner A, Gilliam TC, Trask B, Patterson N,
Zetterberg A, Wigler M. Large-scale copy number polymorphism
in the human genome. Science 305: 525–528, 2004.
Seifert A, Allan LA, Clarke PR. DYRK1A phosphorylates
caspase 9 at an inhibitory site and is potently inhibited in human
cells by harmine. FEBS Lett 275: 6268 – 6280, 2008.
Sencan A, Mir E, Gunsar C, Akcora B. Symptomatic annular
pancreas in newborns. Med Sci Monit 8: CR434 – 437, 2002.
Seo H, Isacson O. Abnormal APP, cholinergic and cognitive function in Ts65Dn Down’s model mice. Exp Neurol 193: 469 – 480, 2005.
Sethupathy P, Borel C, Gagnebin M, Grant GR, Deutsch S,
Elton TS, Hatzigeorgiou AG, Antonarakis SE. Human microRNA-155 on chromosome 21 differentially interacts with its
polymorphic target in the AGTR1 3⬘ untranslated region: a mechanism for functional single-nucleotide polymorphisms related to
phenotypes. Am J Hum Genet 81: 405– 413, 2007.
Shapiro LA, Whitaker-Azmitia PM. Expression levels of cytoskeletal proteins indicate pathological aging of S100B transgenic
mice: an immunohistochemical study of MAP-2, drebrin and GAP43. Brain Res 1019: 39 – 46, 2004.
Sharp AJ, Hansen S, Selzer RR, Cheng Z, Regan R, Hurst JA,
Stewart H, Price SM, Blair E, Hennekam RC, Fitzpatrick CA,
Segraves R, Richmond TA, Guiver C, Albertson DG, Pinkel D,
Eis PS, Schwartz S, Knight SJ, Eichler EE. Discovery of previously unidentified genomic disorders from the duplication architecture of the human genome. Nat Genet 38: 1038 –1042, 2006.
Sharp AJ, Locke DP, McGrath SD, Cheng Z, Bailey JA, Vallente RU, Pertz LM, Clark RA, Schwartz S, Segraves R, Oseroff VV, Albertson DG, Pinkel D, Eichler EE. Segmental duplications and copy-number variation in the human genome. Am J
Hum Genet 77: 78 – 88, 2005.
Sharp AJ, Mefford HC, Li K, Baker C, Skinner C, Stevenson
RE, Schroer RJ, Novara F, De Gregori M, Ciccone R, Broomer
A, Casuga I, Wang Y, Xiao C, Barbacioru C, Gimelli G, Bernardina BD, Torniero C, Giorda R, Regan R, Murday V, Mansour S, Fichera M, Castiglia L, Failla P, Ventura M, Jiang Z,
Cooper GM, Knight SJ, Romano C, Zuffardi O, Chen C,
Schwartz CE, Eichler EE. A recurrent 15q13.3 microdeletion
syndrome associated with mental retardation and seizures. Nat
Genet 40: 322–328, 2008.
Sharp AJ, Selzer RR, Veltman JA, Gimelli S, Gimelli G, Striano P, Coppola A, Regan R, Price SM, Knoers NV, Eis PS,
Brunner HG, Hennekam RC, Knight SJ, de Vries BB, Zuffardi
O, Eichler EE. Characterization of a recurrent 15q24 microdeletion syndrome. Hum Mol Genet 16: 567–572, 2007.
Physiol Rev • VOL
335. Shaw CJ, Lupski JR. Implications of human genome architecture
for rearrangement-based disorders: the genomic basis of disease.
Hum Mol Genet 13: R57– 64, 2004.
336. Sherman S. Correction of the evaluation of recombination in
meiosis I and II nondisjunction in trisomy 21. Am J Hum Genet 50:
1137–1138, 1992.
