NoAssociation Between aCommonSingleNucleotide
Autism Spectrum Disorder
Sarah Curran,1* Patrick Bolton,1,2Kinga Rozsnyai,2Andreas Chiocchetti,3Sabine M. Klauck,3
Eftichia Duketis,4Fritz Poustka,4Sabine Schlitt,4Christine M. Freitag,5Irene Lee,6
Pierandrea Muglia,7(on behalf of the ITAN), Martin Poot,8Wouter Staal,9Maretha V. de Jonge,9
Roel A. Ophoff,10Cathryn Lewis,2David Skuse,6Will Mandy,11Evangelos Vassos,2
Ragnheidur Fossdal,12P? all Magnusson,13Stefan Hreidarsson,14Evald Saemundsen,14
Hreinn Stefansson,12Kari Stefansson,12David Collier2
1Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Kings College London, London, UK
2SGDP Research Centre, Institute of Psychiatry, Kings College London, De Crespigny Park, Denmark Hill, SE5 8AF UK
3Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany
4Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University of Frankfurt, Frankfurt, Germany
5Department of Child and Adolescent Psychiatry, Saarland University Hospital, Saarbrucken, Germany
6Institute of Child Health, University College London, Behavioural and Brain Sciences Unit, London, UK
7University of Toronto, *on behalf of the ITAN, NeuroSearch A/S, Denmark
8Department of Medical Genetics, University Medical Centre Utrecht, Utrecht, the Netherlands
9Department of Child and Adolescent Psychiatry, UMC Utrecht, Utrecht, the Netherlands
10UCLA, UMC Utrecht, Utrecht, the Netherlands
11University College London, Research Department of Clinical, Educational and Health Psychology, London, UK
12deCode Genetics, Reykjavik, Iceland
13Landspitali University Hospital, Child & Adolescent Psychiatry, Reykjav? ık, Iceland
14Greining, State Diagnostic & Counseling Centre, K? opavogur, Iceland
Received 8 December 2010; Accepted 25 April 2011
The Autism Genome Project (AGP) Consortium recently
reported genome-wide significant association between autism
and an intronic single nucleotide polymorphism marker,
rs4141463, within the MACROD2 gene. In the present study
we attempted to replicate this finding using an independent
case–control design of 1,170 cases with autism spectrum disor-
der (ASD) (874 of which fulfilled narrow criteria for Autism
(A)) from five centers within Europe (UK, Germany, the
Netherlands, Italy, and Iceland), and 35,307 controls. The
combined sample size gave us a non-centrality parameter
(NCP) of 11.9, with 93% power to detect allelic association of
rs4141463 at an alpha of 0.05 with odds ratio of 0.84 (the
best odds ratio estimate of the AGP Consortium data), and
for the narrow diagnosis of autism, an NCP of 8.9 and power
of 85%. Our case–control data were analyzed for association,
stratified by each center, and the summary statistics were
This resulted in an odds ratio (OR) of 1.03 (95% CI
Bravaccio, Paolo Curatolo, Lucio Da Ros, Bernardo Della Bernardina,
Maurizio Elia, Serenalli Grittani, Lucia Margari, Gabriele Masi, Massimo
Trabetti, Leonardo Zoccante, Alessandro Zuddas
Grant sponsor: UK Medical Research Council; Grant number: G0500079;
Grant sponsor: Deutsche Forschungsgemeinschaft; Grant sponsor: EU
Grant PsychCNV; Grant number: HEALTH-2007-2.2.1-10-223423;
Grant sponsor: NIH; Grant number: MH071425; Grant sponsor: The
Netherlands Foundation for Brain Research (Hersenstichting); Grant
numbers: 2008(1).34, F2008(1).
Psychiatry, Kings College London, London, UK.
Published online 8 June 2011 in Wiley Online Library
? 2011 Wiley-Liss, Inc.
Therefore, this study does not provide support for the reported
association between rs4141463 and autism.
?2011 Wiley-Liss, Inc.
