Genetic and Environmental Influences on Intellectual Disability in Childhood

Abstract

Scientific literature on atypical development is so vast that a systematic review could not fit in some 40 pages; therefore, we had to make choices. First, we have limited our presentation to intellectual disability (ID), leaving aside behavioral and psychiatric disorders. After defining ID, the main causes are presented (genetic and environmental) with special emphasis on gene–environment correlations and/or interactions. We then selected two genetic disorders linked to ID (Phenylketonuria and Fragile X) to present both the research methodologies and the type of findings, before discussing the contribution of cross-syndrome comparisons. To uncover a causal link between genetic events and a behavioral phenotype, it is often essential to use model organisms. The advantage of such models, plus the requirements and limitations involved in their use, are presented before concluding the chapter

Full text

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Non-normative development in childhood
Michèle Carlier1 and Pierre L. Roubertoux2
1 Psychologie Cognitive, UMR 7290 Aix-Marseille University and Centre National de la
Recherche Scientifique (CNRS), Fédération 3C, Marseille, France
2 Génétique Médicale, Génomique Fonctionnelle U910 Aix-Marseille University and Institut
national de la santé et de la recherche médicale (Inserm), Marseille, France
Scientific literature on atypical development is so vast that a systematic review could not fit in
some forty pages. We therefore had to make choices. First we have limited our presentation to
intellectual disability (ID) leaving aside behavioral and psychiatric disorders. After defining
intellectual disability, the main causes are presented (genetic and environmental) with special
emphasis on gene-environment correlations and/or interactions. We then selected two genetic
disorders linked to ID (Phenylketonuria and Fragile X) to present both the research
methodologies and the type of findings, before discussing the contribution of cross-syndrome
comparisons. To uncover a causal link between genetic events and a behavioral phenotype, it
is often essential to use model organisms. The advantage of such models, plus the
requirements and limitations involved in their use, are presented before concluding the
chapter.
1. Definition and Epidemiology
1.1 Definition
The history of non-normative development in cognition is probably as long as the story of the
human species, although the dating of biological evidence on developmental disabilities is
relatively recent. Czarnetzki et al. (2003) studied osseous remains (7 063 specimens) from
different points in Europe; one skeleton dated as being 2 550 years old, was diagnosed as a

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woman with signs of trisomy 21 who had died at the age of 18 or 20. “Psychomotor
retardation” was described in the Book of Hearts in Ebers papyrus written in 1 600 BC
(Okasha, 1999). It is beyond the scope of the present chapter to give an overview of the main
views on intellectual disabilities from ancient times to the present, but one point is worth
noting: the acceptance of disabled persons by society has varied at different periods of time
and from country to country. Misconceptions on the nature and causes of non-normative
development have had dramatic consequences for persons with intellectual disabilities
(Roubertoux, 2004; Smith, 2006), and while considerable progress has been made, a recent
survey of American college students has shown that misconceptions about cognitive and
adaptive behavior of people with mild intellectual disabilities are still relatively frequent
(Musso et al. 2012) and that an implicit negative stereotype is still alive (Enea-Drapeau et al.
2012). In modern Western societies, the late 18th century and early 19th century marked a
major milestone in the care of these persons. Jean-Marie Gaspard Itard (1774-1838) was
probably the first person in a western country to attempt to stimulate and educate an
“incurable” child – the wild boy of Aveyron discovered in 1798. His observation of the
child’s behavior (1801) is a model of humanistic thinking and contains many accurate insights
into developmental psychology. Later, Edouard Seguin (1812-1880) developed a systematic
method of education for “idiots” and “imbeciles” at Bicêtre Hospital (Paris). Despite the very
good appraisal of his method by the Académie royale des sciences (Royal Academy of
Science, December, 1843), Seguin came into in conflict with the hospital administration; he
left the hospital, set up a private center and published a book with the first description of
children with trisomy 21 (1846). He later migrated to the USA and in 1876 became the first
president of the Association of Medical Officers of American Institutions for Idiotic and
Feeble-minded Persons. The organization has changed its name several times over the past
100 years, going from the “American Association on Mental deficiency” (AAMD), to the

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“American Association on Mental Retardation” (AAMR) and finally, in 2006, to the
“American Association on Intellectual and Developmental Disabilities” (AAIDD). Changes in
the nomenclature and the choice of the term “intellectual disabilities” to replace “mental
retardation” are in line with changes in biological and social knowledge of non-normative
development, but debate on the pros and cons is still continuing – see Fisch, 2011; and for a
historical presentation of the definitions of mental retardation in the AAID, see Leonard and
Wen (2002).
Four classifications system are widely used to describe ID. In the 11th edition of the AAIDD
Definition Manual on Intellectual Disability, ID is characterized as a “limitation both in
intellectual functioning and adaptive behavior as expressed in conception, social, and
practical adaptive skills” (2010, p. 1). The disability is developmental as it occurs before the
age of 18. Five assumptions need to be validated for the definition to apply: (1) consideration
of the context of the community environment where the person lives, (2) consideration of
cultural and linguistic diversity, (3) a valid assessment of not only limitations but also
strengths, (4) a profile of support needed and, (5) the expectation that the person will improve.
The definition in the International Classification of Diseases and Related Health Problems
(10th revised edition: ICD-10 version 2010) of the World Health Organization (WHO) is close
to the AAID definition, but the term “mental retardation” is still used. The classification
considers mental retardation as “impairment of skills manifested during the developmental
period, skills which contribute to the overall level of intelligence, i.e. cognitive, language,
motor, and social abilities. Retardation can occur with or without any other mental or physical
condition”. Assuming an improvement “as a result of training and rehabilitation” is also a key
point, but the focus on social adaptation is less significant than in the AAIDD definition as
there is no requirement for an assessment of social adaptation (”Degrees of mental retardation

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are conventionally estimated by standardized intelligence tests. These can be supplemented by
scales assessing social adaptation in a given environment.”)
All 191 WHO Member States officially endorsed the International Classification of
Functioning, Disability and Health, known more commonly as the ICF (Who, 2001; 2002). It
is a classification of health and health-related domains on three levels: the level of the body or
body part, the level of the whole person, and the level of the whole person in a social context).
The classification uses four lists: body function (mental function, sensory functions and pain
etc.), body structure (structures of the nervous system, structures of the cardiovascular,
immunological and respiratory systems etc.), activity and participation (learning and applying
knowledge, communication), and environmental factors (support and relationships, the natural
environment and human-made changes to the environment). Impairment, disability and
handicap are distinct concepts. Impairment is defined as “any loss or abnormality of a
psychological, physiological or anatomical structure or function” (e.g. blindness or mental
retardation). Disability is a “restriction or lack (resulting from an impairment) of ability to
perform an activity in the manner or within the range considered normal for a human being”
and describes a functional limitation or restriction of activity caused by impairment (e.g.
difficulty in seeing or speaking). Handicap is defined as a “disadvantage for a given
individual, resulting from an impairment or disability, that limits or prevents the fulfillment of
a role that is normal (depending on age, sex and social and cultural factors) for that
individual.” The term is also a classification of “circumstances in which disabled people are
likely to find themselves” , and finally “Such disadvantages affect the interaction of the
person with a specific environment and culture” (e.g. being confined to home or unable to use
public transport). This “ecological” perspective is a significant step forward from the classical
medical and functional models (although these are still useful for certain cases) which focus

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on the personal deficits and limitations of the individual and fail to take into account the
social, economic and attitudinal barriers faced by persons with disability (Fuchs et al 2007).
The fourth well know classification of ID is from the American Psychiatric Association’s
Diagnostic and Statistical Manual (DSM-IV). The fifth edition is scheduled for May 2013,
and proposed revisions are already available on the American Psychiatric Association
Website (code name: A 00-01). It is relevant to quote the definition here:
“Intellectual Developmental Disorder is a disorder that includes both a current intellectual
deficit and a deficit in adaptive functioning with onset during the developmental period. All
three of the following criteria must be met.”
The criterion for a diagnosis of ID is the same in all classifications: approximately two
standard deviations below the mean (i.e. an IQ score below 70 in the most commonly used
scales). The WHO classification still has subdivisions for mild, moderate, severe and
profound deficiency with approximate IQ ranges of, respectively, 50 to 69, 35 to 49, 29 to 34,
and under 20. It may be noted that these subdivisions are now outdated. Most of the
psychological instruments currently available for assessing general cognitive levels
(Wechsler, Stanford-Binet and Kaufman scales) have floor effects for persons with disability
and generally fail to detect valid differences in the lower ranges (Youngstrom et al. 2003;
Carlier and Ayoun 2007; Heissl et al. 2009; AAIDD, 2010). Some studies, have overcome
this difficulty by considering only the raw scores (Hessl et al. 2009; Couzens et al 2011) or by
using a scale developed for children younger than the subjects of the study (Chabrol et al
2005). Another solution is to develop a specific assessment battery for individuals with ID
(Edgin et al. 2010), but such types of procedures are not relevant for epidemiological studies
where the use of standardized scores is mandatory.
1.2 Epidemiology

