Neurexin 3 polymorphisms are associated with alcohol dependence ...

Human Molecular Genetics, 2007, Vol. 16, No. 23 doi:10.1093/hmg/ddm247 Advance Access published on September 4, 2007

2880–2891

Neurexin 3 polymorphisms are associated with alcohol dependence and altered expression of specific isoforms Akitoyo Hishimoto1, Qing-Rong Liu1, Tomas Drgon1, Olga Pletnikova2, Donna Walther1, Xu-Guang Zhu1, Juan C. Troncoso2 and George R. Uhl1,* 1

Molecular Neurobiology Branch, NIDA-IRP, NIH, DHSS, 333 Cassell Drive, Suite 3510, Baltimore, MD 21224, USA and 2Department of Pathology, Neuropathology Division, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21205, USA

Received July 3, 2007; Revised and Accepted August 23, 2007

dbSNP accession no. ss68362653

Neurexins are cell adhesion molecules that help to specify and stabilize synapses and provide receptors for neuroligins, neurexophilins, dystroglycans and a-latrotoxins. We previously reported significant allele frequency differences for single nucleotide polymorphisms (SNPs) in the neurexin 3 (NRXN3) gene in each of two comparisons between individuals who were dependent on illegal substances and controls. We now report work clarifying details of NRXN3’s gene structure and variants and documenting association of NRXN3 SNPs with alcohol dependence. We localize this association signal with the vicinity of the NRXN3 splicing site 5 (SS#5). A splicing site SNP, rs8019381, that is located 23 bp from the SS#5 exon 23 donor site displays association with P 5 0.0007 (odds ratio 5 2.46). Including or excluding exon 23 at SS#5 produces soluble or transmembrane NRXN3 isoforms. We thus examined expression of these NRXN3 isoforms in postmortem human cerebral cortical brain samples from individuals with varying rs8019381 genotypes. Two of the splice variants that encode transmembrane NRXN3 isoforms were expressed at significantly lower levels in individuals with the addiction-associated rs8019381 ‘T’ allele than in CC homozygotes. Taken together with recent reports of NRXN3 association with nicotine dependence and linkage with opiate dependence, these data support roles for NRXN3 haplotypes that alter expression of specific NRXN3 isoforms in genetic vulnerabilities to dependence on a variety of addictive substances.

INTRODUCTION Addictions are major public-health problems, providing the underlying causes for more than 12% of deaths (World Health Organization report the global burden of addiction (http://www.who.int/substance_abuse/facts/global_burden/en/). Family, adoption, and twin data document that: (i) dependence on addictive substances is a complex trait with strong genetic influences and (ii) most of this genetic vulnerability is common to addictions to different classes of legal and illegal addictive substances (1 – 7). Identifying which allelic variants contribute to individual human differences in vulnerability to addictions can aid in understanding neurobiological pathways that contribute to addiction vulnerabilities and may even help matching anti-addiction treatment and prevention

efforts with the individuals who are most likely to benefit from them (8). Addiction vulnerability allelic variants have been sought with genome-wide association studies of increasing resolution (9 – 12). We recently reported that a single nucleotide polymorphism (SNP) in the 30 region of the neurexin 3 (NRXN3) gene (rs760288) displays allele frequencies that distinguish individuals who are dependent on illegal substances from control individuals in each of two independent samples, based on data from a 10 000 SNP genome-wide association study (10). As we were preparing the present manuscript, these observations have received support from results of an association study of a nicotine-dependence phenotype (13) and a linkage study of opioid dependence (14).

*To whom correspondence should be addressed. Tel: þ1 4105502843, ext. 146; Fax: þ1 4105501535; Email: [email protected]

Published by Oxford University Press 2007.

Human Molecular Genetics, 2007, Vol. 16, No. 23

Neurexins function as cell adhesion molecules in the nervous system at excitatory and inhibitory synapses (15 – 25). The three mammalian neurexin genes, NRXN1 (2q16.3), NRXN2 (11q13.2) and NRXN3 (14q31.1), each display multiple promoters from which longer a-neurexins and shorter b-neurexins are transcribed. Differential promoter usage and/or differential splicing events provide many neurexin isoforms (24,26 –29). Several of these isoforms display differential abilities to bind to ligands that include largely membrane-bound endogenous neuroligins and dystroglycans, largely soluble endogenous neurexophilins and a-latrotoxin spider neurotoxins (30 – 32). Neurexin splicing variants provide opportunities to produce both membrane-bound and soluble isoforms (26 –28). Variants in cell adhesion molecules are especially interesting for thinking about individual differences in vulnerability to human addictions. Individual differences in cell adhesion molecule expression could lead to differential development of brain circuits, differences in adult brain circuits, differences in brain adaptations to addictive drugs and even differences in brain adaptations to drug-associated environmental cues. Haplotypes at almost two dozen cell adhesion molecules are nominated and/or confirmed for roles in addiction vulnerability through genome scanning, fine mapping and/or animal model studies (9,33,34). Such variants in cell adhesion molecules need to be considered on the background of the large amount of diversity that is found in the products of most cell adhesion molecule genes. Many cell adhesion molecule genes display (i) variations in levels of expression that include regulation by acute and/or chronic administration of addictive substances (34 –38); (ii) diverse transcripts produced through use of alternative promoter, splicing and/or polyadenylation sites (9) and (iii) missense variations. Many cell adhesion molecules are expressed in neurons in brain regions that are implicated in rewarding and mnemonic processes likely to contribute to addiction vulnerabilities (8). NRXN3 expression in layers 2 and 3 and 5 and 6 of specific cerebral cortical regions is documented in rodent brain atlas images (39). Although NRXN3 is also expressed in other brain regions of interest for addiction, its expression in glutamatergic projections that arise from pre-frontal cortex to innervate nucleus accumbens and other striatal regions and/ or in GABAergic neurons that project from cortical area to cortical area provide sites at which altered expression could readily influence circuits that are key for addictive behaviors. Alterations in the size or strength of synapses in these circuits could provide alterations in brain connectivity and function that could predispose to development of substance dependences. Mice with deletions of single and/or multiple NRXN genes display altered calcium-triggered neurotransmitter release and changed activities of excitatory and inhibitory neurotransmitter systems, underscoring the roles that human variants in these genes might play (23,25,40). Despite these potentially interesting NRXN3 features, many details of this gene’s structure, expression and variations have not been completely characterized. We thus now report assembly of NRXN3 sequences and documentation of the expression of a-NRXN3 and b-NRXN3 messenger ribonucleic acid (mRNA) variants in postmortem human brain samples. We focus on 30 aspects of the NRXN3 gene near alternative

