Global increases in both common and rare copy
number load associated with autism
Santhosh Girirajan1,2,3,∗, Rebecca L. Johnson4,5, Flora Tassone6,8, Jorune Balciuniene4,5,10,
Neerja Katiyar2, Keolu Fox1, Carl Baker1, Abhinaya Srikanth2, Kian Hui Yeoh2, Su Jen Khoo2,
Therese B. Nauth4,5, Robin Hansen6,7, Marylyn Ritchie2, Irva Hertz-Picciotto6, Evan E. Eichler1,
Isaac N. Pessah6,9and Scott B. Selleck2,4,5,∗
1Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA,
2Department of Biochemistry and Molecular Biology and3Department of Anthropology, The Pennsylvania State
University, University Park, PA 16802, USA,4The Developmental Biology Center, Department of Genetics,
Cell Biology and Development and5Department of Pediatrics, University of Minnesota, Minneapolis, MN 55455, USA,
6The MIND (Medical Investigation of Neurodevelopmental Disorders) Institute and7Department of Pediatrics, Davis
School of Medicine, University of California, Sacramento, CA 95817, USA,8Department of Biochemistry and
Molecular Medicine and9Department of Molecular Biosciences, School of Veterinary Medicine, University of California
Davis, Davis, CA 95616, USA and10Department of Biology, Temple University, Philadelphia, PA 19122, USA
Received February 4, 2013; Revised and Accepted March 20, 2013
load of deletions or duplications, per se, and their size, location and relationship to clinical manifestations of
autism have not been documented. We examined CNV data from 516 individuals with autism or typical develop-
ment from the population-based Childhood Autism Risks from Genetics and Environment (CHARGE) study. We
interrogated120regionsflankedbysegmentalduplications(genomichotspots)forevents >50 kbpandtheentire
genomic backbone for variants >300 kbp using a custom targeted DNA microarray. This analysis was comple-
mented by a separate study of five highly dynamic hotspotsassociated with autism or developmental delay syn-
dromes, using a finely tiled array platform (>1 kbp) in 142 children matched for gender and ethnicity. In both
studies, a significant increase in the number of base pairs of duplication, but not deletion, was associated
with autism. Significantly elevated levels of CNV load remained after the removal of rare and likely pathogenic
events. Further, the entire CNV load detected with the finely tiled array was contributed by common variants.
The impact of this variation was assessed by examining the correlation of clinical outcomes with CNV load.
The level of personal and social skills, measured by Vineland Adaptive Behavior Scales, negatively correlated
(Spearman’s r 5 20.13, P 5 0.034) with the duplication CNV load for the affected children; the strongest associ-
ation was found for communication (P 5 0.048) and socialization (P 5 0.022) scores. We propose that CNV load,
predominantly increased genomic base pairs of duplication, predisposes to autism.
With the rapidly evolving tools of modern genomics, investi-
gators have sought to understand the genetic contributors
to neurobehavioral and psychiatric disorders. Autism has
received considerable attention on account of the high levels
of heritability measured from twin studies as well as the docu-
mented increasing prevalence. Recent studies on copy number
∗To whom correspondence should be addressed at: 206 Life Sciences Building, Pennsylvania State University, University Park, PA 16802, USA.
Email: email@example.com (S.B.S.); 205A Life Sciences Building, Pennsylvania State University, University Park, PA 16802, USA. Email: sxg47@
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Human Molecular Genetics, 2013, Vol. 22, No. 14
Advance Access published on March 27, 2013
variants (CNVs) have suggested that rare, large events contrib-
ute significantly to autism risk and are found at very low or
negligible frequencies in control groups, allowing a statistical-
ly significant association for individual variants with disease
(1). This strategy has successfully identified an ever-growing
list of distinct CNVs that confer a significant risk for autism
and has revealed a large number of genes or genomic loci
that can affect autism susceptibility. Exome sequencing
studies have also identified several non-recurrent de novo
single-nucleotide variants in simplex autism families (2–4).
Several important themes have emerged from these recent
genetic studies on autism. First, the number of genes or
genomic loci contributing to autism susceptibility is large,
now estimated in the hundreds. A recent genome-wide copy
number variation analysis projected between 156 and 280
genomic intervals contributing to autism and exome sequen-
cing of over 900 individuals provided an estimate of nearly
1000 contributing genes (2–5). It is evident that the ‘genetic
target’ contributing toward autism is large and the gene dis-
covery process is still ongoing. Second, the contribution of
common variants to autism, at present measured principally
as single-nucleotide polymorphisms (SNPs), is modest,
making it difficult to use these genetic variants for predicting
clinical outcomes (6,7).
While the degree of heritability for autism is still debated,
the estimates from the largest twin studies place it at 38–
60% of the variance (8,9). The entire catalog of rare deletions
and duplications to date accounts for perhaps 5–10% of clin-
ical cases (10–12), a significant level, but still far short of the
level of heritability estimated from twin studies (13). Although
some of the missing heritability may reside in gene-by-
environment and gene-by-gene interactions (14), some may
still be explained by undiscovered genetic variation, in par-
ticular variants of intermediate frequency and penetrance. A
recent review of the genetic architecture of psychiatric disor-
ders pointed out a gap between rare, highly penetrant variants
represented typically by large (.1 Mbp) CNVs and common
but weakly penetrant common variants represented as SNPs
in our current data sets (15). The existing genetic paradigms,
which will allow the discovery of a single region or locus at
a time, have not sufficiently explained the missing heritability
and increases in the prevalence of autism (16). Although
recent studies have shown an elevated frequency of large,
rare CNVs in autism, the global load of deletions or duplica-
tions in base pairs and its correlation with the clinical manifes-
tations have not been documented. One approach to this
problem is a comprehensive CNV analysis that measures all
events, without removing common events, and assessing the
genetic contribution of these events collectively, as copy
number load. In this study, we examined global CNV load
and assessed for correlation with clinical outcomes for two in-
dependent groups of children with autism, using two separate,
but complementary, approaches.
We analyzed 274 children with autism and 242 controls ascer-
tained from the CHARGE study (Supplementary Material,
Table S1) (17). We restricted our cases to include only those
children with an Autism Diagnostic Observation Schedule
(ADOS) and Autism Diagnostic Interview, Revised (ADI-R)
confirmed diagnosis of autism. We excluded children with de-
velopmental delay but lacking symptoms of autism as well as
those with autism spectrum disorder as defined by the
CHARGE protocol (17). Controls were identified by sampling
the general population, using birth records, matching on age,
sex and broad geographic region, and then restricting to
those who were clinically confirmed to be without autism
symptoms and in the normal range of development for age
confirmed by clinical assessment.
