Download association study of 37 genes suggests involvement of DDC

The World Journal of Biological Psychiatry, 2011; Early Online: 1–12
ORIGINAL INVESTIGATION
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Neurotransmitter systems and neurotrophic factors in autism:
association study of 37 genes suggests involvement of DDC
CLAUDIO TOMA1,2, AMAIA HERVÁS3, NOEMÍ BALMAÑA3, MARTA SALGADO3, MARTA
MARISTANY4, ELISABET VILELLA5, FRANCISCO AGUILERA6,
CARMEN OREJUELA6, IVON CUSCÓ2,7, FÁTIMA GALLASTEGUI2,7,
LUIS ALBERTO PÉREZ-JURADO2,7,8, RAFAELA CABALLERO-ANDALUZ9,
YOLANDA DE DIEGO-OTERO10, GUADALUPE GUZMÁN-ALVAREZ11,
JOSEP ANTONI RAMOS-QUIROGA12,13, MARTA RIBASÉS12,14, MÒNICA BAYÉS15 &
BRU CORMAND1,2,16
1Departament
de Genètica, Facultat de Biologia, Universitat de Barcelona, Spain, 2Biomedical Network Research Centre on
Rare Diseases (CIBERER), Spain, 3Child and Adolescent Mental Health Unit, Hospital Universitari Mútua de Terrassa,
Spain,4Developmental Disorders Unit (UETD), Hospital Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain, 5Hospital
Psiquiàtric Universitari Institut Pere Mata, IISPV, Universitat Rovira iVirgili, Reus, Spain, 6Intellectual Disabilities and
Developmental Disorders Research Unit (UNIVIDD), FundacióVillablanca, Grup Pere Mata, Reus, Spain, 7Unitat de Genètica,
Universitat Pompeu Fabra, Barcelona, Spain, 8Programa de Medicina Molecular i Genètica, Hospital UniversitariVall d’Hebron,
Barcelona, Spain, 9Autism Unit, Department of Psychiatry, Universidad de Sevilla, Spain, 10Laboratorio de Investigación,
Fundación IMABIS, Hospital Carlos Haya, Málaga, Spain, 11Unidad de Psiquiatría Infanto-Juvenil. Hospital Clínico
UniversitarioVirgen de laVictoria de Málaga, Spain, 12Department of Psychiatry, Hospital UniversitariVall d’Hebron, Barcelona,
Spain, 13Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Spain, 14Psychiatric Genetics Unit,
Vall d'Hebron Research Institute (VHIR), Barcelona, Spain. 15Centro Nacional de Análisis Genómico (CNAG), Parc Científic de
Barcelona (PCB), Spain, 16Institut de Biomedicina de la Universitat de Barcelona (IBUB), Spain
Abstract
Objectives. Neurotransmitter systems and neurotrophic factors can be considered strong candidates for autism spectrum
disorder (ASD). The serotoninergic and dopaminergic systems are involved in neurotransmission, brain maturation and
cortical organization, while neurotrophic factors (NTFs) participate in neurodevelopment, neuronal survival and synapses formation. We aimed to test the contribution of these candidate pathways to autism through a case–control association study of genes selected both for their role in central nervous system functions and for pathophysiological evidences.
Methods. The study sample consisted of 326 unrelated autistic patients and 350 gender-matched controls from Spain. We
genotyped 369 tagSNPs to perform a case-control association study of 37 candidate genes. Results. A significant association
was obtained between the DDC gene and autism in the single-marker analysis (rs6592961, P ⫽ 0.00047). Haplotype-based
analysis pinpointed a four-marker combination in this gene associated with the disorder (rs2329340C–rs2044859T–rs6592961A–rs11761683T, P ⫽ 4.988e-05). No significant results were obtained for the remaining genes after applying
multiple testing corrections. However, the rs167771 marker in DRD3, associated with ASD in a previous study, displayed a
nominal association in our analysis (P ⫽ 0.023). Conclusions. Our data suggest that common allelic variants in the DDC gene
may be involved in autism susceptibility.
Key words: Genetics, autistic disorder, serotonin, dopamine, DDC gene
Introduction
Autism is a childhood-onset neurodevelopmental disorder characterised by impairment in reciprocal social
interactions, communication and repetitive and stereotyped behavioural patterns (Lord et al. 2000).
Autism is part of a larger group of neuropsychiatric
Correspondence: Bru Cormand, PhD, Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Av. Diagonal 645, edifici
annex, 3ª planta, 08028 Barcelona, Spain. Tel: ⫹34 93 402 1013. Fax: ⫹34 93 403 4420. E-mail: [email protected]
(Received 6 February 2011; accepted 22 June 2011)
ISSN 1562-2975 print/ISSN 1814-1412 online © 2011 Informa Healthcare
DOI: 10.3109/15622975.2011.602719
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2
C. Toma et al.
disorders defined as PDDs (pervasive developmental
disorders) that also include Asperger syndrome,
childhood disintegrative disorder and pervasive developmental disorder not otherwise specified (PDDNOS). The disorder is approximately four times more
frequent in males than in females. Prevalence estimations are around 0.2% for autism and 0.6–0.7% for
PDDs, making it one of most prevalent disorders in
childhood (Fombonne 2009). Although twin and
family studies provide strong evidence for a genetic
basis in PDD, only a few rare and highly penetrant
mutations have been found to be involved in autism
in several synaptic genes: NLGN3, NLGN4, NRXN1,
SHANK3, SHANK2 and PTCHD1 (Jamain et al.