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The use of the ICF based indicators has been more widely adopted in some countries
(Australia, Canada, India, Italy, Japan, Mexico and the Netherlands) than in others (WHO
Website, January 30, 2012). The WHO Website refers users to the United Nation Statistics
Division (DISTAT) Website for epidemiological data. The demographic yearbook recently
published by the United Nations (2011) does not contain data on handicaps, but some items
should be of interest to the reader of this chapter (items on live births, infant births and foetal
deaths). An earlier DISTA report (1990) included a warning for interpreting prevalence rate
comparisons across countries because of differences in the concepts and methods used to
identify persons with disabilities, and two interesting comments were made. First, for reports
on severe impairments (blind, deaf, leg amputated, mentally retarded etc.), rather than mild to
moderate impairments, male/female ratios of disabled subjects were greater than 1.0,
indicating a predominance of disabled males for severe impairments; and secondly, a large
proportion of surveys found that, on the average, disabled persons are less educated, have
lower socio-economic status and are more likely to reside in rural and poor areas compared to
able-bodied persons.
Studies using ICF criteria can be found in Canadian statistics, and data extracted from a
national survey (Participation and Activity Limitation Survey, 2006) are presented in Table 1.
In children, disability rates are higher for boys than for girls, in particular for the types of
disability linked to ID, i.e. affecting development, communication, learning and memory.
Reported rates of learning and developmental disabilities amongst young people are also
higher for boys, but the difference is smaller; the reverse is found for emotional/psychological
disability and pain. One limitation of the PALS (as for other surveys developed with the
WHO) was the use of self-reporting to identify disability (or reporting by parents or guardians
for children 14 and under).

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----Insert Table 1-------
Fuchs et al. (2007) also used ICF and reported epidemiological data from a survey in the
Canadian province of Manitoba, describing the population of children with disabilities cared
for by the child welfare system in Manitoba during the 2004-2005 fiscal year (n = 1 869).
One-third of children in care were found to have a disability. Boys are overrepresented (60%),
as are First Nations children (68.7%). The number of children with disabilities increases until
the age of 13 years and then declines. Disabilities were classified into six main categories:
intellectual (75.1% of the children affected), mental health (45.8%), medical (22%), physical
(18%), sensory (5%), and learning (3%). Children often had more than one disability (58.1%)
and the most common combination was intellectual and mental health. Approximately 49% of
disabilities had no known cause. Fetal Alcohol Spectrum Disorder (FASD) was diagnosed in
34.2% of the children and for 51.6% maternal substance abuse was considered, or suspected,
to be the cause of the disability.
McDermott et al. (2007) noted that the distinction made by epidemiologists between
incidence (the risk of developing a condition within a specified period of time) and prevalence
(the total number of cases in the population at a given time) is difficult to use for ID as this
may vary for the same person at different periods of her/his life (prenatally, at birth, at school-
age). Reviewing data (mostly published before 2000), the authors reported a prevalence of ID
at 10-20 per 1000, but lower and higher estimates could also be found depending on the
populations surveyed and methods used (nationality and age of the population, national
registry or not, cross-sectional data on children in mainstream public schools, data from
special education schools etc.). Such inconsistency in data collected may be largely
attributable to the classifications system revisions. In practice many epidemiological studies
do not take adaptive behavior into account and the sole criterion used to estimate the

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prevalence of ID is IQ. The few studies to include adaptive behavior as one of the criteria
suggest that the prevalence of ID would go down from 2% to 1% when it is included
(Leonard and Wen, 2002).
A number of consistencies can be found in the literature. First, the prevalence of mild to
moderate ID is higher than severe ID. Second, age-specific prevalence rates increase with age,
peaking at about 10-14 years. This trend could reflect differences in case ascertainment, the
ability of adults with ID to adapt to the demands of society with the passage of time, IQ
changes, or differentials in mortality between people with ID and the general population
(Leonard and Wen, 2002). Third, males are more likely to have ID than females, and
especially the younger age groups. Some biological factors may be put forward to explain the
higher proportion of males (see below). Fourth, social, economic, cultural and ethnic factors
influence the prevalence of ID. A higher prevalence of moderate ID was consistently found in
groups with low socio-economic status, and with certain ethnic groups (e.g. Afro-American
children, indigenous Australians, Canadian Aboriginals). Many variables could explain these
differences (Leonard and Wen, 2002), for example, social, demographic, economic and
cultural factors, prenatal and/or post-natal biological factors, plus probable interactions
between these factors.
2. Main causes of ID.
ID has many different causes. The AAIDD 2010 proposes a multifactorial approach with four
types of factor: biomedical (genetic disorders, nutrition), social (social and family interaction,
child abuse), behavioral (e.g. activities causing injury, and maternal substance abuse), and
educational (availability of educational support); the last factor being outside the scope of this
chapter, it will not be discussed here. Another categorization can be made according to the
timing of the risk factors – prenatal, perinatal and postnatal.

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2.1 Genetic factors
There is no doubt that genetic factors are of primary importance in the etiology of ID. How
many genes are involved? In the database Online Mendelian Inheritance in Man (OMIM),
1 883 items can be found when using “mental retardation” as the key words (but only 181
with the more recent term of “intellectual disability”). The number of entries in the catalog
has been increasing since the beginning of the century with the explosion of genetic
information (McKusick 2007). Certain disorders occur relatively frequently, while others are
very rare (Billuart et al. 1998; Chabrol et al. 2005 for example) and more difficult to detect. It
is frequently assumed that in approximately half of ID cases, there is no known cause, but
more and more requests are being made to screen for genetic defects in cases of moderate to
severe ID.
Most numerical chromosomal anomalies are lost by miscarriage. Trisomy 13, and 18 are
found among live births but also have a high rate of fetal death. Many fetuses with trisomy 21
can survive and consequently the syndrome is the most common genetic disorder involving
ID. An extra copy of one chromosome is relatively easy to detect, but more sophisticated
techniques are needed to detect of balanced or unbalanced chromosomal rearrangements. de
Vries et al. (2001) developed a checklist to help preselect of cases for subtelomere testing
which included: (1) family history of ID, (2) prenatal onset growth retardation, (3) postnatal
growth abnormalities, (4) ≥ 2 dysmorphic facial features, (5) one or more dysmorphic non-
facial features. Following these recommendations, Popp et al. (2002) selected 30 patients with
unexplained developmental delay; using conventional cytogenetics and multiplex FRSH
telomere integrity assay, chromosomal aberrations were detected in 4 of the 30 patients
(13.3%). All were young children (under 3 years). The authors observed that facial
dysmorphy is more difficult to detect in younger children; it is, however, an important

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criterion in the decision to carry out genetic screening. de Vries et al. (2003) reviewed 20
studies including 2 500 persons with ID of unknown cause. In 125 patients (4.8%), a
telomeric defect was detected. One year later, Koolen et al. (2004) confirmed the high
probability of finding subtelomeric rearrangements in patients with unexplained ID and
reported an aberration in 14 of 210 patients (6.7%: 10 deletions and 4 duplications). Once a
telomeric defect is found, a key question still has to be solved: can the defect be considered as
the cause of the ID? It is important to establish whether the defect has been observed in other
patients, with ID, and examples can be found in recently published data. Manolakos et al.
(2010) used array-CGH in a cohort of 82 Greek children (mean age 4.9 years) with
unexplained ID (normal karyotype), dysmorphic facial features and congenital malformations,
and detected 13 patients (15.8%) with cryptic chromosomal imbalances: 6 patients with
duplications, 5 patients with deletions, one with triplication and one with two duplications. In
3 out of the 13 patients, the chromosomal rearrangements occurred de novo and were said to
be the putative cause of the ID. As the other aberrations had been inherited from a healthy
parent, the authors concluded that they were probably benign. After sequencing the exomes of
10 case-parents trios, Vissers et al. (2010) identified unique non-synonymous de novo
mutations in nine genes. Three genes do not seem to play a role in ID, but the other six genes
are linked to ID. The authors concluded that de novo mutations are a major cause of
unexplained ID.
Autosomal single mutations with either dominant or recessive or X-linked modes of
transmission, and short deletions are known to be linked to ID. Severe dominant forms of ID
are not transmitted, as it is unlikely that the patients will reproduce. According to Ropers
(2008), little is known about the prevalence of dominant ID, but such cases are probably not
so rare, given the high proportion of apparently relevant de novo CNVs (Copy Number
Variants). Autosomal recessive forms of ID (AR-ID) due to mutations are probably common,

