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. Author manuscript; available in PMC: 2015 Oct 8.

Identification of Expanded Alleles of theFMR1 Gene in the CHildhood Autism Risks from Genes and Environment (CHARGE) Study

Flora Tassone1,✉,Nimrah S Choudhary2,Federica Tassone3,4,Blythe Durbin-Johnson5,Robin Hansen6,7,Irva Hertz-Picciotto8,9,10,Isaac Pessah11,12,13,✉
1Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, 2700 Stockton Blvd, Suite 2102, Sacramento, CA 95817, USA
2Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, 2700 Stockton Blvd, Suite 2102, Sacramento, CA 95817, USA
3Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, 2700 Stockton Blvd, Suite 2102, Sacramento, CA 95817, USA
4MIND Institute, University of California Davis Health System, Sacramento, CA, USA
5Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, CA, USA
6MIND Institute, University of California Davis Health System, Sacramento, CA, USA
7Department of Pediatrics, School of Medicine, University of California, Davis, Sacramento, CA, USA
8MIND Institute, University of California Davis Health System, Sacramento, CA, USA
9Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, CA, USA
10UC Davis Center for Children’s Environmental Health and Disease Prevention, University of California, Davis, Davis, CA, USA
11MIND Institute, University of California Davis Health System, Sacramento, CA, USA
12UC Davis Center for Children’s Environmental Health and Disease Prevention, University of California, Davis, Davis, CA, USA
13Department of Molecular Biosciences, School of Veterinary Medicine, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
✉

Corresponding author.

PMCID: PMC4596818  NIHMSID: NIHMS725797  PMID:22767137
The publisher's version of this article is available atJ Autism Dev Disord

Abstract

Fragile X syndrome (FXS) is a neuro-developmental disorder characterized by intellectual disabilities and autism spectrum disorders (ASD). Expansion of a CGG trinucleotide repeat (>200 repeats) in the 5′UTR of the fragile X mental retardation gene, is the single most prevalent cause of cognitive disabilities. Several screening studies for FXS, among individuals with ID from different ethnic populations, have indicated that the prevalence of the syndrome varies between 0.5 and 16 %. Because the high co-morbidity with autism, we have conducted a screening study of the cohort from CHARGE, a large-scale, population-based, case control study. We have identified six subjects carrying an expanded allele, which emphasize the importance of screening for FXS in a population with intellectual disabilities and ASD.

Keywords: Autism spectrum disorder, Developmental delay, Fragile X, Premutation, Screening, CGG

Introduction

Fragile X syndrome (FXS) is the most common inherited cause of intellectual disabilities (ID), and the most common single gene mutation associated with autism (AUT). It is caused by a trinucleotide repeat expansion (CGG)n in the 5′ untranslated region of the fragile X mental retardation 1 (FMR1) gene, located atXq27.3. The full mutation, present in individuals with more than 200 CGG repeats, typically involves methylation, subsequent transcriptional silencing of theFMR1 gene, and lack of theFMR1 protein, FMRP (Fu et al. 1991;Pieretti et al. 1991;Verkerk et al. 1991;Yu et al. 1991).

Although FXS is associated with a characteristic phenotype, there is considerable variation in the severity of clinical presentation and the cadre of cognitive, motor and behavioral impairments, and dysmorphology displayed. Moreover, AUT is frequently co-morbid with FXS, with estimates ranging up to 30 % of FXS patients displaying autism spectrum disorders (ASD), and an additional 30 % of affected patients receiving a diagnosis of pervasive developmental disorder-not otherwise specified, more commonly known by its acronym PDD-NOS (Hagerman 2002;Harris et al. 2008;Rogers et al. 2001).

