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Family based association of GRIN2A and GRIN2B with Korean autism spectrum disorders
Neuroscience Letters 512 (2012) 89–93
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Family based association of GRIN2A and GRIN2B with Korean autism spectrum disorders Hee Jeong Yoo a , In Hee Cho b , Mira Park c , So Young Yang d , Soon Ae Kim d,∗ a
Department of Psychiatry, Seoul National University Bundang Hospital, Seongnam, Kyeonggi, Republic of Korea Department of Psychiatry, Gil Medical Center, Gachon University of Medicine and Science, Incheon, Republic of Korea Department of Preventive Medicine, School of Medicine, Eulji University, Daejeon, Republic of Korea d Department of Pharmacology and Eulji University Medical Sciences Research Center, School of Medicine, Eulji University, Daejeon, Republic of Korea b c
a r t i c l e
i n f o
Article history: Received 28 November 2011 Received in revised form 23 January 2012 Accepted 26 January 2012 Keywords: Autism spectrum disorders (ASDs) Single nucleotide polymorphisms (SNPs) Glutamate receptor, ionotropic, N-methyl-d-aspartate, subunit 2B GRIN gene (GRIN2B) Family-based association study
a b s t r a c t N-Methyl-d-aspartate (NMDA) receptor, one of the glutamate receptors, has a role in the regulation of synaptic activity. It functions as an ion channel in the central nervous system and its inappropriate activation has been implicated in several neurological conditions. To test the association between candidate genes related with NMDA receptors and autism spectrum disorders (ASDs), we examined single nucleotide polymorphisms (SNPs) for GRIN2A and GRIN2B by using the family-based association test (FBAT) in 151 Korean trios. There was a statistically significant associations between ASDs and haplotypes in GRIN2B (bi-allelic mode additive model P-value = 0.003; FDR P-value = 0.012). This study supports a possible role of GRIN2B as a candidate gene for the etiology of ASDs. © 2012 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Autism spectrum disorders (ASDs) are neuropsychiatric developmental disorders associated with multiple symptoms, including impairment of social communication/interaction and restrictive/repetitive behaviors [34]. Autism might be highly heritable owing to the large monozygotic/dizygotic (MZ:DZ) difference in concordance [2]. ASDs may occur in a child who inherits several genes with each of them contributing to the disease phenotype. In the etiology of ASDs, it has been proposed that the genetic components are complicated by substantial locus heterogeneity [13]. Glutamate is a major excitatory neurotransmitter and has important roles in neuronal plasticity and cognitive functions such as memory and learning, which are usually impaired in ASDs. Glutamate and its regulatory proteins are being evaluated for their role as important excitatory neurotransmitters in the pathophysiology of ASDs, and evidences suggesting that abnormalities in glutamatergic signaling pathways occur in ASDs have been gathered through multidisciplinary approaches. These studies support the exploitation of
∗ Corresponding author at: Department of Pharmacology, School of Medicine, Eulji University, 77, Gyeryong-ro 771 Beon-gil, Jung-gu, Daejeon 301-746, Republic of Korea. Tel.: +82 42 259 1677; fax: +82 42 259 1679. E-mail address: [email protected] (S.A. Kim). 0304-3940/$ – see front matter © 2012 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2012.01.061
the glutamatergic neurotransmitter system for future therapeutic interventions for ASDs [8]. Extracellular glutamate is considered as a promoting factor in the cause of ASDs via its neurotoxic capabilities [4]. Previous studies suggest that serum or platelet-poor plasma levels of glutamate were significantly increased in patients with autism compared to healthy controls and correlated with disease severity [31,33]. There are also evidences that metabotropic and ionotropic glutamate receptors are affected in ASDs and that glutamate receptor dysregulation may be involved in the manifestation of ASDs [6,8]. Among the different types of glutamate receptors, Nmethyl-d-aspartate (NMDA) receptors may be interesting targets for autism therapy. A study with autistic individuals showed that daily doses of d-cycloserine (DCS), an NMDA receptor partial agonist, significantly improved social withdrawal [28]. Furthermore, previous studies have reported that daily doses of the NMDA receptor noncompetitive antagonist, amantadine (memantine), reduced some of the negative symptoms of autism, such as hyperactivity [7]. NMDA receptors are neurotransmitter-gated ion channels and have roles in the regulation of synaptic functions in the central nervous system [9]. Inappropriate activation of NMDA receptors has been implicated in several neurological conditions, such as schizophrenia and Alzheimer’s disease [19]. It is known that the identity of the specific subunits determines many of the physiological and pharmacological properties of NMDA receptors [10]. In addition, Moskal et al. [22] reported that gene expression patterns in an
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animal model of autism show significant enrichment in autismassociated genes and the NMDA receptor family was identified as a significant node. GRIN2A, which encodes NMDA receptor subunit 2A (GluN2A), is located on chromosome 16p, a region identified as a candidate autism susceptibility locus in genome-wide screens [27]. Family-based or case–control analyses by Barnby et al. [3] revealed that GRIN2A polymorphism (rs1014531) and haplotypes were associated with autism. Although many studies have been performed to determine the association between NMDA receptor genes and other neuropsychiatric disorders, SNPs studies on the association of these genes with ASDs are few in number. The present study investigates this association in Korean ASDs families by using common SNPs in the 2 NMDA receptor-related genes GRIN2A and GRIN2B.