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splicing sites 4 and 5 termed ‘SS#4’ and ‘SS#5’, as the rs760288 SNP that we initially associated with addiction vulnerability lies in this 30 NRXN3 region (Fig. 1A). To seek further generalization and better localization of this initial association finding, we report examination of frequencies of allelic variants that lie near NRXN3 SS#4 and SS#5 in alcoholdependent versus control individuals. We describe characterization of expression of a-NRXN3, b-NRXN3 and 10 potential NRXN3 SS#5 splice variants in mRNAs extracted from several human brain regions. Finally, we report study of associations between the SNPs that displayed the strongest association with alcohol dependence and the patterns of expression of specific NRXN3 isoforms in samples from human pre-frontal cortex. Taken together, the data from these different approaches support contributions of common human haplotypes that alter the quantities of specific NRXN3 transcripts to individual differences in vulnerabilities to dependence on alcohol and other addictive substances.

RESULTS Sequence analysis and confirmation of the exon/intron structures of NRXN3 Assembly of genomic, cDNA and expressed sequence tag (EST) sequences covering 1 826 818 nucleotides confirms many previously reported aspects of the NRXN3 gene’s structure (26 –28) (Fig. 1). a-NRXN3 mRNA is transcribed from an a-specific promoter at the 50 end of the gene. b-NRXN3 mRNA is transcribed from a b-specific promoter located between exons b1 and 17. Figure 1 depicts the NRXN3 alternative splicing sites SS#1 –5 and emphasizes the regions of SS#4 and SS#5. Within these regions, we confirm several previously reported SNPs. We also document a novel simple sequence length polymorphism (SSLP), an AC dinucleotide repeat (ss68362653), that is located 1.6 kb 50 from exon 23 and displays at least 16 allelic variations (Supplementary Material, Fig. S1). a-NRXN3 and b-NRXN3 mRNA expression levels in postmortem human brains To confirm EST data and to provide a more precise picture of the repertoire of NRXN3 gene products, we assess relative levels of a-NRXN3 and b-NRXN3 mRNAs among mRNAs extracted from 59 pre-frontal cortical samples and from more modest numbers of samples from other brain regions. RT – PCR assays with a-NRXN3- and b-NRXN3-specific primers and minor groove binding (MGB) probe sets provide amplifications that avoid amplifying genomic DNA contaminants (Supplementary Material, Table S1). In brains from subjects whose characteristics are noted in Table 1, frontal cortical a-NRXN3 mRNA levels are 5-fold higher than b-NRXN3 mRNA levels (P ¼ 0.0001, two-tailed Wilcoxon signed rank test) (Fig. 2). We identify no significant correlation between a-NRXN3 or b-NRXN3 mRNA levels and either age (P ¼ 0.809, Spearman r ¼ 20.032 and P ¼ 0.734, Spearman r ¼ 0.045, respectively), gender, ethnicity/race or postmortem interval (data not shown). We explore the expression of a-NRXN3 and

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Figure 1. (A) Organization of the human NRXN3 gene described by Rowen et al. (26) and Tabuchi and Sudhof (27). The exon–intron structure of the NRXN3 gene is depicted. The a-NRXN3 mRNA is transcribed from a promoter at the beginning of the gene, where the b-NRXN3 mRNA is transcribed from a promoter located between exons 17 and b1. Exon numbers are depicted above and below each exon. Five alternative splicing sites (SS#1– 5) are indicated. The NRXN3 gene spans 1 826 818 nucleotides (28). The approximate location of rs760288 SNP is shown. (B) Enlarged depiction of SS#4 and SS#5 NRXN3 gene regions. The approximate location of each polymorphism (SNP1–9) studied here, LD and haplotype block structures are depicted. Each box represents the D0 value that corresponds to each pair wise SNP combination. Bright red and shades of pink/red denote LOD score of 2 for the LD, whereas blue boxes denote LOD score of ,2.

b-NRXN3 mRNAs in hippocampus (n ¼ 5), substantia nigra (n ¼ 8), midbrain (n ¼ 4), caudate (n ¼ 1), putamen (n ¼ 1) and cerebellum (n ¼ 4) (Supplementary Material, Fig. S2). Although the expression of a-NRXN3 mRNA shows less than 2-fold differences among the seven brain regions examined, b-NRXN3 is expressed in frontal cortex, hippocampus, midbrain and caudate at levels that are lower than those in the substantia nigra (P ¼ 0.0392 by two-tailed Mann – Whitney test when compared with frontal cortex), cerebellum (P ¼ 0.0032) and putamen (n ¼ 1). In cerebellum, b-NRXN3

expression was over 50-fold higher than a-NRXN3 expression (P ¼ 0.0032 by two-tailed Mann – Whitney test). NRXN3 SS#5 splice variants and their expression The NRXN3 SS#5 provides more than 30 variants, exhibiting the greatest number of variants in this gene (26 – 28) (Fig. 3A). Exon 23 is a key SS#5 exon. Exon 23 contains multiple alternative splice acceptor sites, a single donor site and multiple inframe stop codons for variants that produce


Table 1. Characteristics of subjects for NRXN3 mRNA measurements Subject

n

Race

Sex

Age

PMI

Pre-frontal cortex Substantia nigra Hippocampus Cerebellum Midbrain Caudatea Putamena

59 8 5 4 4 1 1

54C/5AA 8C 5C 4C 4C — —

14F/45M 2F/6M 2F/3M 2F/2M 1F/3M — —

45.8 + 19.6 35.5 + 11.3 69.4 + 18.6 77.3 + 12.7 35.0 + 4.69 — —

10.5 + 6.3 Unknown 16.6 + 3.6 11.3 + 5.5 Unknown — —

n, number of subjects; C, Caucasian; AA, African-American; F, female; M, male; PMI, postmortem interval (hours). a Data not available for human total RNAs from caudate and putamen that were purchased from Clontech (Mountain View).