For CNV analysis, we utilized a custom microarray targeted
to 120 genomic regions flanked by segmental duplications at a
high probe density (?2.6 kbp) and with a median probe
density of ?36 kbp across the genomic backbone for com-
parative genomic hybridization experiments (10). Owing to
the high sequence identity of segmental duplications, the
unique sequence regions between segmental duplications,
termed ‘genomic hotspots’, have a high propensity to
undergo rearrangements by unequal crossover leading to dele-
tions and duplications (18,19). In fact, these regions have a
25-fold increase in frequency for undergoing rearrangements
compared with the other unique, non-hotspot regions in the
genome (20) and therefore are useful sites for assessing the
rate of genomic instability. Previous empirical estimates indi-
cated a high accuracy (.99%) and sensitivity for events
.50 kbp within the hotspots and .300 kbp in the genomic
backbone using this microarray platform (10). Quality
control filtering and validation of the discovered rare patho-
genic events were performed as described previously (10).
Increased duplication CNV load in children with autism
compared with controls
Previous studies have suggested an overrepresentation of
large, rare (.1 Mbp) CNVs in individuals with autism com-
pared with controls or individuals with subtle neurological dis-
orders such as dyslexia (10). We hypothesized that although
some genetic variants individually may not have a sufficiently
large effect to show a statistically significant association with
autism, in modest size samplings, these genetic changes might
have an impact on disease susceptibility globally. Such global
changes in copy number can then be expected to occur in
regions prone for recurrent rearrangements, i.e. within
genomic hotspots. Moreover, if these events affect autism sus-
ceptibility, collectively, there should be a difference in total
copy number load between children with autism and unaffect-
ed, control individuals.
We measured global changes in copy number as total
length, i.e. base pairs of deletion or duplication in each indi-
vidual, or collectively, as total base pairs of altered copy
number (i.e. CNV load). We found that children with autism
showed a significant increase in total base pairs of copy
number change (deletions and duplications) (unpaired t-test,
P ¼ 0.0003) (Fig. 1A). A complete list of CNVs detected in
autism and controls is shown in Supplementary Material,
Tables S2 and S3. When variants were analyzed separately
as deletions and duplications, the level of duplication load
was significantly (unpaired t-test, P ¼ 0.0052) elevated in
individuals with autism but the deletion load was not (unpaired
Human Molecular Genetics, 2013, Vol. 22, No. 142871
t-test, P ¼ 0.3) (Fig. 1A). These findings show that autism is
characterized by an increase in duplicated base pairs. We
next sought to determine whether this elevated CNV load is
independent of potentially pathogenic large CNVs and
re-analyzed the data after removing these variants. We
defined potential pathogenic CNVs as those that are rare
[,0.1% (,8/8629) in the controls population] and/or those
already known to be associated with neurodevelopmental phe-
notypes (21,22) (see Supplementary Material, Table S4 for po-
tentially pathogenic CNVs). An increase in CNV load in
autism cases compared with controls remained (total load, un-
paired t-test, P ¼ 0.0054), represented principally as duplica-
tions (unpaired t-test, P ¼ 0.032) (Fig. 1B). These findings
suggest that autism is associated with an increase in
duplications that are common in frequency in addition to an
elevated level of rare, large genetic variants (22).
We also assessed the distribution of copy number load in the
individuals to determine whether the increased duplication
load is a consequence of a few outliers with a high degree
of copy number changes or is an overall characteristic of the
group. Boxplots showing all individuals with the median
(central line), 25th and 75th percentile (box) distributions
clearly show that the overall distribution of base pairs of dupli-
cation is shifted upward for the individuals with autism com-
pared with the general population controls. This shift was not
observed for deletions among these samples. The upward shift
is also evident after the removal of the potential pathogenic
events, showing that the statistically significant level of
Figure 1. Copy number load and CNV size distributions for children in the CHARGE cohort. (A) Copy number load (Mbp) including all CNV events detected
per individual is shown. Plots show duplication, deletion and total load length separately for controls and children with autism. (B) Copy number load per in-
dividual (deletion, duplication and total load) is shown after removing known and likely pathogenic events. Frequency distribution of total duplications (C) and
deletions (D) for each individual for all events and after removing pathogenic events is also shown as boxplots. Horizontal line shows the median, and box limits
represent 25th and 75th percentiles; ‘whiskers’ represent boundaries of all values within 1.5 SD of the mean. P-values were calculated using a t-test comparing
control individuals and children with autism. Asterisks represent P , 0.05.
2872 Human Molecular Genetics, 2013, Vol. 22, No. 14
increased duplication load is not due to a few outlier samples
with large events (Fig. 1C and D).
Replication of increased duplication load in an
independent sample cohort
To replicate these findings in an independent cohort, we reex-
amined CNV data from 350 individuals with sporadic autism
ascertained from the Simons Simplex Collection compared
with a set of 337 control subjects ascertained by the NIMH
Genetics Initiative (23,24). These samples were analyzed
using the same hotspot array platform as the CHARGE
samples (10). Since there was no bias in the array platforms
used, this cohort served as an appropriate replication set. We
measured copy number load as base pairs of deletion or dupli-
cation per individual both before and after the removal of rare,
large events of potential pathogenic significance. Individuals
with autism have significantly elevated total copy number
load compared with controls (unpaired t-test, P ¼ 0.012),
and duplications (unpaired t-test, P ¼ 0.013), not deletions
(unpaired t-test, P ¼ 0.28), show statistically increased levels
(Fig. 2A–C). Similar to the analysis on the CHARGE
cohort, after the removal of known or likely pathogenic
events in the Simons Simplex Collection, only the duplication
load showed statistical significance (unpaired t-test, P ¼
0.045) when the autism group was compared with controls
(Fig. 2D, Supplementary Material, Fig. S1). In addition,
these data show that children with intellectual disability and
multiple congenital anomalies, unlike those with autism,
have both increased duplication and deletion load compared
with controls after the removal of known pathogenic variants
In order to replicate this finding in an orthogonal CNV plat-
form, we re-analyzed CNV data from 1124 autism families
reported by Sanders et al. (12) on Simons Simplex collection.
These samples were processed using a high-density Illumina
Figure 2. Copy number load comparison for neurodevelopmental disorders, including the Simons Simplex Cohort of children with autism and individuals with
intellectual disability. Copy number load per individual (in Mbp) for controls, children with autism (Simons Simplex Cohort; AU SSC) and children with in-
tellectual disability (ID) or multiple congenital anomalies (MCA) are shown as base pairs of duplications (A), deletions (B) and total load (C). Note that all
events, rare pathogenic and common CNVs, were included in this analysis. (D) Duplication load for the three groups after the removal of identified pathogenic
events is shown. P-values were determined using t-test comparisons with control individuals.∗P , 0.05,∗∗P , 0.01 and∗∗∗P , 0.001.