2003; Durand et al. 2007; Szatmari et al. 2007; Noor
et al. 2010; Pinto et al. 2010). These genes have also
been associated with other neuropsychiatric disorders. It is likely that the autistic phenotype results
from the combined effect of penetrant rare variants,
such as structural variants or point mutations, and
common susceptibility alleles of modest effect.
Recent findings support the hypothesis that synaptogenesis is disrupted in autism (Bourgeron 2009),
although other pathways may also have a role in
autism susceptibility. In this regard, neurotransmission systems and neurotrophic factors have been
proposed to be involved in the disorder on the basis
of numerous pathophysiological and genetic evidences (Pardo and Eberhart 2007; Cuscó et al. 2009;
Nickl-Jockschat and Michel 2010).
Serotonin and dopamine are neurotransmitter
monoamines involved in modulating adult cortical
plasticity and known to have a critical role in early
cortex development by regulating proliferation,
migration and neuronal differentiation (Vitalis and
Parnavelas 2003). Serotonin acts via seven families
of receptors (5-HT1–5-HT7) and is related to sleep,
mood, memory, learning, muscle contraction homeostasis and endocrine functions (Haavik et al. 2007).
Dopamine acts through five receptors (D1–D5) and
modulates multiple brain functions, including reward
response, motivation, memory, attention, problem
solving and is critical to control voluntary movements (Haavik et al. 2007). The metabolism of these
two neurotransmitters is complex and tissue-type
specific, both sharing the biosynthethic enzyme
DOPA decarboxylase (DDC) and the catabolic
enzymes monoamine oxidase A (MAOA) and B
(MAOB).
Many findings show that both the serotoninergic
and the dopaminergic systems may be considered as
strong candidate pathways for autism: First, elevated
levels of serotonin in blood and urine have been
observed in approximately one-third of autistic individuals (Cook and Leventhal 1996; Croonenberghs
et al. 2000; Burgess et al. 2006), whereas normal
peripheral levels of dopamine have been reported in
the majority of studies performed so far (McDougle
et al. 2005). Second, selective serotonin reuptake
inhibitors (SSRIs) and dopamine receptor antagonists have a role in reducing specific associated
symptoms in autism: aggression, self-injury and
compulsive behaviours (Nikolov et al. 2006). And
third, neuroimaging studies with positron emission
tomography (PET) have shown abnormal asymmetry of serotonin synthesis in frontal, temporal and
parietal cortex in autistic individuals compared to
controls (Chandana et al. 2005). In addition, the
dopaminergic activity seems to be altered in the
anterior, medial and prefrontal cortex of autistic
individuals (Rumsey and Ernst 2000).
The serotonin transporter gene SLC6A4-HTT is
one of the most studied genes in autism, with evidence of linkage to 17q11–12 reported in several
genome-wide scan studies for autism (Auranen et al.
2002; Yonan et al. 2003; McCauley et al. 2005). Two
variations, an insertion/deletion polymorphism in the
promoter region and a Variable Number of Tandem
Repeats (VNTR) in intron 2 have been analysed in
many autistic samples through case-control and
family-based association studies (Huang and Santangelo 2008). The role of this gene in autism susceptibility is still unclear due to discrepancies among
different studies, although a recent meta-analysis
failed to find an overall association (Huang and
Santangelo 2008). Other serotonin-related genes,
such as HTR1B, HTR2A, HTR3A and HTR5A, that
encode the serotonin 5HT1B, 5HT2A, 5HT3 and
5HTR5A receptors, have been proposed to contribute to autism susceptibility (Cho et al. 2007; Coutinho
et al. 2007; Orabona et al. 2008; Anderson et al.
2009) as well as genes encoding the dopamine receptors D1 and and D3 (Hettinger et al. 2008; de Krom
et al. 2009).
Neurotrophic factors (NTFs) and their receptors
represent another group of candidate genes for autism.
NTFs are crucial during neurodevelopment, regulating many functional and structural aspects of the central nervous system (CNS), including differentiation,
neuronal survival, synaptogenesis, synaptic plasticity
and axonal and dendritic outgrowth (Reichardt 2006).
Several studies suggest that NTFs may be at the
basis of the pathophysiology of several neuropsychiatric disorders, such as schizophrenia and depression
(Durany and Thome 2004; Hashimoto et al. 2005;
Otsuki et al. 2008). The potential contribution of
NTFs to autism has also been investigated. Interestingly, some reports described elevated levels of
BDNF and NTF4/5 and low levels of NT3 in serum
of autistic patients, suggesting that the corresponding
genes may be deregulated in autism (Miyazaki et al.
2004; Connolly et al. 2006; Nelson et al. 2006).
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Association between the DDC gene and autism
However, it is still unclear whether the changes
observed in NTFs reflect a primary pathogenic
mechanism or are secondary to cortical abnormalities in ASD. Recently, genetic studies have also provided evidence for the involvement of NTFs in
autism: association with BDNF has been reported in
two independent studies and a common variant of
NTRK1 has been associated with autistic traits
(Nishimura et al. 2007; Chakrabarti et al. 2009;
Cheng et al. 2009). These data support the hypothesis that neuronal survival, differentiation and growth
may be at the basis of autism aetiopathology.