2. Materials and methods The present study was conducted with 151 Korean complete ASDs trios comprising patients with ASDs (79.9 ± 35.6 months of age, 86.1% male, 87.4% with autism, 13.5% with Pervasive Developmental Disorder not otherwise specified [PDD-NOS], and 1.6% with Asperger’s disorder) and their biological parents, as previously described [15,36]. The ASDs probands were diagnosed using the Korean version of Autism Diagnostic Interview-Revised (ADI-R) and the Korean version of the Autism Diagnostic Observation Schedule (ADOS), together with the evaluation of 2 board-certified child psychiatrists. Subject ascertainment and diagnostic methods have been previously described. Genomic DNA from blood samples was prepared using the G-spin Genomic DNA Extraction Kit (Intron, Daejeon, Korea). Gene structure of candidate genes was determined using the Entrez SNP database (http://www.ncbi.nlm.nih.gov/) and a publicly available genotype database for Asian populations from the International HapMap project (www.hapmap.org). SNPs which are located in the coding region (cSNPs), 5 and 3 region of each gene were first selected (minor allele frequencies (MAFs) > 0.05 in Chinese and Japanese populations). To get more informative families for statistical analysis, the common SNPs in intronic region (MAFs > 0.1 in Chinese and Japanese populations) are also included. Twelve SNPs in the 2 candidate genes (rs1014531, rs8049651, rs3104703, rs865678, rs837694, rs1650420 for GRIN2A; rs3026174, rs1805502, rs1805247, rs1806201, rs1805522, rs3764030 for GRIN2B) were selected for the study and genotyped using the GoldenGateTM Assay (Illumina, San Diego, CA, USA). Mendelian inheritance error for each individual polymorphism was checked by PedCheck (v.1.1). Hardy–Weinberg equilibrium and linkage disequilibrium (LD) values for each pair of SNPs were evaluated with the transmission disequilibrium test (TDT) method in 3.2 (http://www.broad.mit.edu/mpg/haploview). Haploview Family-based association tests for each individual polyand haplotype were assessed using the morphism Family-based Association Test (FBAT) program package (http://www.biostat.harvard.edu/˜fbat/default.html). HBAT, the haplotype version of the FBAT program, was used to find haplotypes with a >5% frequency of association with ASDs. Haplotype tests were performed using permutations (N = 100,000 cycles) with the HBAT Monte Carlo option. The power calculation for the association test and samples was performed using the transmission disequilibrium test (TDT) for discrete traits, available at the genetic power calculator website (http://pngu.mgh.harvard.edu/∼purcell/gpc/). P-value < 0.05 were considered statistically significant. We applied the false-discovery rate (FDR) procedure which proposed by Benjamini and Hochberg (1995) for handling multiple comparisons problems. FDR corrections were performed separately for single-marker and haplotype. FDR corrected P-values (PFDR ) that were <0.05 were considered significant.
Table 1 Pairwise disequilibrium (D /r2 ) matrix in GRIN2B gene.
rs1805502 rs1805247 rs1806201 rs1805522 rs3764030
rs3026174
rs1805502
rs1805247
rs1806201
rs1805522
0.94/0.29 0.95/0.31 0.99/0.78 0.88/0.25 0.22/0.02
0.98/0.93 0.94/0.23 0.88/0.76 0.28/0.01
0.97/0.26 0.89/0.75 0.28/0.01
0.85/0.19 0.23/0.02
0.22/0.01
3. Results In the linkage disequilibrium test for each pair of markers, 5 GRIN2B polymorphisms (except rs3764030) had relative strong LD values (0.85 < D < 0.99) (Table 1). However, GRIN2A polymorphisms showed relative weak LD values (Supplement Table 1). In FBAT analysis, though there were no significant results with any model/mode method for specific polymorphisms (Supplement Table 2), we observed significant P-values for some haplotypes containing markers for GRIN2B that have strong LD values. A maximum of 24 haplotypes was observed with 6 markers in GRIN2B, and haplotypes with a frequency of >0.05 were selected. We conducted haplotype analyses by using the sliding windows methods to find out specific haplotypes that were significant with the multi allelic mode. Haplotypes made by 4 SNPs (rs3026174, rs1805502, rs1805247 and rs1806201) revealed statistical significant association with both the additive (2 = 12.451, df = 4, P = 0.014) and the dominant (2 = 10.868, df = 4, P = 0.028) model (Table 2). After performing the permutation test, these results were confirmed (additive model P = 0.021, dominant model P = 0.024). Addition of an SNP (rs1805522) that has a high LD value in the haplotype analysis also yielded a statistically significant association for both the additive (2 = 15.086, df = 4, P = 0.005) and the dominant (2 = 10.647, df = 4, P = 0.031) model and these results