Figure 2. Levels of expression of mRNAs encoding a-NRXN3 and b-NRXN3 in human pre-frontal cortex (n ¼ 59). Fold differences were calculated on the basis of the mean expression levels of a-NRXN3 as a reference. P , 0.0001. P-values were calculated using two-tailed Wilcoxon-matched pair tests.

exons 23a, 23b, 23c and 23d. These variants thus generate 40, 22, 7, 17 amino acids insertions that follow the exon 22 splice site (Supplementary Material, Fig. S3). Soluble isoforms are thus encoded by transcripts that include exon 23. In contrast, transmembrane NRXN3 isoforms are encoded by transcripts that splice exon 22a or 22b directly to exon 24 and omit exon 23. In mRNAs extracted from postmortem human brain regional samples, we first document levels of expression of exon 22a-containing mRNAs that are much more abundant than those for mRNAs containing exon 22b (Supplementary Material, Fig. S4). We then document the patterns of expression of SS#5 variants in mRNAs extracted from dorsolateral pre-frontal cortex (n ¼ 20), hippocampus (n ¼ 5), substantia nigra (n ¼ 8), midbrain (n ¼ 4), caudate (n ¼ 1), putamen (n ¼ 1) and cerebellum (n ¼ 4) using TaqMan probes that selectively recognize 30 sequences of

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exon 22a and 50 sequences of exon 23 or 24 (Supplementary Material, Table S1). Splice variants ex22a24a, ex22a24b, ex22a24c, ex22a23a, ex22a23c and ex23 – 24a are detected among both a-NRXN3 and b-NRXN3 isoforms in all brain regional mRNAs tested (Fig. 3B). Expression of ex23 – 24b and ex23 –24c variants is restricted to cerebellum for both a-NRXN3 and b-NRXN3. Neither ex22a23b nor ex22a23d is detected in any brain region using either a-NRXN3 or b-NRXN3 templates. Real-time quantitative PCR assessments confirm this pattern of expression for 10 NRXN3-SS#5 variants (Supplementary Material, Fig. S5). Of the transmembrane isoforms studied, expression of ex22a24b is greater than that of either ex22a24a or ex22a24c in most brain regions. In hippocampus and putamen, ex22a24b and ex22a24a variants are expressed at similar levels. Exon 24a encodes C-terminal peptide sequences that include sequences with moderate homology with fibronectin III (FNIII) domains (http://smart.embl-heidelberg.de/smart/set_ mode.cgi?NORMAL ¼ 1), a transmembrane domain and intracellular domains. Exons 24a, 24b and 24c provide different-length peptide sequences that lie N-terminal to the transmembrane domain. In comparison with 22a24a, the 22a24b variant deletes 101 amino acids and shortens the FNIII domain. The 22a24c variant deletes 208 amino acids and omits the entire FNIII domain (Supplementary Material, Fig. S3). In pre-frontal cortex, ex22a24b expression is 3- and 1.4-fold higher than expression of ex22a24a or ex22a24c, respectively (P ¼ 0.0002 and 0.035, respectively by two-tailed Wilcoxon signed rank test). For the soluble isoforms that contain exon 23, expression of ex22a23a mRNA is higher than that of ex22a23c in each tested brain region. In pre-frontal cortex, ex22a23a expression is approximately 15 times higher than ex22a24a (P , 0.0001 by two-tailed Wilcoxon signed rank test) and over 500-fold higher than ex22a23c expression (P ¼ 0.0001 by twotailed Wilcoxon signed rank test). Assays using MGB probes for ex22a23a and ex23–24a demonstrate that soluble isoforms are predominant in all brain regions (Supplementary Material, Fig. S5). The predominant patterns of alternative splicing at SS#5 are thus ex22a – ex24b, ex22a – ex24c and ex22a – ex24a for transmembrane isoforms and ex22a-ex23a-ex24a for soluble isoforms. These patterns are maintained in most of the brain regions tested and for both a- NRXN3 and b- NRXN3 isoforms (Supplementary Material, Fig. S5). Association between NRXN3 SS#5-region genomic variants and alcohol dependence With this improved understanding of the NRXN3 gene and the isoforms found among its products, we seek replication and generalization of associations with addictions. We focus on the SS#5 areas identified by the initial association between dependence on illegal substances and rs760288, located in the 30 region of NRXN3 gene. We genotype nine SNPs in this 30 NRXN3 region with focus on the SS#4 and SS#5 regions. We determine allele frequencies in 144 unrelated European –American individuals with alcohol dependence and 188 matched controls selected from Collaborative Study on the Genetics of Alcoholism (COGA) pedigrees, as described previously (12,41) (Table 2, Fig. 1B). Allele