337. Shibuya K, Kudoh J, Obayashi I, Shimizu A, Sasaki T,
Minoshima S, Shimizu N. Comparative genomics of the keratinassociated protein (KAP) gene clusters in human, chimpanzee, and
baboon. Mamm Genome 15: 179 –192, 2004.
338. Shibuya K, Obayashi I, Asakawa S, Minoshima S, Kudoh J,
Shimizu N. A cluster of 21 keratin-associated protein genes within
introns of another gene on human chromosome 21q22.3. Genomics
83: 679 – 693, 2004.
339. Shiga M, Takigawa I, Mamitsuka H. Annotating gene function by
combining expression data with a modular gene network. Bioinformatics 23: i468-i478, 2007.
340. Shinohara T, Tomizuka K, Miyabara S, Takehara S, Kazuki Y,
Inoue J, Katoh M, Nakane H, Iino A, Ohguma A, Ikegami S,
Inokuchi K, Ishida I, Reeves RH, Oshimura M. Mice containing
a human chromosome 21 model behavioral impairment and cardiac
anomalies of Down’s syndrome. Hum Mol Genet 10: 1163–1175,
2001.
341. Shumway-Cook A, Woollacott MH. Dynamics of postural control
in the child with Down syndrome. Phys Ther 65: 1315–1322, 1985.
342. Siarey RJ, Kline-Burgess A, Cho M, Balbo A, Best TK, Harashima C, Klann E, Galdzicki Z. Altered signaling pathways
underlying abnormal hippocampal synaptic plasticity in the
Ts65Dn mouse model of Down syndrome. J Neurochem 98: 1266 –
1277, 2006.
343. Siarey RJ, Villar AJ, Epstein CJ, Galdzicki Z. Abnormal synaptic plasticity in the Ts1Cje segmental trisomy 16 mouse model of
Down syndrome. Neuropharmacology 49: 122–128, 2005.
344. Singleton AB, Farrer M, Johnson J, Singleton A, Hague S,
Kachergus J, Hulihan M, Peuralinna T, Dutra A, Nussbaum R,
Lincoln S, Crawley A, Hanson M, Maraganore D, Adler C,
Cookson MR, Muenter M, Baptista M, Miller D, Blancato J,
Hardy J, Gwinn-Hardy K. alpha-Synuclein locus triplication
causes Parkinson’s disease. Science 302: 841, 2003.
345. Sitz JH, Tigges M, Baumgartel K, Khaspekov LG, Lutz B.
Dyrk1A potentiates steroid hormone-induced transcription via the
chromatin remodeling factor Arip4. Mol Cell Biol 24: 5821–5834,
2004.
346. Squire LR, Stark CE, Clark RE. The medial temporal lobe. Annu
Rev Neurosci 27: 279 –306, 2004.
347. Stankiewicz P, Lupski JR. Molecular-evolutionary mechanisms
for genomic disorders. Curr Opin Genet Dev 12: 312–319, 2002.
348. Stasko MR, Costa AC. Experimental parameters affecting the
Morris water maze performance of a mouse model of Down syndrome. Behav Brain Res 154: 1–17, 2004.
349. Stranger BE, Forrest MS, Dunning M, Ingle CE, Beazley C,
Thorne N, Redon R, Bird CP, de Grassi A, Lee C, Tyler-Smith
C, Carter N, Scherer SW, Tavare S, Deloukas P, Hurles ME,
Dermitzakis ET. Relative impact of nucleotide and copy number
variation on gene expression phenotypes. Science 315: 848 – 853,
2007.
350. Suetsugu M, Mehraein P. Spine distribution along the apical
dendrites of the pyramidal neurons in Down’s syndrome. A quantitative Golgi study. Acta Neuropathol 50: 207–210, 1980.
351. Sultan M, Piccini I, Balzereit D, Herwig R, Saran NG, Lehrach
H, Reeves RH, Yaspo ML. Gene expression variation in “Down
syndrome” mice allows to prioritize candidate genes. Genome Biol
8: R91, 2007.
