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An analysis of candidate autism loci on chromosome 2q24Цq33 Evidence for association to the STK39 gene.

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American Journal of Medical Genetics Part B (Neuropsychiatric Genetics) 147B:1152 –1158 (2008)
An Analysis of Candidate Autism Loci on Chromosome
2q24–q33: Evidence for Association to the STK39 Gene
Nicolas Ramoz,1,2,3 Guiqing Cai,1,2,3 Jennifer G. Reichert,1,2,3
Jeremy M. Silverman,2,3 and Joseph D. Buxbaum1,2,3,4*
1
Laboratory of Molecular Neuropsychiatry, Mount Sinai School of Medicine, New York, New York
Department of Psychiatry, Mount Sinai School of Medicine, New York, New York
3
Seaver Autism Research Center, Mount Sinai School of Medicine, New York, New York
4
Departments of Neuroscience, Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, New York
2
A susceptibility locus for autism was identified to
the chromosome 2q24–q33 region in independent
cohorts of families, especially in subsets clinically
defined with phrase speech delay (PSD). In the
present work, we screened 84 linkage-informative
SNPs covering this locus in a cohort of 334 families
with autism and in subsets identified with
PSD. We observed linkage to autism with the
highest non-parametric linkage score (NPL) of
2.79 (P ¼ 0.002) in the PSD subset with at least
two affected subjects. In addition, using a set of
109 additional gene-oriented SNPs in this interval
we observed that several SNPs encompassing
the SLC25A12 gene provided the maximum
evidence for linkage (NPL ¼ 3.32, P ¼ 0.0003).
Using the transmission disequilibrium test to
test for associations, we observed significant
over-transmissions of rs2056202 (P ¼ 0.006) within the SLC25A12 gene, rs1807984 (P ¼ 0.007) within
the STK39 gene, and rs2305586 (P ¼ 0.009) within
the ITGA4 gene. We also found evidence for
association between autism and two other SNPs
(rs1517342, P ¼ 0.012 and rs971257, P ¼ 0.030) or
haplotypes (P ¼ 0.003) of the STK39 gene. STK39
encodes a serine/threonine kinase (SPAK/PASK/
STE20-SPS1 homolog) abundantly expressed in
the brain with roles in cell differentiation, cell
This article contains supplementary material, which may be
viewed at the American Journal of Medical Genetics website
at http://www.interscience.wiley.com/jpages/1552-4841/suppmat/
index.html.
Nicolas Ramoz and Guiqing Cai contributed equally to this
work.
Please cite this article as follows: Ramoz N, Cai G, Reichert JG,
Silverman JM, Buxbaum JD. 2008. An Analysis of Candidate
Autism Loci on Chromosome 2q24–q33: Evidence for Association
to the STK39 Gene. Am J Med Genet Part B 9999:1152–1158.
Grant sponsor: Beatrice and Samuel A. Seaver Foundation;
Grant sponsor: National Institutes of Health; Grant numbers:
MH-066673, NS-042165, MH64547.
Nicolas Ramoz’s present address is INSERM Unité 675 (IFR02),
Faculté Xavier Bichat, 16 rue Henri Huchard, 75018 Paris,
France.
*Correspondence to: Joseph D. Buxbaum, Ph.D., 1 Gustave L
Levy Place, Box 1668, New York, NY 10029.
E-mail: joseph.buxbaum@mssm.edu
Received 29 June 2007; Accepted 23 January 2008
DOI 10.1002/ajmg.b.30739
Published online 17 March 2008 in Wiley InterScience
(www.interscience.wiley.com)
ß 2008 Wiley-Liss, Inc.
transformation and proliferation, and in regulation of ion transporters. In summary, we have
observed further evidence for linkage and association between autism and loci within the 2q24–
q33 region, including at STK39, a novel candidate
gene for autism.
ß 2008 Wiley-Liss, Inc.
KEY WORDS:
autistic disorder; phrase-speech
delay; STK39; serine-threonine
kinase; transmission disequilibrium test
Please cite this article as follows: Ramoz N, Cai G,
Reichert JG, Silverman JM, Buxbaum JD. 2008. An
Analysis of Candidate Autism Loci on Chromosome
2q24–q33: Evidence for Association to the STK39 Gene.
Am J Med Genet Part B 147B:1152–1158.