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Figure 3. (A) Splicing patterns at SS#5 of the NRXN3 gene. The number of potential variants for the splicing site is 30. Exon 24 is the last exon of the gene that codes for the transmembrane region, cytoplasmic tails and also contains 30 -UTR. Because any exon 23 isoforms include inframe stop codons, if it is inserted, soluble a- and b-NRXN3 can be produced from this gene. (B) The 10 alternative splice variants are investigated in pre-frontal cortex (PFC), hippocampus (Hip), substantia nigra (SN), midbrain (MD), caudate (Cau), putamen (Put) and cerebellum (Cb) from normal control subjects. For those interested in ‘classical’ addiction-associated brain regions, we note that high-level expression in neurons of the substantia nigra approximates levels of expression in adjacent ventral tegmental area neurons and that moderate levels of expression in caudate and putamen approximate levels of expression of NRXN3 in adjacent nucleus accumbens in Allan Reference Atlas rodent brain images (http://www.brain-map.org). Each probe for the RT–PCR was designed across both exons (Supplementary Material, Table S1). The table shows presence (þ) or absence (2) of the specific transcript of a-NRXN3 and b-NRXN3 in seven brain regions.

frequencies at each SNP fit Hardy – Weinberg equilibria using Haploview v3.2 software (data not shown). Allele frequencies in the samples studied here agree with frequencies from other samples. The rs8019381 T allele frequency of the control samples reported here, 0.074 (376 chromosomes), is similar to the 0.071 frequency reported from 168 European chromosomes in dbSNP build 127 (http://www.ncbi.nlm.nih.gov/ SNP/snp_ref.cgi ?rs ¼ 8019381). Minor allele frequencies at SNPs near SS#5, termed SNPs 4, 5, 6 and 7, are each higher in alcohol-dependent than in control samples (nominal P ¼ 0.071, 0.051, 0.0073 and 0.0007 for rs7155520, rs2215840, rs760288 and rs8019381, respectively). On the basis of these observed allele frequencies, the current sample size provides power of 0.556, 0.628, 0.883 and 0.975 to detect nominally significant results at SNPs 4– 7. Correction for multiple testing for nine SNPs in linkage disequilibrium (LD) was applied as described by Nyholt (42), using 8.6854 as the effective number of independent marker loci. Association of rs8019381 with alcohol

dependence remains significant after applying this correction for multiple testing (corrected P ¼ 0.0062). Displaying the rs8019381 ‘T’ allele is associated with a 2.46 odds ratio of belonging to the alcohol-dependent group in this sample (95% CI: 1.49– 4.07). To seek possible additional associations, we studied alleles of the novel dinucleotide AC repeat marker ss68362653 located 1.6 kb 50 to exon 23. Differences between ‘short’ (24 repeats) versus ‘long’ (.24 repeats) alleles provide nominally significant differences between alcohol-dependent versus control groups (two-tailed Fisher’s exact test: P ¼ 0.045, odds ratio ¼ 1.104, 95% CI: 1.005 – 1.213) (Supplementary Material, Fig. S1). However, these nominally significant differences do not retain significance after correction for multiple comparisons. The most robustly associated marker, SNP7 (rs8019381), is located 23 bp 30 from the 30 end of exon 23. This SNP thus lies near a donor site that could change the splicing efficiency of NRXN3 primary transcripts (43,44). SNPs 6 –8 (rs760288,

Haplotypes

Alcoholism Controls Global (2n ¼ 288) (2n ¼ 376) P-valuesa

Individual P-valuesb

SNP 1-2

0.764 0.153 0.083 0.389 0.313 0.128 0.146

0.949 (1.000) 0.353 (0.990) 0.238 (0.934) 0.241 (0.936) 0.164 (0.847) 0.611 (0.999) 0.000598 (0.00580)

0.186 0.280 0.050 0.556 0.628 0.883 0.975 0.282 0.185

CT GT CC SNP 6-7-8 TCC TCT CCT CTT

0.761 0.128 0.112 0.434 0.364 0.120 0.064

0.356 (x2 ¼ 2.07, df ¼ 2) 0.00447 (x2 ¼ 13.2, df ¼ 3)

a

Global P-values were calculated by two-tailed Fisher’s exact test. Individual P-values were calculated by x2 test with 1 df (and corrected P-values with permutation test based on 100 000 replications).

b

SNP position was based on NCBI database, Build 36 assembly, SNP database 126 (http://www.ncbi.nlm.nih.gov/SNP/snpblastByChr.html). This column shows nominal P-values and corrected P-values for multiple testing (in parentheses). c Boldfaced SNPs display nominally significant differences between alcohol-dependent and control individuals.

b

a

0.679 0.285 0.978 0.191 0.0499 0.0139 0.00106 0.151 0.667 0.366 (1.000) 0.319 (1.000) 0.996 (1.000) 0.0713 (0.619) 0.0516 (0.448) 0.00728 (0.0632) 0.000709 (0.00616) 0.263 (1.000) 0.397 (1.000) 0.128 0.108 0.489 0.473 0.286 0.196 0.074 0.451 0.210 0.153 0.080 0.489 0.545 0.359 0.288 0.160 0.404 0.240 0 31 376 2943 58 339 46 347 36 862 13 653 6499 3050 SS#4 SS#4 SS#4 n/a n/a SS#5 SS#5 SS#5 30 -UTR rs17836262 rs12147956 rs11159412 rs7155520 rs2215840 rs760288 rs8019381 rs2293847 rs12879016 SNP1 (C . G) SNP2 (T . C) SNP3 (G . A) SNP4 (G . T) SNP5 (T . C) SNP6 (T > C)c SNP7 (C > T)c SNP8 (T . C) SNP9 (T . G)

79,200,816 79,232,192 79,235,135 79,293,474 79,339,821 79,376,683 79,390,336 79,396,835 79,399,885

P-value: Fisher’s exact test

Genotypic Control (2n ¼ 376)

Minor allele frequency

Alcohol dependence (2n ¼ 288)

Distance from neighboring SNP (bp) Nearby splicing site Chr 14 positiona dbSNP ID SNP ID

Table 2. Allele frequencies for NRXN3 SNPs

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Table 3. Estimated haplotype distributions of the SNP1-2, the SNP 6-7-8 combinations in alcoholism and controls

Allelicb

Sample power for allele difference


rs8019381 and rs2293847) provide a block of restricted haplotype diversity that encompasses SS#5 (as evaluated with Haploview v3.2 in Fig. 1B). This block can be distinguished from the block nearer SS#4, which is identified by SNPs 1 – 2 (rs17836262 and rs12147956) (Fig. 1B). Common haplotypes of the SNP 6-7-8 block are strongly associated with alcohol dependence (Table 2, P ¼ 0.00447). Association of the CTT haplotype of SNPs 6-7-8 displays P ¼ 0.000598, which is corrected to P ¼ 0.00580 based on permutation testing with 100 000 replications (Table 3). In contrast, there is no association between common haplotypes for the SS#4 SNPs 1-2 and alcohol dependence (Table 3).