352. Sylvester PE. The hippocampus in Down’s syndrome. J Ment
Defic Res 27: 227–236, 1983.
353. Takashima S, Becker LE, Armstrong DL, Chan F. Abnormal
neuronal development in the visual cortex of the human fetus and
infant with down’s syndrome. A quantitative and qualitative Golgi
study. Brain Res 225: 1–21, 1981.
354. Takashima S, Ieshima A, Nakamura H, Becker LE. Dendrites,
dementia and the Down syndrome. Brain Dev 11: 131–133, 1989.
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
324.
DIERSSEN, HERAULT, AND ESTIVILL
DOWN SYNDROME: A GENOMIC BRAIN DISORDER
Physiol Rev • VOL
376. Vuksic M, Petanjek Z, Rasin MR, Kostovic I. Perinatal growth of
prefrontal layer III pyramids in Down syndrome. Pediatr Neurol 27:
36 –38, 2002.
377. Wahlsten D, Bachmanov A, Finn DA, Crabbe JC. Stability of
inbred mouse strain differences in behavior and brain size between
laboratories and across decades. Proc Natl Acad Sci USA 103:
16364 –16369, 2006.
378. Walz K, Spencer C, Kaasik K, Lee CC, Lupski JR, Paylor R.
Behavioral characterization of mouse models for Smith-Magenis
syndrome and dup(17)(p11.2p11 2). Hum Mol Genet 13: 367–378,
2004.
379. Wang PP, Doherty S, Hesselink JR, Bellugi U. Callosal morphology concurs with neurobehavioral and neuropathological findings in two neurodevelopmental disorders. Arch Neurol 49: 407–
411, 1992.
380. Ward JO, Reinholdt LG, Hartford SA, Wilson LA, Munroe RJ,
Schimenti KJ, Libby BJ, O’Brien M, Pendola JK, Eppig J,
Schimenti JC. Toward the genetics of mammalian reproduction:
induction and mapping of gametogenesis mutants in mice. Biol
Reprod 69: 1615–1625, 2003.
381. Waterston RH, Lindblad-Toh K, Birney E, Rogers J, Abril JF,
Agarwal P, Agarwala R, Ainscough R, Alexandersson M, An P,
Antonarakis SE, Attwood J, Baertsch R, Bailey J, Barlow K,
Beck S, Berry E, Birren B, Bloom T, Bork P, Botcherby M,
Bray N, Brent MR, Brown DG, Brown SD, Bult C, Burton J,
Butler J, Campbell RD, Carninci P, Cawley S, Chiaromonte F,
Chinwalla AT, Church DM, Clamp M, Clee C, Collins FS, Cook
LL, Copley RR, Coulson A, Couronne O, Cuff J, Curwen V,
Cutts T, Daly M, David R, Davies J, Delehaunty KD, Deri J,
Dermitzakis ET, Dewey C, Dickens NJ, Diekhans M, Dodge S,
Dubchak I, Dunn DM, Eddy SR, Elnitski L, Emes RD, Eswara
P, Eyras E, Felsenfeld A, Fewell GA, Flicek P, Foley K,
Frankel WN, Fulton LA, Fulton RS, Furey TS, Gage D, Gibbs
RA, Glusman G, Gnerre S, Goldman N, Goodstadt L, Grafham
D, Graves TA, Green ED, Gregory S, Guigo R, Guyer M,
Hardison RC, Haussler D, Hayashizaki Y, Hillier LW, Hinrichs
A, Hlavina W, Holzer T, Hsu F, Hua A, Hubbard T, Hunt A,
Jackson I, Jaffe DB, Johnson LS, Jones M, Jones TA, Joy A,
Kamal M, Karlsson EK. Initial sequencing and comparative analysis of the mouse genome. Nature 420: 520 –562, 2002.