Human Molecular Genetics, 2013, Vol. 22, No. 142873
1Mv1 or 1Mv3 Duo Bead arrays, and CNV predictions were
made using PennCNV as described previously (12). We calcu-
lated the ratio of total base pairs of duplications and deletions
among the rare, high-confidence data set of CNVs for each
proband compared with their corresponding parents (Supple-
mentary Material, Fig. S2). We found a .7-fold increase in
duplicated base pairs in the probands, in aggregate, compared
with father (mean proband/father ratio ¼ 7.5) or mother (mean
proband/father ratio ¼ 7.7) and a more modest increase in
deleted base pairs (mean proband/father ratio ¼ 2.3; mean
proband/mother ratio ¼ 1.7). These results show a preferential
accumulation of duplication load over deletions among
children with autism and replicate our findings for the rare,
high-confidence set of CNVs detected with a different CNV
High-resolution microarray detects increased duplication
load contributed by common variants
To determine whether a more sensitive assay would uncover
significantly greater levels of copy number change, we ana-
lyzed 71 autism cases and 71 controls matched for ethnicity
and sex using a finely tiled array. Of note, 34 of the autism
individuals includedin this
CHARGE study sample, also evaluated using the genomic
hotspot array, whereas the remainder was obtained from the
Autism Genetic Resource Exchange (AGRE) study. We
selected five highly dynamic, segmental duplication-rich
genomic hotspots including 7q11.2 associated with Williams
syndrome (25), 10q22q23 associated with autism and other de-
velopmental deficits (26), 15q11.2q13 associated with Prader–
Willi/Angelman syndrome (27) and autism (28), 17q12 asso-
ciated with renal cysts and diabetes (29) and autism (30) and
22q11.2 region associated with DiGeorge/velocardiofacial
syndrome (31). These regions were selected based on the
length and size distribution of flanking segmental duplications
and severity of the disorders associated with the CNV
mapping within these regions. We designed a custom micro-
array with average probe spacing of one probe every 180 bp
providing a CNV size resolution as high as 1–2 kbp (desig-
nated as LCR5 array). The sensitivity and specificity of the
LCR5 arrays were evaluated by comparing CNV data from
two HapMap control samples with CNV data from orthogonal
whole-genome platforms reported previously (32) (see Supple-
mentary Material, Fig. S3). Utilizing two complementary
CNV detection algorithms and quantitative polymerase chain
reaction validations, we estimate a true positive rate between
71.25 and 80% and false positive rate between 5.1 and 6.6%
(see Materials and Methods). We performed LCR5 array
hybridizations on 71 autism and 71 control subjects matched
for age, sex and ethnicity. For the entire 75 Mbp of DNA inter-
rogated by the LCR5 array, the autism samples showed a sig-
nificantly higher total copy number load (unpaired t-test, P ¼
0.032) represented mainly as an increase in total duplication
length in base pairs (unpaired t-test, P ¼ 0.011, autism/
control ratio ¼ 1.37) (Fig. 3A and B). The load of deletions
was not significantly different between autism cases and con-
trols (unpaired t-test, P ¼ 0.089). Boxplot representation of
the copy number load (Fig. 3B), shown separately as duplica-
tions or deletions, reveals that the statistically significant in-
crease in duplication load is not achieved through a few
outliers, but rather is reflected in an elevated median and
25th and 75th percentile measures for the group. Twenty of
the 71 autism individuals show a greater total length of dupli-
cation in the size range of ≥4 Mbp per person, emphasizing
that the duplication load detected was not a consequence of
a few outliers (Supplementary Material, Fig. S4). These differ-
ences in distributions were not detected for the measures of
Figure 3. Copy number load measures using a high-resolution, finely tiled LCR5 array to examine five SD-rich intervals. (A) Copy number load for all events,
separated into duplication and deletion load per individual (in Mbp), is shown. (B) Total copy number load per individual for all events (in Mbp).∗P , 0.05.
(C and D) Frequency distribution for duplications (C) and deletions (D) for each individual for all events and after removing pathogenic variants is shown as
boxplots. The graphs show a comparison between controls and individuals with autism. P-values were calculated after a t-test comparison of cases and controls.
2874 Human Molecular Genetics, 2013, Vol. 22, No. 14
base pairs of deletion. We note that the amount of copy
number variation detected using LCR5 array was greater
than the whole-genome hotspot array reflecting the increased
sensitivity gained with a finely tiled design. None of the var-
iants detected with this platform included rare or previously
identified pathogenic variants, suggesting that the increase in
copy number load is contributed by common variants, at
least for these five highly variant regions of the genome.
Measures of clinical severity show correlation with levels
of copy number load
Our data indicate that autism and other neurodevelopmental
disorders show an elevated level of global copy number load
beyond the increased frequency of rare and large CNVs that
have been characterized to date. If this copy number change
has an effect on the susceptibility or level of deficit, then we
would expect a relationship between the clinical outcome
and the level of copy number change. Several measures of
neurodevelopmental outcomes were obtained for CHARGE
participants, including Mullen Scales of Early Learning
(MSEL) (33) for cognitive function and the Vineland Adaptive
Behavior Scales (VABS) (34) for assessments of social and
adaptive behaviors on all study children, as well as the
direct assessment of autism using the ADOS, given to those
recruited with a diagnosis of autism (35). We examined the
correlation between these clinical assessments and the levels
of copy number load, measured as base pairs of deletion, du-
plication or total load. Negative correlations at significant
levels, using the Spearman rank test, were observed for total
CNV load as well as duplication load when assessed with
VABS scores including communication, socialization and
total VABS scores. Table 1 shows both corrected and uncor-
rected P-values for the five Spearman correlation tests per-
formed using the VABS scores. We did not observe any
significant level of correlation, with and without multiple
testing corrections, between copy number load and either
MSEL or ADOS scores (36) (data not shown). It is of interest
that VABS are based on interviews of caregivers and seek to
provide a detailed context for the child’s current functional
daily living skills and activities, whereas MSEL and ADOS
measures are taken in a 30–40 min assessment that can be
affected by the age and attendance-to-task of the subject. Re-
cently, similar observations were also made on autism samples
from the Simons Simplex Collection, with the size of the du-
plication directly correlating with autism severity and with no
impact on verbal IQ whereas the size of the deletion inversely
correlating with IQ (37). Further replication of these results is
warranted to fully understand the role of duplications toward
Novel potentially pathogenic CNVs found in the CHARGE
A number of CHARGE study children with a diagnosis of
autism were found to have CNVs not previously reported
and not found in an additional set of 8329 control individuals
(22). We report these rare variants (Table 2) in order that other
studies can attempt to replicate these events to determine their
contribution to autism susceptibility.
A 3.6 Mbp, paternally inherited deletion was detected in one
autism proband. No clinical phenotypes were reported for
the father. This is a novel CNV not observed in 15 767 devel-
opmental delay (DD) children or 8329 controls (22). A large,
19 Mbp de novo deletion associated with autism has been
reported for this region, indicating that this genomic interval
may contribute to autism and other behavioral disorders (38).
We detected a de novo 1.5 Mbp duplication in a child with
autism near the EPHA5 gene. Previous genome-wide associ-
ation study analysis identified a marker near EPHA5 that
had a significant association with autism (39).
A novel 290 kbp maternally inherited duplication spanning the
DRG11 gene was detected in an individual with autism. This
CNV was not detected in any controls or DD individuals (22).
Table 1. Copy number load and VABS correlations
Score Load Spearman’s correlation (r)
P-value (uncorrected)Bonferroni-corrected P-value∗(five tests)
Vineland totalTotal load
Daily living skills
∗Cutoff for corrected (for five tests) P-value ¼ 0.01.