Individuals with anFMR1 premutation have an allele with 55–200 CGG repeats that is typically unmethylated, which usually does not result in gene inactivation. They also present with a spectrum of phenotypes including developmental delay, autism spectrum disorder, attention deficit/hyperactivity disorder (ADHD), and behavior problems (Aziz et al. 2003;Bailey et al. 2008;Clifford et al. 2007;Farzin et al. 2006;Loesch et al. 2007). Individuals with FXS + AUT appear more cognitively impaired, especially so in scores on the social and communication domains than in domains of restricted interests and repetitive behaviors. Medical problems that affect the central nervous system, including seizures, malformations, or other genetic disorders, seem more likely to occur in those individuals presenting with both FXS and ASD compared to those with FXS alone (Garcia-Nonell et al. 2008). Furthermore, the diagnosis of ASD in FXS could be related to other genetic and/or environmental factors leading to brain dysfunction additive to theFMR1 mutation (Loesch et al. 2007). However, the reason ASD occurs only in a subgroup of individuals with FXS is not known (Loesch et al. 2007). One proximal mechanism contributing to ASD risk in FXS is the loss of theFMR1 protein (FMRP) (Hagerman et al. 2008). Indeed, recent reports indicate that FMRP may be deficient in other disorders including autism not associated with FXS (Fatemi and Folsom 2011), schizophrenia, bipolar disorder, and even depression (Fatemi et al. 2010). Finally, many studies over the past 25 years have documented the higher incidence of ASD in subjects with FXS (Reddy 2005).

Thus, because the of high co-morbidity with autism, we have conducted a screening for expanded alleles of theFMR1 gene in a cohort from CHARGE (CHildhood Autism Risks from Genes and Environment), a comprehensive, ongoing, population-based case–control investigation that is sampled from three strata: children with autism, children with developmental delay but not autism, and general population controls (Hertz-Picciotto et al. 2006). We have determined theFMR1 CGG size distribution in four groups and examined the association with IQ (Vineland and Mullen test scores); in this study, these groups were divided into the neurotypical control group (typical development, TD; n = 346), the developmental delay group without AUT/ASD (DD, n = 152), the autism spectrum disorders group (ASD, n = 144), and the full autism syndrome group (AUT, n = 313).

No expanded alleles were identified in the TD group. However, of the 457 children aged 2–5 years with confirmed diagnosis of AUT or ASD, we identified two subjects (0.4 %) with full mutation allele, in line with previous prevalence reports (Reddy 2005). Two individuals carrying a premutation allele and two others with a full mutation allele were identified in the DD group (1.4 %).

In addition, we have investigated if there was a difference in the location and in the number of AGG interruptions within eachFMR1 allele among the diagnostic groups. Within the CGG repeats, interspersions of one to three AGG “anchors” are commonly found in normal, intermediate, and premutation range alleles and generally occur after 9 or 10 uninterrupted CGG repeats, with a pattern of [(CGG)9AGG(CGG)9AGG(CGG)n]. These AGG interruptions can be stably inherited, such that the number of AGG interruptions and their position is likely to correspond in parent and offspring; however, like the length of CGG-repeat tracts inFMR1, there is a level of instability, such as the loss of an interruption during transmission (Dombrowski et al. 2002). Although the presence of AGGs does not influence the transcriptional level of theFMR1 gene, (Yrigollen et al. 2011) they significantly increase genetic stability by reducing the risk of transmission of a full mutation for all maternal premutation repeat lengths below ~100 CGG repeats (Yrigollen et al. 2012). No differences were observed for both distribution and number of CGG interruptions among the TD, AUT, ASD and DD groups.

Our findings confirm the importance of screening for FXS, individuals with ASD and ID.

Materials and Methods

Subjects

Participants in this study were part of the CHARGE (CHildhood Autism Risks from Genetics and the Environment) study, with includes children from the following groups: children with autism, children with developmental delay but not autism, and general population controls (Hertz-Picciotto et al. 2006). Children with AUT or with other developmental delays were identified through the California Department of Developmental Services (DDS), which provides services regardless of socioeconomic level, citizenship, or racial/ethnic group. Children from the general population were identified in the state birth files and matched to the autism cases on age, sex, and broad geographic area. Children were between the ages of 24 and 60 months and born in California. Children meeting the recruitment criteria (Hertz-Picciotto et al. 2006) were seen at the MIND Institute in Sacramento, California; medical history was collected, and a battery of tests and a physical examination were performed. There were no exclusions for any known genetic or chromosomal disorders; however these were noted in the medical assessment. The only developmentally-related exclusions were for those with serious disabilities that would impede our ability to obtain valid scores on the developmental tests used, e.g., blindness, deafness, or serious motor disability.