Association between NRXN3 SS#5 genotypes, overall expression of a-NRXN3 and b-NRXN3 and expression of specific NRXN3 splice variants To seek biochemical phenotypes that might provide behaviorally relevant differences associated with SS#5 NRNX3 variants, we first test whether the pre-frontal cortical mRNA levels of differential transcription of a-NRXN3 or b-NRXN3 were associated with SNP7 (rs8019381) genotypes. We tested 47 mRNAs from rs8019381 CC homozygotes, 11 from CT heterozygotes and one from a TT homozygote. Although there are several trends, there is no overall significance to relationships between levels of a-NRXN3 or b-NRXN3 expression and SNP7 (rs8019381) genotypes (data not shown). We next examine possible relationships between the haplotype identified by SNP 7 rs8019381 genotypes and levels of alternatively spliced NRXN3 mRNAs in pre-frontal cortex. Individuals with one or two copies of the minor rs8019381 T allele express each of the splice variants identified in CC homozygous individuals. When we focus on the expression of the transmembrane and soluble isoforms, however, we find that the levels of the transmembrane isoforms are decreased in individuals with either one or two T alleles (Fig. 4). The major transmembrane isoform ex22a24b and the minor transmembrane isoform ex22a24a mRNA levels are each significantly lower in CT and TT subjects than in CC homozygotes (P ¼ 0.0008 and 0.021 for genotypes by two-tailed Mann –Whitney test, respectively). The mRNAs for both ex22a24a and 22a24b variants are expressed at

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Figure 4. Levels of expression of mRNAs encoding soluble NRXN3 isoforms (ex22a24a, ex22a24b and ex22a24c variants) in pre-frontal cortical samples from normal control subjects with CC, CT and TT genotypes for the rs8019381 SNP (n ¼ 47, 11 and 1, respectively). Relative levels of expression of each splice variant were obtained after normalization to levels of GAPDH. Error bars ¼ standard errors of the mean. P , 0.05; P , 0.001, calculated using two-tailed Mann–Whitney tests. Differences in expression levels between CC versus CT/TT genotypes reach statistical significance for both ex22a24a and ex22a24b variants.

lower levels in the TT homozygous individual than in the CT heterozygotes, suggesting that there might even be a gene dose/effect relationship. There are no significant correlations between mRNA levels for either ex22a24a or ex22a24b variants and postmortem interval (Spearman r ¼ 0.026 and 0.088, P ¼ 0.459 and 0.361, respectively). In contrast, expression of the major ex22a23a soluble isoform does not correlate with rs8019381 genotype (P ¼ 0.171 by two-tailed Mann –Whitney test). The ratio between this soluble isoform and the expression of the major transmembrane isoforms, ex22a24a and ex22a24b, is significantly altered in individuals with CT/TT genotypes (P ¼ 0.042, two-tailed Mann – Whitney test), although the ratios between expression of transcripts encoding all soluble versus all transmembrane isoforms for individuals with CC and CT/TT genotypes do not provide significant differences (2.9- versus 3.1-fold).

DISCUSSION NRXN3 is an interesting gene in relation to addiction vulnerability for a number of reasons. Its expression in both development and in adult brain, its likely contributions to proper development and maintenance of excitatory and inhibitory synapses and its expression in brain circuits important for reward and memory all provide highly interesting contexts for potential NRXN3 roles in altering vulnerability to addictions. Studies of NRXN3 gene’s structure and variants provide numerous sites at which variation could influence NRXN3 function, brain structure, brain function and behavior. Association or linkage data from four independent addiction samples (10,13,14,45) point strongly toward roles for NRXN3 and its variants in addiction biology and nosology even before considering the data from the current work. The patterns of diversity and conservation of NRXN1, 2 and 3 structures and variants among different species are consist-

ent with important roles for NRXN3’s gene products and for its variants. Each of the longer a-neurexins primary transcripts is transcribed from an a-specific promoter and contains splicing sites SS#1 –5. Each of the shorter b-neurexin primary transcripts is transcribed from a b-specific promoter and contains splicing sites SS#4– 5 (26,27). Inserting exon 23 at SS#5 creates unique soluble isoforms for NRNX3. These soluble isoforms can be identified for NRXN3 homologs in species as distant as zebrafish (46). Splicing variants within transmembrane isoforms also display the potential to alter NRXN3 functions. The NRXN3 exon 22a24a variant encodes a fibronectin type III (FNIII)-like domain that is conserved in other adhesion molecules and extracellular matrix proteins such as contactin-associated protein 1, bone morphogenetic protein 1 and lactadherin (http://www.ebi.ac.uk/InterProScan/). Exons 24a and 24b encode different-length FNIII domains, whereas exon 24c lacks FNIII domain sequences altogether. Different NRXN3 transmembrane isoforms with shorter or absent FNIII domains might influence pre-synaptic neuronal recognition by post-synaptic neurons mediated by neuroligins (47). Although the NRXN3 FNIII domain does not contain the Arg-Gly-Asp motif that has been identified as important for binding to integrins (48,49), interactions that are independent of this domain (50) have been identified and might also be modified by the sequence variants identified in the present work. The wealth of variants identified in this gene, especially the variety of splice variants, supports general models in which alternative splicing of neuronal adhesion molecules provides molecular coding that helps to support the large diversity and the precisely regulated specificity of synaptic connections that are observed in the brain. The patterns of brain expression of NRXN3 isoforms help to define which of the gene’s variants are likely to be of regionspecific importance and also to identify variants in which inter-individual differences might provide important functional differences in brain. The ratios between a-NRXN3 and b-NRXN3 expression vary among brain regions. Higher