INTRODUCTION
Autism (MIM#209850) is a neurodevelopmental disorder
characterized by difficulties in verbal and nonverbal communication, impairments in reciprocal social interactions, and the
presence of restricted interests and/or repetitive or stereotyped
behaviors [Lord et al., 2000, 2001]. The prevalence of autism
and associated disorders is estimated at about 60/10,000
[Fombonne, 2005; ADDM, 2007]. Autism has a strong genetic
basis with a sibling relative risk (l) of 50–100, a concordance
rate of 90% for autism and spectrum disorders in monozygotic
twins—versus 10% in dizygotic twins, and a heritability of
idiopathic autism estimated at above 90% [Folstein and Rutter,
1977; Bailey et al., 1995; Veenstra-VanderWeele and Cook,
2004]. A proportion (>10%) of autism cases appear to due to
chromosomal abnormalities or known genetic conditions,
including fragile-X syndrome, Rett syndrome, neurofibromatosis, and tuberous sclerosis. For the remaining cases, there is
likely a complex genetic etiology possibly involving several
interacting genes.
Several independent studies of whole-genome linkage
analysis have reported a linkage between autism and the
chromosome 2q region [Philippe et al., 1999; Buxbaum et al.,
2001; IMGSAC, 2001; Shao et al., 2002; Romano et al., 2005;
Lauritsen et al., 2006; Spence et al., 2006]. In our studies, we
identified a susceptibility locus for autism on the chromosome
2q24–q33 region with a peak at marker D2S335 [Buxbaum
et al., 2001]. This linkage was particularly evident within a
subset of families with more severe autism, defined by delayed
onset (at age >36 months, ADI-R A13 item) of phrase speech
(PSD, MIM#606053), with a nonparametric linkage (NPL)
score of 3.32 and a heterogeneity LOD (HLOD) score of 2.29.
The International Molecular Genetics Study of Autism
Autism and 2q24 – q33 Loci
Consortium (IMGSAC) detected a maximum multipoint LOD
score of 3.74 on 2q21–q33 region in a sample ascertained with
language delay [IMGSAC, 2001]. The Collaborative Autism
Team also found a linkage between autism and chromosome
2q33 with a maximum LOD score of 2.86 and a HLOD score of
2.12 at D2S116 when the PSD endophenotype was used [Shao
et al., 2002]. Recently, the study of 143 Sicilian trios also
reported a significant association between autism and the
D2S2188 marker in the 2q31 region using the transmission
disequilibrium test [Romano et al., 2005]. Furthermore, a
recent report showed an association between autism and the
D2S2381 marker located in the 2q31 region in a case-control
study involving 12 subjects from a common ancestor in Faroe
Island [Lauritsen et al., 2006]. In addition, a de novo deletion of
2q32 region has been found in a case with high functioning
autism [Gallagher et al., 2003].
About 20 candidate genes have been screened in the
chromosome 2q24–q33 region [Bacchelli et al., 2003, 2006;
Weiss et al., 2003; Rabionet et al., 2004; Ramoz et al., 2004;
Conroy et al., 2005; Hamilton et al., 2005]. Nonsynonymous
mutations have been found for cAMP-GEFII, DLX2, SCN1A,
and SCN2A genes but further analyses are needed to evaluate
their involvement in autism. We recently screened for mutations in nine candidate genes and found two variants, both
within the SLC25A12/AGC1 gene, that showed a significant
divergents of distribution in a preliminary case control
analysis [Ramoz et al., 2004]. Genotyping these 2 single
nucleotide polymorphisms (SNPs) in 411 autism families
demonstrated linkage (NPL score of 1.57; HLOD score of
2.11) and association (transmission disequilibrium test for
haplotype P-value of 0.000003) of SLC25A12 with autism. This
association between autism and SLC25A12 polymorphisms
has been confirmed in an independent study on a cohort of
158 trio families of Irish origin and in a cohort of 129 families of
Finish origin [Segurado et al., 2005; Turunen et al., 2006], but
not in three additional studies [Blasi et al., 2006; Correia et al.,
2006; Rabionet et al., 2006].
Recently, a novel method that allows thousands of individual
amplicons to be scanned for all common and rare genetic
variants in a multiplexed manner has been developed. This
method, termed multiplexed variation screening (MVS) was
previously applied to 372 subjects with autism and 404
controls, focusing on a 20 Mb region within 1 LOD score from
a peak in the chromosome 2q24–q33 region [Faham et al.,
2005]. Nearly all exons in the region (&1,200) were screened
and variants were identified that showed association with
autism in a case-control analysis. Evidence for a strong
association (P < 0.0001) between autism and a variant within
the integrin alpha 4 gene, ITGA4, was observed. Interestingly,
an independent study has since identified this gene as a
potential autism susceptibility locus [Conroy et al., 2005;
Louise Gallagher, Personal Communication].