Key words: autism; autism spectrum; genetic association;
common genetic risk variants; MACROD2
There is compelling evidence from twin, family, and population-
based studies that genetic factors are the most significant contrib-
utors to the etiology of autism spectrum disorders (ASD) and
related traits [Freitag, 2007], with a heritability, estimated to be
about 70–90% [Skuse, 2007] among the highest observed for any
common neuropsychiatric disorder. The genetic architecture of
ASD is, however, likely to be complex and its exact structure
remains elusive [El-Fishawy and State, 2010]. Previously, the most
widely accepted hypothesis for the genetic basis of common dis-
orders was the ‘‘common variant’’ hypothesis, in which many
common, low risk (odds ratio—OR<1.5) alleles act together to
novo copy number variants are an important contributor to
complex disease risk, especially for autism and schizophrenia
[Miller et al., 2010]. These comprise microscopically observable
high risk cytogenetic abnormalities (e.g., maternal duplication of
and together account for about 10% of ASD cases [Abrahams and
Geschwind, 2008]. In addition a number of moderate risk copy
number variants (CNVs) have been associated with autism found
thus far in about 10% of cases [Sebat et al., 2007; Szatmari et al.,
2007; Christian et al., 2008; Marshall et al., 2008; Glessner et al.,
re-sequencing, such as those found in SHANK3 [Gauthier et al.,
2009]. However, in the majority of ASD cases (>80%), there is no
associated CNV or chromosomal abnormality, and overall, the
genetic studies [Coon et al., 2010].
While empirical observations currently favor a major role for
rare, moderate risk variants in autism, common, low risk genetic
variants are also expected to be involved, as is the case for all other
complex genetic disorders studied so far which have undergone
GWAS (genome-wide association study) analysis [Cichon et al.,
2009]. Common variants might account for some of the ‘‘dark
matter’’ or ‘‘missing heritability’’ [Manolio et al., 2009] of undis-
covered susceptibility alleles, and therefore it is important to
information on genetic architecture. Evidence for one genome-
wide significant GWAS association in autism with the single
nucleotide polymorphism rs4141463, located in an intron of the
MACROD2 gene, comes from a family-based GWAS study per-
formed by the AGP Consortium, in which a total of 1,385 ASD
probands from 1,369 families were analyzed [Anney et al., 2010].
cance at P¼2.1?10?8(OR 0.56; 95% CI 0.47–0.67) was for
rs4141463 (C/T) in a sub-set of 720 ASD probands (from 718
families) with a strictly defined ASD diagnosis and European
ancestry, in which the common European allele rs4141463C
(dbSNP build 131, RefSNP alleles: C/T; ancestral allele: T;
ss126770843) was over transmitted in cases. In a replication
sample in the same study, a somewhat higher but non-significant
OR was observed (P¼0.13; OR 0.84; 95% CI 0.67–1.04). Here, we
aimed to replicate the reported association of rs4141463 in a large,
independent sample of individuals with ASD with European
MATERIALS AND METHODS
A sample of 1,170 ASD subjects of European origin was collected
from centers in South-East England (MGAS, UCL, and TEDS
cohorts), Germany (Frankfurt/Heidelberg), the Netherlands
(UMC Utrecht), Italy, and Iceland and genotyped. This study was
approved by the National Bioethics Committees or the Local
Research Ethical Committees, and was compliant with Data Pro-
tection Commissionsorlawsineachcountry.Written consentwas
obtained from all individuals, their and assent or consent from
parents when appropriate. All cases met criteria for autism,
Asperger’s syndrome, or pervasive developmental disorder, not
otherwisespecified (PDD-NOS)according tothe DSM-IV classifi-
cation system using a standard research assessment protocol that
included the autism diagnostic interview-revised (ADI-R) [Lord
et al., 1994] and autism diagnostic observation schedule (ADOS)
[Lord et al., 1989] and was diagnostically confirmed by clinician
similar to the study by Anney et al. . Eight hundred seventy-
four out of 1,032 (85%) subjects were classified as fulfilling narrow
autism criteria. Excluded were ASD subjects with identified meta-
profound intellectual disability (IQ/DQ<20). Each center had
ethnically matched controls. Genotyping was performed using
TaqMan SNP Genotyping Assays. Quality control measures in-
cluded placing 3 blank negative control samples on each 384-well
How to Cite this Article:
Curran S, Bolton P, Rozsnyai K, Chiocchetti
Freitag CM, Lee I, Muglia P (on behalf of the
ITAN), Poot M, Staal W, de Jonge MV,
Ophoff R A, Lewis C, Skuse D, Mandy W,
Vassos E, Fossdal R, Magnusson P,
Hreidarsson S, Saemundsen E, Stefansson H,
Between a Common Single Nucleotide
Gene and Autism Spectrum Disorder.