Human Molecular Genetics, 2013, Vol. 22, No. 14 2875
We detected a 2.1 Mbp duplication spanning the GJA1 gene.
Loss of GJA1 function is responsible for oculodentodigital
dysplasia, and mutations at this locus have been associated
with Sudden Infant Death Syndrome (40,41). The detection
of a duplication affecting this channel gene, connexin43, sug-
gests that gain-of-function mutations could have different neu-
rodevelopmental and behavioral consequences.
Known potentially pathogenic CNVs found in the
The detection and mapping of CNVs in 516 autism and typic-
ally developing individuals provided the opportunity to evalu-
ate the representation of CNVs previously reported with
autism in this ethnically diverse cohort from California.
15q11.2q13 duplications. These duplications are perhaps one
of the common genomic causes for autism occurring in 1–
3% of cases (28,42); the frequency (3/256, 1.2%) of this
CNV in our study is therefore consistent with previous
reports. One of these events was de novo, and for the other
two children, parental DNA was not available. We also
detected 15q13.3 duplications in two autism probands encom-
passing CHRNA7. A recent study of a large set of individuals
with duplications in this interval makes the direct association
of these CNVs with autism uncertain but suggests the possibil-
ity that it is a common disease-contributing variation (43).
three individualswith autism carrying
We detected a paternally inherited 450 kbp 16p11.2 duplica-
tion in an autism proband. This variant has been associated
with autism, schizophrenia and intellectual disability (44,45).
Earlier work has found this variant in 28 out of 15 767 cases
of developmental delay cases and 2 out of 8329 controls
(P ¼ 0.0004; OR ¼ 7.41).
We also detected in one individual an ?840 kbp deletion that
includes the AUTS2 gene. Translocations that disrupt AUTS2
have been reported in autistic twins (46) and children with
cognitive deficits (47). Our finding provides additional data
supporting a role for functional changes in this gene contribut-
ing to autism susceptibility.
Recent progress in understanding the genetic underpinnings of
autism has provided some unexpected results and outlined the
challenges that remain toward understanding autism. First, it is
clear from both copy number and single-nucleotide variant
analysis that, at the molecular level, autism is a very heteroge-
neous disorder. The genetic target for autism is now estimated
in the hundreds to thousands of genes or genomic loci. Second,
it would appear that genetic variants associated with autism
are rarely unique to the disorder. A number of genomic
regions that have a significant role in autism are associated
Table 2. Rare CNVs detected in children with autism from CHARGE cohort
169 876 274
Novel event not found in 8329 controls or 15767 DD.
Includes SPOCK3 and KLHL 2
Represents classic duplication found in 1–3% of all
autism cases; 0 out of 8329 controls and 27 out of
15767 DD cases
Duplication involving CHRNA7
Observed 0 out of 8329 controls, 1 out of 15767 DD
Implicated in AU, schizophrenia, ID. Observed: 2 out of
8329 controls, 28 out of 15767 DD
144 529 218
Observed: 2 out of 8329 controls, 19 out of 15767 DD
Observed: 0 out of 8329 controls, 1 out of 15767 DD.
Duplication 3′to EPHA5 associated with autism
Novel duplication encompassing DRG11. Observed: 0 out
of 8329 controls, 0 out of 15767 DD
Includes AUTS2. Observed: 0 out of 8329 controls
122 799 034
Duplication spanning GJA1.Observed: 0 out of 8329
DD, developmental delay.
2876 Human Molecular Genetics, 2013, Vol. 22, No. 14
with substantial clinical heterogeneity (48), including intellec-
tual disability, seizure disorder, schizophrenia and develop-
mental delay. These findings indicate that there will likely
be few autism-specific genes, but rather a collection of
genes affecting the phenotypes associated with autism, princi-
pally languageand socialization
autism-associated genetic variants discovered thus far only
begin to account for the estimated heritability, emphasizing
there is a great deal of genetic heterogeneity yet to be uncov-
ered. Finally, the incidence of autism reported is increasing
(49) and there is no biological model to account for these epi-
demiological findings. As an alternative to the traditional ap-
proach of searching for the enrichment of individual genetic
variants associated with autism, we performed a genome-wide
CNV study of two independent cohorts based on a hypothesis
that children with autism will exhibit global increases in copy
number variation, particularly in those regions of the genome
prone to rearrangement. This search for relatively large var-
iants (.50 kbp) both across the genome and within unstable
segment of the genome was bolstered by a high-resolution
analysis (CNVs .2 kbp) using a finely tiled array of five seg-
mental duplication-rich intervals where rare variants are
known to contribute to behavioral disorders.
We analyzed total base pairs of copy number change in a
total of 624 children with autism compared with 579 controls.
Our analysis draws from two independent groups of children
with autism: the population-based case–control CHARGE
study, and the Simons Simplex Cohort. These two groups of
children were assessed with a microarray that provides cover-
age of the entire genome at 300 kbp resolution, and for 120
SD-rich intervals prone to rearrangement, a resolution of
50 kbp. In addition to the whole-genome assessment, we
examined five SD-rich intervals at high resolution (.1 kbp)
in 142 autism cases and controls matched for ethnicity and
sex. In all three of these studies, children with autism exhib-
ited a significantly elevated copy number load, represented
principally as an increase in duplicated base pairs found in
large CNVs (.200 kbp) (Supplementary Material, Fig. S5).
The level of deletion load was not different from controls
for these cohorts. These findings were further replicated by
analysis of published data that examined rare, high-confidence
CNVs in 1024 Simons Simplex trios using a 1 million feature
Illumina array (12). This analysis, comparing copy number
load as the ratio of base pairs of deletion or duplication in
proband to parent, showed an ?7-fold increase in duplication
base pairs and roughly a 2-fold increase in deletion base pairs.
Consistent with previous reports on an increase in de novo
CNV load (50), we find that the increase in global CNV
load from data from Sanders et al. is mainly due to de novo
events in the affected child. This preponderance of duplication
load further emphasizes the large contribution of duplication
events to autism.
In the autism cases, the majority of copy number load is
represented as large duplications, in contrast with ID/MCA,
where both large deletions and duplications are increased com-
paredwithcontrol groups. These findings suggest that deletions
are typically associated with more severe phenotypes (ID/
MCA), and that autism, on average, is associated with
genomic variants with more modest functional impact,
namely duplications. This conclusion is supported by the
observation that there is no elevated load of large, rare events
in children with dyslexia, a neurological disorder with a rela-
tively narrow set of deficits (10). Our results, therefore, validate
the previously observed graded distribution of phenotypic se-
verity correlating with levels and type of copy number vari-
Significant levels of duplication load remained even after
the removal of rare, potentially pathogenic variants for
autism and ID/MCA, suggesting some contribution from var-
iants occurring at higher frequencies than the large, highly
penetrant CNVs classified as pathogenic. Current studies
have overlooked variants of intermediate penetrance and fre-
quency because of the practice of removing common variants
from CNV studies and focusing only on those individually rare
variants with high penetrance. In a recent review of the genetic
architecture of psychiatric disorders, it was pointed out that
our current understanding includes rare variants (CNVs) of
high penetrance and common variants of low penetrance
(SNPs) but little about the variants of intermediate penetrance
(15). The variants we have detected, and assessed collectively
as copy number load, are likely to encompass all types, includ-
ing those of intermediate penetrance and frequency (Supple-
mentary Material, Fig. S5).