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although the often-quoted estimate of up to 25% of unexplained cases of ID has not been
confirmed by recent epidemiological data. Cumulating the data, Ropers (2008) concluded that
22 loci for non-syndromic AR-ID have been found. To date, only 6 AR-ID genes1 have been
identified, but Rogers predicted that “their number will soon explode.” (p. 244). And he was
right. Performing homozygosity mapping in a cohort of 136 consanguineous families mainly
from Iran, he and his co-authors (Najmabadi et al. 2011) announced three years later, that they
had discovered 50 novel genes as AR-ID genes. However the causal links between the new
genes and ID have yet to be confirmed. In the same year, Abou Jamra et al. (2011) used the
same strategy with 64 Syrian consanguineous families with non-specific ID and uncovered 11
novel loci. On the basis of the number of ID genes on the X chromosome, Schuurs-
Hoeijmakers et al. (2011) estimated that there are approximately 2 000 AR-ID genes (11% of
the autosomal protein-coding genes). To overcome the difficulties encountered by colleagues
who used large (but very rare) consanguineous families, these authors performed
homozygosity mapping in outbred families with multiple ID-affected siblings. In 10 families,
they found 21 homozygous regions shared by affected siblings; the regions did not overlap
with the nonsyndromic genes. The authors concluded that homozygosity mapping in outbred
families may help identify novel AR-ID genes.
With more boys with ID amongst institutionalized children and the disproportionate number
of families with intellectually disabled boys only there has long been an argument for the sex
linkage of ID, and this form of transmission is easier to detect. In a survey of all children with
a very low IQ (30 to 50) born between 1955 and 1964 in the State of New South Wales
(Australia), Turner and Turner (1974) estimated a prevalence rate from brother pair excess of
0.74/1000 males, concluding that 1 in every 5 of the “mentally retarded” boys in the IQ range
of the survey may have an X-chromosomal form of ID. Ropers (2008) reported more than 80
1+In some paper the old label « mental retardation » is kept and the genes are labeled MR
genes.+

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genes for X-linked ID identified after collecting data in large cohorts of families studied by
international consortia (e.g., EuroMRX consortium, de Brouwer et al. 2007). The Fragile X
syndrome may account for 25% of X-linked ID. One year later (Gécz, Shoulbridge and
Corbett, 2009) estimated that more than 90 different X-linked ID genes (∼11% of the X-
chromosome genes) had been identified but that many more genes remain uncharacterized. In
many cases, ID is not the sole disorder; there is frequently co-occurrence of autism spectrum
disorder, epilepsy or behavioral and psychiatric problems.
2.2 Environmental factors
Mwaniki, Atiena et al. (2012) conducted a systematic review to estimate risks of long-term
neurocognitive and other sequelae after intrauterine and neonatal insults such as preterm-birth
complications, intrapartum-related factors (hypoxic ischaemic encephalopathy, infections and
in particular sepsis, meningitis and neonatal tetanus) and other conditions such as jaundice
and congenital infections (cytomegalovirus, toxoplasmosis, syphilis, and rubella). Of 28 212
papers identified by search, only 153 met their inclusion criteria (identifiable and well defined
neonatal insult, the use of standardized tests or controls in neurodevelopmental assessment
and less than 20% of survivors lost to follow-up). In all, 22 161 neonates were assessed. The
overall median risk of at least one sequela in any domain was 39.4%. The most common
impairments were learning difficulties and cognition or developmental delay (59%). Multiple
impairments were frequent (e.g., cognitive impairment, motor impairment and hearing and
vision loss). Behavioral problems were relatively low (11%) but may have been
underestimated (Thompson and Gillberg, 2012).
Alcohol and drug use by pregnant woman are risk factors for the neonate causing intra-uterine
growth retardation, birth defects, altered behavior, and withdrawal syndromes. Fortunately
most adverse effects of prenatal drug exposure are rare or less than might be expected, with

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the exception of alcohol exposure (Chiriboga, 2003). The highly adverse effect of alcohol
appears to have been known since ancient times (see, for example, the story of Samson’s
mother in the Bible, and Aristotle’s warnings), although whether the teratological effects were
directly known at the time is debatable - Warren and Hewitt 2009). The major features of fetal
alcohol syndrome (FAS) can be divided into three categories: intrauterine and postnatal
growth retardation, craniofacial dysmorphisms (e.g., small palpebral fissures, flattened
philtrum and thin upper lip) and evidence of central nervous system anomalies (decreased
cranial size, structural brain anomalies, neurological hard or soft signs) – Stratton et al. 1996.
It is not easy to diagnose FAS at birth as facial dysmorphisms have also been reported in
children exposed to substances other than alcohol (Chiriboga, 2003). Fetal alcohol exposure is
the leading known cause of ID and a dose response is observed: the stigmata are present in
proportion to the degree of exposure, but it is difficult to detect a threshold below which the
risk does not exist; pregnant women are therefore advised to avoid drinking alcohol. Less
severe outcomes for the child are categorized into Fetal Alcohol Spectrum Disorder (FASD).
The prevalence in the USA has been reported as 1-3 and 9.1 per 1000 live births for FAS and
FASD respectively (Chudely et al. 2005). It may be higher in some countries and/or
populations as can be seen in the following data. In a Canadian First Nations community the
prevalence of FAS and partial FAS was estimated at 55-101 per 1000. In other Canadian
communities the rates were also very high, but it was very low in Saskatchewan: 0.51 per
1000 in the period 1973-1977 (Chudley et al. 2005). In a recent central Italian population-
based screening of children attending primary school, the prevalence of FAS was estimated at
4.0-12.0 per 1000, and of FASD between 23.1 and 62.1 per 1000 (May et al., 2011). In a
group of 100 Israeli children under the age of 2 who were candidates for domestic adoption or
in foster care, 15% either had FASD or were at risk of developing symptoms (Tenenbaum et

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al. 2011). In short, it is impossible to establish a prevalence level that applies to all
populations.
Many postnatal environmental risk factors have been reported and some examples are
presented here. Severe malnutrition during development can cause infant mortality, smaller
physical size and ID among the survivors. The relation between malnutrition and cognitive
level is complex as both nutrition and intellectual factors are associated with a number of
social factors (e.g. the caregivers who may themselves be ill or malnourished, the
geographical conditions and/or socio-economic status). Data published by Ivanovic et al.
(2000) are particularly valuable. The authors studied the long-term effects of severe
undernutrition during the first year of life on brain development and IQ in two groups of poor
Chilean high-school graduates, one which had been undernourished and the other which had
not suffered from undernutrition. The socioeconomic conditions were similar for both groups,
except for the mean number of years of education of the mothers, which was 2 years less for
the group that had been undernourished. The group of students who had suffered from
undernutrition recorded a mean IQ lower than the other group (a difference of up to 24.5
points). Multiple regression analysis showed that maternal education and undernutrition
explained 71.4% of the IQ variance. The effect of childhood iodine deficiency is considered
to be the most common cause of preventable ID worldwide, with pregnant women and young
children being particularly susceptible. The number of iodine-deficient countries is
decreasing, but more than 200 million school-age children still have an insufficient iodine
intake (Andersson et al. 2012). An association has also been established between the body
burden of lead (in blood or tooth dentine) and a lower IQ, even after adjustments are made for
other environmental factors (Taylor and Rogers 2005).
We do not want to end this short and non-exhaustive overview of environmental risk factors
without mentioning acute and chronic psychological stress, physical abuse, exposure to