To refine the locus on 2q24–q33, to further assess the role of
SLC25A12, and to explore whether there may be additional loci
and genes of susceptibility in this region, a total of 193 SNPs
were genotyped in a larger cohort of 334 families with autism.
Linkage analysis and family-based association test were
performed in the entire cohort and in clinically defined subsets
for the PSD phenotype. We found several SNPs encompassing
the STK39 gene to be associated with autism.
MATERIALS AND METHODS
Subjects
A total of 334 families, including 252 multiplex families (two
or more affected family members) and 82 singleton families,
were recruited by the Seaver Autism Research Center (SARC)/
Greater New York Autism Research Center for Excellence/
1153
STAART Center and/or the Autism Genetic Resources Exchange (AGRE) [Geschwind et al., 2001]. All parents provided
written informed consent for affected individuals. The Autism
Diagnostic Interview-Revised (ADI-R) (3rd edition) was used
to assess and define affected children with autism or borderline
autism [Lord et al., 1994, 2000]. Boderline autism has been
previously defined [see Buxbaum et al., 2001; also called ‘‘not
quite autism’’] and included those who failed to meet the ADI-R
algorithm criteria for autism by no more than one point in the
social domain and either the communication or repetitive
behavior domain but not both, or alternatively those with all
three domains above threshold who did not meet the onset
criterion. The exclusion criteria included fragile X syndrome,
tuberous sclerosis, or chromosomal anomalies. A total of
1,597 individuals were genotyped, including 610 patients,
comprised of 478 males (78.4%) and 132 females (21.6%).
Among the siblings, 37 subjects assessed with borderline
autism were considered affected while 41 siblings assessed
with broad spectrum and/or PDD-NOS were not considered
as affected in the current study. The ethnicity status was as
previously described [Ramoz et al., 2006].
The chromosomal region 2q31 has been reported as an
autism candidate region particularly in a subset of families
with the phrase speech delay (PSD) endophenotype [Buxbaum
et al., 2001; IMGSAC, 2001; Shao et al., 2002; Spence et al.,
2006]. Thus, for the current study (to account for the presence
of singleton families in the sample), two successively more
stringent subsets of autism PSD families were defined
according to an ADI-R (3rd edition) item A13, using onset of
phrase speech at age >36 months as previously described
[Buxbaum et al., 2001]. A family with at least one affected child
having PSD was categorized in the PSD1 subset and a family
with two or more affected children having PSD was categorized
in the PSD2 subset (severe PSD). This resulted in a PSD1
subset of 158 families and a PSD2 subset of 86 families.
Genotyping and Assessment of SNPs
DNA samples were obtained from blood or transformed cells.
A total of 193 SNPs were genotyped in the 334 families
with autism (See Supplementary Fig. 1). Eighty-four ‘‘linkage’’
SNPs were selected based on their known informativeness for
linkage and their positions in the genome to cover 40.5 Mbps of
the 2q24–q33 region with an average distance of 488 Kbps and
no gap greater than 2.2 Mbps. A further 109 SNPs within this
region were chosen to increase the density of markers across
35 candidate genes, including the SLC25A12 gene (14 SNPs),
10 genes (17 SNPs) previously associated with autism in the
MVS study (Supplementary Table 1) [Faham et al., 2005], and
24 additional candidate genes (59 SNPs). Subsequently, for
a better coverage of select genes, 33 additional SNPs were
genotyped. SNPs were selected according to the information
available at the time of the study in the gene and SNP
databases (http://www.hapmap.org, http://www.ncbi.nlm.nih.
gov/ and http://genome.perlegen.com/browser/index.html). In
addition, select SNPs testing positive in other studies were also
included [Conroy et al., 2005; Bacchelli et al., 2006; Louise
Gallagher, Personal Communication].
Among the 193 SNPs, 143 SNPs were genotyped using the
SNP BeadArray platform from Illumina, Inc. (San Diego, CA).
Quality was assessed by genotyping replicates and triplicates
of 120 individuals and the second child of 27 pairs of
monozygotic twins. The remaining 50 SNPs were genotyped
using Custom Taqman1 SNP Genotyping Assays or Taqman1
Pre-designed SNP Genotyping Assays from Applied Biosystems (Foster City, CA). Reaction procedures were carried
out according to the manufacturer’s protocol and products
were detected on ABI PRISM1 7900HT real-time PCR
sequence detection instrument from Applied Biosystems.