Am J Med Genet Part B 156:633–639.
634 AMERICAN JOURNAL OF MEDICAL GENETICS PART B
reproducibility. Samples from UK and NL were genotyped in the
same lab and cross-validation of UK and German genotyping calls
were made by genotyping 12 UK samples at the German site with
perfect matching of results.
Power was calculated using the genetic power calculator (GPC)
[Purcell et al., 2003], with parameters of the protective allele
frequency (A), 0.42; prevalence, 0.01 and genotypic relative risk
(GRR) for Aa, 0.85 and AA, 0.72 which is equivalent to the best
evaluated by the AGP, namely the AGRE sample [Anney et al.,
us a non-centrality parameter (NCP) of 11.9, with 93% power to
detect a common genetic variant at a significance level (alpha) of
power fell to 85% at alpha¼0.05 and 66% at alpha¼0.01. Power
was 99% for detection of a GRR of 0.65, as in the AGP discovery
exaggerated due to scanning the entire genome for significant
The results of case–control association tests for each center are
presented inTable I,where data forASD andstrict autism areboth
presented, and Figure 1. Genotypes were checked for HWE using
http://www.oege.org/software/hwe-mr-calc.shtml (UK controls,
c21.97, P¼0.3734; Germany controls, c2¼0.95, P¼0.6219; the
Netherlands controls, c2¼1.47, P¼0.4795; Italy controls
c2¼1.08, P¼0.5827). One data set (Iceland) had genome control
data. As our data came from geographically distinct regions, we
combined the summary statistics from each center, analyzed sepa-
rately, using the meta-analysis software tool, GWAMA [genome-
wide association meta-analysis; Magi and Morris, 2010] http://
www.well.ox.ac.uk/GWAMA. Combining the association data for
all ASD subjects in our study, the GWAMA output (Table II) gave
an OR of 1.03 (95% CI 0.944–1.133) with P¼0.5. The test of
heterogeneity between samples gave a Q statistic of 9.68 (P¼0.05)
and I2¼0.587, indicating that there was moderate heterogeneity
between the samples, although there were only five different
populations. On the one hand, given that there were only five
centers, this level of heterogeneity might be noteworthy, although
The German sample reached nominal significance for ASD
(P¼0.029) and narrowly defined autism (P¼0.039). The meta-
analysis results using data from the subjects meeting strict autism
criteria were similar (Table III). Here the OR was 0.99 (95% CI
0.88–1.11) with P-value¼0.85. There was somewhat less hetero-
geneity between samples detected by GWAMA (the Q statistic was
7.05 (P¼0.133) and I2¼0.43).
The purpose of this study was to attempt to replicate a reported
genome-wide significant association between ASD and a common
genetic variant in an intron of MACROD2, rs4141463, from a
TABLE I. MACROD2 rs4141463 Genotyping Results
N (ASD¼1,170; autism¼760;
Odds ratio for C allele 95%
CURRAN ET AL.