382. Watkins-Chow DE, Pavan WJ. Genomic copy number and expression variation within the C57BL/6J inbred mouse strain. Genome Res 18: 60 – 66, 2008.
383. Waye JS, Durfy SJ, Pinkel D, Kenwrick S, Patterson M, Davies KE, Willard HF. Chromosome-specific alpha satellite DNA
from human chromosome 1: hierarchical structure and genomic
organization of a polymorphic domain spanning several hundred
kilobase pairs of centromeric DNA. Genomics 1: 43–51, 1987.
384. Weiss LA, Shen Y, Korn JM, Arking DE, Miller DT, Fossdal R,
Saemundsen E, Stefansson H, Ferreira MA, Green T, Platt
OS, Ruderfer DM, Walsh CA, Altshuler D, Chakravarti A,
Tanzi RE, Stefansson K, Santangelo SL, Gusella JF, Sklar P,
Wu BL, Daly MJ. Association between microdeletion and microduplication at 16p11.2 and autism. N Engl J Med 358: 667– 675,
2008.
385. Wiig KA, Cooper LN, Bear MF. Temporally graded retrograde
amnesia following separate and combined lesions of the perirhinal
cortex and fornix in the rat. Learn Mem 3: 313–325, 1996.
386. Willcocks LC, Lyons PA, Clatworthy MR, Robinson JI, Yang
W, Newland SA, Plagnol V, McGovern NN, Condliffe AM,
Chilvers ER, Adu D, Jolly EC, Watts R, Lau YL, Morgan AW,
Nash G, Smith KG. Copy number of FCGR3B, which is associated
with systemic lupus erythematosus, correlates with protein expression and immune complex uptake. J Exp Med 205: 1573–1582, 2008.
387. Winter TC, Ostrovsky AA, Komarniski CA, Uhrich SB. Cerebellar and frontal lobe hypoplasia in fetuses with trisomy 21: usefulness as combined US markers. Radiology 214: 533–538, 2000.
388. Wishart JG. The development of learning difficulties in children
with Down’s syndrome. J Intellect Disabil Res 37: 389 – 403, 1993.
389. Wisniewski K, Kida E. Abnormal neurogenesis and synaptogenesis in Down syndrome brain. Dev Brain Dysfunction 7: 289 –301,
1995.
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
355. Takashima S, Iida K, Mito T, Arima M. Dendritic and histochemical development and ageing in patients with Down’s syndrome.
J Intellect Disabil Res 38: 265–273, 1994.
356. Teyler TJ, DiScenna P. The hippocampal memory indexing theory. Behav Neurosci 100: 147–154, 1986.
357. The Project Consortium ENCODE. Identification and analysis of
functional elements in 1% of the human genome by the ENCODE
pilot project. Nature 447: 799 – 816, 2007.
358. Thompson P, Cannon TD, Toga AW. Mapping genetic influences
on human brain structure. Ann Med 34: 523–536, 2002.
359. Thompson PM, Cannon TD, Narr KL, van Erp T, Poutanen VP,
Huttunen M, Lonnqvist J, Standertskjold-Nordenstam CG,
Kaprio J, Khaledy M, Dail R, Zoumalan CI, Toga AW. Genetic
influences on brain structure. Nat Neurosci 4: 1253–1258, 2001.
360. Tommerdahl M, Favorov O, Whitsel BL, Nakhle B, Gonchar
YA. Minicolumnar activation patterns in cat and monkey SI cortex.
Cereb Cortex 3: 399 – 411, 1993.
361. Torfs CP, Christianson RE. Anomalies in Down syndrome individuals in a large population-based registry. Am J Med Genet 77:
431– 438, 1998.
362. Tran SH, Caughey AB, Norton ME. Ethnic variation in the
prevalence of echogenic intracardiac foci and the association with
Down syndrome. Ultrasound Obstet Gynecol 26: 158 –161, 2005.