Through clinical assessment (see below), diagnosis of AUT, ASD, DD and TD were confirmed. For molecular analysis 313 children with AUT, 144 children with ASD, 152 children with DD, and 346 TD children (Hertz-Picciotto et al. 2006) were screened by PCR. The male to female ratio was 6:1 in children with AUT/ASD (394 males, 63 females) and 3:1 in TDs (262 males, 84 females).

The distribution of ages was similar among diagnoses, with a mean age of 42 months in TD subjects (range 24–61 months), 46 months in ASD subjects (range 26–72 months), 45 months in AUT subjects (range 15–69 months), and 46 months in DD subjects (range 26–61 months).

Clinical Assessment and Assignment of Diagnostic Groups

For all participants, we collected a detailed medical history and conducted a medical examination. All children were also administered tests of IQ and adaptive skills using the Mullen Scales of Early Learning (MSEL) (Mullen 1995) and the Vineland Adaptive Behavior Scales (VABS) (Sparrow et al. 1984). The TD group consisted of children from the general population who scored 70 or above on both MSEL and VABS, and below 15 on the social communication questionnaire. The diagnosis of autism was confirmed using the standardized autism measures: the Autism Diagnostic Interview-Revised (ADI-R) (Lord et al. 1994) given to the primary caregiver, and through direct assessment of the child using the Autism Diagnostic Observation Schedules (Lord et al. 2000). The onset of ASD was also assessed by ADI-R and regression was considered to have occurred if the primary caregiver responded that the child had lost either language (ADI-R question 11 = 1)and/or social skills (ADI-R question 25 ≥1). Children that did not meet these criteria were included in the “non-regressive” group. A full autism diagnosis was defined as meeting criteria on the communication, social interaction, and repetitive behavior domains of the ADI-R with onset prior to 36 months, and scoring at or above the social + communication cutoff for autism on the ADOS module 1 or 2. Children were defined as having ASD if they did not meet full criteria for autism on either or both the ADI-R and ADOS, but did meet criteria on either the communication or the social interaction domain of the ADI-R prior to 36 months, were within two points of the cut-off on the other domain, and were above the social + communication cutoff for ASD on the ADOS module 1 or 2. Parents of children with other developmental delays and those from the general population completed the Social Communication Questionnaire (Rutter et al. 2003) to screen for ASD. Those who screened positive (at or above a score of 16) were then assessed using both the ADOS and ADI-R; children who met criteria for AUT or ASD were then included in the corresponding diagnostic group, regardless of the group from which they were initially recruited. Eleven TD subjects were re-classified as DD, 13 DD subjects were reclassified as ASD, and 16 as AUT.

Molecular Measures

Genomic DNA Isolation

DNA was extracted from 0.5 to 1.5 ml of the cellular fraction of anticoagulated blood collected from children with AUT (n = 313), ASD (n = 144), DD (n = 152), and TD (n = 346). DNA isolation was carried out according to standard procedure (Qiagen, Valencia, CA, USA).

FMR1 Genotyping

FMR1 allele size was determined by PCR amplification using a combination of anFMR1-specific PCR and a two-tier PCR approach as previously described (Chen et al. 2010;Filipovic-Sadic et al. 2010;Tassone et al. 2008). Briefly, samples from males that did not yield a product and females that yielded only one band (amplicon) after theFMR1-specific PCR underwent a second PCR screening using the CGG linker primer. Conditions were as detailed previously inChen et al. (2010) andFilipovic-Sadic et al. (2010). PCR products were stored at 4 °C prior to electrophoresis analyses. PCR products were sized and analyzed using capillary electrophoresis (Applied Biosystems, Foster City, CA, USA). In this study, according to the guidelines of the American College of Medical Genetics (Maddalena et al. 2001),FMR1 alleles were classified as normal (TD; <45 CGG repeats), gray zone (GZ; 45–54 CGG repeats), premutation (pre CGG; 55–200 CGG repeats), and full mutation (FXS; 200 CGG repeats).

Number and Location of the AGGs

The presence and location of AGG interruptions was determined by PCR using a CGG chimeric primer (CCG)5 that, when it anneals to the CGG tract, amplifies intermediate fragments of variable length. Because the chimeric primer is unable to anneal to a CGG tract containing an AGG interruption, mapping of the AGGs by identification of a corresponding absence of PCR product, as visualized by capillary electrophoresis, is possible. The position of the AGGs within each allele was determined from raw Gene-scan files imported into Peakscanner software (v1.0) (Applied Biosystems, Foster City, CA, USA). Details of the methodology are reported inYrigollen et al. (2011).