GWAS study [Anney et al., 2010]. However, we were unable to
replicate orprovide supportforthe original association,asour OR
was close to 1, consistent with the null hypothesis. The potential
reasons for the non-replication of genetic association findings are
many, and include the four most obvious explanations, that (i) the
original association was a chance false-positive finding, (ii) the
association was caused by population stratification in the original
study, (iii) there was a technical genotyping artifact, or (iv) the
replication study was underpowered, that is, there was a lack of
statistical power [Redden and Allison, 2003]. Even with genome-
wide significant P-values of 2?10?8or lower (as in the original
study) there is the possibility of false positive association. The
wide. With such a level there is still 5% chance of finding false
positives. To avoid this possibility the requirement that genome-
wide significance should be reached, at least once, in a single study
population may be appropriate. However, this will be difficult to
achieve with current sample sizes. Population stratification seems
unlikely in the analysis by Anney et al.  since both family-
of a genotyping artifact with rs4141463; as it is not an isolated
SNP, with neighboring SNPs showing evidence of association
and it is not in a repetitive DNA segment (UCSC browser,
chr20:14,747,221–14,747,721, February 2009 (GRCh37/hg19)
a deletion hotspot [Bradley et al., 2010], although these seem too
rare to cause genotyping problems. One strand of supportive
evidence for a role for the MACROD2 gene in autism is a rare
deletion of the locus, seen in a case of Kabuki syndrome [Maas
et al., 2007], which can feature autistic-like symptoms [Ho and
Eaves, 1997; Akin Sari et al., 2008] and one individual with
schizophrenia [Xu et al., 2009], although the deletion was not seen
in 43 other patients with Kabuki syndrome [Kuniba et al., 2008].
Without clear evidence of disease association to date, MACROD2
In the manuscript by Anney et al. , rs4141463 and other
SNPs reaching significance of P<5?10?6were selected for repli-
cation in an independent sample of 1,086 ASD probands from 595
families (?50% with a strict autism diagnosis) from the Autism
Genetics Resource Exchange (AGRE) database. The association
with rs4141463 did not replicate in this sample (P¼0.13, OR 0.84
et al., 2009; Ma et al., 2009; Wang et al., 2009; Weiss et al., 2009]
found evidence for implicating MACROD2 or nearby variants in
ASD, despite each study testing hundreds of cases in multiplex
families or thousands of ASD subject cases and controls of
European ancestry. Interestingly, a key resource for the Wang,
Weiss, and Anney studies is theAGREdata resource,so these three
papers do not describe three independent pieces of information
these samples found association and some not. The reasons these
FIG. 1. Forest plot of odds ratios are shown with 95% confidence
intervals. These were generated with the program ForestPlot
(http://amchang.net/StatTools/ForestPlot_Pgm.php). Codes for
Excelplot were generated by ForestPlot, and these were then
generated and then adapted into a formal forest plot by editing
the plot preferences in Excelplot.
TABLE II. GWAMA Output for ASD
Q statistic and P-value
TABLE III. GWAMA Output for Autism (Refined Phenotype)
Q statistic and P-value
636AMERICAN JOURNAL OF MEDICAL GENETICS PART B
studies have obtained considerably differing results may be due to
genotyping differences (differing genotyping platforms), different
data cleaning procedures and statistical analyses, and to the use of
partly different sub-samples of the AGRE sampler source.
(at P<0.05) for a risk variant with a genotype relative risk of the
same order as the best estimate from Anney et al. , 0.84, and
has even greater power to detect the AGP (OR<0.56) or AGPþ
AGRE (OR<0.65)samples.However, there may stillhavebeen an
overestimation of the genetic effect in that first study (‘‘winners
curse’’), and if the true OR is closer to 1 (e.g., GRR 0.9) then the
power in our sample will be less, at 48% for alpha¼0.05. There is
also disagreement about what constitutes an adequate replication
or refutation [Chanock et al., 2007], which can range from a null
same direction as the original observation albeit not significant,
through to a GWAS-significance replication level of association at
<5?10?8. In the present study, our OR of 1.03 is significantly
higher than that of Anney et al.  and our 95% confidence
intervals for a GRR of 0.94–1.13 do not cross the original GRR of
cannot formally exclude a role for rs4141463 in risk of developing
autism. It might, for example, be a proxy for a pathogenic variant
that is rare or has varying linkage disequilibrium with rs4141463
according to geographic origin of the study population, making it
difficult to consistently replicate.