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family violence, and institutional deprivation. One example can be taken from the excellent
English and Romania Adoptee (ERA) study – see Rutter et al. (2010) – and other chapters of
the 2010 Monograph. In a follow-up of children who had suffered severe institutional
deprivation in Romania during the Ceauşescu regime, the team found sound evidence that
institutional deprivation does truly cause deprivation-specific psychological patterns (quasi-
autistic patterns, disinhibited attachment, inattention/overactivity, and cognitive impairment).
2.3 Gene-environment interactions/and or correlations
The etiology of ID is complex, and in practice it is often difficult to disentangle genetic and
environmental risk factors when considering individual cases. The idea of a causal linear
relationship between genes and behavior, or between the environment and behavior is now
obsolete (Roubertoux and Carlier 2007; 2011). In almost all cases, the phenotype linked to a
specific genetic disorder is highly variable. Causes may be biological (e.g. an epistastic effect
or an interaction between genes) or environmental (e.g. environmental adversity or cultural
transmission). De Smedt et al. (2007), to cite an example, reported that one of the factors
contributing to the variability of the 22q11 deletion phenotype (Di George/Velo-Cardio-Facial
syndrome) is the mode of transmission of the deletion (de novo vs familial): children with
familial deletion have a lower IQ than children with a de novo deletion. Studying a sample of
103 children, they found that the difference in IQ between the two groups of children could be
attributed to the lower educational attainment level of the parents of children with familial
inherited deletion.
Another example can be found with Fragile X syndrome. Maternal responsivity predicts
language development in young children with Fragile X syndrome (Warren et al 2010); it has
been well established in the literature that maternal responsivity is dependent on the child’s
behavior (transactional model; Warren and Brady 2007). In disorders such as Fragile X (see

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below), not only does the child have a full mutation affecting his/her ability to communicate,
but the mother also has a genetic defect (either a full mutation or premutation) which may, in
turn, affect her own skills required for communicating with her child(ren). There is evidence
supporting this hypothesis, showing that differential sensitivity to life stress is associated with
CGG repeat length (Seltzer et al. 2011) which characterizes the mutation (see below).
Fetus vulnerability in FASD is an excellent illustration of gene-environment interaction. Less
that 10% of women who drink during pregnancy have children with FAS. What is the reason
for the differential vulnerability of fetuses? One explanation may be in differences in the
genetic background of the fetus and of the mother. Alcohol dehydrogenase (ADH) is the
principal enzyme catalyzing ethanol oxidation to acetaldehyde. Three functionally distinct
polymorphisms exist for ADH1B with different binding affinity for alcohol and maximal
turnover rates. Warren and Li (2005) reviewed the literature on human and animal studies,
and reported that the presence of either ADH1B*2 or ADH1B*3 alleles in the maternal and
fetal genomes appears to afford protection from alcohol-derived teratogenesis; this is not the
case when the ADH1B*1 allele is present. Other candidate genes are highly probable
(Lombard et al., 2007).
3. Neuronal and behavioral phenotypes of genetic developmental disorders.
As explained when introducing the chapter, we are not presenting all genetic diseases
associated with intellectual disability. McKusik’s team, in the database OMIN – Online
Mendelian Inheritantce in Man, is carrying out this useful and daunting task. We have chosen
to give a brief review of current knowledge of two disorders (Phenylketonuria and Fragile X)
to show how knowledge has progressed in the field of ID linked to genetic disorders. We
shall then discuss the contribution of a research method used extensively in this area: the
cross-syndrome comparison.

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3.1 A single gene genetic disorder: phenylketonuria
Phenylketonuria (PKU, OMIN 261600) is an autosomal recessive genetic disorder caused by
the PAH gene (located at 12q23.2) which encodes the phenylalanine hydroxylase enzyme
needed to metabolize phenylalanine (Phe) into tyrosine. Some 500 mutations of the gene
have been identified. This locus heterogeneity explains part of the within-group biological
phenotypic variability (Kayaalp et al. 1997). The mutated allelic form produces a deficiency
of the enzyme phenylalanine hydroxylase, thereby causing an accumulation of Phe, which in
turn affects the biosynthesis of neurotransmitters (dopamine and norepinephrine). Elevated
Phe and low tyrosine levels are thought to impair, inter alia, brain myelination. In Europe,
PKU occurs in approximately 1/10,00O – 1/15,000 births, but regional differences in
incidence have been reported (see Williams et al 2008 for a qualitative review). As with any
other autosomal recessive genetic disorder, parental consanguinity increases the prevalence of
PKU. Most cases of untreated PKU are associated with growth failure, microcephaly,
seizures and severe ID caused by the accumulation of a toxic by-product of phenylalanine
metabolism. Interestingly some untreated patients develop normally (Möller et al. 2003).
Treatment is a low-phenylalanine diet and dietary compliance is difficult in adolescence and
adult life; even though new treatments have been developed, diet is still the best therapy
(Giovannini et al 2012). What are the outcomes for early-treated individuals with PKU? In
our qualitative review on cognitive development we concluded (Carlier and Ayoun, 2007)
that these individuals had a mean IQ close to 100 (i.e., normal) provided they followed the
diet until at least 10 years of age. However, some lower scores, compared to controls, were
found for executive functions. DeRoche and Welsh (2008) conducted a meta-analysis on
neurocognitive outcomes of early-treated patients with “classical PKU” (blood Phe levels
from 600 to 1,200 µmol/l) to establish whether a profile of deficits in intelligence and

18
executive functions had emerged from empirical research published between 1980 and 2004.
The meta-analysis covered 33 studies totaling 1 109 individuals with early-treated PKU, and
1 145 peer control individuals from 5 to 35 years of age. For intelligence tests, the effect size
of the differences, with lower scores for patients, was small to moderate (from 0.20 to 0.42).
Differences were greater for executive functions with an effect size of 0.79 for the Total
intelligence score, and up to 1.15 for cognitive flexibility. Of the different measurement
tools, intelligence tests had effect sizes that were homogeneous across outcomes, but this was
not the case for executive functions tasks. Studies published more recently have reported
larger effect sizes for these functions than did earlier studies. This may be due to advances in
the assessment of executive functions and/or the use of more sensitive tasks to detect subtle
impairments of cognitive processes. The deficit observed in executive functions was
consistent with the prefrontal model of PKU: as noted earlier, the mutation disrupts the
normal synthesis of dopamine and norepinephrine. However, as DeRoche and Welsh (2008)
observed, there is an overlap between neuropsychological tasks measuring “prefrontal
processes” and “white matter integrity.” The white matter hypothesis could, therefore, also be
put forward. Neuroimaging data has provided considerable evidence of white matter
abnormalities associated with early-treated PKU – see for example Anderson et al. 2007 for a
qualitative review. DeRoche and Welsh published their own data, presenting new evidence of
links between diffuse white matter damage and cognitive deficits, including attention and
executive functions (citing planning ability, spatial organization, cognitive flexibility, and
conceptual reasoning). There was one limitation to their study and that was the large mean
difference in IQ (WISC-III; 91 vs 104) between the PKU group and the control group.
Controlling for the effect of IQ (and not only for age, gender and SES) would have provided
interesting additional information. A study by Anderson et al. (2007) showed peripheral
levels of phenylalanine to be inversely correlated with cognitive performance, confirming

19
earlier observations. With two groups matched for IQ, gender and demographical variables,
Banerjee, Grange, Steiner, and White (2011) assessed executive strategic processing during
verbal fluency performance in 32 children with PKU. The two groups of children had the
same mean IQ (i.e. global cognitive level), but mean differences were found in phonemic
fluency trials (word generation in a food/drink category; words beginning with S and F) trials,
and for a number of semantic or phonemic switches. On average, the performance of the
PKU group was 0.6 standard deviation below the control group (i.e. a medium effect size),
with a larger effect size for the older children (1.5). No significant correlations were found
between any of the Phe and verbal fluency variables. The negative correlation between IQ
and Phe level has been well documented (Waisbren et al., 2007 for a meta-analysis), but less
is known about more specific aspects of cognition. Viau et al. (2011) studied a sample of 55
patients and found that the correlations between cognitive tests and treatment variables were
highly variable and depended on the cognitive variable under consideration. In addition to the
Phe level, the ratio between phenylalanine and tyrosine levels may potentially play a role in
brain development, and therefore in cognitive processes (Sharman, Sullivan, Young, and
McGill, 2010). Campistol et al. (2011) drawn attention to the fact that the mild form of
hyperphelylalaninemia, characterized by a plasma Phe concentration lower than 360µmol/l,
may also, to a lesser extent, have a negative impact on cognitive development.
Not only is a high Phe level a high risk factor for patients, but also, in the event of pregnancy,
for the fetus, with more neonatal sequelae in untreated pregnancies (see Prick et al. for data on
a large cohort, 2012).
3.2 A single gene X-linked disorder: The Fragile X syndrome
Fragile X syndrome (FXS, OMIN 300624) is the most frequent cause of mental disability due
to mutations to a single gene, and also the most common monogenic cause of Autism