remained significant after the permutation test (additive model P = 0.016, dominant model P = 0.024). In addition, we conducted more analysis for these haplotypes with bi-allelic mode, these haplotypes revealed statistical significance after performing the whole marker permutation test. Although most results lost significances after correcting multiple comparison problems, we could observe that the haplotype made by 4 SNPs (rs3026174 (G), rs1805502 (A), rs1805247 (A), and rs1806201(G)) and the haplotype made by 5 SNPs (rs3026174 (G), rs1805502 (A), rs1805247 (A), rs1806201(G), and rs1805522 (G)) analyzed within the same families revealed consistent statistical significant associations according to the additive (Z = −3.000, P = 0.003, PFDR = 0.012) and the dominant (Z = −2.959, P = 0.003, PFDR = 0.012) models (Table 3). Contrary to what we observed for GRIN2B, the analysis for polymorphisms/haplotypes in GRIN2A, determined by FBAT, did not reach statistical significance with any model and mode analyzed (Supplement Tables 3 and 4). When we used an allelic odds ratio of 1.5 at power calculation, the powers for SNPs ranged from 0.485 to 0.560 (Supplement Table 5). 4. Discussion In our knowledge, this study is the first to identify family-based association between GRIN2B haplotypes and ASDs and it supports a possible role of GRIN2B in ASDs. It is expected that marker haplotypes may provide more information than SNPs for association test and indeed our results suggest the existence of causable variants in LD regions of significantly associated haplotype. In addition, positive replication test results may give more confidence. NMDA receptors are hetero-tetramers composed of an essential glutamate-binding NMDA receptor subunit (GluN) 1 and 4 GluN2 (GluN2A–GluN2D; also called NR2A-D) subunits. NMDA
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Table 2 Haplotype analyses of GRIN2B gene polymorphisms using sliding windows in FBAT module. Haplotypes
A-B B-C C-D D-E E-F A-B-C B-C-D C-D-E D-E-F A-B-C-D B-C-D-E C-D-E-F A-B-C-D-E B-C-D-E-F A-B-C-D-E-F
Multi-allelic mode P-value
Permutation P-value
Additive
Dominant
Recessive
Additive
Dominant
Recessive
0.527 0.063 0.534 0.155 0.251 0.212 0.045 0.083 0.867 0.014 0.052 0.848 0.005 0.737 0.124
0.636 0.806 0.690 0.530 0.031 0.512 0.833 0.827 0.342 0.028 0.824 0.919 0.031 0.875 0.746
0.905 0.611 0.674 0.348 0.179 0.861 0.446 0.364 0.335 0.504 0.226 0.310 0.387 0.269 0.370
0.525 0.269 0.541 0.187 0.376 0.536 0.309 0.153 0.322 0.021 0.230 0.443 0.016 0.674 0.094
0.550 0.335 0.727 0.230 0.118 0.560 0.487 0.231 0.220 0.024 0.420 0.448 0.024 0.705 0.126
0.924 0.530 0.673 0.390 0.182 0.879 0.437 0.361 0.350 0.544 0.227 0.330 0.384 0.277 0.382
The order of SNPs A: rs3026174; B: rs1805502; C: rs1805247; D: rs1806201; E: rs1805522 and F: rs3764030.
receptors play a critical role in cortical development and activitydependent plasticity and these functional properties may depend on the combinations of the different subunits [30]. Unlike GluN1, GluN2 subunits are differentially expressed in various cell types and control the electrophysiological properties of the NMDA receptor. More specifically, GluN2B is mainly present in immature neurons and in extra-synaptic locations. The composition of native NMDA receptors undergoes a developmental change from containing predominantly GluN2B subunits in the early postnatal brain to containing mainly GluN2A subunits [14]. The GluN2B–GluN2A developmental switch of NMDA receptors is thought to be a major determinant of the developmental and experience-dependent properties of synaptic plasticity [37]. The remodeling of the number and the subunit composition of synaptic NMDA receptors is considered an important factor for neuronal activity and development. In the adult cortex and hippocampus, GluN2A and GluN2B are the predominant subunits and GluN2B-containing NMDA receptors have slower channel kinetics and lower open probabilities than those containing GluN2A [9]. It is known that GluN2A/GluN2B ratio and LTP-induction thresholds can be modified by synaptic activity, sensory experience, and learning, which suggests a functional contribution to behavioral plasticity [5,16,29]. Based on these observations, NMDA glutamate receptors are already being considered as potential targets for the treatment of autism. As an example, treatment with GLYX-13, a GluN2B subunit partial agonist, which uses the NMDA receptor glycine-site, has shown positive results in animal model [22]. In mice, GluN2B has an essential role for neuronal pattern formation and synaptic plasticity and for channel function and formation of dendritic spines in hippocampal pyramidal cells [1,9]. Yang et al.