363. Tsai TF, Jiang YH, Bressler J, Armstrong D, Beaudet AL.
Paternal deletion from Snrpn to Ube3a in the mouse causes hypotonia, growth retardation and partial lethality and provides evidence for a gene contributing to Prader-Willi syndrome. Hum Mol
Genet 8: 1357–1364, 1999.
364. Tybulewicz VL, Fisher EM. New techniques to understand chromosome dosage: mouse models of aneuploidy. Hum Mol Genet 15:
R103–109, 2006.
365. Uddin M, Wildman DE, Liu G, Xu W, Johnson RM, Hof PR,
Kapatos G, Grossman LI, Goodman M. Sister grouping of chimpanzees and humans as revealed by genome-wide phylogenetic
analysis of brain gene expression profiles. Proc Natl Acad Sci USA
101: 2957–2962, 2004.
366. Uecker A, Obrzut JE. Hemisphere and gender differences in
mental rotation. Brain Cogn 22: 42–50, 1993.
367. Vacik T, Ort M, Gregorova S, Strnad P, Blatny R, Conte N,
Bradley A, Bures J, Forejt J. Segmental trisomy of chromosome
17: a mouse model of human aneuploidy syndromes. Proc Natl
Acad Sci USA 102: 4500 – 4505, 2005.
368. Van der Graaf M, Julia-Sape M, Howe FA, Ziegler A, Majos C,
Moreno-Torres A, Rijpkema M, Acosta D, Opstad KS, van der
Meulen YM, Arus C, Heerschap A. MRS quality assessment in a
multicentre study on MRS-based classification of brain tumours.
NMR Biomed 21: 148 –158, 2008.
369. Verucci L, Menghini D, Vicari S. Reading skills and phonological
awareness acquisition in Down syndrome. J Intellect Disabil Res
50: 477– 491, 2006.
370. Vicari S, Bates E, Caselli MC, Pasqualetti P, Gagliardi C,
Tonucci F, Volterra V. Neuropsychological profile of Italians with
Williams syndrome: an example of a dissociation between language
and cognition? J Int Neuropsychol Soc 10: 862– 876, 2004.
371. Vicari S, Bellucci S, Carlesimo GA. Evidence from two genetic
syndromes for the independence of spatial and visual working
memory. Dev Med Child Neurol 48: 126 –131, 2006.
372. Vicari S, Bellucci S, Carlesimo GA. Visual and spatial long-term
memory: differential pattern of impairments in Williams and Down
syndromes. Dev Med Child Neurol 47: 305–311, 2005.
373. Vicari S, Marotta L, Carlesimo GA. Verbal short-term memory in
Down’s syndrome: an articulatory loop deficit? J Intellect Disabil
Res 48: 80 –92, 2004.
374. Vissers LE, van Ravenswaaij CM, Admiraal R, Hurst JA, de
Vries BB, Janssen IM, van der Vliet WA, Huys EH, de Jong PJ,
Hamel BC, Schoenmakers EF, Brunner HG, Veltman JA, van
Kessel AG. Mutations in a new member of the chromodomain
gene family cause CHARGE syndrome. Nat Genet 36: 955–957,
2004.
375. Vrijenhoek T, Buizer-Voskamp JE, van der Stelt I, Strengman
E, Sabatti C, Geurts van Kessel A, Brunner HG, Ophoff RA,
Veltman JA. Recurrent CNVs disrupt three candidate genes in
schizophrenia patients. Am J Hum Genet 83: 504 –510, 2008.
919
920
DIERSSEN, HERAULT, AND ESTIVILL
Physiol Rev • VOL
398.
399.
400.
401.
402.
403.
tiation in hippocampal progenitor cells. J Biol Chem 276: 39819 –
39824, 2001.