The aim of this study was to identify common
alleles of modest effect involved in autism. We genotyped 369 single nucleotide polymorphisms (SNPs)
that tag most allelic variability of 37 functional candidate genes involved in the serotoninergic and dopaminergic neurotransmission or encoding neurotrophic
factors and their receptors to perform a populationbased association study in 326 ASD patients and 350
gender-matched controls from Spain.
Methods
Subjects
The autism cohort under study included 326 individuals of singleton families that met DSM-IV-TR
criteria for autism, Asperger disorder and PDDNOS based on ADI-R (Autism Diagnostic Interview-Revised) and ADOS-G (Autism Diagnostic
Observation Schedule-Generic) diagnostic instruments (Lord et al. 1994, 2000a, 2000b) (see Table
I). The sample was recruited from different Hospitals of Northern and Southern Spain (Catalonia
and Andalusia). Cytogenetic abnormalities and
positive Fragile X test were considered as exclusion
criteria. The control sample consisted of 350
healthy donors, sex-matched with the case sample,
recruited from the Blood and Tissue Bank at
Hospital Universitari Vall d’Hebron (Barcelona).
To minimize ethnic heterogeneity we have included
only Spanish Caucasian cases and controls in our
study. The study was approved by the relevant
ethical committee of each participating institution
and written informed consent was obtained from
all parents/guardians.
DNA isolation and quantification
Genomic DNA was isolated from peripheral blood
lymphocytes using the salting out method (Miller et
al. 1998) or magnetic bead technology with the
Chemagic Magnetic Separation Module I and the
Chemagic DNA kit, according to the manufacturer’s
recommendations (Chemagen AG, Baesweiler,
Germany). The double-stranded DNA concentrations
of all samples were determined on a Gemini XPS
fluorometer (Molecular Devices, Sunnyvale, CA,
USA) using the PicoGreen dsDNA Quantitation Kit
(Molecular Probes, Eugene, OR, USA), following the
manufacturer's instructions.
Selection of genes and SNPs
We selected 38 functional candidate genes encoding the serotonin receptors (5HT1A, 5HT1B,
5HT1D, 5HT1E, 5HT1F, 5HT2A, 5HT2B, 5HT2C,
5HT3A, 5HT3B, 5HT4, 5HT5A, 5HT6, 5HT7), the
serotonin and dopamine transporters (SLC6A4 and
SLC6A3), enzymes involved in the serotonin and
dopamine metabolic pathways (TH, TPH1, DDC,
MAOA, MAOB, COMT and DBH), the dopamine
receptors (DRD1, DRD2, DRD3, DRD4, DRD5),
neurotrophic factors (NGF, BDNF, NTF3, NTF4/5,
CNTF) and their receptors (NTRK1, NTRK2,
NTRK3, NGFR, CNTFR) (Supplementary Table
S1 available online).
The SNPs selection was based on genetic coverage criteria, by considering linkage disequilibrium
(LD) patterns within the candidate genes. SNPs
covering each gene plus 3–5 kb flanking sequences
were picked from the CEU panel of the HapMap
database (www.hapmap.org, release 20). We used the
LD-select software (droog.gs.washington.edu/ldSelect.html) to evaluate LD of the genomic regions in
order to minimize redundancy between the selected
SNPs (Carlson et al. 2004). A total of 400 tagSNPs
were selected with the following criteria: r2 ⬍ 0.85
from any other SNP according to CEU HapMap
data and a minor allele frequency (MAF) ⬎ 0.15 for
genes with less than 15 tagSNPs and MAF ⬎ 0.25
for those genes with more than 15 tagSNPs in the
serotoninergic and dopaminergic systems. However,
we considered a MAF ⬎ 0.10 for genes encoding
Table I. Description of autism spectrum disorder (ASD) patients included in our study.
Males
Mental retardation∗
Average age (years)
∗Mean
3
Autism (56%)
Aperger (29%)
PDD-NOS (15%)
All ASD
85%
73%
17
86%
0%
10
72%
74%
27
83%
51%
17
IQ ⬍ 70. PDD-NOS, pervasive developmental disorder not otherwise specified.
4
C. Toma et al.
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neurotrophic factors and their receptors as they were
part of a previous design that followed distinct criteria
(Ribasés et al. 2008) (Supplementary Table S1 available online). Some additional non-synonymous SNPs
(nsSNPs) were included in our selection as potential
functional polymorphisms: rs1007211 (NTRK1 exon
1, NP_001012331.1:p.Gly18Glu), rs1058576 (5HT2A
exon 3, NP_000612.1:p.Ser421Phe), rs6318 (5HT2C
exon 4, NP_000859.1:p.Cys23Ser), rs2228673
(SLC6A4 exon 5, NP_001036.1:p.Lys201Asn) and
rs6265 (BDNF exon 2, NP_001137277.1:p.Val66Met).
Plex design, genotyping and quality control
A total of 400 tagSNPs were initially selected in our
study, of which 31 did not pass through the SNPlex
design pipeline (ms.appliedbiosystems.com/snplex/
snplexStart.jsp), resulting in a design rate of 92%.
Eight SNPlex genotyping assays including 369
SNPs were designed: two for the serotoninergic system (48 and 47 SNPs), two for the dopaminergic
system (46 and 45 SNPs) and four for the neurotrophic factors and their receptors (45, 48, 46
and 44 SNPs). The possible presence of population
stratification that could lead to false positive results
in the population-based association study was tested
by genotyping an additional plex of 48 unlinked
SNPs distributed across different chromosomes
and located at least 100 Kb distant from known
genes (Sanchez et al. 2006).