[35] also reported that the activation of GluN2B was required for hippocampal metaplasticity, the plasticity of synaptic plasticity, which usually reflects synaptic history. Transgenic overexpression of GRIN2B in the forebrain of mice and in the cortex and hippocampus of rats resulted in superior performances in learning and memory [32]. GRIN2A knockout mice showed increased spontaneous locomotor activity and deficits in contextual fear conditioning and spatial learning, together with reduced hippocampus long-term potentiation, the cellular basis for learning and memory [17]. The phenotype of GRIN2B-deficient mice is more severe, as they die perinatally due to severe developmental brain defects [18]. Thus, GRIN2B seems to represent a rate-limiting genetic factor in establishing the functions of NMDA receptors both in the developing and in the adult mammalian brain, strongly suggesting an involvement of the GluN2B subunits in human brain function and cognition. Based on all these results, Endele et al. [12] suggested a model according to which polymorphisms in GRIN2B may induce different phenotypes in individuals with different alterations in NMDA receptors, which affect neuronal ion flux and electrical transmission between neurons in the human brain and this has profound effects on neuronal development and activity in humans, resulting in ASDs and attention deficit hyperactivity disorder (ADHD). Dorval et al. [11] suggested an association between variations in GRIN2B and ADHD either measured as categoric traits or as quantitatively distributed traits. Recently, Mori et al. [21] reported that individuals carrying the G allele in the rs1805247 (GRIN2B) show greater intra-cortical facilitation and greater long-term potentiation-like cortical plasticity by comparing the response to single, paired, and repetitive trans-cranial magnetic stimulations of the motor
Table 3 Biallelic mode haplotype analysis results for haplotype blocks in GRIN2B. Haplotype analysis
Additive
Dominant
Markers
Haplotype
Frequency
N
Z
P
N
Z
P
rs3026174 + rs1805502 + rs1805247 + rs1806201
GAAA AAAG AGGG GAAG
0.504 0.227 0.194 0.057
102 92 85 33
1.246 1.224 −0.558 −3.000 P = 0.021
0.213 0.221 0.577 0.003
67 84 84 33
0.688 1.434 −0.443 −2.959 P = 0.024
0.492 0.152 0.658 0.003
GAAAG AAAGG AGGGA GAAGG
0.494 0.222 0.176 0.057
101 92 81 33
1.565 1.139 −0.096 −3.000 P = 0.016
0.117 0.255 0.923 0.003
67 84 81 33
0.876 1.271 −0.003 −2.959 P = 0.026
0.381 0.204 0.998 0.003
Whole marker permutation P-value rs3026174 + rs1805502 + rs1805247 + rs1806201 + rs1805522
Whole marker permutation P-value N, number of informative nuclear families; df, degree of freedom; 2 , 2 statistic; P, P-value.
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cortex in healthy subjects. In addition, there are several positive association studies for SNPs in GRIN2B for short-term memory in dyslexia, language lateralization, and decision-making process [20,24,25]. In this study, we used common SNPs to find association between NMDA receptor genes and ASDs and therefore there are many untested rare variants. Recently, the Rare Allele-Major Effects (RAMEs) model, which predicts that rare variants (minor allele frequency <0.01–0.05) can be key to the genetic cause of common diseases, is gathering consensus. In addition, several reports suggest that the genetic basis for ASDs in sporadic cases may differ from that in families with multiple affected individuals and rare mutations or de novo mutation events would be more likely to explain the pathogenesis of ASDs in the former situation. O’Roak et al. [26] reported the results of exome sequencing in ASDs trios and identified de novo mutations in GRIN2B. However, although these studies suggest that de novo mutations may contribute substantially to the genetic causes of ASDs, they cannot explain the phenotypic variation of ASDs. Recently, Myers et al. [23] reported a significant excess of rare missense mutations compared to silent ones in GRIN2B in autism and schizophrenia patients. This suggests that rare variants (mutations) cause a portion of the phenotypic heterogeneity of complex disorders. If this is confirmed, gene mapping for complex disorders can be done by resequencing samples with smaller sizes than those required for genome-wide association studies. There are also other considerations that are needed for interpreting our results in a genetic background. First, the markers in the study were not selected by linkage disequilibrium and the number of markers may be relative small to cover for gene. And it also was estimated a lack of statistical power at the genetic power calculation in this study (<0.8). Therefore, studies with more markers and samples from a larger population and different ethnic groups are needed in order to confirm our results. In addition, other candidate genes and causable environmental factors could be responsible for the occurrence of ASDs. Therefore, gene–gene and gene–environment interactions must be considered. Acknowledgements This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (2010-0007583). Mira Park was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the ministry of Education, Science and Technology (2011-0004376). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.neulet.2012.01.061. References [1] K. Akashi, T. Kakizaki, H. Kamiya, M. Fukaya, M. Yamasaki, M. Abe, R. Natsume, M. Watanabe, K. Sakimura, NMDA receptor GluN2B (GluR epsilon 2/NR2B) subunit is crucial for channel function, postsynaptic macromolecular organization, and actin cytoskeleton at hippocampal CA3 synapses, J. Neurosci. 29 (2009) 10869–10882. [2] A. Bailey, A. Le Couteur, I. Gottesman, P. Bolton, E. Simonoff, E. Yuzda, M. Rutter, Autism as a strongly genetic disorder: evidence from a British twin study, Psychol. Med. 25 (1995) 63–77. [3] G. Barnby, A. Abbott, N. Sykes, A. Morris, D.E. Weeks, R. Mott, J. Lamb, A.J. Bailey, A.P. Monaco, International molecular genetics study of autism consortium. Candidate-gene screening and association analysis at the autism-susceptibility locus on chromosome 16p: evidence of association at GRIN2A and ABAT, Am. J. Hum. Genet. 76 (2005) 950–966. [4] R.L. Blaylock, A. Strunecka, Immune-glutamatergic dysfunction as a central mechanism of the autism spectrum disorders, Curr. Med. Chem. 16 (2009) 157–170.