Yang Y, Chung EK, Wu YL, Savelli SL, Nagaraja HN, Zhou B,
Hebert M, Jones KN, Shu Y, Kitzmiller K, Blanchong CA,
McBride KL, Higgins GC, Rennebohm RM, Rice RR, Hackshaw
KV, Roubey RA, Grossman JM, Tsao BP, Birmingham DJ,
Rovin BH, Hebert LA, Yu CY. Gene copy-number variation and
associated polymorphisms of complement component C4 in human
systemic lupus erythematosus (SLE): low copy number is a risk
factor for and high copy number is a protective factor against SLE
susceptibility in European Americans. Am J Hum Genet 80: 1037–
1054, 2007.
Yurov YB, Iourov IY, Monakhov VV, Soloviev IV, Vostrikov
VM, Vorsanova SG. The variation of aneuploidy frequency in the
developing and adult human brain revealed by an interphase FISH
study. J Histochem Cytochem 53: 385–390, 2005.
Yurov YB, Iourov IY, Vorsanova SG, Liehr T, Kolotii AD,
Kutsev SI, Pellestor F, Beresheva AK, Demidova IA, Kravets
VS, Monakhov VV, Soloviev IV. Aneuploidy and confined chromosomal mosaicism in the developing human brain. PLoS ONE 2:
e558, 2007.
Zellweger H. Down syndrome. In: Handbook of Clinical Neurology-Congenital Malformations of the Brain and Skull, Part II.
Amsterdam: Elsevier/North-Holland Biomedical, 1977, p. 367– 471.
Zoghbi HY. Postnatal neurodevelopmental disorders: meeting at
the synapse? Science 302: 826 – 830, 2003.
Zola-Morgan SM, Squire LR. The primate hippocampal formation: evidence for a time-limited role in memory storage. Science
250: 288 –290, 1990.
89 • JULY 2009 •
www.prv.org
Downloaded from http://physrev.physiology.org/ by 10.220.33.3 on June 18, 2017
390. Wisniewski KE. Down syndrome children often have brain with
maturation delay, retardation of growth, and cortical dysgenesis.
Am J Med Genet Suppl 7: 274 –281, 1990.
391. Wisniewski KE, Dalton AJ, McLachlan C, Wen GY,
Wisniewski HM. Alzheimer’s disease in Down’s syndrome: clinicopathologic studies. Neurology 35: 957–961, 1985.
392. Wisniewski KE, Laure-Kamionowska M, Connell F, Wen GY.
Neuronal density and synaptogenesis in the postnatal stage of brain
maturation in Down syndrome. In: Neurobiology in Down Syndrome, edited by Epstein CJ. New York: Raven, 1986, p. 29 – 44.
393. Wisniewski KE, Laure-Kamionowska M, Wisniewski HM. Evidence of arrest of neurogenesis and synaptogenesis in brains of
patients with Down’s syndrome. N Engl J Med 311: 1187–1188,
1984.
394. Wu H, Kim KJ, Mehta K, Paxia S, Sundstrom A, Anantharaman T, Kuraishy AI, Doan T, Ghosh J, Pyle AD, Clark A,
Lowry W, Fan G, Baxter T, Mishra B, Sun Y, Teitell MA. Copy
number variant analysis of human embryonic stem cells. Stem Cells
26: 1484 –1489, 2008.
395. Yan J, Bi W, Lupski JR. Penetrance of craniofacial anomalies in
mouse models of Smith-Magenis syndrome is modified by genomic
sequence surrounding Rai1: not all null alleles are alike. Am J Hum
Genet 80: 518 –525, 2007.
396. Yan J, Keener VW, Bi W, Walz K, Bradley A, Justice MJ,
Lupski JR. Reduced penetrance of craniofacial anomalies as a
function of deletion size and genetic background in a chromosome
engineered partial mouse model for Smith-Magenis syndrome.
Hum Mol Genet 13: 2613–2624, 2004.
397. Yang EJ, Ahn YS, Chung KC. Protein kinase Dyrk1 activates
cAMP response element-binding protein during neuronal differen-