1154
Ramoz et al.
Alleles were called with the SDS 2.1 software from Applied
Biosystems. Quality was estimated using 60 replicates of
individuals and 23 pairs of monozygotic twins. Errors of
transmission were corrected by recoding both alleles of a SNP
as unknown when there was only one such error in a sample,
otherwise the individual was not included in the analysis.
Statistical Analysis
Hardy–Weinberg equilibrium was estimated for each SNP,
using Haploview 3.32 software with a threshold P-value of
0.001 [Barrett et al., 2005].
Two-point and multipoint linkage analyses were carried out
with GENEHUNTER using both the non-parametric (NPL)
and parametric heterogeneity (HLOD) methods [Kruglyak
et al., 1996]. Two models, recessive (r) and dominant (D), were
studied for the parametric HLOD method, both using a
penetrance of 50% and a value of 0.001 for the disease allele
frequency.
Transmission disequilibrium test (TDT) was performed
using Haploview 3.32 and the family based association test
(FBAT) from the FBAT package making use of all affected in
families [Horvath et al., 2001; Barrett et al., 2005]. The FBAT
analyses were performed under the additive, recessive,
dominant, and genotype models.
Linkage disequilibrium D0 values between pairs of SNPs
were calculated using Haploview 3.32 [Barrett et al., 2005].
Haploview 3.32 software and the HBAT application from the
FBAT package were also used to test for associations between
haplotypes and autism [Horvath et al., 2001; Barrett et al.,
2005]. Power for the Haploview 3.32 and HBAT calculations
were computed using the Monte Carlo permutation with
1,000 replications. Gene–gene analysis was carried out using
the gene-based tests of the PLINK program [Purcell et al.,
2007].
RESULTS
Genotyping
A total of 193 SNPs were genotyped in 334 families with
autism (252 multiplex and 82 simplex), including 610 autism
subjects (See Supplementary Fig. 1). Eighty-four SNPs were
selected for linkage to cover 40.5 Mbps of the 2q24–q33 region
with an average distance of 488 Kbps and no gap higher than
2.2 Mbps. A further 109 SNPs within this region were chosen to
increase the density of markers across 35 candidate genes,
including 14 SNPs that encompass the SLC25A12 gene and
additional variants among 13 genes previously associated with
autism (See Supplementary Table 1 and Conroy et al., 2005;
Bacchelli et al., 2006; Louise Gallagher, Personal Communication). Replicates and triplicates of 120 samples and of
27 pairs of monozygotic twins were analyzed to estimate
the genotyping error rate (<0.01%). Segregation of SNPs in
families was checked. Identified errors of Mendelian transmission (3%) were recoded as unknown genotypes when it they
appeared only with one marker in a sample, otherwise the
individual was not maintained in the pedigree (7 exclusions of
paternity). Hardy–Weinberg equilibrium (HWE) was assessed
and two SNPs among the 193 (rs1473041 in an intergenic
region and rs155138 in the ITGA4 gene) showed significant
deviation from HWE (Supplementary Table 2).
Linkage Analysis
We analyzed the 84 linkage SNPs encompassing the 2q24–
q33 region to detect evidence for linkage across this interval
(Fig. 1 and Supplementary Table 3). A maximum multipoint
non-parametric linkage (NPL) score value of 1.26 (P ¼ 0.077)
was observed at SNPs rs930191 and rs147180 (that are
separated by 50 Kbps), in the cohort of 334 families. In twopoint analysis, the maximum values for NPL, parametric
heterogeneity LOD score under recessive (HLODr) and
dominant (HLODd) models were, respectively, 1.68 (P ¼
0.030), 0.92, and 2.14 at rs1541781, which is located 890 Kbps
from the 30 region of SLC25A12 gene (Supplementary Table 3).
The multi-point maximum NPL value went up to 2.05 (P ¼
0.016) at rs752355 in a subset (N ¼ 158, PSD1) of the cohort
where the delayed onset of phrase speech (PSD) endophenotype
was diagnosed in at least one affected per family (Fig. 1 and
Supplementary Table 3). In two-point analysis, the maximum
values for NPL (1.56, P ¼ 0.051), HLODr (1.05) and HLODd
(1.44) were still observed for rs1541781. Finally, in a subset
(N ¼ 86, PSD2) of affected families with PSD diagnosed in
Fig. 1. Multi-point linkage analysis of autism with 84 SNPs covering the chromosome 2q24–q33 region for the entire cohort and the PSD1 and PSD2
subsets. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]
Autism and 2q24 – q33 Loci
at least two subjects per family, the highest NPL score of
2.79 (P ¼ 0.002) was found at SNPs rs2032965 and rs1364529
which are separated by 72 Kbps and located on chromosome
2q31.1 region (Fig. 1 and Supplementary Table 3). The next SNP
telomeric, rs1541781, was again the marker which showed
significant values for NPL (1.63, P ¼ 0.041), HLODr (1.12), and
HLODd (1.63) in two-point analysis.