Genotyping was performed at the Barcelona node
of the National Genotyping Center (CeGen, www.
cegen.org) using the SNPlex technology (Applied
Biosystems, Foster City, CA, USA) (Tobler et al.
2005). Two CEPH samples (NA11992 and
NA11993) were included in the different genotyping
assays, and a concordance rate of 100% with HapMap data was obtained. In addition, no differences
were found in the genotypes of two replicas. No
heterozygote calls were obtained in SNPs of candidate X-linked genes (5HT2C, MAOA, MAOB) in the
male sample.
deviation from Hardy–Weinberg equilibrium (HWE;
threshold set at P ⬍ 0.01 in our control population).
The only SNP that was genotyped in the DRD4 gene
was excluded from the statistical analysis because it
did not overcome the quality control filters.
The analysis of study power was estimated post hoc
with the Power Calculator for Genetic Studies software (sph.umich.edu/csg/abecasis/CaTS) (Skol et al.
2006), assuming an odds ratio (OR) of 1.5, disease
prevalence of 0.07, significance level (α) of 0.05 and
the minimum MAF value in our sample, 0.10, under
the additive model.
Potential genetic stratification was assessed using
the STRUCTURE v2.3 software (Pritchard et al.
2000) by analysing 46 unlinked SNPs in HWE out
of the 48 that were genotyped. The analysis was performed under the admixture model, with a length of
the burning period and a number of MCMC repeats
of 100,000 and performing five independent runs at
each K value (from 1 to 5), with K referring to the
number of groups to be inferred.
Single-marker analysis
The analysis of HWE and the case-control association study were performed with the SNPassoc R
package (Gonzalez et al. 2007). For the case–control
study we analyzed all single markers under the additive model using the Cochran–Armitage Trend Test
(ATT) (Supplementary Table S1 available online). In
our analysis we considered also the dominant (11 vs.
12 ⫹ 22) and recessive (11 ⫹ 12 vs. 11) models only
for those SNPs that reached nominal P-values in the
ATT test. Chromosome X markers were analyzed
separately with an allelic test using the Haploview
v4.2 software (Barrett et al. 2005). A Q-Q plot was
generated with the ggplot2 R library (Wickham
2009). For the multiple comparison correction, we
considered all tests performed and assumed a false
discovery rate (FDR) of 15% with the Q-value R
library (Storey 2002), which corresponds to a significance threshold of P ⬍ 4.7e-04.
Multiple-marker analysis
Statistical analysis
All the individuals with less than 85% of successful
genotyping rate were excluded from the analysis that
finally included 326 autistic patients and 350 controls. From the 369 SNPs that were genotyped, 307
were finally analyzed in the population-based association study, whereas 62 SNPs (17%) were excluded
for one of the following reasons: more than 15%
missing genotypes, r2 ⬎ 0.85 from any other studied
SNP in our control sample, monomorphic SNPs and
To minimize multiple testing and type I errors (α),
we decided a priori to restrict the haplotype-based
association study to those genes associated with
autism in the single markers analysis after FDR correction. We ascertained the best two-marker haplotypes from all possible combinations, rather than
simplifying the study only to physically contiguous
SNPs. Likewise, additional markers (up to four)
were added in a stepwise manner to the initial twoSNP haplotype. The risk haplotype was identified
Association between the DDC gene and autism
among those haplotypes defined by two-, threeor four-markers showing the highest OR values.
In all cases, significance was estimated using
10,000 permutations with the UNPHASED 3.0
software (Dudbridge 2003). Since the expectationmaximization algorithm implemented in the
UNPHASED software does not accurately estimate
low haplotype frequencies, haplotypes with frequencies ⬍ 0.05 were excluded.
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Results
We genotyped 369 tagSNPs in 326 autistic patients
and 350 controls to assess the potential role in
autism of 38 candidate genes encoding proteins
involved in the serotoninergic and dopaminergic
neurotransmission and also neurotrophic factors
and their receptors. After quality control procedures, 62 tagSNPs were discarded from the statistical analysis for the following reasons: 32 SNPs with
genotyping call rate ⬍ 85%, 14 SNPs that were
in strong LD in the control group with other SNPs
in the same candidate gene (r2 ⬎ 0.85), 10 SNPs
with MAF ⬍ 0.1 or monomorphic, 6 SNPs showing
significant deviation from HWE in the control sample (P ⬍ 0.01) (Supplementary Table S1 available
online). These filters left the DRD4 gene out of the
analysis, so the final number of genes included in
the case-control study was 37.
The statistical power of our sample was 71% under
the additive model. Population stratification was
5
excluded using the Structure software on 46 unlinked
SNPs that were genotyped in cases and controls
(Supplementary Table S2 available online).
Single-marker analysis
In summary, 676 individuals were successfully analysed for 307 tagSNPs that finally passed through the
quality control filters with an average genotyping
efficiency of 97%. A quantile–quantile plot representation of all the results under the additive model is
shown in Figure 1.