There were differences in the research design of the cohorts
studied; the AGP and AGRE samples are family trios, with control
cases, and ours was a case–control study. The diagnostic criteria
(ADI-R diagnosis of autism or ASD) and population types
(Northern European) were, however, comparable in both studies.
One cannot rule out the possibility that the original association,
despite reaching genome-wide significance, is a false positive
association. By looking closer to the study by Anney et al.
, we observe that the original finding was not supported in
their second sample (AGRE) (P¼0.13). In the overall sample
(AGPþAGREþSAGE) the association retained genome-wide
significance despite the increase in the OR from 0.56 to 0.73 due
to the increase in the overall sample size.
Several other potential common, low risk variants for autism
alleles detected by GWAS in that they have ORs of <1.3 [Pawitan
et al., 2009]. These GWAS results also appear to rule out moderate
risk common variants (i.e., increasing relative risk by twofold or
more), as is the case for most other common, complex diseases.
Three such potential loci for ASD have been identified: rs4307059
on 5p14.1, between neuronal cadherin genes CDH9 and CDH10
(SEMA5A) and bitter taste receptor (TAS2R1) genes [Weiss et al.,
2009] and MACROD2 [Anney et al., 2010]. In addition there are
many other reported associations from candidate gene analysis,
which have variable levels of evidence for association. Thus, at
present there are no strongly associated common low risk alleles
have been identified for other complex disorders, such as obesity
[Peterson et al., 2011].
Thus, a major role for common, low risk variants in autism
remains unproven. Quantitative genetic studies point towards the
involvement of many common variants, together influencing ASD
or sub-domains of ASD [Ronald et al., 2010]. Since common
variants are generally of small effect size [median OR<1.25;
explained by these, hundreds of risk variants would need to exist
[Pawitan et al., 2009], and many thousands, even hundreds of
the role of common variants will only be known once better-
powered GWAS studies are performed, and the results replicated.
subjects and 125,000 follow-up subjects (total n¼250,000) mea-
sured for BMI [Speliotes et al., 2011], and this approach has so far
that it will be difficult to determine whether rs4141463 is a true
association or not, given current sample sizes in autism genetic
studies of just a few thousand cases.
The contrary or complimentary hypothesis to the common
is under strong negative genetic selection pressure, with fecundity
Mouridsen, 1997], genetic risk variants of moderate or high effect
they may be of recent origin, for example, through de novo
mutational events [Uher, 2009]. There is further evidence from
the advanced paternal age effect seen in autism, indicative of
mutations occurring in paternal gametes [Reichenberg et al.,
2006], a classical mechanism for the generation of new deleterious
control subjects [Awadalla et al., 2010]. The best evidence for this,
however, is empirical evidence for the role of rare, largely de novo
cases. There may still be a major contribution from common risk
small effect size (GRR<1.3) and could theoretically escape nega-
moderate risk CNVs, but hypotheses on its overall genetic archi-
tecture can only be confirmed by large-scale molecular genetic
studies [Cirulli and Goldstein, 2010].
of the parents and children in the Twins Early Development Study
(TEDS), supported by a program grant (G0500079) from the UK
Medical Research Council; for the German sample the families for
their cooperation and professionals for collecting data, supported
by grants from the Deutsche Forschungsgemeinschaft, and K.
Przibilla for excellent technical assistance; Genotyping at deCODE
10-223423) and NIH grant MH071425. We also thank the kind
CURRAN ET AL.
contribution of the clinicians in the Departments of Medical
Genetics and Child and Adolescent Psychiatry of the University
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