Among the CHARGE study children with autism, we found
significant negative correlations between the level of copy
number load and socialization and communication modules
of the VABS. In contrast, no such significant correlations
were found for ADOS or Mullen scores. These findings
suggest that measures of adaptive skills provide a very sensi-
tive assessment of functional change. A comparison of VABS
and ADOS scores for children assessed in two different clinic-
al centers showed VABS to be significantly reduced in high
functioning autistic children with normal IQ scores. In add-
ition, there was only a weak correlation between VABS and
ADOS scores (51). Indeed, Klin et al. (51) suggested the
VABS may be particularly useful in genetic studies of
autism since it was designed to assess graded changes in adap-
tive ability, including the normal range of function, whereas
ADOS measures were designed to identify disability, and
may therefore not be as sensitive to some functional deficits.
Increased duplication load associated with autism can be
explained by more than one mechanism. It is known that dele-
tions are generally deleterious and duplications are relatively
well tolerated in the genome; our observations suggest a selec-
tion bias toward duplication in autism. In fact, SD-rich regions
where deletions have been associated with developmental
delay often have reciprocal duplications that produce autistic
features. Examples include reciprocal duplication of the Wil-
liams syndrome region and 17p11.2 duplication or Potocki–
Lupski syndrome, which is a reciprocal duplication of the
Smith–Magenis syndrome interval. Notably, one of the first
CNVs identified as predisposing for autism is the reciprocal
duplication of the Prader–Willi/Angelman syndrome region
on chromosome 15q11.2q13.1. Alternatively, the elevated
level of duplication could be not only due to selection, but as-
certainment; namely, the generation of these variants could be
increased in the autism population. Segmental duplication-rich
intervals possess an inherent instability and it is possible that
these segments of the genome show an additional propensity
to change in the autism population either from genetic or
Human Molecular Genetics, 2013, Vol. 22, No. 142877
environmental causes. There are several factors that could
contribute to genomic instability, including imbalances in
DNA replication or recombination mechanisms (52), maternal
and paternal age (53,54) and DNA methylation (55). It is
notable that perinatal vitamin/folate supplementation, which
would potentially increase DNA methylation levels, is asso-
ciated with a lower autism incidence (56). Given the large
genetic target of neurodevelopmental disorders, estimated in
the hundreds or even thousands of genomic loci, it stands to
reason that anything that increases genomic instability could
contribute to the genesis of these disorders.
MATERIALS AND METHODS
Patients from each of study cohort were recruited after appro-
priate human subjects’ approval and informed consent.
All samples were obtained after informed written consent and
in accordance with IRB protocols at all facilities. Autism
patients’ DNA samples were acquired from the CHARGE
study (17) conducted through the Medical Investigation of
UC-Davis, and from the AGRE Repository (57). All patients
for CHARGE and AGRE cohorts were selected based on
meeting full criteria for Autistic Disorder (AU) (OMIM
209850) using ADOS, ADI-R and/or DSM-IV-TR criteria.
The ADOS instrument consists of a series of structured and
semistructured presses for interaction, accompanied by
coding of specific target behaviors associated with particular
tasks and by general ratings of the quality of behaviors (58).
Based on documentation in the AGRE database, efforts were
made to exclude patients with syndromic autism and known
genetic causes of autism, including fragile X syndrome
(OMIM 300624). Samples from the CHARGE study were
screened for fragile X syndrome by PCR (59). For the
custom targeted hotspot array study, samples only from
CHARGE study participants were used. In summary, 274
autism and 242 control samples were hybridized, of which
243 and 223 passed QC criteria (10) and were included in
the final analysis. Based on self-reported ethnicity, this
cohort consists of 52% of individuals of European descent,
28% Hispanic, 2% African or African-American ancestry,
5% Asian ancestry and the remaining 12% of mixed ancestry
(Supplementary Material, Table S1). The finely tiled analysis
using the LCR5 array included a total of 71 autism patients, 37
samples from the MIND Institute and 34 samples from the
AGRE repository, with a total of 34 Caucasian males, 21 His-
panic males, 8 Caucasian females and 8 Hispanic females.
Typically developing control DNA samples were obtained
from the MIND Institute, the University of Minnesota Psych-
ology Department and the CEPH Utah Pedigree (Centre
de’Etude du Polymorphism Human, Coriell Institute for
Medical Research, Camden, NJ, USA). DNA samples from
the CHARGE study participants and the University of Minne-
sota were from whole blood, whereas the CEPH and AGRE
samples were from transformed lymphoblastoid cells. A total
of 71 controls, matched to the autism patient sample set
based on gender and ethnicity, were included in this study,
with a total of 40 samples from the MIND Institute, 28
samples from the University of Minnesota collection and 3
samples were obtained from the CEPH collection.
Custom targeted hotspot analysis
Custom targeted hotspot arrays comprised 135 000 probes
(Roche NimbleGen), with higher density probe coverage
(median probe spacing 2.6 kbp) in the genomic hotspots
(regions flanked by segmental duplications) and a lower
probe density in the genomic backbone (median probe
spacing 36 kbp). Hybridization, quality control and segmenta-
tion analysis were all conducted as previously described (10).
All potentially pathogenic events detected with the hotspot
array were confirmed with the higher resolution Agilent
hotspot 2 × 400K array according to the manufacturer’s
LCR5 finely tiled array design and data analysis
We designed a custom 385K oligonucleotide array from
Roche NimbleGen Systems, Inc. (Madison, WI, USA) target-
ing five genomic regions with an average probe density of one
probe every 120 bp in segmental duplication-containing
regions and one probe every 200 bp in unique sequence
regions. Probe sequences were based on Build 36 (Hg18) of
the human reference genome. In SD-containing regions,
probes were required to have a minimum of one unique nu-
cleotide per probe; probes in unique sequences were required
to have at least five unique nucleotides per probe. The five
(20.9 Mb), chr10: 77 000 071–91 999 959 (15.0 Mb), chr15:
18260 026–34 999 973(16.7 Mb),
22187 066 (10.2 Mb) and chr22: 14 430 001–26000 041
(11.6 Mb). SD-containing regions accounted for 24.5% of
the sequence on the array (18.2 out of 74.4 Mb). Details for
LCR5 experimental methods, including platform comparisons
and CNV calling criteria, are provided in the Supplementary
61 058 424–82 000 033
chr17:12 000 112–
Enrichment analysis for unique and sequences embedded
within segmental duplications
To identify the location of deletion, duplication or total copy
number load, sequences within a CNV were parsed in to
those that are entirely unique, those containing segmental
duplication-only sequences. Enrichment statistics were calcu-
lated for total base pairs of deletion or duplication for each
of these categories.