As we also had data on the additional SNPs that covered
candidate genes in the interval, we also tested them for
linkage, recognizing that the non-random distribution of these
SNPs and their different levels of informativeness complicate
the interpretation. In the analysis of the cohort of all families,
the maximum multipoint NPL value of 2.09 (P ¼ 0.010)
was observed at rs1010533 within SLC25A12 gene
(Supplementary Fig. 2 and Supplementary Table 4). In the
PSD1 subset, maximum NPL values went up to 3 (P ¼ 0.001) at
several SNPs covering the SLC25A12 gene. Finally, in the
PSD2 subset, the highest NPL scores (up to 3.32 with
P ¼ 0.0003) were found for SNPs encompassing the SLC25A12
gene.
Association Analysis
Using the transmission disequilibrium test in the cohort of
all families, the strongest nominally significant association
(P < 0.01) was found with rs2056202 (allele G, 146 Transmissions versus 103 Non-Transmissions, P ¼ 0.006) within the
SLC25A12 gene, rs1807984 (allele C, 285 T vs. 224 NT,
P ¼ 0.007) within the STK39 gene, and rs2305586 (allele T,
136 T vs. 96 NT, P ¼ 0.009) within the ITGA4 gene (Table I and
Supplementary Table 2). A significant over-transmission for
two other SNPs encompassing the STK39 gene was also
observed, rs1517342 (allele A, 293 T vs. 235 NT, P ¼ 0.012) and
rs971257 (allele A, 280 T vs. 231 NT, P ¼ 0.030) (Table I).
Significant association between autism and SNPs encompassing the STK39 gene was also found using FBAT under additive,
recessive and dominant models (Supplementary Table 2). Two
SNPs within SLC25A12 gene, rs2292813 and rs2056202, were
associated to autism under different FBAT models (Supplementary Table 2). Five SNPs within ITGA4 gene showed
association to autism using a recessive model in FBAT
(Supplementary Table 2). Association between autism and
SNPs encompassing the STK39 gene was observed in both the
PSD1 (rs1517342 P ¼ 0.007) and PSD2 (rs1517342 P ¼ 0.002
and rs1807984 P ¼ 0.033) subsets (Table I).
Haplotype Analysis
Analysis of linkage disequilibrium between pairs of SNPs
encompassing the STK39 gene indicates that this gene contains
1155
at least 4 haplotype blocks (data not shown). Significant
association was found between autism and different haplotypes
of SNPs encompassing STK39 gene in the cohort of all
families (Table II). Thus, the frequent haplotypes
rs4668030*A-rs1517342*A-rs12616582*A-rs10930310*A (Frequency or F ¼ 0.376) and rs12616582*A-rs10930310*Grs1807984*C (F ¼ 0.375) showed the greatest significant overtransmission in autism (P ¼ 0.0003). Finally, several STK39
haplotypes were also found associated with autism in the PSD1
subset but not in the PSD2 subset (Table II).
A frequent haplotype in SLC25A12 (comprised of rs925881*
A-rs2056202*G-rs1996425*A-rs1878583*G, F ¼ 0.837) showed a
significant association with autism in the cohort of all families
(152.6 T vs. 113.5 NT, P ¼ 0.017). This haplotype was also
found significantly over-transmitted in the subsets PSD1
(F ¼ 0.828, 82.1 T vs. 55 NT, P ¼ 0.020) and PSD2 (F ¼ 0.852,
46.1 T vs. 24.1 NT, P ¼ 0.008).
Various haplotypes of ITGA4 (comprised of two to seven
SNPs but all containing rs2305586), were significantly overtransmitted in autism (data not shown). However, the
frequency of these haplotypes was somewhat low (ca. 0.145)
and these associations appeared to be driven by the overtransmission of rs2305586.
Gene–Gene Interaction Analysis
Given the large number of informative families among
the cohort of 334 families (207 informative families for
STK39 and 132 for SLC25A12 and ITGA4), we search for a
co-association of the genes in autism to identify a possible
gene–gene interaction using TDT with PLINK (Supplementary Table 5). We found significant evidence for
gene–gene interaction with STK39 and SLC25A12 (P ¼
0.035) in all families but no association in the smaller PSD1
and PSD2 subsets.