Statistical Analysis

A total of 955 samples were screened for the presence of anFMR1 expanded allele. Six subjects identified with an expanded allele (four with FXS, two AUT and two DD; and two premutations, both DD) were excluded from analyses of CGG-repeat size distribution and number of AGG interruptions. Four male subjects (two AUT, two DD) showed two bands (corresponding to two alleles) using two different sets of primers and were not analyzed further. Although we cannot completely exclude that some of these samples may have been mislabeled with respect to the gender, it is also possible that some could have been samples from Klinefelter subjects (XXY). After these exclusions, data from 945 participants remained for the statistical analysis: 346 TD (262 males, 84 females), 309 AUT (270 males, 39 females), 144 ASD (121 males, 23 females), and 146 DD (95 males, 51 females). The mean total CGG length was compared across all four diagnosis categories, and between the AUT and ASD groups pooled versus subjects with TD, using one-way analysis of variance (ANOVA) models; CGG length was used as the response, and diagnosis as the independent variable. Chi-square tests were used to look for an association between diagnosis and number of AGG interruptions. Fisher’s exact test was used to compare the proportion of GZ alleles between AUT/ASD and TD groups.

Results

According to our workflow, only DNA samples from male subjects that do not yield a band (no amplified allele obtained) after the first round of PCR with primers c and f (FMR1-specific PCR), and DNA samples from female subjects that yield only one band (one allele) are usually subjected to a second PCR round using the CGG primer-based PCR methodology (Chen et al. 2010;Filipovic-Sadic et al. 2010;Tassone et al. 2008). However, as the use of the CGG primer allows for the detection and characterization of the AGG interruptions (location and number) within eachFMR1 allele on capillary electrophoresis, all samples underwent the second PCR round using the CGG primer as previously described (Yrigollen et al. 2011). Six subjects carrying anFMR1 expanded allele were identified (seeFig. 1): one male and one female with an expanded allele in the full mutation range (FXS; >200 CGG repeats) in the AUT group, and two full mutation males in the DD group. One pre CGG male and one pre CGG female (55–200 CGG repeats) were also identified in the DD group. Allele size was determined for all subjects, and the summary statistics for total CGG length (mean, median, standard deviation, and range) was calculated for subjects with alleles in the normal or intermediate range in each diagnosis group (Table 1).

Fig. 1.

Fig. 1

Capillary electrophoresis (CE) analysis showing the presence of an expandedFMR1 allele in a DD male (a andb), in an autism female (c), and in an autism male (d). Two premutation alleles were also identified in the DD group (1 female,e; 1 male,f). Thex-axis indicates the number of base pairs and they-axis indicates relative fluorescence intensity

Table 1.

CGG repeat number by diagnosisa

DiagnosisMean (SD)Median (Range)
Typical development (n = 346)30.0 (4.3)30 (17–50)
Autism (n = 309)30.1 (4.9)30 (17–50)
ASD (n = 144)29.6 (4.8)30 (13–48)
Developmental delayed (n = 146)29.8 (4.6)30 (15–46)
Autism/ASD pooled (n = 453)29.9 (4.8)30 (13–50)
a

Expanded alleles or males with 2 alleles not included in summaries

Alleles in the GZ range were identified in five females (two ASD/AUT; two TD; one DD) and six male carriers (five ASD/AUT; one TD). The observed frequency of GZ alleles in subjects in this sample with AUT/ASD was 3.2 % in females (95 % CI 0.9 %, 11.0 %) and 1.3 % in males (95 % CI 0.5 %, 2.9 %). The observed frequency of GZ alleles in TD subjects in this sample was 2.4 % in females (95 %CI 0.7 %, 8.3 %) and 0.4 % in males (95 %CI 0.0 %, 2.1 %). No statistical significant difference was observed between the frequency of GZ alleles in the AUT/ASD group compared to TD subjects in females (Fisher’s exact testp > 0.99) or in males (Fisher’s exact testp = 0.41).