The results of our case-control analysis found
nominal associations (P ⬍ 0.05) under the additive
model in 21 SNPs located in the following 10 genes:
DDC (rs1982406, rs6592961, rs3823674), COMT
(rs2020917, rs933271), DRD1 (rs251937), DRD2
(rs4630328, rs4245146, rs17529477), DRD3
(rs167771), BDNF (rs1491851), NTF3 (rs6489630,
rs7956189), NTF4/5 (rs17206784), NTRK3
(rs7176520, rs3784406, rs12440144, rs1435403)
and CNTFR (rs2381164, rs2381165, rs2274592).
The P-values of these SNPs are shown in Table II,
together with those under the recessive and the
dominant models. However, after applying corrections for multiple testing using a 15% FDR
(P ⬍ 4.7e-04) only the rs6592961 marker (P ⫽ 4.7e04, OR ⫽ 1.79 [1.29–2.49]) in the DDC gene
remained significant under the dominant model
(Figure 2). No SNP remained significant after the
restrictive Bonferroni correction.
Multiple-marker analysis
The analysis of possible risk haplotypes in our study
was considered only for the DDC gene, the only one
in which a marker remained associated after correcting
for multiple testing. The LD patterns observed in our
sample were similar to those in the HapMap CEU
sample, indicating that the tagSNPs for this study were
properly selected. The haplotype analysis performed in
the DDC gene tested all possible SNP combinations
and identified a risk haplotype of four markers
(rs2329340–rs2044859–rs6592961–rs11761683)
associated with autism (best adjusted P ⫽ 9.9e-05)
(Table III). The allelic combination C-T-A-T was overrepresented in the autistic sample (OR ⫽ 2.44, 95%
CI ⫽ 1.55–3.83, Table III), while the haplotype defined
by the allelic combination C-T-G-T was more frequent
in controls (OR ⫽ 0.65, 95% CI ⫽ 0.50–0.83).
Figure 1. Quantile–quantile plot of the 307 P-values obtained
in the association study of ASD patients versus controls. The
most significant result (SNP rs6592961 in the DDC gene) is
indicated.
Discussion
Several lines of evidence suggest that genes of the
serotoninergic and dopaminergic systems and
rs167771
rs1491851
rs6489630 218 (70)
rs7956189 247 (77)
rs17206784 98 (30)
rs7176520
rs3784406
rs12440144
rs1435403
rs2381164 123 (39)
rs2381165 212 (67)
rs2274592 163 (50)
DRD3 (Dopamine)
BDNF (Neurotrophins)
NTF3 (Neurotrophins)
NTF4/5 (Neurotrophins)
NTRK3 (Neurotrophins)
CNTFR (Neurotrophins)
94 (30) 11 (4)
4 (1)
2 (1)
312 222 (64)
320 243 (71)
(49)
(50)
(40)
(38)
63
66
21
26
(21)
(20)
(7)
(8)
312
321
318
322
129
124
212
229
(37)
(35)
(62)
(65)
148 (47) 47 (14) 318 150 (44)
98 (31) 6 (2)
316 263 (77)
137 (42) 23 (8) 323 211 (60)
154
159
126
121
156 (48) 70 (22) 324 130 (37)
90 (29)
71 (22)
65 (19)
305 259 (74)
158 (49) 75 (23) 320
12
22
28 (8)
40 (12)
27 (8)
28 (8)
12 (3)
77 (22)
(48)
(49)
(33)
(30)
164 (47)
75 (22)
118 (34)
168
172
115
102
164 (47)
115 (33)
94 (27)
186 (53)
82 (23)
30 (9)
5 (1)
20 (6)
52 (15)
54 (16)
17 (5)
19 (5)
56 (16)
12 (3)
7 (2)
99 (28)
9 (3)
177 (51) 77 (22)
181 (52) 103 (29)
171 (49) 58 (16)
160 (46)
159 (45)
132 (37)
124 (35)
83 (24)
177 (51)
344
343
349
349
350
344
350
350
349
344
350
350
349
350
350
350
350
350
350
350
350
Sum
OR (95% CI)
0.76 (0.55–1.04)
0.769 (0.56–1.04)
1.41 (1.03–1.93)
1.33
1.28
1.38
1.59
(0.96–1.85)
(0.93–1.77)
(1.01–1.88)
(1.16–2.16)
1.36 (0.98–1.87)
0.75 (0.54–1.04)
0.71 (0.50–1.00)
0.61 (0.42–0.88)
0.03334 1.22 (0.89–1.67)
0.00881 1.61 (1.14–2.27)
0.01636 1.50 (1.10–2.03)
0.029
0.047
0.042
0.0040
0.022
0.039
0.030
0.012
0.02298 1.49 (1.06–2.09)
0.01306 0.69 (0.49–0.97)
0.02752 0.62 (0.43–0.90)
0.03048 0.72 (0.52–0.99)
0.017
0.038
0.01
0.036
1.39 (1.02–1.90)
0.00129 1.79 (1.29–2.49)
0.00574 0.62 (0.45–0.87)
P value
OR (95% CI)
P value
Genotype 11 ⫹ 12 vs. 22
0.15283
0.44245
0.05953
0.24395
0.14544
0.01293
0.08097
0.04696
0.69
0.70
0.73
0.65
(0.46–1.03)
(0.47–1.04)
(0.38–1.42)
(0.35–1.20)
0.19837 0.55 (0.33–0.89)
0.00613 0.76 (0.23–2.52)
0.00917 0.79 (0.42–1.47)
0.07734
0.12798
0.04088
0.00338
0.05868 0.69 (0.46–1.02)
0.01512
0.65888
0.46193
0.07315
0.08311
0.35839
0.17042
0.06221
0.08847 2.74 (0.87–8.59)
0.07173
0.05521 3.30 (0.681–16.01) 0.11643
0.00782 1.28 (0.91–1.82)
0.01882 0.70 (0.28–1.72)
0.03259 1.47 (0.98–2.19)
0.01336 1.22 (0.86–1.73)
0.04580 1.39 (0.89–2.17)
0.09118 2.57 (1.19–5.54)
0.09697 1.61 (0.939–2.79)
0.02825 0.59 (0.34–0.99)
0.03621 0.738 (0.431–1.26) 0.26493
0.00047a 0.730 (0.33–1.60) 0.43214
0.00579 1.399 (0.94–2.07) 0.09516
P value
Genotype 11 vs 12 ⫹ 22
Only those markers with a nominal association (P ⬍ 0.05) after applying the Cochran–Armitage’s trend test are shown; association results under dominant and recessive models are also displayed.