DISCUSSION
We and others reported a susceptibility locus for autism
across the chromosome 2q24–q33 region in independent cohort
of families, especially in subsets ascertained with phrase speech
delay [Philippe et al., 1999; Buxbaum et al., 2001; IMGSAC,
2001; Shao et al., 2002; Romano et al., 2005; Lauritsen et al.,
2006; Spence et al., 2006]. In the present study, using a set of
dense map of SNPs that cover the 2q24–q33 region, we extended
our prior report of linkage to autism [Buxbaum et al., 2001] in a
large cohort, including 247 additional families. We observed
that SNPs encompassing the SLC25A12 gene provided the
maximum evidence for linkage.
Several reports showed that two SNPs, rs2056202 and
rs2291813, both within the SLC25A12 gene were associated
TABLE I. Transmission Disequilibrium Test Between Autism and SNPs Encompassing the STK39 Gene Among the Cohort of 334
Families and the Subsets PSD1 and PSD2
334 autism families
SNP#
1
2
3
4
5
6
7
8
a
b
NCBI rs#
rs971257
rs715878
rs4668030
rs1517342
rs12616582
rs10930310
rs1807984
rs1517319
Allele
A
A
A
A
A
A
G
C
T/NTa
280:231
280:266
227:198
293:235
134:117
212:190
285:224
234:194
Chi-square
4.699
0.359
1.979
6.371
1.151
1.204
7.31
3.738
Transmitted allele (T) versus non-transmitted allele (NT).
Significant P-value are indicated in bold.
158 autism PSD1 families
P
b
0.030
0.549
0.160
0.012
0.283
0.273
0.007
0.053
86 autism PSD2 families
T/NT
Chi-square
P
T/NT
Chi-square
P
140:117
159:142
112:99
163:118
64:48
95:91
134:104
114:113
2.058
0.96
0.801
7.206
2.286
0.086
3.782
0.004
0.151
0.327
0.371
0.007
0.131
0.769
0.052
0.947
82:59
86:81
62:58
96:57
32:22
50:49
75:51
78:66
3.752
0.150
0.133
9.941
1.852
0.010
4.571
1.000
0.053
0.699
0.715
0.002
0.174
0.920
0.033
0.317
2.77
1.47
2.25
1.40
1.97
1.23
0.39
1.09
1.27
0.47
0.16
0.29
3.63
2.52
0.03
2.39
1.14
1.28
10.3:4.0
15.2:9.2
21.0:12.3
18.8:12.2
22.7:14.2
22.7:15.8
23.3:27.8
19.2:13.3
23.0:16.0
22.1:17.8
24.9:22.1
25.7:22.0
27.0:14.7
27.3:16.8
17.6:16.5
28.8:18.2
32.5:24.4
29.6:21.5
0.077
0.161
0.226
0.232
0.268
0.274
0.333
0.215
0.293
0.306
0.353
0.358
0.34
0.363
0.676
0.353
0.493
0.368
0.0022
0.0156
0.0243
0.0515
0.107
0.1407
0.1705
0.0343
0.1465
0.1845
0.4005
0.344
0.0549
0.0623
0.6291
0.0234
0.0316
0.0691
9.41
5.85
5.07
3.79
2.60
2.17
1.88
4.48
2.11
1.76
0.71
0.90
3.69
3.48
0.23
5.14
4.62
3.31
A
A
A
A
A
A A A A
A A A
A A
A A A
A A
A A
A A A A
A A A
A A
A
Haplotype digit numbers correspond to SNP# of Table I.
Transmitted allele (T) versus non-transmitted allele (NT).
Significant P-value are indicated in bold.
