An analysis of candidate autism loci on chromosome 2q24Цq33 Evidence for association to the STK39 gene.код для вставкиСкачать
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: firstname.lastname@example.org 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). REFERENCES Autism and Developmental Disabilities Monitoring (ADDM) Network Surveillance Year 2002 Principal Investigators; Centers for Disease Control and Prevention. 2007. 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