20
Spectrum Disorder characterized by three dysfunctions before 3 years of age: atypical social
behavior, deficits in verbal and non-verbal communication, and repetitive and highly
restricted interests. The gene involved is FMR-1 (Fragile X site Mental retardation–1) located
at Xq27.3. The syndrome is caused by an expansion of CGG (cytosine guanine-guanine)
repeats in the 5’ untranslated region of exon 1 of the FMR-1 gene. The normal size of CGG
repetitions ranges from 5 to 54, the most common value being 30. In the event of CGG
expansion being transmitted by the female, the number of repetitions increases and the
woman transmits a premutation to her offspring; any of her female offspring are then likely to
transmit an even larger number of repetitions to the next generation. When there are more
than 200 repetitions, the offspring will carry the full mutation with hypermethylation of the
FMR1 gene, and then does not produce the Fragile X Mental Retardation Protein (FMRP).
Crawford et al. (2001) conducted a review of population-based studies and estimated the
prevalence of the full mutation ranges from 1/3,717 to 1/8,918 males in the general Caucasian
population. The prevalence of the premutation in Caucasian populations is ~1/1,000 for
males and from 1/246 to 1/468 for females. FMRP is mainly expressed in the brain and
gonads and has multiple functions in RNA metabolism, including mRNA decay, dendritic
targeting of mRNAs, and protein synthesis (see De Rubeis and Bagni, 2011; De Rubeis et al.
2012 for recent reviews).
The facial characteristics are more pronounced in males than in females and are more
apparent in male carriers after puberty (long, narrow face, large ears, prominent jaw and
forehead). Motor and cognitive development is delayed in infancy and adolescence (Reiss
and Dant 2003 for a thorough qualitative review); the mean adult IQ is in the range 42-55.
The estimate clearly depends on the method of recruitment of patients and the psychological
test used to measure IQ. As noted previously, intelligence scales have very limited
discriminative power in low scores because floored scores are frequent. Hessl et al. (2009)

21
found the mean IQ of 217 school-age boys and girls with FXS to be 50 with high variability
(standard deviation 19.5, range 40-123). The percentage of participants with floored standard
scores in the subtests of Wechsler’s WISC III scale ranged from 40% (picture completion) to
70% (arithmetic). The rate of intellectual development during school age was measured in a
longitudinal study where boys and girls with FXS and their unaffected siblings were assessed
2 times. During the time between the first and second assessments (on average 3.89 years),
the annual rate of intellectual development was approximately 2.2 times faster in the
unaffected children compared to the children with FXS (Hall et al. 2008). These results
highlight an important fact: in most cases, the IQ decline observed in children with ID cannot
be attributed to cognitive regression but rather to a slower rate of development compared to
normally developing children. Weaknesses in executive function, visual memory, visual-
spatial relationships, arithmetic and relatively less severe impairments in verbal skills were
also reported in male individuals with FXS. Not only is there frequently Autistic Spectrum
Disorder, but also Attention Deficit Hyperactivity Disorder and depression coexisting in
males with FXS. The most prominent feature of FXS brain morphology is the dysgenesis of
the dendritic spines that are longer and thinner than normal (Koukoui and Chaudhri 2007; De
Rubeis et al. 2011; De Rubeis et al. 2012). Structural studies have pointed out a significantly
enlarged caudate nucleus and a decrease in the size of the cerebellar vermis. Functional MRI
studies have detected specific patterns of activation linked to cognitive and emotional tasks
(Lightbody and Reiss 2009).
As females have two X chromosomes, the effects of the full mutation are less than for males.
According to Jacquemont et al. (2007) most of the females have an IQ in the 75-90 range, and
about 25% have an IQ<70. We recommend once again that these figures should not be taken
literally. Even though the females may have a normal intellectual level, other difficulties, in
visuospatial processing and mathematics, have been reported, and, at the emotional level,

22
hyperactivity, shyness and anxiety (Lachiewicz and Dawnson, 1994; Gallagher and Hallahan
2012, for a recent review)
A mild “fragile X phenotype” has been described in carriers of the permutation – the Fragile
X Tremor/Ataxia syndrome (FXTAS, OMIN 300623). Older persons carrying a premutation
are more likely to develop neurological disorders, with severe tremor and difficulty in
walking and maintaining balance, and eventually parkinsonism and cognitive decline
(Hagerman and Hagerman, 2007). In premutation females, the prevalence of premature
ovarian failure is high (Jacquemont et al. 2007; Cornish et al. 2008). Subtle cognitive
impairments were described in young permutated women (Goodrich-Hunsaker et al. 2011)
and male premutation carriers (Hunter et al 2012)
The discovery of CGG expansion in the FMR-1 gene has provided an opportunity to study
correlations between the characteristics of the mutation (the number of CGG repeats, the
amount of protein produced, the methylation output ratio and the activation ratio) and scores
on cognitive tasks. Some authors have observed very high correlations, but recent
publications suggest that the relationship is too small to make any individual prediction; in the
study by Lightbody et al. (2006) for example, protein levels could explain only 7% of IQ
variance. In the follow-up study (Hall et al. 2008), they concluded that the FRMP level
accounted for only 5% of the intellectual score at time 1 and 13% at time 2. However
reference should be made to a recent report using the methylation status of FREE2 CpG sites
to identify low-functioning full mutation females (Godler et al. 2012).
3. 3 Cross-syndrome comparisons
Table 2 gives an approximate picture of profiles of patients with one of four genetic
syndromes: T21 (or Down), Williams Beuren, Fragile X and DiGeorge/Velocardio facial

23
syndromes. Fragile X syndrome has already been described, but information is needed on the
other three syndromes before commenting on the table.
Williams-Beuren syndrome (WBS, OMIN 194050) is caused by hemizygous continuous gene
deletion (1.5 to 1.8 Mb) on chromosome 7q11.23, which contains approximately 28 genes.
The syndrome is rare. However it has probably been underestimated: 1 in 20,000 live births
was the prevalence reported in early publications but a more recent estimation is for up to 1 in
7,500 (Strømm et al 2002). In addition to medical problems, the main characteristics are
distinctive facial features and a specific psychological profile with a hypersocial personality
and severe difficulties in visuospatial tasks (Morris and Mervis 2000; Eckert et al. 2006).
Velocardiofacial (OMIN 192430) and DiGeorge (OMIN 188400) syndromes are both caused
by a 1.5 to 3.0Mb hemizygous deletion on chromosome 22q11.2, a common deletion which
encompasses approximately 45 genes. Although there is a distinction between the two
syndromes in the OMIN database, many papers considered VCFS/DGS as a single category
and we have chosen to do this. The deletion occurs in approximately 1/4,000 live births;
patients have an IQ in the borderline range, with learning difficulties and, in adulthood,
psychiatric disorders (Murphy et al. 1999; Raux et al. 2007; De Smedt et al. 2009; Campbell
et al. 2010; Philip and Bassett 2011).
Trisomy 21 (T21) or Down syndrome (OMIN 190685) remains the major genetic cause of ID.
Jérôme Lejeune (Lejeune et al. 1959) reported that what was then called “mongolism” was
caused by an extra copy of chromosome 21, now labeled HSA21 for Homo sapiens autosome
chromosome 21. Watanabe et al. (2004) recorded 283 genes encoding proteins on this
chromosome. T21 is caused by a chromosomal imbalance involving HSA21. Although the
cell carries three allelic forms, the genes of HSA21 show dosage-dependent difference in
persons with trisomy 21, i.e. the genes are over-expressed to varying degrees, and some are
not over-expressed at all (Reymond et al. 2002). Lyle et al. (2004), Kahlem et al. (2004), and

