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Psychiatric Genetics:
doi: 10.1097/YPG.0b013e3283437194
Original Articles

Dual association of a TRKA polymorphism with schizophrenia

Van Schijndel, Jessica E.a; Van Zweeden, Martinea; Van Loo, Karen M.J.a; Djurovic, Srdjanb; Andreassen, Ole A.b,c,d; Hansen, Thomase; Werge, Thomase; Nyegaard, Mettef,k,h; Sørensen, Karina Medenj; Nordentoft, Meretek; Mortensen, Preben B.g; Mors, Olei; Børglum, Anders D.f,i; Del-Favero, Jurgenm,n; Norrback, Karl-Fredrikn,q,r; Adolfsson, Rolfq,r; Hert, Marc Deo; Claes, Stephanp; Cichon, Svens,t,u; Rietschel, Marcellav; Nöthen, Markus M.s,u; Kallunki, Pekkal; Pedersen, Jan T.l; Martens, Gerard J.M.a

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Author Information

aDepartment of Molecular Animal Physiology, Donders Institute for Brain, Cognition and Behaviour, Centre for Neuroscience and Nijmegen Centre for Molecular Life Sciences (NCMLS), Faculty of Science, Radboud University Nijmegen, Nijmegen, The Netherlands

bInstitute of Psychiatry, University of Oslo

cDepartments of Medical Genetics

dPsychiatry, Oslo University Hospital – Ulleval, Oslo, Norway

eResearch Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Copenhagen University Hospital, Roskilde

fDepartment of Human Genetics

gNational Centre for Register-based Research, Aarhus University, Aarhus C

hDepartment of Haematology, Aarhus University Hospital, Aalborg Hospital, Aalborg

iCentre for Psychiatric Research, Aarhus University Hospital, Risskov

jMolecular Genetics Laboratory, Department of Clinical Biochemistry and Immunology, Statens Serum Institute, Copenhagen S

kPsychiatric Centre Bispebjerg, Copenhagen University, Bispebjerg Bakke, Copenhagen NV

lH. Lundbeck A/S, DK-2500 Valby, Copenhagen, Denmark

mApplied Molecular Genomics Group, VIB Department of Molecular Genetics

nUniversity of Antwerp, Antwerp

oCampus Kortenberg

pCampus Leuven, University Psychiatric Centre, Catholic University Louvain, Belgium

qDepartment of Clinical Sciences, Psychiatry, Umeå University, Umeå

rDepartment of Psychiatry, Hospital of Sunderby, Luleå, Sweden

sInstitute of Human Genetics

tDepartment of Genomics, Life and Brain Center, University of Bonn, Bonn

uInstitute of Neurosciences and Medicine (INM-1), Research Center Juelich, Juelich

vDepartment of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Mannheim, Germany

Correspondence to Gerard J.M. Martens, PhD, Donders Institute for Brain, Cognition and Behaviour and Nijmegen Centre for Molecular Life Sciences, NCMLS RT282, Geert Grooteplein Zuid 28, 6525 GA, Nijmegen, The Netherlands Tel: +31 24 3610564; fax: +31 24 3615317; e-mail: g.martens@ncmls.ru.nl

Received April 7, 2010

Accepted November 15, 2010

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Objective: An interaction between predisposing genes and environmental stressors is thought to underlie the neurodevelopmental disorder schizophrenia. In a targeted gene screening, we previously found that the minor allele of the single nucleotide polymorphism (SNP) rs6336 in the neurotrophic tyrosine kinase receptor 1 (NTRK1/TRKA) gene is associated with schizophrenia as a risk factor.

Methods: We genotyped the TRKA SNP in a total of eight independent Caucasian schizophrenia case–control groups.

Result: Remarkably, although in five of the groups a higher frequency of the risk allele was indeed found in the patients compared with the controls, in the three other groups the SNP acted as a protective factor.

Conclusion: An intriguing possibility is that this dual character of the TRKA SNP is caused by its interaction with endophenotypic and/or epistatic factors.