For purposes of comparison, we used the GZ allele frequencies observed in a newborn screening pilot study ongoing in California (Iong et al. 2011). Specifically, a GZ allele frequency of 1.4 % was observed in a sample of 6,013 newborn females from the general population and a GZ allele of 0.7 % was observed in a sample of 6,441 newborn males from the general population. While the observed frequency of GZ alleles in AUT/ASD subjects in this study sample is numerically higher than the frequencies observed for males and females in the newborn screening sample, GZ allele frequencies in AUT/ASD males and females in this study do not significantly differ from the observed newborn screening frequencies. The frequency of GZ alleles observed in the DD subjects in this study was 2.0 % in females (95 % CI 0.1 %, 10.3 %) and 0 % in males (95 % CI 0 %, 3.8 %), which did not differ significantly compared to the TD subjects in either females or males (Fisher’s exact testp > 0.99 in both cases). Lack of significance was also obtained when the frequency of the GZ alleles in the DD group was compared to those observed in the newborn screening subjects. The CGG-repeat length distribution was also measured and means were found not to differ significantly among the four groups (F (3, 941) = 0.32,p = 0.81). Full mutation (n = 4) and premutation (n = 2) alleles were excluded from the analysis. Allele size distribution is shown inFig. 2 by diagnosis. The data show similar distributions within each diagnosis group. In addition, no significant difference between groups in total CGG-repeat length was observed when the AUT and ASD groups were pooled together (F (1, 797) = 0.003,p = 0.96).

Fig. 2.

Fig. 2

Boxplots of CGG-repeat number by diagnosis. Thesolid lines inside eachbox represent the medians in each diagnosis group, thelower andupper edges of eachbox represent the 25th and 75th percentiles in each group, respectively; the lower and upper ‘whiskers’ represent the smallest and largest observations, respectively, that lie within 1.5 times the interquartile range away from the edges of each box. Outlying observations are indicated with acircle

We also determined the distribution of the number of AGG interruptions in the four diagnostic groups. No significant difference in the distribution and numbers of AGG interruptions between diagnoses was observed (Table 2) either when all four diagnoses were included separately, c2 (9, N = 945) = 5.35,p = 0.80, or when the AUT/ASD groups were pooled and the DD group was excluded, c2 (3, N = 799) = 1.63,p = 0.65. No differences in either the mean CGG size or in the number and location of the AGG interruptions were detected between the regressive and non-regressive AUT/ASD groups.

Table 2.

Number of AGG interruptions by diagnosis

0 interruptions1 interruption2 interruptions3 or 4 interruptions
Typical development (n = 346)11 (3 %)72 (21 %)256 (74 %)7 (2 %)
Autism (n = 309)6 (2 %)68 (22 %)225 (73 %)10 (3 %)
ASD (n = 144)5 (3 %)34 (24 %)101 (70 %)4 (3 %)
Developmental delayed (n = 146)7 (5 %)31 (21 %)102 (70 %)6 (4 %)

The association of IQ with CGG-repeat number was investigated in the three groups (AUT, ASD and DD). Both Vineland and Mullen test scores were regressed on total CGG length using data from patients with the ASD, AUT, and DD diagnoses, and TD. The estimated change in Vineland test score for each additional repeat was b = 0.01, 95 % confidence interval (−0.31, 0.34), t (914) = 0.08,p = 0.94 (Supplemental Fig. 1). The estimated change in Mullen test score for each additional repeat was b = 0.11, 95 % confidence interval (−0.27, 0.50), t (914) = 0.58,p = 0.56. (Supplemental Fig. 2). Models were also fitted separately for each diagnosis group; conclusions were the same as when the AUT and ASD diagnosis categories were combined.

Discussion

FXS is an X-linked disorder characterized by intellectual disability, and behavioral and physical features (Hagerman 2002); and is caused by a CGG trinucleotide expansion in the 5′UTR of theFMR1 gene. Behavioral features present in both males and females with FXS can also include impairments in social interaction and communication, social anxiety, gaze avoidance, hand and finger mannerisms, and repetitive and stereotypic behavior (Hagerman 2002;Lachiewicz and Dawson 1994;Miller et al. 1999;Sudhalter et al. 1990), typical of autism.