24
Kahlem (2006) have shown that a number of genes were not over-expressed, and that the
level of expression was tissue-dependent and age-dependent. In addition to skeletal and
medical abnormalities (Roubertoux and Kerdelhué 2006), ID is the main characteristic, but
with large within-group differences (Chapman and Hesketh 2003, Carlier and Ayoun 2007).
The cognitive behavioral phenotype includes deficits in speech, and language production, and
broad impairment of the memory domain (Chapman and Hesketh 2000; Vicari 2006; Carlier
and Ayoun 2007; Menghini et al. 2011). Roubertoux and Carlier (2009) summarized earlier
studies and concluded that not only is the size of the brain structures generally smaller in
persons with T21 (compared to normally developing persons), but the size of the
hippocampus is also dramatically reduced (by more than 50%). The challenge is now to
determine which genes have an extra copy causing ID and to describe the pathophysiological
pathways of the brain and cognitive dysfunction involved. One methodology for shedding
light on genotype-phenotype correlations is the use of mouse models (see Roubertoux and
Carlier, 2009,, and below the part “Model organism of ID”).
---------- Insert Table 2 ----------
Studies of a single genetic disorder could pave the way to uncover causal mechanisms
between the biological and/or environmental events and the patient’s phenotype. Recent
illustrations can be found in Menghini et al (2011a and b) for T21 and WBS syndromes. A
methodology commonly used has the disorder group matched to two separate typically
developing control groups, one matched for chronological age and the second matched for
mental age, and is based on a standardized test (Thomas et al. 2009). We could say, quoting
Meyer-Lindenberg et al. (2006), that the study of neural or behavioral mechanisms in one
specific disorder provides “a unique window to genetic influences on cognition and
behavior”.

25
Another approach is to compare the behavioral phenotypes of two or more disorder groups.
Many studies have been conducted comparing persons with FRX and T21 syndromes (58
items in EBSCO database) and comparing WBS and T21 (50 items in the same database).
The samples used are generally matched for different characteristics including mental age or
IQ. As the mean IQ is lower in the T21 group than in the other groups (see Table 2), persons
with higher cognitive scores are selected in the trisomy 21 group and persons with lower
cognitive scores for the other group, which substantially restricts any meaningful comparison.
Notwithstanding these limitations, the methodology demonstrates that behind differences in
general cognitive levels, persons with different genetic disorders have very different neural
and behavioral phenotypes, thus offering scope for causal gene to phenotype hypotheses
(Walter et al. 2009).
It is also particularly helpful to compare behavioral and/or neural phenotypes in syndromes
with identifiable genetic causes in a bid to identify the ways in which certain cognitive traits
may influence one another. This strategy was adopted by McDuffie and Abbeduto (2009)
when they compared language development in children with T21, FRX and WBS; they
concluded that the relation between language and cognition differs across the three
syndromes. Annaz et al. (2009) used the cross-syndrome design to study the development of
holistic face recognition in children with autism, T21, WBS and typically developing persons.
Atypical profiles were found in each group of patients, but every disorder group was atypical
in a different way. The same strategy was chosen by Carlier et al. (2011) when seeking to
establish whether atypical laterality observed in persons with ID was mainly due to ID and
cognitive delay. They compared hand, foot, eye and ear patterns of laterality in groups of
patients with one genetic disorders (T21, WBS, VCFG/DGS) and one group of typically
developing persons. Their data showing the existence of a cognitive threshold, below which

26
lateral preference is atypical argues in favor of a causal link between cognition and laterality
in persons with a low IQ.
4. Model organism of intellectual disability
Model organisms are part of the translational strategy which includes not only cellular
models, but also a pathophysiological investigation and a clinical approach. Translational
strategy endeavors to decipher or confirm the role of a gene, and more precisely the genetic
mechanisms that cause the disease, and then to propose remedial molecules. The need to
identify the gene and subsequently the defective protein so as to discover a treatment is the
rule even if, paradoxically, the first treatment of the genetic disease, phenylketonuria,
considered the biochemical aspect of the disease only. There has never been a model
organism of phenylketonuria.
Model organisms of diseases can be seen as a direct consequence of the Darwinian view of
evolution. We use model organisms because species have a common ancestor and because
they have similar characteristics. Model organisms were first analogous. A species or strain
is considered to be a model for a disease when the observed characteristics of the organism
tally with the anatomical, physiological and pathological criteria defining the disease.
Phenomenological similarities originally appeared to be satisfactory. Senescent rats have
been presented as models of Alzheimer disease, an A/J mouse as a model for leukemia and
C57BR and C3H mouse strains that have been judged poor learners and therefore suggested
as models of ID. McKinney (1977) and later Robbins and Sahakian (1979) proposed more
stringent rules to improve the validity of model organisms. The advent of transgenic and KO
mice technologies and the development of common tools for humans and other organisms
such as MRI have led experts to reconsider and refine the criteria (Tordjman et al. 2012). We
suggest the following criteria for a model organism of ID. 1) The disorder must have

27
identical etiology in Humans and the model organism. This criterion means that it is possible
to modify the homologous gene in the model organism (living animal or cell line) to
reproduce the genetic events occurring in humans, i.e. for genetic etiology. 2) The metabolic
and cellular mechanisms must be the same. 3) Brain structure volumes and neurotransmission
mechanisms contributing to ID must tally. 4) The impaired intellectual processes must be
comparable. 5) The physiological mechanisms and intellectual processes must improve in the
same way by using similar compounds.
4.1 Identical Human and model organism etiology
The development of a model organism provides a tool to confirm a hypothesis on the role of a
gene in the development of a disease. This requires preliminary examination of human
genetic results, e.g. for the development of mice with an extra chromosomal copy which may
be involved in the ID and neurological disorders in trisomy 21. Lejeune et al. (1959) proved
that the syndrome is caused by an extra copy of the human chromosome 21 (HSA21). The
estimated number of genes encompassed in the triplicated region is relatively small, thus
making it feasible to adopt a genotype-phenotype correlation approach for the HSA21 genes
and the cognitive characteristics observed in TRS21 (Hattori et al. 2000; Watanabe et al.
2004); there is only a small number of HSA 21 genes, approximately 300. A region between
D21S17 and ETS2 has been reported as being associated with most of the Jackson signs,
including ID (Delabar et al. 1993; Korenberg et al. 1994). Smith et al. (1995, 1997)
developed a mouse model of trisomy in which extra fragments from the human D21S17 and
ETS2 region were inserted into the mouse genome. The D21S17 and ETS2 regions being
syntenic to MMU16, they created segmental trisomy for the region. As an extra copy of a
chromosomal fragment including the Dyrk1a gene was known to generate cognitive disorders,
Altafaj et al. (2001) developed a transgenic mouse overexpressing the Dyrk1a gene only, as it

28
was suspected of playing a major role in cognitive disorders. The story of Fragile-X
syndrome also shows that the development of a mouse model depended on knowledge of the
disease. Oberlé et al. (1991) and Yu et al. (1991) simultaneously reported that the syndrome
was the consequence of both the instability of a DNA-segment and abnormal methylation.
Both repeats and hypermethylation shut down the transcription of FMR1 with a loss of the
FMR protein that contributes to synaptic functions. The two genetic events create a loss of
function similar to the one generated by gene targeting. Oostra’s group (Bakker et al. 1994)
developed a homologous Fmr1 knockout mouse model. FMR knockout mice present various
cognitive disorders and brain dysfunctions generally associated with ID. However, the
development of model organism cannot be simply the addition or deletion of a gene
associated with a disease. The genetic mechanisms of the diseases are often more complex
than a full null allele or an allele overexpression, as shown by Hutchinson-Gilford in the case
of progeria syndrome, caused by a heterozygote point mutation (nucleotide 1824 - C1824 to
T1824) that causes a splicing event in Lamine A (LMNA) gene (located at 1.q22). The
mutation leads to the elimination of the 3’ half of exon 11 (about 150bp or 50 amino-acid)
resulting in a truncated form of prelamin A called progerin (De Sandre-Giovannoli et al.,
2003). The relevant mouse model for Hutchinson-Gilford progeria (Osorio et al. 2011)
carried a deletion of exon 11 in the homologous mouse Lmna.
A number of qualitative reviews have pointed out the limits of mouse models for medical
genetics, but genetic engineering is making progress in this field. Until recently, gene
targeting was performed using one of the many 129 stem cells transferred into C57BL/6
blastocysts, producing a heterogeneous genetic background that cannot compensate for an
insufficient number of backcrosses. The heterogeneous genetic background generates “noise”
that interacts with the gene effect. It is now possible to generate targeted mice with stem cells
that belong to the inbred strain that is used as host. More care is now given to the selection of