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Schizophrenia is a complex disorder characterized by psychotic symptoms, negative symptoms, and cognitive impairment. Although these symptoms are usually displayed during late adolescence or early adulthood, the etiology of the disorder is thought to be neurodevelopmental (Weinberger, 1995). Family and adoption studies have shown that both genetic and environmental factors play a role in the etiology of schizophrenia. The genetic factors result in a concordance rate of 40–65% in monozygotic twins (Cardno and Gottesman, 2000). Linkage analyses have shown multiple susceptibility chromosomal regions (Lewis et al., 2003) that contain various candidate genes. Meta-analyses based on studies on a number of single nucleotide polymorphisms (SNPs) in these genes have elucidated nominally significant SNPs but with low average summary odds ratios (ORs; Allen et al., 2008). Recently, genome-wide association studies have shown yet additional candidate SNPs and genes (O'Donovan et al., 2008) and copy number variations (Rujescu et al., 2008; Stefansson et al., 2008). Among the multiple SNPs and genes genetically associated with schizophrenia a substantial number is involved in neurodevelopment, including a neurotrophin gene, namely the gene encoding the brain-derived neurotrophic factor (Jonsson et al., 2006). On the basis of mRNA and protein expression profiles, other neurotrophins and neurotrophic tyrosine kinase receptors have been linked to schizophrenia (Shoval and Weizman, 2005; Buckley et al., 2007). For example, compared with controls lower plasma levels of nerve growth factor have been detected in both first-episode psychotic and medicated chronic schizophrenia patients (Parikh et al., 2003). Furthermore, the mRNA levels of nerve growth factor and its high-affinity receptor neurotrophic tyrosine kinase 1 (better known and hereafter referred to as TRKA) have been found to be reduced in the hippocampus, striatum, and (hypo)thalamus of rats treated with subchronic levels of ketamine, which in healthy humans induces psychotic and negative symptoms and cognitive impairment (Becker et al., 2008). At the genetic level, SNPs in TRKA have been studied in genome-wide association studies on schizophrenia case–control cohorts, but no association has been found (affymetrix 500 K array set; Lencz et al., 2007). Recently, however, we performed a targeted gene screening involving nonsynonymous SNPs in most neurodevelopmental genes and found that only TRKA SNP rs6336 (NM_001007792.1: c.1702C>T) was associated with schizophrenia (OR=1.73; Van Schijndel et al., 2009). Yet, schizophrenia is a disorder with a high level of heterogeneity and thus reliable association data are difficult to obtain. Consequently, screenings of additional cohorts are necessary to establish the validity of an association. We, therefore, decided to examine whether TRKA contains SNPs other than rs6336 and to study SNP rs6336 in five additional independent Caucasian schizophrenia case–control groups.

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Materials and methods


As we genotyped SNP rs6336 previously in three independent Caucasian schizophrenia case–control groups (from USA, Norway, and Denmark I; Van Schijndel et al., 2009), below, these three groups are described only briefly, whereas the five additional, independent Caucasian schizophrenia case–control groups genotyped here are defined in detail.

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USA, Norway, and Denmark I

The USA groups consisted of 488 Caucasian patients with schizophrenia (age 50.9±9.8 years; 332 male, age 50.1±9.9 years, and 156 female, age 52.7±9.4 years), diagnosed according the Diagnostic and Statistical Manual of Mental Disorders, fourth Edition (DSM-IV), and 297 unrelated Caucasian controls (age 72.1±14.1 years; 113 male, age 73.5±13.4 years, and 184 female, age 71.2±14.5 years). The Norwegian groups involved 133 patients with schizophrenia (age 37.8±10.8 years; 74 male, age 36.9±9.9 years, and 59 female, age 38.8±11.6 years), selected according to DSM-IV, and 195 unrelated Caucasian controls (age 37.0±10.3 years; 90 male, age 37.5±10.2 years, and 105 female, age 36.7±10.5 years). The Danish I groups consisted of 451 Caucasian patients with schizophrenia (age 44.9±12.2 years, age of onset 27.3±8.9 years; 264 male, age 43.8±11.9 years, and 187 female, age 46.3±12.5 years), clinically diagnosed with schizophrenia or schizoaffective disorder according to the International Classification of Disease version 10 (ICD-10) and 96% of the patients also to the DSM-IV standards, and 1032 unrelated Caucasian controls (age 44.5±12.2 years; 607 male, age 43.7±11.7 years, and 425 female, age 45.7±12.7 years). For detailed sample description of case–control groups of the USA, Norway, and Denmark I, see Van Schijndel et al. (2009).