CI, Confidence Interval; OR, Odds Ratio.
aStatistically significant P value after applying a FDR (false discovery rate) of 15% (P ⬍ 0.00047).
95 (30)
96 (30)
171 (53)
175 (54)
87 (28)
200 (66)
142 (49) 47 (16) 291 95 (27)
143 (48) 76 (25) 300 66 (19)
134 (45) 37 (13) 296 121 (35)
275 162 (46)
rs4630328 102 (35)
rs4245146 81 (27)
rs17529477 125 (42)
120 (44) 9 (3)
DRD2 (Dopamine)
146 (53)
rs251937
DRD1 (Dopamine)
11
128 (43) 22 (7) 298 151 (43)
121 (42) 36 (12) 290 191 (55)
Sum
rs2020917 148 (50)
rs933271
133 (46)
22
COMT (Dopamine)
12
Genotypes controls N (%)
121 (41) 31 (11) 294 198 (57)
107 (35) 14 (5) 302 255 (73)
136 (46) 50 (17) 298 96 (27)
11
Genotypes cases N (%)
DDC (Dopamine/Serotonin) rs1982406 142 (48)
rs6592961a 181 (60)
rs3823674 112 (38)
Gene (System)
SNP
(P ⬍ 0.05)
Table II. Case–control association study in 326 autistic patients and 350 sex-matched controls from Spain.
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6
C. Toma et al.
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Association between the DDC gene and autism
7
Figure 2. Genomic structure of the DDC gene, with coding exons indicated as black boxes. All tagSNPs included in our study are listed
above. The SNPs found nominally associated (P ⬍ 0.05) are indicated with an asterisk (∗); the single SNP showing association after 15%
FDR correction for multiple testing (P ⬍ 4.7e-04) is indicated with a double asterisk (∗∗). The SNPs that form the risk haplotype as
determined with UNPHASED are underlined.
neurotrophic factors and their receptors represent
good candidates for autism susceptibility. Numerous
association studies have been performed in past years
in selected candidate genes of these systems, but
results are controversial. Here, we have designed a
comprehensive gene-system association study including 37 genes that participate in these pathways to identify common allelic risk variants. We analyzed 307
SNPs in 326 autistic patients and 350 sex-matched
controls, all of them Spanish and Caucasian to minimize the possible effects of genetic heterogeneity. The
SNPs have been selected to cover the target genes in
terms of LD.
The results of our case–control association study
identified a single SNP (rs6592961) in the DOPA
decarboxylase gene (DDC, 7p12.2) that remained
significantly associated with autism after correction
for multiple tests. A previous family-based study did
not find association between autism and two polymorphisms (rs11575267 and rs3837091) at 5’UTR
of the DDC gene, although the sample size was small
(90 trios) and gene coverage was limited to the promoter region (Lauritsen et al. 2002). The DDC gene
encodes the enzyme that catalyzes the last step of
the biosynthesis of three essential neuromolecules:
the decarboxylation of L-3,4 dihydroxyphenylalanine (L-DOPA) to dopamine, 5-hydroxytryptophan
(5HTP) to serotonin and L-tryptophan to tryptamine. Hence, it represents a good candidate gene for
autism: the gene product is crucial to synthesize
serotonin and dopamine, and interestingly both
neurotransmitter systems have been proposed to be
altered in autism at different levels.
Noteworthy, some evidences indicate that the
serotoninergic and dopaminergic neurotransmitter
systems are involved in aggressive behaviours (Chen
et al. 2005; Seo et al. 2008). In this regard, drugs
such as the atypical antipsychotics (AAPs) and the
selective serotonin reuptake inhibitors (SSRIs), acting on the dopaminergic and serotoninergic systems,
are widely used in autism to target symptoms like
aggression or self-injury and compulsive rituals
(Nikolov et al. 2006). Recently, DDC has been suggested to be involved in anger and aggression traits
in suicide behaviours (Giegling et al. 2008). Positive
associations of this gene with other neuropsychiatric
disorders, such as Bipolar Affective Disorder
(BPAD) and Attention-Deficit/Hyperactivity Disorder (ADHD) have also been reported (Børglum
et al. 2003; Ribasés et al. 2009). Replication studies
performed in several Caucasian populations make
the association of DDC with ADHD consistent
(Lasky-Su et al. 2008). Interestingly, autism and
ADHD are known to share some clinical features.