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Family based association of GRIN2A and GRIN2B with Korean autism spectrum disorders Hee Jeong Yoo a , In Hee Cho b , Mira Park c , So Young Yang d , Soon Ae Kim d,∗ a
Department of Psychiatry, Seoul National University Bundang Hospital, Seongnam, Kyeonggi, Republic of Korea Department of Psychiatry, Gil Medical Center, Gachon University of Medicine and Science, Incheon, Republic of Korea Department of Preventive Medicine, School of Medicine, Eulji University, Daejeon, Republic of Korea d Department of Pharmacology and Eulji University Medical Sciences Research Center, School of Medicine, Eulji University, Daejeon, Republic of Korea b c
a r t i c l e
i n f o
Article history: Received 28 November 2011 Received in revised form 23 January 2012 Accepted 26 January 2012 Keywords: Autism spectrum disorders (ASDs) Single nucleotide polymorphisms (SNPs) Glutamate receptor, ionotropic, N-methyl-d-aspartate, subunit 2B GRIN gene (GRIN2B) Family-based association study
a b s t r a c t N-Methyl-d-aspartate (NMDA) receptor, one of the glutamate receptors, has a role in the regulation of synaptic activity. It functions as an ion channel in the central nervous system and its inappropriate activation has been implicated in several neurological conditions. To test the association between candidate genes related with NMDA receptors and autism spectrum disorders (ASDs), we examined single nucleotide polymorphisms (SNPs) for GRIN2A and GRIN2B by using the family-based association test (FBAT) in 151 Korean trios. There was a statistically significant associations between ASDs and haplotypes in GRIN2B (bi-allelic mode additive model P-value = 0.003; FDR P-value = 0.012). This study supports a possible role of GRIN2B as a candidate gene for the etiology of ASDs. © 2012 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Autism spectrum disorders (ASDs) are neuropsychiatric developmental disorders associated with multiple symptoms, including impairment of social communication/interaction and restrictive/repetitive behaviors [34]. Autism might be highly heritable owing to the large monozygotic/dizygotic (MZ:DZ) difference in concordance [2]. ASDs may occur in a child who inherits several genes with each of them contributing to the disease phenotype. In the etiology of ASDs, it has been proposed that the genetic components are complicated by substantial locus heterogeneity [13]. Glutamate is a major excitatory neurotransmitter and has important roles in neuronal plasticity and cognitive functions such as memory and learning, which are usually impaired in ASDs. Glutamate and its regulatory proteins are being evaluated for their role as important excitatory neurotransmitters in the pathophysiology of ASDs, and evidences suggesting that abnormalities in glutamatergic signaling pathways occur in ASDs have been gathered through multidisciplinary approaches. These studies support the exploitation of
∗ Corresponding author at: Department of Pharmacology, School of Medicine, Eulji University, 77, Gyeryong-ro 771 Beon-gil, Jung-gu, Daejeon 301-746, Republic of Korea. Tel.: +82 42 259 1677; fax: +82 42 259 1679. E-mail address: [email protected] (S.A. Kim). 0304-3940/$ – see front matter © 2012 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2012.01.061
the glutamatergic neurotransmitter system for future therapeutic interventions for ASDs [8]. Extracellular glutamate is considered as a promoting factor in the cause of ASDs via its neurotoxic capabilities [4]. Previous studies suggest that serum or platelet-poor plasma levels of glutamate were significantly increased in patients with autism compared to healthy controls and correlated with disease severity [31,33]. There are also evidences that metabotropic and ionotropic glutamate receptors are affected in ASDs and that glutamate receptor dysregulation may be involved in the manifestation of ASDs [6,8]. Among the different types of glutamate receptors, Nmethyl-d-aspartate (NMDA) receptors may be interesting targets for autism therapy. A study with autistic individuals showed that daily doses of d-cycloserine (DCS), an NMDA receptor partial agonist, significantly improved social withdrawal [28]. Furthermore, previous studies have reported that daily doses of the NMDA receptor noncompetitive antagonist, amantadine (memantine), reduced some of the negative symptoms of autism, such as hyperactivity [7]. NMDA receptors are neurotransmitter-gated ion channels and have roles in the regulation of synaptic functions in the central nervous system [9]. Inappropriate activation of NMDA receptors has been implicated in several neurological conditions, such as schizophrenia and Alzheimer’s disease [19]. It is known that the identity of the specific subunits determines many of the physiological and pharmacological properties of NMDA receptors [10]. In addition, Moskal et al. [22] reported that gene expression patterns in an
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animal model of autism show significant enrichment in autismassociated genes and the NMDA receptor family was identified as a significant node. GRIN2A, which encodes NMDA receptor subunit 2A (GluN2A), is located on chromosome 16p, a region identified as a candidate autism susceptibility locus in genome-wide screens [27]. Family-based or case–control analyses by Barnby et al. [3] revealed that GRIN2A polymorphism (rs1014531) and haplotypes were associated with autism. Although many studies have been performed to determine the association between NMDA receptor genes and other neuropsychiatric disorders, SNPs studies on the association of these genes with ASDs are few in number. The present study investigates this association in Korean ASDs families by using common SNPs in the 2 NMDA receptor-related genes GRIN2A and GRIN2B.