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Denmark II

The second Danish sample (Denmark II) consisted of 247 incident schizophrenia cases (age 26.4±7.0 years; 133 male and 114 female; age at onset 24.4±6.1 years) and 286 control individuals (age 32.9±16.7 years; 76 male and 210 female). The cases were diagnosed according to ICD-10 Diagnostic Criteria for Research and DSM-IV using Schedules for Clinical Assessment in Neuropsychiatry interviews and a best estimate procedure. The cases and controls were of Danish parentage for three generations. The study was approved by the Danish Data Protection Agency and the ethics committees in Denmark.

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Denmark III

The third Danish sample (Denmark III) consisted of 363 cases with schizophrenia and 430 control individuals. The 363 cases (age 20.0±1.7 years; 209 male and 154 female; age at onset 20.0±1.7 years) were obtained from the Danish Newborn Screening Biobank (Norgaard-Pedersen and Hougaard, 2007). The cases, all born in Denmark, were clinically diagnosed with schizophrenia according to ICD-10. The cases were matched on sex and date of birth to at least one control individual from the Biobank. In total, 430 controls (age 20.0±1.7 years; 232 male and 198 female) with no record of mental illness were included. The study was approved by the Danish Data Protection Agency and the ethics committees in Denmark.

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The patient sample was composed of 486 unrelated Caucasian individuals (age 53.1±15.1 years; 180 female, 306 male; age at onset 24.8±7.3), fulfilling the DSM-IV criteria of schizophrenia (American Psychiatric Association, 1994). The patients were initially identified through the inpatient hospital registers in the north part of Sweden and had at least on one occasion received a discharge diagnosis of schizophrenia. The ascertainment of the patients was performed during 1992–2005 (for details, refer Ekholm et al., 2005). The control sample of 512 Caucasians (age 58.0±13.0 years; 273 female, 238 male) were randomly selected from the same geographic area as the patients (Nilsson et al., 1997). A diagnosis of schizophrenia or other psychotic disorder was excluded on the basis of a health examination performed by a research nurse, a self-report questionnaire, and studies of psychiatric case records. All participants participated after giving written informed consent. The study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Review Board of the universities of Umeå and Antwerp.

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The Belgium sample consisted of 518 Caucasian patients with schizophrenia (age 38.7±12.1 years; 343 male, age 36.3±11.2 years and 175 female, age 43.4±12.5 years) and 246 randomly selected Caucasian controls (age 37.8±13.1 years; 153 male, age 41.9±14.6 years and 93 female, age 31.0±5.6 years) from the same geographic region (Leuven, Belgium). Patients were selected according to the DSM-IV criteria [disorganized type schizophrenia (295.1): 10 patients; paranoid type (295.3): 216 patients; schizophreniform disorder (295.4): 58 patients; residual type (295.6): two patients; schizoaffective disorder (295.7): 106 patients; undifferentiated type (295.9): 126 patients]. All patients and controls had given informed consent.

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The German schizophrenia sample was recruited from consecutive admissions to the inpatient unit of the Department of Psychiatry and Psychotherapy of the University of Bonn and of the Central Institute of Mental Health in Mannheim. The sample composed of 866 patients with a DSM-IV lifetime diagnosis of schizophrenia, made by a consensus best-estimate procedure (Leckman et al., 1982) based on all available information, including a structured interview (Spitzer et al., 1992), medical records, and the family history method. We also used the operational criteria checklist for psychotic and affective illness (Farmer et al., 1992) system to obtain detailed polydiagnostic documentation of symptoms. Three hundred and sixty (41.57%) of the patients were female, 506 (58.43%) were male. The mean age was 36.9±11.9 years. All individuals and their parents were of German descent. The German control sample consisted of 1000 population-based individuals, 52.2% were female, 47.8% were male. The mean age was 48.8±15.6 years. All individuals were German. For all patient and control individuals, written informed consent was obtained before study participation. Protocols and procedures were approved by the Ethics Committees of the Faculties of Medicine at the Universities of Bonn and Mannheim/Heidelberg.