Studies assessing the prevalence of autism among subjects with FXS range from 5 to 60 % depending on the diagnostic criteria used (Hagerman 2002;Harris et al. 2008;Rogers et al. 2001), but it is lower in females with FXS (Bailey et al. 1993;Hagerman 2002). Several studies have also been carried out in different populations of subjects including ID, AUT, or those with special educational needs, to both assess the prevalence of FXS among these populations and to identify subjects with FXS, which is very important for families. In the above studies, using both cytogenetic and molecular approaches, the full mutation rate varies between 0.5 and 16 % and the premutation rate varies between 0 and 0.8 % (Biancalana et al. 2004;Blomquist et al. 1985;Brown et al. 1986;de Vries et al. 1998;de Vries et al. 1997;Hecimovic et al. 2002;Major et al. 2003;Mazzocco et al. 1997;Mila et al. 1997;Pandey et al. 2002;Patsalis et al. 1999;Pouya et al. 2009;Reddy 2005;Schaefer and Lutz 2006;Sharma et al. 2001;Syrrou et al. 1998;Watson et al. 1984;Yuhas et al. 2009). A multicenter study conducted in Sweden (Blomquist et al. 1985) found FXS in 16 % of boys with infantile autism, and a multicenter survey among individuals with autism found 13 % were positive for FXS (Brown et al. 1986).Bailey et al. (1993) determined the prevalence of FXS among males and females with autism in three groups, 45 pairs of twins, 2 sets of triplets, and clinical control samples, and found FXS mutations in 1.6 % of the individuals with autism in the twin and clinical sample sets, with a similar prevalence in both sexes. The variation of the incidence among these studies and many others (also reviewed in (Reddy 2005)) are likely due to different clinical criteria utilized for the definition of positive cases, and to different sample sizes. Thus, although the prevalence of FXS among individuals with ASD differs between these studies and samples, strong evidence points toward an association between ASD and FXS. However, the underlying cause of this co-morbidity is unknown.

We screened the CHARGE study for FXS and identified six subjects with an expandedFMR1 allele, suggesting that the presence of an expansion of the trinucleotide repeats within theFMR1 gene could account for the etiology of the developmental delay in these children. Two individuals with a premutation allele were also identified.

The premutation alleles are common in the general population with a prevalence of approximately 1 in 113–259 females (0.3–0.8 %) and 1 in 251–813 males (0.1–0.3 %) (Dombrowski et al. 2002;Fernandez-Carvajal et al. 2009;Rousseau et al. 1995;Toledano-Alhadef et al. 2001). Individuals with the premutation can present with a range of clinical involvement including fragile X-associated primary ovarian insufficiency (FXPOI) (Cronister et al. 1991;Sullivan et al. 2005;Wittenberger et al. 2007) and fragile X-associated tremor/ataxia syndrome (FXTAS) (Hagerman et al. 2001;Jacquemont et al. 2003), in addition to emotional problems—particularly depression and anxiety (Bourgeois et al. 2009;Hessl et al. 2005;Roberts et al. 2009). Furthermore, ASD and ADHD have been found to be significantly more prevalent in boys with the premutation who presented clinically as probands, compared with their non-probandbrothers and with their brothers without the premutation (Aziz et al. 2003;Bailey et al. 2008;Chonchaiya et al. 2012;Farzin et al. 2006). Causes of these neurodevelopmental and behavioral problems need to be further investigated to better understand the nature of such problems, and to possibly develop targeted treatments for those with the premutation.

Interestingly, we have identified five female (2 ASD/AUT, 2 TD, 1 DD) and six male carriers (5 ASD/AU, 1TD) of a GZ allele with a twofold higher frequency in AUT/ASD subjects that in the general population. Understanding the phenotypic effects of small CGG-repeat alleles of theFMR1 gene is of great importance considering the bridging position between the pathogenic premutation and the normal allele categories. Indeed, GZ alleles are considered quite unstable and both abnormal molecular and clinical phenotypes have been recently reported, including a higher frequency of GZ among females with premature ovarian failure (Bodega et al. 2006;Bretherick et al. 2005;Haddad et al. 1999;Hall et al. 2011;Loesch et al. 2009;Murray et al. 1996;Sherman 2000;Sullivan et al. 2002), and among females with parkinsonism. In addition, a recent study reported on four subjects, carriers of a gray-zone allele, with symptoms of the late-onset neurodegenerative disorder, fragile X-associated tremor/ataxia syndrome (Hall et al. 2011).