Rommelse et al. (2010) reported that 20–50% of
children with ADHD fulfill diagnostic criteria for
autism spectrum disorders (ASD) and 30–80% of
ASD children meet criteria for ADHD. In addition,
in both autism and ADHD, aggressive and selfinjury traits are commonly described.
A wide range of mutations that abolish the activity
of DDC have been described in aromatic L-aminoacid decarboxylase deficiency (AADCD), a recessively inherited disease with a severe neurological
condition characterized by developmental delay,
oculogyric crises and autonomic dysfunction (Lee
et al. 2009). To our knowledge, no rare variants in
the DDC gene with a potential etiologic role have
been described in any of the neuropsychiatric disorders in which association has been reported, and no
further evidence arises from CNVs studies. However,
some reports described chromosomal aberrations in
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8
C. Toma et al.
the region encompassing the DDC gene: a duplication (dup(7)p11.2–p12) in a three-generation family,
in which patients show mild cognitive deficiencies
and limited IQ (Leach et al. 2007) and a de novo
inverted duplication of 7p11.2–p14.1 in a patient
that meets diagnostic criteria for autism (Wolpert et
al. 2001). All these evidences suggest that common
variants of modest effect in the DDC gene may be
involved in the genetics of autism.
Association studies in autism have been performed
in the past on several candidate genes included in
the present analysis, but results did not clearly implicate any of them. These previous studies were performed in one or few candidate genes. Although
different populations and statistical approaches were
used, we compared all the positive findings obtained
by several association studies with those obtained in
our target systems to determine if coincident results
in independent samples may pinpoint one or more
susceptibility genes in autism (Table IV). Nominal
associations have been found in our analysis in three
genes previously associated with autism: DRD1
(rs251937, P ⫽ 0.017) (Hettinger et al. 2008), DRD3
(rs167771, P ⫽ 0.023) (de Krom et al. 2009) and
BDNF (rs1491851, P ⫽ 0.012) (Cheng et al. 2009),
although only in one case, DRD3, we replicated
exactly the same SNP (rs167771).
In this regard, de Krom et al. (2009) investigated
132 candidate genes for autism in a two-stage design
association study. SNP rs167771 was the only marker
showing association in a first Dutch autistic sample
of 136 individuals (P ⫽ 2.0e-04) and in a second
British sample of 125 individuals (P ⫽ 0.0011). In
our study we also found (nominal) association with
this marker. The replication in several European
cohorts suggests that DRD3 may also be involved in
autism spectrum disorders. The DRD3 gene encodes
the subtype D3 of the dopamine receptor, highly
expressed in brain and involved in cognitive, emotional and endocrine factors. Recently, association
studies have been performed to elucidate the role of
this gene also in schizophrenia and major depression
(Light et al. 2006; Domínguez et al. 2007; Nunokawa
et al. 2010). Interestingly, risperidone and AAPs,
that act as agonists of the dopamine receptor D3, are
used in autism to alleviate manifestations such as
aggression, self-injury, compulsive and repetitive
behaviors (Nikolov et al. 2006). Noteworthy, the
rs167771 SNP has also been associated with extrapyramidal symptoms in patients treated with risperidone (Gassó et al. 2009). Recently, Allen-Brady
et al. (2009) performed a high-density genome-wide
linkage analysis in an extended pedigree with autism.
In this study suggestive linkage was detected in five
genomic regions that include the 7p14.1–p11.22 and
3q13.2–q13.31 loci, where DDC and DRD3 map.
However, these two regions do not represent the top
linkage regions replicated by several autism consortia (Abrahams and Geschwind 2008).
Both rs6592961 (DDC) and rs167771 (DRD3)
are intronic polymorphisms located in poorly conserved regions, although rs6592961 is placed in a
potential regulatory region identified by ESPERR
(Evolutionary and Sequence Pattern Extraction
through Reduced Representations, www.bx.psu.
edu/projects/esperr) (Taylor et al. 2006). In both
cases the minor allele is associated with autism.
However, no data are available to clarify whether
these alleles have functional effects or are rather in
linkage disequilibrium with the actual risk alleles.
For the two markers, no differences in the MAF
values were observed among the different groups of
ASD (Autism, Asperger and PDD-NOS) when
compared to the group of controls (data not shown).
We did not re-sequence the coding or regulatory
regions of the DDC gene in our sample, so it is
possible that we have missed novel variants involved
in the disease. In our study we achieved a reasonable SNP coverage, although we cannot exclude the
presence of other variants involved in the susceptibility to autism not captured by our SNPs
selection.
Table III. Haplotype analysis of 11 SNPs in 326 autistic patients and 350 controls in the DDC gene using the UNPHASED software.
Marker haplotype
5-8
5-8-10
2-5-8-10a
Haplotypes 2-5-8-10a
C-C-G-T
C-T-A-T
C-T-G-T
T-C-G-C
T-C-A-C
Global P value
Risk allele combinations
Risk haplotype P value
(adjusted P value)
Risk haplotype
OR (CI)
0.00038
0.000697
0.000087
Cases (%)
85 (18.8)
54 (12)
181 (40)
80 (17.7)
52 (11.5)
T-A
T-A-T
C-T-A-T
Controls (%)
101 (16.1)
33 (5.3)
317 (50.6)
120 (19.2)
55 (8.8)
0.00054 (0.0012)
0.0005943 (0.0019)
0.000049 (0.000099)
Haplotype specific P value
0.19
0.000049
0.00057
0.04
0.08
1.66 (1.24–2.19)
2.02 (1.32–3.10)
2.44 (1.55–3.83)
aMarker Haplotype: 2-rs2329340; 5-rs2044859; 8-rs6592961; 10-rs11761683. Best multiple marker combination is indicated in bold.