a-NRXN3 mRNA levels in human pre-frontal cortex and higher b-NRXN3 mRNA levels in human cerebellum are consistent with previously reported northern analyses of mRNA from rat brain regions (17). Both a- and b-NRXN3 gene products contain exon 23-expressing ‘soluble’ and exon 23-omitting ‘transmembrane isoforms’. Interestingly, except in cerebellum, the abundance of mRNA encoding the major soluble NRXN3 ex22a23a isoform is at least as great as the summed quantities of the mRNAs encoding all of the transmembrane isoforms. In contrast, neither the ex22a23b, ex22a23c nor ex22a23d soluble isoforms were detected at substantial levels in brain regions. Conceivably, these variants might display short half-lives through processes such as nonsense-mediated mRNA decay (51). The association data that we have previously obtained, the additional results that we report here from an independent sample and recent reports from other laboratories can be superimposed on this pattern of NRXN3 gene structure and variation. Data from 10 000 SNP genome-wide association nominated and provided initial replication of rs760288 SNP in the NRXN3 gene as a marker for allelic variation that contributes to human vulnerabilities to dependence on illegal addictive substances. Our current data extend this observation by identifying associations of rs760288 and the nearby SNP rs8019381 with alcohol dependence. As we were preparing this work for publication, reports of association to a nicotinedependence phenotype and linkage to opioid dependence provide further support for this locus (13,14). The NRXN3 gene locus has thus now been identified in five independent samples. None of our association data or data from reported nicotine-dependence association with rs2221299 in the NRXN3 gene (45) supports a major gene effect at this locus, however. It is thus conceivable that relatively large chromosome 14q linkage findings in opiate-dependent individuals may receive contributions from variants in the NRXN3 gene as well as other nearby loci, as has been reported in other complex disorders (52). The current data focus our attention on a specific haplotype at SS#5 in the NRXN3 gene marked by several nearby SNPs. The highest level of nominal significance is found at rs8019381 (P ¼ 0.0007), which lies on the same haplotype block and less than 14 kb from rs760288. rs760288, rs8019381 and rs2293847 SNPs encompass SS#5 of the NRXN3 gene, display moderately strong LD with D0 ¼ 0.82– 0.91 and provide a ‘CTT’ rs760288–rs8019381–rs2293847 haplotype, whose P ¼ 0.0006 association with alcohol dependence is modestly stronger than the P ¼ 0.0007 association of rs8019381 itself. However, the vast majority of the alcohol dependence versus control difference appears to be captured by the rs8019381 SNP. The genetic association findings noted earlier are buttressed by the fit between the alleles for the dependence-associated SNP and levels of expression of SS#5 mRNA variants noted in postmortem brain samples. Although the precise roles that different levels of soluble versus transmembrane NRXN3 isoforms might play are not clear, differential splicing is a mechanism that provides diversity to a number of neurexin-related genes and to their functions. Alternative splicing of presynaptic b-neurexins at SS#4 dramatically alters their

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affinities for neuroligins (21,53,54). Alternative splicing of post-synaptic neuroligins at site B dramatically alters their affinities for a-neurexins (18). The molecular mechanisms through which 30 NRXN3 haplotypes are reflected in reduced mRNA levels for several isoforms will require additional study. However, similar phenomena have been observed in other disease-related genes, including observations that SNPs at the branch point sequence at acceptor site of exon 4 of HLA-DQB1 influence the relative expression levels of transmembrane and soluble isoforms in ways that appear to provide implications for autoimmune disorders (55). A donor site SNP in the neuronal sodium-channel gene (SCN1A) also influences the relative expression levels of splice variants (56). The current data indicate that the NRXN3 exon 23 SNP rs8019381 is associated with significant alterations in levels of the specific transmembrane isoforms ex22a24a and ex22a24b, although total levels of expression of a- or b-neurexin 3 are not significantly associated with haplotypes defined by this SNP. Future work will be required to identify mechanisms for this possible discrepancy, including the possibility of nonsense-mediated mRNA decay and/or the potential presence of additional a- and b-neurexin 3 isoforms among the total 50 NRXN3 transcripts that contain hundreds of more 30 splicing events. Standard models for development and alteration of excitatory and inhibitory synapses posit that neurexins provide pre-synaptic cell adhesion molecules that bind to postsynaptic cell adhesion molecules to form trans-synaptic complexes that help to stabilize excitatory or inhibitory synapses (19). These models note that synaptogenesis is a dynamic process that is under multifaceted regulation during development and in adulthood, with neuronal adhesion molecules providing temporal and spatial codes for synaptic connectivity (18). Repertoires of diffusible entities enrich this picture. Neurexophilins provide soluble neurexin ligands that are expressed in neurons in a number of brain regions that also express NRXN3. Diffusible NRXN3 isoforms appear to be expressed in brain regions that express several neuroligins and dystroglycan (57). Conceivably, some of the diffusible neurexins and/or neurexophilins could diffuse only as far as extracellular matrix, where they could be immobilized through binding to matrix molecules. However, soluble neurexins and neurexophilins might also diffuse to sites at which membrane-bound neuroligins and neurexins were localized. Enhancing ratios between diffusible and membrane-bound NRXN3 isoforms in individuals with haplotypes marked by CT and TT rs8019381 genotypes might thus provide more diffused signaling in ways that could alter pruning, spreading and/or strength of synaptic contacts (58,59). We anticipate that effects of common human haplotypes that alter splicing, differentially impact soluble versus membrane-bound NRXN3 and influence vulnerability to addictions are also likely to provide pleiotropic influences on other phenotypes. Phenotypes that are both genetically mediated and co-occur with addictions at rates higher than anticipated by chance may be of especial interest (8). Recent linkage and other genetic studies have implicated neurexin

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and neuroligin family genes in vulnerability to autism (60 – 63). Conceivably, some of these non-addiction phenotypes might contribute to balancing selection that might have been responsible for the relatively high frequencies of addiction-associated NRXN3 SS#5 haplotypes that are identified in the present work.