Statistical analysis of CNV load
Statistical comparison of copy number load data described in
this study was performed using the unpaired t-test reporting
2878 Human Molecular Genetics, 2013, Vol. 22, No. 14
Supplementary Material is available at HMG online.
We gratefully acknowledge the technical contributions and as-
sistance of the following colleagues: Sarah Pendergrass, Emre
Karakoc, Bradley Coe, Gregory Cooper, Caitlin M. Conboy,
Angela N. Klossner, Ryan Davis, Jeff Gregg and Maria Krasil-
nikova. We also thank Majid Alsagabi, Abdullah Alqallaf and
Ahmed Tewfik for the development of algorithms for segmen-
tation assessment. We are also indebted to Tonya White and
Monica Luciano (University of Minnesota) for providing
control DNA samples from their University of Minnesota-
Conflict of Interest statement. E.E.E. is on the scientific advis-
ory boards for Pacific Biosciences, Inc., SynapDx Corp and
This work received support from the Kempf Fund as well as
from the University of Minnesota General Clinical Research
Center Award. This work was supported by Autism Speaks/
Cure Autism Now (to S.B.S.), the University of Minnesota
Harrison Autism Initiative Fund (to S.B.S.), Pennsylvania
State University (to S.B.S.), the Minnesota Medical Founda-
tion (to R.L.J.) and Autism Speaks/Cure Autism Now Envir-
onmental Innovator Award (to I.N.P.) (matching funds for
the CHARGE study), the MIND Institute [matching funds
for the CHARGE Study (I.H.-P.)] and by R01-ES015359
and P01ES011269 from the NIEHS and Award Numbers
R833292 and R829388 from the Environmental Protection
Agency. The funders had no role in study design, data collec-
tion and analysis, decision to publish or preparation of the
manuscript. Funding to pay the Open Access publication
charges for this article was provided by The Pennsylvania
State University to Scott B. Selleck.
1. Malhotra, D. and Sebat, J. (2012) CNVs: harbingers of a rare variant
revolution in psychiatric genetics. Cell, 148, 1223–1241.
2. Neale, B.M., Kou, Y., Liu, L., Ma’ayan, A., Samocha, K.E., Sabo, A., Lin,
C.F., Stevens, C., Wang, L.S., Makarov, V. et al. (2012) Patterns and rates
of exonic de novo mutations in autism spectrum disorders. Nature, 485,
3. O’Roak, B.J., Deriziotis, P., Lee, C., Vives, L., Schwartz, J.J., Girirajan,
S., Karakoc, E., Mackenzie, A.P., Ng, S.B., Baker, C. et al. (2011) Exome
sequencing in sporadic autism spectrum disorders identifies severe de
novo mutations. Nat. Genet., 43, 585–589.
4. Sanders, S.J., Murtha, M.T., Gupta, A.R., Murdoch, J.D., Raubeson, M.J.,
Willsey, A.J., Ercan-Sencicek, A.G., DiLullo, N.M., Parikshak, N.N.,
Stein, J.L. et al. (2012) De novo mutations revealed by whole-exome
sequencing are strongly associated with autism. Nature, 485, 237–241.
5. Iossifov, I., Ronemus, M., Levy, D., Wang, Z., Hakker, I., Rosenbaum, J.,
Yamrom, B., Lee, Y.H., Narzisi, G., Leotta, A. et al. (2012) De novo gene
disruptions in children on the autistic spectrum. Neuron, 74, 285–299.
6. Anney, R., Klei, L., Pinto, D., Regan, R., Conroy, J., Magalhaes, T.R.,
Correia, C., Abrahams, B.S., Sykes, N., Pagnamenta, A.T. et al. (2010) A
genome-wide scan for common alleles affecting risk for autism. Hum.
Mol. Genet., 19, 4072–4082.
7. Wang, K., Zhang, H., Ma, D., Bucan, M., Glessner, J.T., Abrahams, B.S.,
Salyakina, D., Imielinski, M., Bradfield, J.P., Sleiman, P.M. et al. (2009)
Common genetic variants on 5p14.1 associate with autism spectrum
disorders. Nature, 459, 528–533.
8. Hallmayer, J., Cleveland, S., Torres, A., Phillips, J., Cohen, B., Torigoe,
T., Miller, J., Fedele, A., Collins, J., Smith, K. et al. (2011) Genetic
heritability and shared environmental factors among twin pairs with
autism. Arch. Gen. Psychiatry, 68, 1095–1102.
9. Pennington, B.F., McGrath, L.M., Rosenberg, J., Barnard, H., Smith, S.D.,
Willcutt, E.G., Friend, A., Defries, J.C. and Olson, R.K. (2009) Gene X
environment interactions in reading disability and attention-deficit/
hyperactivity disorder. Dev. Psychol., 45, 77–89.
10. Girirajan, S., Brkanac, Z., Coe, B.P., Baker, C., Vives, L., Vu, T.H.,
Shafer, N., Bernier, R., Ferrero, G.B., Silengo, M. et al. (2011) Relative
burden of large CNVs on a range of neurodevelopmental phenotypes.
PLoS Genet., 7, e1002334.
11. Girirajan, S., Campbell, C.D. and Eichler, E.E. (2011) Human copy
number variation and complex genetic disease. Annu. Rev. Genet., 45,
12. Sanders, S.J., Ercan-Sencicek, A.G., Hus, V., Luo, R., Murtha, M.T.,
Moreno-De-Luca, D., Chu, S.H., Moreau, M.P., Gupta, A.R., Thomson,
S.A. et al. (2011) Multiple recurrent de novo CNVs, including
duplications of the 7q11.23 Williams syndrome region, are strongly
associated with autism. Neuron, 70, 863–885.
13. Bailey, A., Le Couteur, A., Gottesman, I., Bolton, P., Simonoff, E.,
Yuzda, E. and Rutter, M. (1995) Autism as a strongly genetic disorder:
evidence from a British twin study. Psychol. Med., 25, 63–77.
14. Zuk, O., Hechter, E., Sunyaev, S.R. and Lander, E.S. (2012) The mystery
of missing heritability: genetic interactions create phantom heritability.
Proc. Natl Acad. Sci. USA, 109, 1193–1198.
15. Sullivan, P.F., Daly, M.J. and O’Donovan, M. (2012) Genetic
architectures of psychiatric disorders: the emerging picture and its
implications. Nat. Rev. Genet., 13, 537–551.
16. Eichler, E.E., Flint, J., Gibson, G., Kong, A., Leal, S.M., Moore, J.H. and
Nadeau, J.H. (2010) Missing heritability and strategies for finding the
underlying causes of complex disease. Nat. Rev. Genet., 11, 446–450.
17. Hertz-Picciotto, I., Croen, L.A., Hansen, R., Jones, C.R., van de Water, J.
and Pessah, I.N. (2006) The CHARGE study: an epidemiologic
investigation of genetic and environmental factors contributing to autism.