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High-resolution melting

The exons of TRKA were analyzed by high-resolution melting (HRM) in 71 samples from Caucasian patients with schizophrenia. Primers surrounding the 16 exons were developed (sequences available on request). Despite various attempts involving a number of primer sets, we did not succeed in amplifying exon 1. PCR amplifications were performed in a total volume of 10 μl on a Rotor-Gene 6000 real-time rotary analyzer (Corbett Research, Sydney, Australia). The reaction mixture contained 10 ng of human genomic DNA, 1× TITANIUM Taq PCR Buffer (Clontech, Takara Bio Europe, Saint-Germain-en-Laye, France), 0.25 mmol/l of dNTP, 375 nmol/l of forward and reverse primers, 1.5 μmol/l of SYTO 9 green fluorescent nucleic acid stain (Invitrogen Ltd, Paisley, UK), and 0.25×TITANIUM Taq polymerase (Clontech). To amplify the amplicon, the cycling conditions were as follows: one cycle of 95°C for 3 min; 45 cycles of 95°C for 10 s, 60°C for 15 s, and 72°C for 20 s. Before the HRM, one cycle of 90°C for 1 min and 40°C for 1 min was applied to form random DNA duplexes. The HRM protocol was a waiting step of 90s at 65°C followed by a gradient rise in temperature from 65 to 95°C, 0.1°C and 1 s per step. HRM was analyzed with the Rotor-Gene 6000 Series Software using the HRM (normalized and difference graphs) and melt analysis tools.

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Single nucleotide polymorphism selection

We previously genotyped over 200 nonsynonymous SNPs of which frequency data were available (Van Schijndel et al., 2009); we excluded SNPs that were in linkage disequilibrium (LD; r2>0.80) according to the National Center for Biotechnology Information database (build 126). In this study, we searched the National Center for Biotechnology Information database (build 129) for SNPs located in the TRKA gene and found 15 nonsynonymous SNPs. Nine SNPs are not validated and do not have frequency data. Two have frequency data but are not present in 60 HAPMAP samples, indicating low minor allele frequencies (MAFs). Only four [including SNPs rs6336 and rs6339 (NM_001007792.1:c.1730G>T)] have MAFs above zero in the HAPMAP or another European sample. In a search for unknown polymorphisms, we scanned the exons of TRKA with HRM in 71 schizophrenia genomic DNA samples, but did not detect new nonsynonymous SNPs. In exon 15, we detected the variations corresponding to SNPs rs6336 and rs6339. DNA sequencing and PCR experiments together with information derived from the Genome Variation Server of the SeattleSNPs Program for Genomic Applications showed that these two SNPs are in complete LD (r2 between 0.82 and 1.00).

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The samples of the cohorts of the USA, Denmark I, Norway, Denmark II, Denmark III, and Germany were genotyped for rs6336 using iPLEX chemistry on a matrix-assisted laser desorption/ionization-time of flight mass spectrometer by Sequenom Inc. (San Diego, California, USA, http://www.sequenom.com). SNP-containing genomic regions were amplified in a multiplex PCR followed by deactivation of the remaining nucleotides by shrimp alkaline phosphatase treatment. A single-base primer extension step was performed and the primer extension (iPLEX) products were desalted using resin and spotted on a SpectroCHIP (Sequenom) using a nanodispenser. The samples were analyzed using a Bruker matrix-assisted laser desorption/ionization-time of flight mass spectrometer and the genotypes were determined using the MassARRAY Typer 3.4 Software (Sequenom). Assay conditions and primer sequences are available on request. Confirmation of those genotypes and genotyping of the Belgium cohort was done by allele-specific PCR using primers specific for SNP rs6336 General primers, forward (fw): 5′-GGCAAGGGCTGAGTCTG-3′ and reverse (rv): 5′-TCCATCTGGGATAGCGAAGG-3′. Specific rv primers: for the T allele: 5′-CTTGGCATCAGGTCCATA-3′ and for the C allele: 5′-CTTGGCATCAGGTCCATG-3′ or HRM using fw primer 5′-GGAGTTCTATCCTCCCAGCCT-3′ and rv primer 5′-CCTGGAGCCACATCCTCCC-3′. Genotyping of the Swedish cohort was performed by pyrosequencing on a PSQ HS96 pyrosequencer (http://www.biotage.com/). Biotinylated PCR products were immobilized onto streptavidin-coated sepharose beads (Amersham Biosciences, GE Healthcare, Uppsala, Sweden). Biotinylated single-stranded DNA was obtained by incubating the immobilized PCR products in 0.5 mol/l of NaOH, followed by two sequential washes in 10 mmol/l Tris–acetate, pH 7.6. Primer annealing was carried out by incubation at 80°C for 2 min and then at room temperature for 5 min. Pyrosequencing was carried out on the PSQ96 pyrosequencer (Biotage, Uppsala, Sweden). Standard PCR was carried out with fw primer 5′-ATCCTCCCAGCCTATCCCCTCT-3′ and 5′ biotine labeled rv primer 5′-CCAGCAGCTTGGCATCAGG-3′ at an annealing temperature of 68°C. Genotyping was carried out using primer 5-CTTTTCTTGTTCACAGATCC-3′.