MATERIALS AND METHODS Sequence analysis and determination of the exon/intron structures of NRXN3 rs760288, the SNP previously associated with illegal substance dependence, is located on chromosome 14q31 at 79 378 883 (Mapviewer build 36.2). Additional candidate SNPs and a novel SSLP, an AC dinucleotide repeat marker (ss68362653), at 50 flanking region of exon 23 were identified in SNP databases (http://www.ncbi.nlm.nih.gov/SNP/snpblast ByChr.html) and in mismatches between NCBI and Celera database sequences, respectively. The SSLP, lying at exon 23 of NRXN3 gene 50 prime (contig position 78308619 – 78308795, based on NCBI database, Build 34 assembly, SNP database 124), was amplified and confirmed by sequencing. Boundaries of SS#4 and SS#5 were determined using previously reported human NRXN3 exonic sequences (27,28) confirmed by EST sequence alignments using SEQUENCHER 4.6 software (Gene Codes Co., Ann Arbor, MI, USA). Human subjects: genotyping About 188 controls and 144 unrelated alcohol-dependent individuals of self-reported European –American ancestry were selected from pedigrees from the COGA, as previously described (41). DNA was isolated and quantified as described previously. Genotyping for nine SNPs was performed by primer extension and MALDI-TOF-based allele detection (Sequenom, San Diego, CA, USA) using PCR and extension primer sequences listed in Supplementary Material, Table S2. Primary PCRs were performed in 5 ml reaction volumes with 2.5 ng genomic DNA, 200 mM dNTP mix, 1.5 mM 10 PCR buffer, 2.5 mM MgCl2, 1 mM each of the oligonucleotide primers and 0.1 U/reaction Taq polymerase (Applied Biosystems, Inc., Foster City, CA, USA). Thermal cycling was carried out as follows: (i) 958C for 10 min, (ii) 45 cycles of 20 s at 958C, 30 s at 568C, 1 min at 728C and (iii) a final 3 min at 728C extension. After PCR amplification, unincorporated dNTPs were removed by 20 min 378C incubation with shrimp alkaline phosphatase, enzymes were inactivated by 5 min incubation at 858C and primer extension was performed according to manufacturer’s instructions (Sequenom). Extension primers (Supplementary Material, Table S2) were added together with 2.25 mM of the appropriate combination of deoxy dNTP, di-deoxy ddNTP, and thermosequenase (32 U/ml). Thermal cycling was carried out as follows: (i) 968C for 1 min, (ii) 50 cycles of 10 s at 968C, 15 s at 438C and 1 min at 608C and (iii) 968C for 30 s. Reactions were cooled on ice, purified, spotted in matrix on Sequenom arrays and subjected to MALDI-TOF mass spectrographic analyses with automatic allele detection and manual allele confirmation. rs760288 and rs8019381 SNPs were also

genotyped using direct sequencing of PCR products to confirm genotypes, using the same PCR primer sequences and conditions noted earlier. Sequences of PCR products were determined using BigDye Terminator v3.1 Cycle Sequencing kits (ABI), thermal cycling of: (i) 968C for 30 s, (ii) 25 cycles of 15 s at 968C, 5 s at 508C, 4 min at 608C and (iii) a final 2 min 608C extension, purification of reaction products using DTR V3 Short Plate Kits (Edge Biosystems, MD, USA), denaturation at 958C for 2 min and capillary electrophoresis on 3100 Genetic Analyzer (ABI). Polymorphisms were detected with SEQUENCHER 4.6 software (Gene Codes Co.). The SSLP (ss68362653) was genotyped by PCR amplification using 6-FAM-labeled forward primer 50 -TCC TGAAGCAGAACTCA TGAAC-30 , and the reverse primer 50 -TCTGAAGGCTTCTTGCCAAT-30 . Thermal cycling was: (i) 958C for 8 min, (ii) 35 cycles of 30 s at 958C, 30 s at 608C, 45 s at 728C and (iii) a final 10 min 728C extension. PCR products were analyzed using an ABI 3700 sequencer equipped with GeneScan software (ABI). SNP localizations in Table 2 are based on NCBI database, Build 36 assembly, SNP database 126 (http://www.ncbi.nlm.nih.gov/SNP/ snpblastByChr.html). Human postmortem brain samples Samples collected from normal control individuals dying without neurological disease at Division of Neuropathology, the Johns Hopkins Medical Institutions included dorsolateral pre-frontal cortex (n ¼ 20), hippocampus (n ¼ 5) and cerebellum (n ¼ 4). Additional pre-frontal cortex (n ¼ 39) and substantia nigra (n ¼ 8), substantia nigra (n ¼ 8), midbrain (n ¼ 4) specimens were collected from normal control individuals from the Brain Tissue Bank, University of Maryland. Characteristics of these subjects are shown in Table 1. RNA isolation and cDNA synthesis Total RNA was extracted from the human brain regions noted above using RNAzolB (Tel-Test, Inc. Friendwood, TX, USA) protocol. Additional RNA from human caudate and putamen samples was purchased from Clontech (Mountain View, CA, USA). Single-strand cDNA was synthesized from total RNA TM using SuperScript One-Step RT –PCR System (Invitrogen, Carsbad, CA). All cases used for quantitative PCR had RNAs that yielded sharp ribosomal 18S and 28S bands when subjected to gel electrophoresis (data not shown). RT –PCR and real-time PCR quantitation Alternative splicing variants were identified by two-step RT – PCR using oligonucleotides with sequences displayed in Supplementary Material, Table S1 and cycles of: (i) 958C for 8 min, (ii) seven cycles of 30 s at 948C, 2 min at 728C with descending temperature of 18C for each cycle, (iii) 45 cycles of 30 s at 948C, 2 min at 658C and (iv) a final 5 min 658C extension. Molecular masses of NRXN3 RT – PCR amplicons were analyzed using 2% agarose gels and ethidium bromide staining or 12% polyacrylamide gel and CYBR green staining.