Environ. Health Perspect., 114, 1119–1125.
18. Bailey, J.A., Gu, Z., Clark, R.A., Reinert, K., Samonte, R.V., Schwartz,
S., Adams, M.D., Myers, E.W., Li, P.W. and Eichler, E.E. (2002) Recent
segmental duplications in the human genome. Science, 297, 1003–1007.
19. Sharp, A.J., Hansen, S., Selzer, R.R., Cheng, Z., Regan, R., Hurst, J.A.,
Stewart, H., Price, S.M., Blair, E., Hennekam, R.C. et al. (2006)
Discovery of previously unidentified genomic disorders from the
duplication architecture of the human genome. Nat. Genet., 38, 1038–
20. Itsara, A., Cooper, G.M., Baker, C., Girirajan, S., Li, J., Absher, D.,
Krauss, R.M., Myers, R.M., Ridker, P.M., Chasman, D.I. et al. (2009)
Population analysis of large copy number variants and hotspots of human
genetic disease. Am. J. Hum. Genet., 84, 148–161.
21. Girirajan, S. and Eichler, E.E. (2010) Phenotypic variability and genetic
susceptibility to genomic disorders. Hum. Mol. Genet., 19, R176–R187.
22. Cooper, G.M., Coe, B.P., Girirajan, S., Rosenfeld, J.A., Vu, T.H., Baker,
C., Williams, C., Stalker, H., Hamid, R., Hannig, V. et al. (2011) A copy
number variation morbidity map of developmental delay. Nat. Genet., 43,
23. Moldin, S.O. (2003) NIMH Human Genetics Initiative: 2003 update.
Am. J. Psychiatry, 160, 621–622.
24. Kessler, R.C. and Ustun, T.B. (2004) The World Mental Health (WMH)
Survey Initiative Version of the World Health Organization (WHO)
Composite International Diagnostic Interview (CIDI). Int. J. Methods
Psychiatr. Res., 13, 93–121.
25. Pober, B.R. (2010) Williams-Beuren syndrome. N. Engl. J. Med., 362,
26. Balciuniene, J., Feng, N., Iyadurai, K., Hirsch, B., Charnas, L., Bill, B.R.,
Easterday, M.C., Staaf, J., Oseth, L., Czapansky-Beilman, D. et al. (2007)
Recurrent 10q22-q23 deletions: a genomic disorder on 10q associated
with cognitive and behavioral abnormalities. Am. J. Hum Genet., 80,
Human Molecular Genetics, 2013, Vol. 22, No. 142879
27. Cassidy, S.B., Dykens, E. and Williams, C.A. (2000) Prader-Willi and Download full-text
Angelman syndromes: sister imprinted disorders. Am. J. Med. Genet., 97,
28. Cook, E.H. Jr, Lindgren, V., Leventhal, B.L., Courchesne, R., Lincoln, A.,
Shulman, C., Lord, C. and Courchesne, E. (1997) Autism or atypical
autism in maternally but not paternally derived proximal 15q duplication.
Am. J. Hum Genet., 60, 928–934.
29. Mefford, H.C., Clauin, S., Sharp, A.J., Moller, R.S., Ullmann, R., Kapur,
R., Pinkel, D., Cooper, G.M., Ventura, M., Ropers, H.H. et al. (2007)
Recurrent reciprocal genomic rearrangements of 17q12 are associated
with renal disease, diabetes, and epilepsy. Am. J. Hum. Genet., 81,
30. Moreno-De-Luca, D., Mulle, J.G., Kaminsky, E.B., Sanders, S.J., Myers,
S.M., Adam, M.P., Pakula, A.T., Eisenhauer, N.J., Uhas, K., Weik, L.
et al. (2010) Deletion 17q12 is a recurrent copy number variant that
confers high risk of autism and schizophrenia. Am. J. Hum. Genet., 87,
31. Shprintzen, R.J. (1994) Velocardiofacial syndrome and DiGeorge
sequence. J. Med. Genet., 31, 423–424.
32. Redon, R., Ishikawa, S., Fitch, K.R., Feuk, L., Perry, G.H., Andrews,
T.D., Fiegler, H., Shapero, M.H., Carson, A.R., Chen, W. et al. (2006)
Global variation in copy number in the human genome. Nature, 444,
33. Akshoomoff, N. (2006) Use of the Mullen scales of early learning for the
assessment of young children with autism spectrum disorders. Child
Neuropsychol., 12, 269–277.
34. Sparrow, S.S. and Cicchetti, D.V. (1985) Diagnostic uses of the Vineland
Adaptive Behavior Scales. J. Pediatr. Psychol., 10, 215–225.
35. Lord, C., Risi, S., Lambrecht, L., Cook, E.H. Jr, Leventhal, B.L.,
DiLavore, P.C., Pickles, A. and Rutter, M. (2000) The autism diagnostic
observation schedule-generic: a standard measure of social and
communication deficits associated with the spectrum of autism. J. Autism
Dev. Disord., 30, 205–223.
36. Lord, C., Leventhal, B.L. and Cook, E.H. Jr. (2001) Quantifying the
phenotype in autism spectrum disorders. Am. J. Hum Genet., 105, 36–38.
37. Girirajan, S., Dennis, M.Y., Baker, C., Malig, M., Coe, B.P., Campbell,
C.D., Mark, K., Vu, T.H., Alkan, C., Cheng, Z. et al. (2013) Refinement
and discovery of new hotspots of copy number variation associated with
autism spectrum disorder. Am. J. Hum Genet., 92, 1–17.
38. Ramanathan, S., Woodroffe, A., Flodman, P.L., Mays, L.Z., Hanouni, M.,
Modahl, C.B., Steinberg-Epstein, R., Bocian, M.E., Spence, M.A. and
Smith, M. (2004) A case of autism with an interstitial deletion on 4q
leading to hemizygosity for genes encoding for glutamine and glycine
neurotransmitter receptor sub-units (AMPA 2, GLRA3, GLRB) and
neuropeptide receptors NPY1R, NPY5R. BMC Med. Genet., 5, 10.
39. Weiss, L.A., Arking, D.E., Daly, M.J. and Chakravarti, A. (2009) A
genome-wide linkage and association scan reveals novel loci for autism.
Nature, 461, 802–808.
40. Paznekas, W.A., Boyadjiev, S.A., Shapiro, R.E., Daniels, O., Wollnik, B.,
Keegan, C.E., Innis, J.W., Dinulos, M.B., Christian, C., Hannibal, M.C.
et al. (2003) Connexin 43 (GJA1) mutations cause the pleiotropic
phenotype of oculodentodigital dysplasia. Am. J. Hum. Genet., 72,
41. Van Norstrand, D.W., Asimaki, A., Rubinos, C., Dolmatova, E., Srinivas,
M., Tester, D.J., Saffitz, J.E., Duffy, H.S. and Ackerman, M.J. (2012)
Connexin43 mutation causes heterogeneous gap junction loss and sudden
infant death. Circulation, 125, 474–481.