29
the promoter in transgenic mice, and differences in gene expressions cannot be attributed to
different efficiencies of the promoter. On the other hand, the discovery of regulatory
sequences on the non-coding regions of the genome has added complications for gene
targeting technologies. Non-coding regions carry micro RNAs, (miRNA) sequences that
regulate transcription factors. Thousands of miRNAs have been reported in mammals
(Kozomara and Griffiths-Jones 2011). miRNAs contribute to development diseases (Sayed
and Abdellatif 2011) and also to neuronal and cognitive development (Hansen et al. 2010).
The deletion of the full gene (intronic plus exonic sequences) cumulates the effect of the
protein for which the gene codes and the effect of other proteins which may be regulated by
the miRNAs.
4.2 The same metabolic and cellular mechanisms
The identification of cellular mechanisms provides the opportunity to use cellular models, but
the model developed is more a model of the cellular or metabolic conditions required for the
onset of the disease rather than a model of the disease. There are several models
(Caenorhabditis elegans, Zebra fish, Drosophila and yeast) of neurological and
developmental diseases. Mason and Giorgini (2011) reviewed the yeast cell model used to test
for a number of mechanistic relationships between the abnormal expansion of a
polyglutamine tract and huntingtin protein toxicity. Tauber et al. (2011) published the
complex gene expression profiling in mutant yeast for huntingtin and the resulting chart is
crucial for the analysis of the transcriptional consequences of huntingtin toxicity.
While the model may fit at the genetic level, it may fail at the metabolic level, as seen with
the attempt to modelize Lesch-Nyhan syndrome in mice. In patients, the syndrome is
characterized by cognitive disorders and self-mutilation. The cause of the syndrome is known
and the development of model organisms could pave the way to treatments. Lesch-Nyhan

30
disease is due to a mutation in the hypoxanthine phosphoribosyltransferase (HPRT) gene
mapped at Xq26.2-q26.3. HPRT regulates the metabolism of purines. The mutation results in
a lack of HPRT in Lesch-Nyhan syndrome inducing an abnormal purine metabolism (over-
production and over-excretion of purines), with patients having no or low levels of HPRT.
Experiments targeting the homologous Hprt gene in the mouse did not generate self-injury-
behavior (Hooper et al. 1987; Kuehn et al. 1987). Purine metabolism is, in fact, different in
Humans and the Mouse. The findings suggest that mice are protected against HPRT loss and
that purine metabolism is less HPRT-dependent in the Mouse than in Humans. Non-mutant
mice did not salvage circulation hypoxanthine. A second enzyme, adenine
phosphoribosyltransferase (APRT), is involved in the purine salvage pathway in mice. Wu
and Melton (1993) observed that the HPRT/APRT ratio was lower in mice than in humans.
They then administered (9-ethyladenine) which inhibits APRT to a group of mice lacking
HPRT. The Hprt targeted mice given 9-ethyladenine displayed self-injurious behavior.
4.3 Brain structure volumes and neurotransmission mechanisms
Post mortem studies and different MRI techniques investigating Humans provide
opportunities for comparing brain structures and brain chemistry with the central nervous
system of a model organism. Here we must overcome prejudices. Small organisms may
provide unexpected models. The DYRK-1A gene is a homolog of the minibrain gene, as
described in Drosophila by Tejedor et al. (1995), Guimera et al. (1996), Song et al. (1996).
The mutation leading to the minibrain phenotype is associated with reduced mushroom bodies
and learning deficits in drosophila (Heisenberg et al., 1985). The reduction of mushroom
bodies can be paralleled with the small brain or small hippocampus that has been reported in
persons with trisomy 21 and with mouse models of segmental trisomy.
The results obtained from MRI and other techniques used to visualize the brain and to

31
estimate brain structures are paving the way for the development of model organisms. The
reduction in the size of brain structures in trisomy 21 (Roubertoux and Carlier 2009) provides
a framework for examining animal models, for example the mouse. The methyl-CpG-binding
protein 2 (MECP2) gene contributes to Rett syndrome. Mecp2-null mice present volumetric
and metabolic brain abnormalities (Saywell et al., 2006) that are also present in patients with
Rett diagnosis (Naidu et al. 2001). The study of the brain phenotype provides the means to
refine the phenotypic comparison between the model organism and the patient. It can also be
a pre-investigation. Brain imaging is time-consuming and money-consuming, and can be
stressful for children, in particular children with cognitive disorders. An examination of
results obtained with a model organism should guide the clinician in decisions on the need for
a brain examination.
The mouse provides valuable models of neurological diseases, but the mouse is not always
relevant for studying the brain or a neurological phenotype. The neurochemical
characteristics of the brain are quite similar in the mouse brain and the primate brain. In
mammals, the different neurotransmitters and their receptors are controlled by orthologous
genes and consequently the functions of the neurotransmitters and their receptors do not differ
across the species. The neurotransmission system does not appear to be differentiated across
the mammalian species. The anatomy of the brain, however, is specific to the species, even
though there are similarities. Ergic systems are like the liquids used by all cars, but they do
not produce the same result in a Trabant as they do in a Porsche. Some striking anatomical
differences between model organisms and the Human must be pointed out. The mouse brain
does not include a language center. While the prefrontal cortex does exist in rodents, it shows
less differentiation than in primates. The cortical layers differ. The prefrontal cortex in
rodents has connections that are more similar to the median cortex connections than to the
pre-frontal cortex of primates. The medullar organization of the motoneurons differs between

32
rodents and primates. The corticospinal tract is a descending medullar way; dexterity depends
on it being intact. The organization of the tract differs across the species and is consequently a
factor in the selection of a model organism for the study of motor disorders. The number of
fibers varies, with the estimated number being greater in Humans (1101,000) than in non-
human Primates (40,000) and rodents (137,000). Direct corticospinal connections are found
with motoneurons in Primates, including Humans, but the connections are different in rodents
which have no direct connection between the corticospinal neurons and the cervical
motoneurons innervating the limb muscles. The organization of the fibers in the spinal chord
also differs. A large percentage of corticospinal fibers follow an ipsilateral descending
medullar way, but in rodents most of the fibers are in the dorsal column, whereas in Primates
most are in the lateral column (Courtine 2007). Differences in motor tracts disqualify the
mouse from modeling motoneuron genetic disorders. Comparative studies of brain substrates
of clinical signs should preclude any attempt to develop model organism of ID.
4.4 Intellectual processes in the model organism
The prospect of mimicking intellectual processes affected in genetic disease comes up against
one main difficulty: the model organisms have no access to language. This is a limiting factor
as speech and language disorders are often features in pediatric symptomatology. To date,
none of the different attempts to find substitutes for language have been satisfactory.
Therefore, only non-speech dependent intellectual processes can be considered in this section.
There can be two attitudes to modeling intellectual processes when using model organisms of
intellectual deficiency. The first is to perform an exhaustive annotation of the cognitive
related traits that can be observed in the organism. This interesting approach provides
information about the phenotypes associated with a given gene or mutation. Schaevitz et al.
(2010), for example, screened various behavioral traits related to cognition in a mouse model

33
of Rett syndrome. Other studies have investigated ethological traits such as aggression
against a conspecific or ultrasound production. The results may be relevant in an annotation
perspective but not in a modeling approach. The second attitude, which will be adopted here
because it is better suited to the use of model organisms for diseases, consists in i) selecting
the traits that characterize the syndrome from clinical observations or from psychological
reports, and ii) creating conditions that could generate responses miming the traits in the
model organism.
Several strategies are available. The testing of model organisms of trisomy 21 has the
advantage of an abundance of publications on the syndrome. A general profile appears with
relative strength in associative tasks, difficulty in responding by new strategies to new
conditions, poor long-term memory and attention difficulties (see Roubertoux and Kerdelhué
2006; Roubertoux and Carlier 2009). The psychological profile deduced from clinical studies
has been used as framework for mouse models of trisomy 21 (Chabert et al. 2004). An
exhaustive review of the studies (Sérégaza et al. 2006; Roubertoux and Carlier, 2009) showed
that most of them attempted to adjust the model organism to the human profile. An
abundance of information on a syndrome is not enough to initiate work to develop a model
organism. Much is known on the psychological profile of patients with Williams-Beuren, but
little has been done on the development of mouse models.
The paper by Milner et al. (1998) that recalls the onset of cognitive psychology provides
another strategy for exploring the intellectual functions. The key point in the approach is to
validate every cognitive alteration by a specific brain structure dysfunction. Milner et al.
(1998) proposed two main types of memory, declarative and non-declarative, based on
distinct brain systems. Performance scores for separate memory categories can be measured
in rodents. Declarative aspects can be found (1) in the reduction in the number of freezing
episodes when the mouse is subjected to fear conditioning with changes in the context, (2) in