For quantitative real-time PCR assessments of NRXN3 SS#5 mRNAs, isoform-specific primers and MGB probes were designed using Primer Express Software (ABI; Supplementary Material, Table S1) and used in TaqMan gene expression assays with the ABI PRISM 7900HT sequence detection system, as per the manufacturer’s instructions. MGB probes were targeted to junctions of 50 and 30 sequences of two spliced exons in order to detect specific isoforms, even though multiple PCR products might be produced by PCR primers. Each 10 ml reaction contained 900 nM of primers, 250 nM of probe, TaqMan Universal PCR Mastermix (ABI) and 100 – 200 ng of cDNA template. Thermal cycling used: (i) 508C for 2 min, (ii) 958C for 10 min, (iii) 40 cycles of 15 s at 958C, 1 min at 608C. PCR data were acquired from Sequence Detector Software (SDS version 2.0, ABI) and quantified using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression as an internal control. Each threshold cycle (Ct) measurement was performed in triplicates, and relative expression levels of mRNA for each variant calculated as the mean of the three replicates of ratio of the target molecule to the internal control and normalization (GAPDH) gene. Relative quantitation was calculated using expression means of particular isoform or brain region as references. Design and verification of SS#5 10 alternative splice variants for a- and b-NRXN3 TaqMan probe sets at SS# 5 were designed by ABI primer express software with MGB probe destined across the specific splicing site of each splice variant to detect isoform specific expression and avoid genomic DNA contamination. To verify the derivation of 10 alternative splice variants, we first amplified specific a-NRXN3 and b-NRXN3 isoforms using a- and b-specific primer sets: 50 -GACATACAGACA GATCC CAAATCTTC-30 for a-NRXN3 forward primer at exon 1, 50 -TTCCCCTGTTTC CCTTCGA-30 for b-NRXN3 forward primer at exon b1 and 50 -CCGAGTACAGC AA AC-30 for both isoforms reverse primer at exon 24. The amplification was restricted to 27 cycles in order to keep the amplification in a linear range. To eliminate single-strand cDNA contamination in the amplicons, we removed the singlestranded cDNA using digestion with S1 nuclease (Invitrogen) to hydrolyze single-stranded cDNA, while leaving doublestranded amplicons intact. After S1 nuclease digestion and denaturation at 908C for 10 min, a-NRXN3 and b-NRXN3-specific amplicons were purified using PCR purification columns (Qiagen, Valencia, CA, USA), used as templates for TaqMan assays. Statistical analyses SNP and haplotype associations were analyzed using twotailed Fisher’s exact tests. Deviations from Hardy –Weinberg equilibria were examined by x2 tests. Correction for multiple testing for nine SNPs in LD was applied as described by Nyholt (42), using 8.6854 as the effective number of independent marker loci. Corrected P-values were thus calculated by the formula: corrected P-values ¼ nominal

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P-values 8.6854. P-values less than 0.05 were considered significant for SNP association. LD between polymorphisms and haplotype block structures and association between haplotype and alcoholic dependence were evaluated with Haploview v3.2 (64). Global P-values represent the overall significance using two-tailed Fisher’s exact tests with the observed versus expected frequencies of all the haplotypes are considered together. Individual haplotypes are tested for association by grouping all others using the Haploview software (64). Individual P-values are corrected by permutation tests based on 100 000 replications for multiple testing with the Haploview software (64). P-values less than 0.025 are considered significant for haplotypic associations. SSLP allelic distributions are analyzed by two-tailed Mann –Whitney tests, with P , 0.05 considered significant for haplotype analyses. Subcategories of SSLP genotypes are also analyzed by two-tailed Fisher’s exact tests with P , 0.025 considered significant. Power analyses are performed using the program PS v2.1.31 (65). Statistical analyses of mRNA expression data are conducted using PRISM (GraphPad Software, CA, USA). Spearman’s rank correlation coefficient analyses are used to assess the contributions of age, sex, race and postmortem interval to the mRNA expression levels of each splice variant. Relative mRNA levels of a-NRXN3 and b-NRXN3 in pre-frontal cortex are compared with those of the a-NRXN3 as reference using two-tailed Wilcoxon-matched pair tests. Differences in the mRNA expression levels based on genotype (CC versus CT and TT) are examined using two-tailed Mann – Whitney tests. P-values less than 0.05 are considered significant for comparing levels of expression.

SUPPLEMENTARY MATERIAL Supplementary Material is available at HMG Online.

ACKNOWLEDGEMENTS The authors acknowledge the financial support from NIH IRP (NIDA), DHHS. We thank NIAAA for providing access to COGA DNAs and COGA investigators who include PI: H. Edenberg, co-PIs L. Bierut, H. Edenberg, V. Hesselbrock and B. Porjesz; University of Connecticut (V. Hesselbrock); Indiana University (H. Edenberg, J. Nurnberger Jr, P.M. Conneally and T. Foroud); University of Iowa (S. Kuperman and R. Crowe); SUNY Downstate Medical Center (B. Porjesz and H. Begleiter); Washington University in St Louis (L. Bierut, A. Goate and J. Rice); University of California at San Diego (M. Schuckit); Howard University (R. Taylor); Rutgers University (J. Tischfield) and Southwest Foundation (L. Almasy); Zhaoxia Ren as NIAAA staff collaborator; support for sample and data collection and storage from U10AA008401 (NIAAA and NIDA) and the fundamental scientific contributions to COGA of Henri Beglieter and Theodore Reich. Conflicts of Interest statement. None declared.

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