42. Thomas, J.A., Johnson, J., Peterson Kraai, T.L., Wilson, R., Tartaglia, N.,
LeRoux, J., Beischel, L., McGavran, L. and Hagerman, R.J. (2003)
Genetic and clinical characterization of patients with an interstitial
duplication 15q11-q13, emphasizing behavioral phenotype and response
to treatment. Am. J. Med. Genet. A, 119A, 111–120.
43. Szafranski, P., Schaaf, C.P., Person, R.E., Gibson, I.B., Xia, Z.,
Mahadevan, S., Wiszniewska, J., Bacino, C.A., Lalani, S., Potocki, L.
et al. (2010) Structures and molecular mechanisms for common 15q13.3
microduplications involving CHRNA7: benign or pathological? Hum.
Mutat, 31, 840–850.
44. McCarthy, S.E., Makarov, V., Kirov, G., Addington, A.M., McClellan, J.,
Yoon, S., Perkins, D.O., Dickel, D.E., Kusenda, M., Krastoshevsky, O.
et al. (2009) Microduplications of 16p11.2 are associated with
schizophrenia. Nat. Genet., 41, 1223–1227.
45. Weiss, L.A., Shen, Y., Korn, J.M., Arking, D.E., Miller, D.T., Fossdal, R.,
Saemundsen, E., Stefansson, H., Ferreira, M.A., Green, T. et al. (2008)
Association between microdeletion and microduplication at 16p11.2 and
autism. N. Engl. J. Med., 358, 667–675.
46. Sultana, R., Yu, C.E., Yu, J., Munson, J., Chen, D., Hua, W., Estes, A.,
Cortes, F., de la Barra, F., Yu, D. et al. (2002) Identification of a novel
gene on chromosome 7q11.2 interrupted by a translocation breakpoint in a
pair of autistic twins. Genomics, 80, 129–134.
47. Huang, X.L., Zou, Y.S., Maher, T.A., Newton, S. and Milunsky, J.M.
(2010) A de novo balanced translocation breakpoint truncating the autism
susceptibility candidate 2 (AUTS2) gene in a patient with autism.
Am. J. Med. Genet. A, 152A, 2112–2114.
48. Coe, B.P., Girirajan, S. and Eichler, E.E. (2012) The genetic variability
and commonality of neurodevelopmental disease. Am. J. Med. Genet. C
Semin. Med. Genet., 160C, 118–129.
49. Hertz-Picciotto, I. (2009) Commentary: diagnostic change and the
increased prevalence of autism. Int. J. Epidemiol., 38, 1239–1241; author
50. Sebat, J., Lakshmi, B., Malhotra, D., Troge, J., Lese-Martin, C., Walsh, T.,
Yamrom, B., Yoon, S., Krasnitz, A., Kendall, J. et al. (2007) Strong
association of de novo copy number mutations with autism. Science, 316,
51. Klin, A., Saulnier, C.A., Sparrow, S.S., Cicchetti, D.V., Volkmar, F.R.
and Lord, C. (2007) Social and communication abilities and disabilities in
higher functioning individuals with autism spectrum disorders: the
Vineland and the ADOS. J. Autism Dev. Disord., 37, 748–759.
52. Zhang, F., Carvalho, C.M. and Lupski, J.R. (2009) Complex human
chromosomal and genomic rearrangements. Trends Genet., 25, 298–307.
53. Parner, E.T., Baron-Cohen, S., Lauritsen, M.B., Jorgensen, M., Schieve,
L.A., Yeargin-Allsopp, M. and Obel, C. (2012) Parental age and autism
spectrum disorders. Ann. Epidemiol., 22, 143–150.
54. Sandin, S., Hultman, C.M., Kolevzon, A., Gross, R., MacCabe, J.H. and
Reichenberg, A. (2012) Advancing maternal age is associated with
increasing risk for autism: a review and meta-analysis. J. Am. Acad. Child
Adolesc. Psychiatry, 51, 477–486.e1.
55. Li, J., Harris, R.A., Cheung, S.W., Coarfa, C., Jeong, M., Goodell, M.A.,
White, L.D., Patel, A., Kang, S.H., Shaw, C. et al. (2012) Genomic
hypomethylation in the human germline associates with selective
structural mutability in the human genome. PLoS Genet., 8, e1002692.
56. Schmidt, R.J., Hansen, R.L., Hartiala, J., Allayee, H., Schmidt, L.C.,
Tancredi, D.J., Tassone, F. and Hertz-Picciotto, I. (2011) Prenatal
vitamins, one-carbon metabolism gene variants, and risk for autism.
Epidemiology, 22, 476–485.
57. Geschwind, D.H., Sowinski, J., Lord, C., Iversen, P., Shestack, J., Jones,
P., Ducat, L. and Spence, S.J. (2001) The autism genetic resource
exchange: a resource for the study of autism and related neuropsychiatric
conditions. Am. J. Hum. Genet., 69, 463–466.
58. Lord, C., Rutter, M., Goode, S., Heemsbergen, J., Jordan, H., Mawhood,
L. and Schopler, E. (1989) Autism diagnostic observation schedule: a
standardized observation of communicative and social behavior. J. Autism
Dev. Disord., 19, 185–212.
59. Tassone, F., Pan, R., Amiri, K., Taylor, A.K. and Hagerman, P.J. (2008) A
rapid polymerase chain reaction-based screening method for identification
of all expanded alleles of the fragile X (FMR1) gene in newborn and
high-risk populations. J. Mol. Diagn., 10, 43–49.
60. Ingason, A., Rujescu, D., Cichon, S., Sigurdsson, E., Sigmundsson, T.,
Pietilainen, O.P., Buizer-Voskamp, J.E., Strengman, E., Francks, C.,
Muglia, P. et al. (2011) Copy number variations of chromosome 16p13.1
region associated with schizophrenia. Mol. Psychiatry, 16, 17–25.
61. Rosenfeld, J.A., Coppinger, J., Bejjani, B.A., Girirajan, S., Eichler, E.E.,
Shaffer, L.G. and Ballif, B.C. (2011) Speech delays and behavioral
problems are the predominant features in individuals with developmental
delays and 16p11.2 microdeletions and microduplications. J. Neurodev.
Disord., 2, 26–38.
62. Klopocki, E., Schulze, H., Strauss, G., Ott, C.E., Hall, J., Trotier, F.,
Fleischhauer, S., Greenhalgh, L., Newbury-Ecob, R.A., Neumann, L.M.
et al. (2007) Complex inheritance pattern resembling autosomal recessive
inheritance involving a microdeletion in thrombocytopenia-absent radius
syndrome. Am. J. Hum. Genet., 80, 232–240.
63. Elia, J., Gai, X., Xie, H.M., Perin, J.C., Geiger, E., Glessner, J.T., D’Arcy,
M., deBerardinis, R., Frackelton, E., Kim, C. et al. (2010) Rare structural
variants found in attention-deficit hyperactivity disorder are preferentially
associated with neurodevelopmental genes. Mol. Psychiatry, 15,
2880 Human Molecular Genetics, 2013, Vol. 22, No. 14