Clinical involvement is observed in premutation carriers and caused by an RNA toxic gain-of-function due to increasedFMR1 mRNA levels observed in subjects with an allele in this repeat range (Tassone et al. 2000). IncreasedFMR1 mRNA levels have also been detected in individuals with GZ alleles; therefore, it is possible that RNA toxicity occurs in smaller expanded alleles, though to a lesser degree (Loesch et al. 2007). Since the frequency of gray-zone alleles in the general population is quite frequent (~1 %) (Iong et al. 2011), even modest deleterious contributions, if substantiated, are likely to be borne by a large number of people.

In conclusion, this study screened a population of young children recruited for participation in the CHARGE study, including subjects with confirmed diagnoses of ASD, AUT, and DD, and determined the prevalence ofFMR1 expanded alleles; the results correlate with similar findings reported from previous studies. The identification of six individuals with an expandedFMR1 allele in this study population confirms and suggests the role played by theFMR1 gene in the etiology of developmental delay in children. Detailed characterization of the molecular variation of theFMR1 gene within the CHARGE cohort demonstrates that both CGG-repeat size distribution and AGG interruptions are equally dispersed in the ASD and DD groups, and therefore do not appear to play a distinctively different role in the physiopathology of ASD versus that of ID. The findings further demonstrate the importance of the FXS DNA screening test in individuals with ID and ASD, which should be strongly encouraged to rule out FXS as well as to reveal potential causes of intellectual disabilities. As several studies have demonstrated that children with FXS and autism have poorer outcomes than children with only FXS or only autism (Bailey et al. 2000,2001;Hatton et al. 2000,2006;Kau et al. 2004;Lewis et al. 2006;Rogers et al. 2001), and because early intervention can improve outcomes for young children with autism (National Research Council 2001), it is very important that young children with FXS and autism be identified as early as possible.

In future studies using the CHARGE cohort, it is important to consider theFMR1 status reported in the present study. As mentioned earlier, children with FXS and autism are at a greater disadvantage than children with only FXS or only autism, thus young children with FXS and autism need to be identified as soon as possible so early intervention can improve outcomes.

Supplementary Material

1
2

Acknowledgments

A particular thanks to the families participating in the CHARGE study. This work was supported by the National Institutes of Health [HD02274], matching funds for the CHARGE study, and by R01-ES015359, P01ES011269 from the National Institute of Environmental Health Sciences and Award Numbers R833292 and R829388 from the Environmental Protection Agency. The project described was also supported by the National Center for Research Resources, National lnstitutes of Health, through grant #UL1 RR024146. This work is dedicated to the memory of Matteo.

Footnotes

Electronic supplementary material The online version of this article (doi:10.1007/s10803-012-1580-2) contains supplementary material, which is available to authorized users.

Contributor Information

Flora Tassone, Email: ftassone@ucdavis.edu, Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, 2700 Stockton Blvd, Suite 2102, Sacramento, CA 95817, USA.

Nimrah S. Choudhary, Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, 2700 Stockton Blvd, Suite 2102, Sacramento, CA 95817, USA

Federica Tassone, Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, 2700 Stockton Blvd, Suite 2102, Sacramento, CA 95817, USA; MIND Institute, University of California Davis Health System, Sacramento, CA, USA.

Blythe Durbin-Johnson, Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, CA, USA.

Robin Hansen, MIND Institute, University of California Davis Health System, Sacramento, CA, USA; Department of Pediatrics, School of Medicine, University of California, Davis, Sacramento, CA, USA.

Irva Hertz-Picciotto, MIND Institute, University of California Davis Health System, Sacramento, CA, USA; Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, CA, USA; UC Davis Center for Children’s Environmental Health and Disease Prevention, University of California, Davis, Davis, CA, USA.

Isaac Pessah, Email: inpessah@ucdavis.edu, MIND Institute, University of California Davis Health System, Sacramento, CA, USA; UC Davis Center for Children’s Environmental Health and Disease Prevention, University of California, Davis, Davis, CA, USA; Department of Molecular Biosciences, School of Veterinary Medicine, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA.

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