34
non-repeated visits of a reinforced arm in the radial maze, and (3) in reversal difficulties or
reduced time in a virtual quadrant in the Morris water maze. The variables are the ‘‘ability to
respond appropriately to stimuli through practice, as the result of conditioning or habit
learning’’ (Milner et al. 1998, p. 450). Non-declarative memory is comprised of three
categories: (1) procedural memory, i.e. the formation of habits and acquisition of skills –
reaching the platform under proximal cue conditions, (2) priming, and (3) associative, with
classical conditioning measured as output; this could be described as an emotional or skeletal
response. The modification of the performance when the conditioned stimulus is presented in
the fear conditioning protocol illustrates classical conditioning with emotional response,
whereas the operant schedule response illustrates classical conditioning with skeletal and
muscular response.
A third strategy consists in transposing a protocol developed for humans to model organisms.
The best known is the eyelid conditioning protocol used in psychiatric investigations and
which was transposed to mice (Chen et al. 1999). An original strategy is to transpose a rat or
mouse protocol to the human species, as was done by Foti et al. (2011) who created a radial
maze for children to measure spatial memory.
The wisest approach in defining homologous processes across the species is to consider a
transversal homology investigating the homology of the pathways between two levels of
biological organization.
4.5 Similar reactions to treatments
The translational approach aims ultimately at offering treatment of genetic diseases. Model
organism functions are seen as a means of providing preliminary screening of potentially
curing compounds. Positive results achieved with a model organism can then be the starting
point of a cure strategy for the clinician. Preliminary positive results are also required in

35
many countries to initiate the legal procedure for prescribing a treatment. There are a number
of examples of humans and mouse models having the same reaction to a treatment. The best
known is the reduction of anxiety induced by the benzodiazepine family, by 5-HT reuptake
inhibitors and by 5- HT 1a agonists. The effects work in the same direction in Humans, as
tested in clinical interviews, and in mice, tested in the elevated plus maze. Tuberous sclerosis
complex – or Bourneville disease - is a mammalian target of rapamycin (mTOR) over-
activation syndrome. Inhibition of mTOR in mice improves the neuronal and behavioral
characteristics in the mouse model (Aarts et al., 2010). de Vries (2010) reported that
“Molecularly-targeted treatments using mTOR inhibitors (such as rapamycin) are showing
great promise for the physical and neurological phenotype of TSC. Pre-clinical and early-
phase clinical studies of the cognitive and neurodevelopmental features of TSC suggest that
some of the neuropsychiatric phenotypes might also be reversible, even in adults with the
disorder.” Partially identical results have been reported with immunization treatment for
Alzheimer disease in a mouse model and patients. Schenk et al. (1999) developed a mouse
model of Alzheimer disease presenting an overproduction of the predominant form found in
the amyloid plaques of Alzheimer disease, the 42-amino-acid form of the peptide (Abeta42).
Mice immunized with Abeta42 at 6 weeks of age showed an improvement in learning and a
reduction of the beta-amyloid-plaque formation. Aβ peptide immunotherapy approach in
patients is associated with clearance of the beta-amyloid-plaque but it does not improve
cognitive performance. Moreover undesirable effects accompany the administration of the
selected molecules used in Aβ peptide immunotherapy (Delrieu et al. 2011).
5. Conclusion and perspectives. Genes involved in rare genetic diseases and gene
contributing to the normal range of variation.
A noticeable field of the Behavior-genetic analysis is deciphering the genetic mechanisms

36
underlying the non-pathological range of variation. Does understanding the genetic
mechanisms of cognitive dysfunction may help understanding the genetic mechanisms
contributing to cognitive differences within the normal range of variation?
The specificity of the pathological processes, and particularly the development of
compensatory processes associated with a punctual mutation, has been defended by the
opponents to the pathological method. Things have changed with the possibility to target
genes or parts of genes. We use daily pathological genetic events for understanding the non-
pathological variation in experimental animal genetics. What is a targeted gene? It is an
abnormality. We use the different annotations resulting from the observation of the disturbed
mouse to predict the genes involved in the non-pathological range of variation. The human
geneticists can adopt a similar strategy as long as they do not forget the developmental
processes. Most of the genetic events contributing to the identification of genetic disorders of
cognition are due to mutations generating truncated proteins or silent proteins. Fragile-X
syndrome is a “natural knock out” occurring in our species. It is equivalent to the
“experimental knock out” produced in the Mouse. We can thus use the results obtained with
genetic disorders to infer the function of genes contributing to non-pathological variation.
Mutations in nicotinic receptor A7 (CHRNA7), dopamine receptor 4 (DRD4) and dopamine
transporter (DAT1) that induce severe cognitive dysfunctions may contribute to quantitative
differences in attention. Catecholamin-O-methyltransferase (COMT) is associated with
several brain pathologies but some well-identified allelic forms modulate episodic memory in
the non-pathological population. We do not defend the idea that all the genes contributing to
individual differences in normal variation can be found by the study of rare genetic disorders
but genetic events at work within the normal range of variation and the rare cognitive
disorders overlap.

37
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Table 1. Disability type by gender and age for children and youths with disabilities (% of the
population) – From Disability in Canada: a 2006 profile.
Disability type
Ages
Children
Youths
Under 5 years
(Overall: 1.7)
5 to 14
(Overall: 4.6)
15-19
(Overall: 4.6)
Boys
Girls
Boys
Girls
Boys
Girls
Chronic condition
1.4
0.9
3.8
2.2
-
-
Developmental
1.3
0.8
1.9
0.9
1.4
0.8
Hearing
0.2
0.2
0.6
0.4
0.5
0.5
Seeing
0.2
0.2
0.5
0.3
0.5
0.6
Communication
-
-
2.8
1.3
1.6
1.1
Emotional/psychological
-
-
2.1
1.0
0.8
1.1
Learning
-
-
4.1
2.2
3.3
2.1
Agility
-
-
1.3
0.6
1.3
1.4
Mobility
-
-
0.6
0.6
1.6
1.8
Memory
1.1
0.7
Pain
1.6
2.5

56
Other
-
-
0.2
0.2
2.2
2.3
Note: More than one disability type could be identified for each survey respondent. The
numbers of specific disability types differed depending on the survey respondent’s age (from
4 to 11).

57
Table+2.++Neuronal+and+behavioural+phenotypes+associated+with+four+genetic+diseases+
Characteristics+
Syndrome
Trisomy+21+
(Down)+
WilliamsJBeuren+
Fragile+X++
Di+
George/veloJ
cardio+facial++
Neuronal+
Reduced+brain+
volume;+
reduced+frontal+
and+temporal+
lobes;+major+
reduction+of+
hippocampus
Reduced+brain+
volume;+
anomalous+sulcal+
patterning;+
primary+dorsal+
stream+
impairment
Enlarged+
caudate+
nucleus+and+
thalamus;+
decreased+
volume+of+
cerebellar+
vermis,+
amygdala+and+
surperior+
temporal+
gyrus
Specific+
anomalies+are+
uncommon;+
reduction+of+
cerebral+white+
matter;+
disturbance+of+
the+GABAergic+
nervous+
system?
IQ+(mean)+
<+50
60J70+
Boys:+<+55++
Higher+in+girls+
About+75
Language++
Seriously+
impaired+
Relatively+strong+
Relatively+
strong+
Preserved

58
Spatial+
cognition++
Relative+
strength+
Seriously+
impaired+
Impaired+
Impaired
Behavioural+or+
psychiatric+
disorders++
Behavioural+
problems+
Hypersensitivity+
to+sound,+
attention+deficit+
disorder+
AutisticJtype+
behaviour,+
hyperactivity+
Psychiatric+
disorders+
Schizophrenia+
Personality+
Loving+
Hypersociability+
Anxiety+
Shyness+