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Statistical analysis

Differences in allele frequencies between cases and controls were analyzed by standard contingency table analysis using two-tailed χ2 test probabilities. The genotype distribution was tested in all of the samples and no deviation was found from Hardy–Weinberg equilibrium. Heterogeneity between studies was assessed using the Cochran Q test and the Cochran–Mantel–Haenszel test was used to calculate the overall association across all samples (EasyMA2001; Cucherat et al., 1997). Power calculations were estimated using Quanto v1.2 (Gauderman, 2002) and showed that power was sufficient to detect a risk effect in the 2475 new cases (99.9%, assuming an OR of 1.73, a disease allele frequency of 5% and a disease prevalence of 1%).

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We first performed HRM to scan TRKA for the presence of any SNP other than rs6336. This analysis showed only one additional nonsynonymous SNP (rs6339), but this polymorphism is in LD with rs6336 (0.82 < r2<1.00; see Materials and methods for details). We therefore decided to examine TRKA SNP rs6336 in detail. We genotyped additional samples of the three independent Caucasian schizophrenia case–control groups (USA: additional eight cases; Denmark I: 647 controls and 73 cases; Norway: 17 controls and 11 cases), which were not used in our earlier screening (Van Schijndel et al., 2009). We found that the MAF was higher in patients with schizophrenia when compared with controls [USA: OR=2.42, 95% confidence interval (CI)=(1.41–4.17), P=0.001; Denmark I: OR=1.23, CI=(0.99–1.69), P=0.21; Norway: OR=2.14, CI=(0.80–5.69), P=0.12]. Furthermore, we now genotyped SNP rs6336 in five additional case–control groups from Denmark (two groups: Denmark II and Denmark III), Sweden, Belgium, and Germany. In these additional screenings, only in the Belgium and Denmark II groups, SNP rs6336 also showed a higher frequency of the risk allele in the patients with schizophrenia compared with the healthy controls, although not significantly different [Belgium: OR=1.30, CI=(0.79–2.12), P=0.30; Denmark II: OR=1.17, 95% CI=(0.69–1.98), P=0.57]. Surprisingly, in the three other groups the SNP displayed a lower frequency of the risk allele in the patients than in the controls [Sweden: OR=0.68, 95% CI=(0.48–0.98), P=0.04; Denmark III: OR=0.71, 95% CI=(0.45–1.14), P=0.15; Germany: OR=0.74, 95% CI=(0.55–0.99), P=0.05; Table 1]. The Cochran–Mantel–Haenszel test showed that SNP rs6336 was not associated with schizophrenia when analyzing across all eight samples [OR=1.00; 95% CI=(0.87–1.16); P=0.98]. However, to exclude the hypothesis-generating data from the original three-sample screenings, we carried out an analysis of the five new case–control groups. The Cochran–Mantel–Haenszel meta-analysis of the five new samples showed that SNP rs6336 was significantly associated with schizophrenia as a protective factor [OR=0.820; 95% CI=(0.687–0.978); P=0.032]. This result is opposite to the hypothesis-generating data.