2. Materials and methods The present study was conducted with 151 Korean complete ASDs trios comprising patients with ASDs (79.9 ± 35.6 months of age, 86.1% male, 87.4% with autism, 13.5% with Pervasive Developmental Disorder not otherwise specified [PDD-NOS], and 1.6% with Asperger’s disorder) and their biological parents, as previously described [15,36]. The ASDs probands were diagnosed using the Korean version of Autism Diagnostic Interview-Revised (ADI-R) and the Korean version of the Autism Diagnostic Observation Schedule (ADOS), together with the evaluation of 2 board-certified child psychiatrists. Subject ascertainment and diagnostic methods have been previously described. Genomic DNA from blood samples was prepared using the G-spin Genomic DNA Extraction Kit (Intron, Daejeon, Korea). Gene structure of candidate genes was determined using the Entrez SNP database (http://www.ncbi.nlm.nih.gov/) and a publicly available genotype database for Asian populations from the International HapMap project (www.hapmap.org). SNPs which are located in the coding region (cSNPs), 5 and 3 region of each gene were first selected (minor allele frequencies (MAFs) > 0.05 in Chinese and Japanese populations). To get more informative families for statistical analysis, the common SNPs in intronic region (MAFs > 0.1 in Chinese and Japanese populations) are also included. Twelve SNPs in the 2 candidate genes (rs1014531, rs8049651, rs3104703, rs865678, rs837694, rs1650420 for GRIN2A; rs3026174, rs1805502, rs1805247, rs1806201, rs1805522, rs3764030 for GRIN2B) were selected for the study and genotyped using the GoldenGateTM Assay (Illumina, San Diego, CA, USA). Mendelian inheritance error for each individual polymorphism was checked by PedCheck (v.1.1). Hardy–Weinberg equilibrium and linkage disequilibrium (LD) values for each pair of SNPs were evaluated with the transmission disequilibrium test (TDT) method in 3.2 (http://www.broad.mit.edu/mpg/haploview). Haploview Family-based association tests for each individual polyand haplotype were assessed using the morphism Family-based Association Test (FBAT) program package (http://www.biostat.harvard.edu/˜fbat/default.html). HBAT, the haplotype version of the FBAT program, was used to find haplotypes with a >5% frequency of association with ASDs. Haplotype tests were performed using permutations (N = 100,000 cycles) with the HBAT Monte Carlo option. The power calculation for the association test and samples was performed using the transmission disequilibrium test (TDT) for discrete traits, available at the genetic power calculator website (http://pngu.mgh.harvard.edu/∼purcell/gpc/). P-value < 0.05 were considered statistically significant. We applied the false-discovery rate (FDR) procedure which proposed by Benjamini and Hochberg (1995) for handling multiple comparisons problems. FDR corrections were performed separately for single-marker and haplotype. FDR corrected P-values (PFDR ) that were <0.05 were considered significant.
Table 1 Pairwise disequilibrium (D /r2 ) matrix in GRIN2B gene.
rs1805502 rs1805247 rs1806201 rs1805522 rs3764030
rs3026174
rs1805502
rs1805247
rs1806201
rs1805522
0.94/0.29 0.95/0.31 0.99/0.78 0.88/0.25 0.22/0.02
0.98/0.93 0.94/0.23 0.88/0.76 0.28/0.01
0.97/0.26 0.89/0.75 0.28/0.01
0.85/0.19 0.23/0.02
0.22/0.01
3. Results In the linkage disequilibrium test for each pair of markers, 5 GRIN2B polymorphisms (except rs3764030) had relative strong LD values (0.85 < D < 0.99) (Table 1). However, GRIN2A polymorphisms showed relative weak LD values (Supplement Table 1). In FBAT analysis, though there were no significant results with any model/mode method for specific polymorphisms (Supplement Table 2), we observed significant P-values for some haplotypes containing markers for GRIN2B that have strong LD values. A maximum of 24 haplotypes was observed with 6 markers in GRIN2B, and haplotypes with a frequency of >0.05 were selected. We conducted haplotype analyses by using the sliding windows methods to find out specific haplotypes that were significant with the multi allelic mode. Haplotypes made by 4 SNPs (rs3026174, rs1805502, rs1805247 and rs1806201) revealed statistical significant association with both the additive (2 = 12.451, df = 4, P = 0.014) and the dominant (2 = 10.868, df = 4, P = 0.028) model (Table 2). After performing the permutation test, these results were confirmed (additive model P = 0.021, dominant model P = 0.024). Addition of an SNP (rs1805522) that has a high LD value in the haplotype analysis also yielded a statistically significant association for both the additive (2 = 15.086, df = 4, P = 0.005) and the dominant (2 = 10.647, df = 4, P = 0.031) model and these results