CI, confidence interval; OR, odds.
2
3
11
5
4
4
SER
SER
SER
SER
SER
DOP
DOP
DOP
NER
NER
HTR1B
HTR2A
HTR3A
HTR5A
SLC6A4
DRD1*
DRD3*
MAOA
BDNF*
NTRK1
rs5906883–rs1137070–
rs3027407 (H)
rs56164415
6337
5-HTTLPR and
STin2VNTR
rs265981
rs4532
rs167771
rs1800883
rs1150220
rs11568817–rs130057–
rs130058–rs6296 (H)
rs6311–rs6313 (H)
Marker/s associated
P ⫽ 0.007 CC
P ⫽ 0.013 CC
P ⫽ 0.00162 (P value
corrected) CC
P ⫽ 0.001 (global test)
CC
P ⫽ 0.02 CC
P ⫽ 0.018 (P value
corrected) CC
252 (Brazialian EA)
P ⫽ 0.036 (global test)
FB
P ⫽ 0.0028 (global test)
FB
P ⫽ 2.0e–04 (global test)
FB
P ⫽ 0.0088 (global test)
FB
Several studies
124 (Chinese)
174 (British)
151 (Korean)
261 (Dutch-British)
112 (American)
Several populations
186 (Portuguese)
403 (American EA)
126 (korean)
Cases (Ethnicity)
P value
Cheng et al. (2009)
Chakrabarti et al. (2009)
Yoo et al. (2009)
de Krom et al. (2009)
Hettinger et al. (2008)
Huang et al. (2008)
Coutinho et al. (2007)
Anderson et al. (2009)
Cho et al. (2007)
Orabona et al. (2008)
Ref.
6
9
2
7
7
2
5
4
18
2
No. of SNPs
per gene
NC
NC
NC
rs11749676r (P ⫽ 0.98)
rs11749676r (P ⫽ 0.98)
rs167771 (P ⫽ 0.023)
NC
NC
NC
rs130058 (P ⫽ 0.53);
rs6296 (P ⫽ 0.86)
NC
SNP (P value)
Replication in our study
SER, serotoninergic system; DOP, dopaminergic system; NER, neurotrophic factors and their receptors; H, haplotype; FB, family-based association study; CC, case–control association study;
EA, European ancestry; NC, markers not considered in our study.
*Gene found nominally associated in our single-marker association study: DRD1, rs251937 (P ⫽ 0.017); DRD3, rs167771 (P ⫽ 0.023); BDNF, rs1491851 (P ⫽ 0.012)
rWhen the SNP found associated by other authors was not directly analyzed in our study, we considered the P value of a marker with r2 ⬎ 0.95 (HapMap CEU population).
2
1
2
4
System
Genes
No. of
polymorphisms
per gene
Association studies performed by other groups
Table IV. Previous association studies between autism and genes encoding neurotrophic factors and receptors, and proteins of the serotoninergic and dopaminergic neurotransmission systems
that displayed significant results. Comparison with the SNPs tested in our study.
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Association between the DDC gene and autism
9
10 C. Toma et al.
In conclusion, our findings provide new insights into
the genetics of autism, showing for the first time a
significant association with DDC. Further investigations are needed to establish the role of this gene in
autism with replications in larger cohorts.
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Acknowledgements
We are grateful to all patients and controls for their
participation in our study, to clinical collaborators
(Montse Causi, Carlota Pont, Julia Ruiz, Inma
Planelles, Mar Margalef, Mar Fernández, David
Seguí and Blanca Gener) for patients’ assessment, to
Lucía Madrigal for blood sampling, to Olaya Villa
for cytogenetic analyses, to M. Dolors Castellar and
others from the “Banc de Sang i Teixits” (Hospital
Universitari Vall d’Hebron) for their collaboration in
the recruitment of controls, to Mònica Gratacòs for
her participation in the selection of part of the studied genes and polymorphisms, and to Miquel Casas
for critical comments. Genotyping services were provided by the Spanish “Centro Nacional de Genotipado” (CEGEN; www.cegen.org). MR is a recipient
of a Miguel de Servet contract from “Instituto de
Salud Carlos III” (Spain) and CT was supported by
fellowships from the Biomedical Network Research
Centre on Rare Diseases (CIBERER) and the European Union (Marie Curie, PIEF-GA-2009-254930).
Financial support was received from “Instituto de
Salud Carlos III-FIS” (PI041267, PI042010,
PI040524, RETICS G03/183, PI042209, PI041208
and PI070539), “Consejería de Innovación, Ciencia
y Empresa”, Junta de Andalucía (CTS-546), “Fundació La Marató de TV3” (092010), Fundación Alicia Koplowitz and “Agència de Gestió d’Ajuts
Universitaris i de Recerca-AGAUR” (2009GR00971).
These institutions had no further role in study design;
in the collection, analysis and interpretation of data;
in the writing of the report; and in the decision to
submit the paper for publication.
Statement of Interest
L.A.P.J. is a member of the scientific advisory board
of qGenomics. No other author reported any biomedical financial interests or potential conflicts of
interest.
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