c
b
a
0.076
0.181
0.259
0.264
0.317
0.322
0.334
0.229
0.321
0.333
0.395
0.398
0.379
0.398
0.707
0.392
0.516
0.399
A
A
A
A
A
A A A A
A A A
A A
A
A
A
A
A
A
A
G
G
G
G
G
G
G
G
G
G
G
G
C
C
C
C
C
C
C
0.075
0.185
0.269
0.271
0.31
0.31
0.327
0.229
0.324
0.332
0.376
0.376
0.375
0.393
0.701
0.384
0.512
0.387
44.7:19.0
83.3:55.6
106.9:63.5
104.5:65.6
113.0:67.4
119.8:72.2
121.1:80.5
91.7:74.9
122.7:74.9
130.0:82.6
138.6:85.1
139.6:87.0
124.8:73.8
107.2:79.7
86.2:77.0
112.9:80.6
117.5:94.4
113.3:83.9
10.35
5.52
11.07
8.89
11.49
11.79
8.16
1.7
11.56
10.54
12.79
12.25
13.12
4.06
0.51
5.40
2.52
4.39
0.0013c
0.0188
0.0009
0.0029
0.0007
0.0006
0.0043
0.1923
0.0007
0.0012
0.0003
0.0005
0.0003
0.0438
0.4736
0.0201
0.1126
0.0362
22.2:5.9
42.4:22.8
47.4:27.8
44.2:27.7
47.0:32.7
48.4:34.9
50.4:37.5
50.2:31.1
47.1:34.0
48.1:35.9
51.9:43.7
52.9:43.6
49.1:31.8
51.1:33.9
36.6:32.6
55.0:33.7
63.5:41.5
55.5:37.9
Chi-square
T/NT
Freq.
Freq.
5
1
2
3
4
6
7
8
Freq.
T/NTb
Chi-square
P
T/NT
Chi-square
P
86 autism PSD2 families
158 autism PSD1 families
TABLE II. Haplotypes of SNPs Covering STK39 Gene Associated With Autism
334 autism families
Haplotype
a
0.0962
0.2246
0.1334
0.2384
0.1607
0.2683
0.5304
0.2972
0.2605
0.4936
0.6889
0.5898
0.0567
0.1124
0.8605
0.122
0.2864
0.2575
Ramoz et al.
P
1156
with autism [Ramoz et al., 2004; Segurado et al., 2005;
Turunen et al., 2006]. In the current study, screening 14 SNPs
covering this gene, we demonstrated here that these 2 SNPs
showed strongest association. Note that the samples in the
current study were taken from our prior association study
[Ramoz et al., 2004] and as such the current differs from
the prior study vis a vis SLC25A12 as it relates to (1) the
genotyping and analysis of additional SNPs within the gene
and (2) gene–gene interaction analyses.
Additional studies also identified putative candidate genes
for autism in this region. The MVS study showed an association
between autism and variants located across 11 genes, including the ITGA4 and OSBPL6 genes, in a case control analysis
[Faham et al., 2005]. The ITGA4 gene was also reported
associated to autism in an independent cohort using familybased study [Conroy et al., 2005; Louise Gallagher, Personal
Communication].
It may be that, in fact, in complex genetic disorders, such as
autism, reproducible linkage in a chromosome region may
reflect several loci and multiple genes located in the region
that contribute to the disease. This has been proposed for
the chromosome 15q11–q13 region and the GABA receptor
subunit genes in autism [Ma et al., 2005]. Thus, in the current
report, we screened a set of SNPs to replicate previous positive
associations and/or to identify novel candidate genes in autism
on the chromosome 2q24–q33 region. Our family-based transmission disequilibrium supported association with ITGA4
observed in the MVS and an additional study. We observed
association for SNPs in the ITGA4 gene under the additive
or recessive model in FBAT, in the entire cohort. This is
particularly interesting as the reports of association of this
gene with autism by another group [Conroy et al., 2005; Louise
Gallagher, Personal Communication] have been observed in a
cohort in which association with SLC25A12 was observed
[Segurado et al., 2005]. This indicates that in two independent
cohorts, association to two genes in a single region is observed.
Furthermore, among the candidate genes that we selected,
in addition to the SLC25A12 gene, one gene, STK39,
showed variants associated with autism. Interestingly, three
polymorphisms encompassing the STK39 gene were overtransmitted in out cohort. Furthermore, significant associations were found for almost all the STK39 haplotype
combinations.
Given the large number of genotyped SNPs and multiple
tests performed, the probability of a false positive finding is
increased in the current study. In order to aid in interpreting
our findings, we also applied a Bonferroni correction in a
gene-wide fashion to help in evaluating the strength of the
association findings for STK39, SLC25A12, and ITGA4. We
found trend levels of association even after this very conservative test (correcting for 8 SNPs within STK39 yielded
rs1807984 pcorrected ¼ 0.056, for 14 SNPs within SLC25A12,
rs2056202 pcorrected ¼ 0.084, and for 11 SNPs within ITGA4,
rs2305586 pcorrected ¼ 0.099). Importantly, the STK39 and
SLC25A12 haplotypes remain significantly associated
after Bonferroni correction, most notably for haplotype
rs12616582*A-rs10930310*G-rs1807984*C of the STK39 gene
(pcorrected ¼ 0.005).