remained significant after the permutation test (additive model P = 0.016, dominant model P = 0.024). In addition, we conducted more analysis for these haplotypes with bi-allelic mode, these haplotypes revealed statistical significance after performing the whole marker permutation test. Although most results lost significances after correcting multiple comparison problems, we could observe that the haplotype made by 4 SNPs (rs3026174 (G), rs1805502 (A), rs1805247 (A), and rs1806201(G)) and the haplotype made by 5 SNPs (rs3026174 (G), rs1805502 (A), rs1805247 (A), rs1806201(G), and rs1805522 (G)) analyzed within the same families revealed consistent statistical significant associations according to the additive (Z = −3.000, P = 0.003, PFDR = 0.012) and the dominant (Z = −2.959, P = 0.003, PFDR = 0.012) models (Table 3). Contrary to what we observed for GRIN2B, the analysis for polymorphisms/haplotypes in GRIN2A, determined by FBAT, did not reach statistical significance with any model and mode analyzed (Supplement Tables 3 and 4). When we used an allelic odds ratio of 1.5 at power calculation, the powers for SNPs ranged from 0.485 to 0.560 (Supplement Table 5). 4. Discussion In our knowledge, this study is the first to identify family-based association between GRIN2B haplotypes and ASDs and it supports a possible role of GRIN2B in ASDs. It is expected that marker haplotypes may provide more information than SNPs for association test and indeed our results suggest the existence of causable variants in LD regions of significantly associated haplotype. In addition, positive replication test results may give more confidence. NMDA receptors are hetero-tetramers composed of an essential glutamate-binding NMDA receptor subunit (GluN) 1 and 4 GluN2 (GluN2A–GluN2D; also called NR2A-D) subunits. NMDA
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Table 2 Haplotype analyses of GRIN2B gene polymorphisms using sliding windows in FBAT module. Haplotypes
A-B B-C C-D D-E E-F A-B-C B-C-D C-D-E D-E-F A-B-C-D B-C-D-E C-D-E-F A-B-C-D-E B-C-D-E-F A-B-C-D-E-F
Multi-allelic mode P-value
Permutation P-value
Additive
Dominant
Recessive
Additive
Dominant
Recessive
0.527 0.063 0.534 0.155 0.251 0.212 0.045 0.083 0.867 0.014 0.052 0.848 0.005 0.737 0.124
0.636 0.806 0.690 0.530 0.031 0.512 0.833 0.827 0.342 0.028 0.824 0.919 0.031 0.875 0.746
0.905 0.611 0.674 0.348 0.179 0.861 0.446 0.364 0.335 0.504 0.226 0.310 0.387 0.269 0.370
0.525 0.269 0.541 0.187 0.376 0.536 0.309 0.153 0.322 0.021 0.230 0.443 0.016 0.674 0.094
0.550 0.335 0.727 0.230 0.118 0.560 0.487 0.231 0.220 0.024 0.420 0.448 0.024 0.705 0.126
0.924 0.530 0.673 0.390 0.182 0.879 0.437 0.361 0.350 0.544 0.227 0.330 0.384 0.277 0.382
The order of SNPs A: rs3026174; B: rs1805502; C: rs1805247; D: rs1806201; E: rs1805522 and F: rs3764030.
receptors play a critical role in cortical development and activitydependent plasticity and these functional properties may depend on the combinations of the different subunits [30]. Unlike GluN1, GluN2 subunits are differentially expressed in various cell types and control the electrophysiological properties of the NMDA receptor. More specifically, GluN2B is mainly present in immature neurons and in extra-synaptic locations. The composition of native NMDA receptors undergoes a developmental change from containing predominantly GluN2B subunits in the early postnatal brain to containing mainly GluN2A subunits [14]. The GluN2B–GluN2A developmental switch of NMDA receptors is thought to be a major determinant of the developmental and experience-dependent properties of synaptic plasticity [37]. The remodeling of the number and the subunit composition of synaptic NMDA receptors is considered an important factor for neuronal activity and development. In the adult cortex and hippocampus, GluN2A and GluN2B are the predominant subunits and GluN2B-containing NMDA receptors have slower channel kinetics and lower open probabilities than those containing GluN2A [9]. It is known that GluN2A/GluN2B ratio and LTP-induction thresholds can be modified by synaptic activity, sensory experience, and learning, which suggests a functional contribution to behavioral plasticity [5,16,29]. Based on these observations, NMDA glutamate receptors are already being considered as potential targets for the treatment of autism. As an example, treatment with GLYX-13, a GluN2B subunit partial agonist, which uses the NMDA receptor glycine-site, has shown positive results in animal model [22]. In mice, GluN2B has an essential role for neuronal pattern formation and synaptic plasticity and for channel function and formation of dendritic spines in hippocampal pyramidal cells [1,9]. Yang et al.
[35] also reported that the activation of GluN2B was required for hippocampal metaplasticity, the plasticity of synaptic plasticity, which usually reflects synaptic history. Transgenic overexpression of GRIN2B in the forebrain of mice and in the cortex and hippocampus of rats resulted in superior performances in learning and memory [32]. GRIN2A knockout mice showed increased spontaneous locomotor activity and deficits in contextual fear conditioning and spatial learning, together with reduced hippocampus long-term potentiation, the cellular basis for learning and memory [17]. The phenotype of GRIN2B-deficient mice is more severe, as they die perinatally due to severe developmental brain defects [18]. Thus, GRIN2B seems to represent a rate-limiting genetic factor in establishing the functions of NMDA receptors both in the developing and in the adult mammalian brain, strongly suggesting an involvement of the GluN2B subunits in human brain function and cognition. Based on all these results, Endele et al. [12] suggested a model according to which polymorphisms in GRIN2B may induce different phenotypes in individuals with different alterations in NMDA receptors, which affect neuronal ion flux and electrical transmission between neurons in the human brain and this has profound effects on neuronal development and activity in humans, resulting in ASDs and attention deficit hyperactivity disorder (ADHD). Dorval et al. [11] suggested an association between variations in GRIN2B and ADHD either measured as categoric traits or as quantitatively distributed traits. Recently, Mori et al. [21] reported that individuals carrying the G allele in the rs1805247 (GRIN2B) show greater intra-cortical facilitation and greater long-term potentiation-like cortical plasticity by comparing the response to single, paired, and repetitive trans-cranial magnetic stimulations of the motor
Table 3 Biallelic mode haplotype analysis results for haplotype blocks in GRIN2B. Haplotype analysis
Additive
Dominant
Markers
Haplotype
Frequency
N
Z
P
N
Z
P
rs3026174 + rs1805502 + rs1805247 + rs1806201
GAAA AAAG AGGG GAAG
0.504 0.227 0.194 0.057
102 92 85 33
1.246 1.224 −0.558 −3.000 P = 0.021
0.213 0.221 0.577 0.003
67 84 84 33
0.688 1.434 −0.443 −2.959 P = 0.024
0.492 0.152 0.658 0.003
GAAAG AAAGG AGGGA GAAGG
0.494 0.222 0.176 0.057
101 92 81 33
1.565 1.139 −0.096 −3.000 P = 0.016
0.117 0.255 0.923 0.003
67 84 81 33
0.876 1.271 −0.003 −2.959 P = 0.026
0.381 0.204 0.998 0.003
Whole marker permutation P-value rs3026174 + rs1805502 + rs1805247 + rs1806201 + rs1805522
Whole marker permutation P-value N, number of informative nuclear families; df, degree of freedom; 2 , 2 statistic; P, P-value.
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cortex in healthy subjects. In addition, there are several positive association studies for SNPs in GRIN2B for short-term memory in dyslexia, language lateralization, and decision-making process [20,24,25]. In this study, we used common SNPs to find association between NMDA receptor genes and ASDs and therefore there are many untested rare variants. Recently, the Rare Allele-Major Effects (RAMEs) model, which predicts that rare variants (minor allele frequency <0.01–0.05) can be key to the genetic cause of common diseases, is gathering consensus. In addition, several reports suggest that the genetic basis for ASDs in sporadic cases may differ from that in families with multiple affected individuals and rare mutations or de novo mutation events would be more likely to explain the pathogenesis of ASDs in the former situation. O’Roak et al. [26] reported the results of exome sequencing in ASDs trios and identified de novo mutations in GRIN2B. However, although these studies suggest that de novo mutations may contribute substantially to the genetic causes of ASDs, they cannot explain the phenotypic variation of ASDs. Recently, Myers et al. [23] reported a significant excess of rare missense mutations compared to silent ones in GRIN2B in autism and schizophrenia patients. This suggests that rare variants (mutations) cause a portion of the phenotypic heterogeneity of complex disorders. If this is confirmed, gene mapping for complex disorders can be done by resequencing samples with smaller sizes than those required for genome-wide association studies. There are also other considerations that are needed for interpreting our results in a genetic background. First, the markers in the study were not selected by linkage disequilibrium and the number of markers may be relative small to cover for gene. And it also was estimated a lack of statistical power at the genetic power calculation in this study (<0.8). Therefore, studies with more markers and samples from a larger population and different ethnic groups are needed in order to confirm our results. In addition, other candidate genes and causable environmental factors could be responsible for the occurrence of ASDs. Therefore, gene–gene and gene–environment interactions must be considered. Acknowledgements This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (2010-0007583). Mira Park was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the ministry of Education, Science and Technology (2011-0004376). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.neulet.2012.01.061. References [1] K. Akashi, T. Kakizaki, H. Kamiya, M. Fukaya, M. Yamasaki, M. Abe, R. Natsume, M. Watanabe, K. Sakimura, NMDA receptor GluN2B (GluR epsilon 2/NR2B) subunit is crucial for channel function, postsynaptic macromolecular organization, and actin cytoskeleton at hippocampal CA3 synapses, J. Neurosci. 29 (2009) 10869–10882. [2] A. Bailey, A. Le Couteur, I. Gottesman, P. Bolton, E. Simonoff, E. Yuzda, M. Rutter, Autism as a strongly genetic disorder: evidence from a British twin study, Psychol. Med. 25 (1995) 63–77. [3] G. Barnby, A. Abbott, N. Sykes, A. Morris, D.E. Weeks, R. Mott, J. Lamb, A.J. Bailey, A.P. Monaco, International molecular genetics study of autism consortium. Candidate-gene screening and association analysis at the autism-susceptibility locus on chromosome 16p: evidence of association at GRIN2A and ABAT, Am. J. Hum. Genet. 76 (2005) 950–966. [4] R.L. Blaylock, A. Strunecka, Immune-glutamatergic dysfunction as a central mechanism of the autism spectrum disorders, Curr. Med. Chem. 16 (2009) 157–170.
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