Most of our selected and associated SNPs were intronic. The
association of these SNPs may reflect linkage disequilibrium
with coding or splice site SNPs that modify the primary amino
acid sequence of the protein and hence its function. Alternatively, these non-coding SNPs may directly modulate
expression or splicing leading to alternate coding mRNA
or abnormal levels of RNA expression. Functional studies,
including allele-specific expression and detailed analysis of
additional SNPs in these genes will be needed to assess these
hypotheses. Our recent studies showing increased expression
of SLC25A12 mRNA in autism brain samples [Lepagnol-
Autism and 2q24 – q33 Loci
Bestel et al., in press] makes these questions particularly
interesting.
Both STK39 and SLC25A12 genes, located in the same
chromosome 2q region, appear to be involved in autism, so it is
interesting to explore the potential for a gene–gene interaction
in this disorder. We found that more than one third of patients
that contributed to apparent over-transmission of rs1807984
in STK39, also contributed to the apparent over-transmission
of rs2056202 in SLC25A12. Gene–gene interaction studies
provided evidence for gene–gene interaction between STK39
and SLC25A12 (P ¼ 0.035). Further studies in additional
samples that directly assess this potential gene–gene interaction are needed to begin to understand whether the STK39
and SLC25A12 genes cooperate in increasing risk for autism.
Note that associations were found between the SLC25A12 gene
and autism with PSD suggesting that SLC25A12 may
be involved in autism with PSD. In contrast, the strong
associations between SNPs and haplotypes of STK39 and
autism were found in the cohort of all families but were
much less pronounced in PSD subsets. It may therefore be
that STK39 is involved in autism per se. Ultimately, while
associations were observed in the PSD subsets, it is not clear
the degree to which subsetting increased power to detect
these associations. This question would need to be addressed in
suitably powered replication studies.
The STK39 gene encodes a serine/threonine kinase (SPAK/
PASK/STE20-SPS1 homolog) of 547-amino acids (59.6 kDa)
containing N-terminal repeats of proline and alanine (PAPA
box), a serine/threonine kinase catalytic domain, a nuclear
localization signal, a caspase cleavage motif, and a C-terminal
region [Johnston et al., 2000]. The protein is localized to both
the cytoplasm and the nucleus, and may acts as a mediator of
stress signals. STK39 is ubiquitously expressed with abundant
detection in brain and pancreas. It has a scaffolding role in
neurons for several ion co-transporters [Dowd and Forbush,
2003; Piechotta et al., 2003; Moriguchi et al., 2005]. A family
member protein, OSR1, is required for axonal ensheathment
[Leiserson et al., 2000]. Furthermore, another family member,
STK9/CDKL5, is involved in some forms of Rett syndrome
[Tao et al., 2004; Lin et al., 2005]. Interestingly, abnormalities
of white matter in autism were observed in several studies
[Hendry et al., 2006; Bloss and Courchesne, 2007; Johansson
et al., 2007]. Reductions in the structural integrity of
white matter were reported in autism subjects compared to
controls using diffusion tensor imaging [Keller et al., 2007]. It
is tempting to speculate that the subtle changes in white
matter of autism may be genetically linked to the STK39
gene. However, replication studies on the STK39 gene need to
be done on independent cohorts prior to try to correlate this
gene to neuropathophysiology of autism.
In summary, in the current report we provide further
evidence of linkage to the chromosome 2q region in autism,
particularly in the presence of PSD. Furthermore, we have
further explored SNPs within SLC25A12 and provide evidence
that the previously associated SNPs show the strongest
association. In addition, we provide supporting evidence
for association of SNPs within ITGA4 with autism. Finally,
we provide first evidence for association of STK39 with
autism. Evidence for two or more loci showing association
with autism in the 2q region may in part explain the
more reproducible linkage to this region observed by several
groups.
ACKNOWLEDGMENTS
This work is supported by the Beatrice and Samuel A. Seaver
Foundation and by the National Institutes of Health through
a Studies of Advance Autism Research and Treatment
1157
(STAART) grant (MH066673) and (NS-042165). We gratefully
acknowledge the resources provided by the Autism Genetic
Resource Exchange (AGRE) Consortium1 and the participating AGRE families. The Autism Genetic Resource
Exchange is a program of Cure Autism Now and is supported,
in part, by grant MH64547 from the National Institute of
Mental Health to Daniel H. Geschwind (PI).
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