Table 1
Table 1
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In our earlier targeted gene screening approach in three independent Caucasian schizophrenia case–control groups, TRKA SNP rs6336 was significantly associated with schizophrenia (Van Schijndel et al., 2009). TRKA might be functionally linked to schizophrenia as antipsychotics decrease TRKA phosphorylation in rat hippocampus and phosphorylation is essential for its receptor activity (Terry et al., 2010). SNP rs6336 results in a His>Tyr substitution located in the kinase-insert region of the tyrosine kinase domain, which is highly conserved in various receptor tyrosine kinases. The His>Tyr substitution has no effect on the autophosphorylation of TRKA (Mardy et al., 2001). However, the combined effect of His>Tyr and Gly>Val (rs6339) on phosphorylation has not been tested. The exact role of rs6336 in TRKA autophosphorylation thus remains unclear. We previously found that rs6336 is associated with schizophrenia as a risk factor (Van Schijndel et al., 2009). However, this study involving the screening of this SNP in five additional Caucasian schizophrenia case–control groups showed that, although not significant in all groups, the SNP was a risk factor in two of the extra groups, whereas in the three other groups it was found as a protective factor. Another remarkable observation in our studies was that the MAFs for SNP rs6336 greatly varied among the groups, in particular among the control cohorts (MAFs ranging from 1.8 to 7.6%). Such a variation in MAFs is not a feature unique for TRKA SNP rs6336, as in schizophrenia association studies reported by others, similar observations have been made as well. For example, in a screening of Caucasian schizophrenia case–control groups the MAFs of the functional dopamine receptor D2) Ser311Cys SNP also greatly varies among the control groups, namely between 0.5 and 4.0% (Glatt and Jonsson, 2006). Furthermore, in the Caucasian control groups of other schizophrenia association studies the MAFs of v-akt murine thymoma viral oncogene homolog 1 SNP rs2498784 varied between 8.3 and 16.5% (Schwab et al., 2005; Norton et al., 2007) and the frequencies of the functional catechol-O-methyltransferase (COMT) Val158Met polymorphism ranged from 40.2 to 54.2% (Munafo et al., 2005). Remarkably, in the various reports, the fact that for a particular SNP the control cohorts displayed significantly different allele frequencies was not discussed. The variation in MAF might be caused by stratification in the control groups. Unfortunately, this hypothesis cannot be tested as the control groups have not been extensively characterized.

In this study, we found that TRKA SNP rs6336 displayed a dual character in that in the initially investigated (hypothesis generating) case–control groups it was associated as a risk factor (highly significant in the USA group and a tendency for association in the other two groups), whereas in the replication groups the SNP was found not only as a risk factor but also as a protective factor as well. Intriguingly, a number of other SNPs have also been significantly associated with schizophrenia as a risk factor in some cases and in other studies as a protective factor. For example, in cohorts with the same ethnic background D-amino-acid oxidase SNP rs3918346 was significantly associated with ORs ranging from 0.70 to 1.64 and the ORs of dopamine receptor D2 deletion rs1799732 varied from 0.49 to 1.43. Furthermore, the frequently studied COMT Val158Met SNP has been found to be associated with schizophrenia not only as a risk factor (OR up to 1.44) but also as a protective factor (OR down to 0.63; Shi et al., 2008). Such flips in the direction of a single-locus association may be attributed to the presence of another disease-influencing genetic variation (located either on a syntenic or a nonsyntenic locus) that is correlated with the target susceptibility locus and differs in LD among various cohorts (correlation coefficient; Lin et al., 2007). In a further attempt to try to understand the dual character of a SNP, the contribution of schizophrenia endophenotypes has been considered. For instance, the COMT polymorphism is associated with lifetime symptomatology and sensorimotor gating (Goghari and Sponheim, 2008; Quednow et al., 2008). Yet, a meta-analysis including the endophenotypes should be carried out to confirm the initial data. Furthermore, the issue whether schizophrenia should be considered as a single neurodevelopmental disorder or represents a collection of endophenotypes is currently being discussed in connection with the preparation of the the Diagnostic and Statistical Manual of Mental Disordersfifth edition (DSM-V; Gaebel and Zielasek, 2008). Thus, in the future a better classification of the patients may well lead to the identification of TRKA SNP rs6336 as a risk or protective factor for a certain endophenotype.

In addition to gene–environment interactions, gene–gene interactions may influence the final outcome of a phenotype and may thus affect the eventual result of an association study. As susceptibility genes can often be grouped into a family with roles in the same pathways or processes (Carter, 2006), SNPs within members of such a gene family may interact (pairwise interacting SNPs). For schizophrenia, examples may include interactions between SNPs in the ERBB and neuregulin gene families (Benzel et al., 2007) or between an intronic tryptophan hydroxylase SNP and the short allele of the serotonin transporter gene (Chotai et al., 2005). Thus, SNPs in components of the TRKA pathway may interact with TRKA SNP rs6336 and as such contribute to the observed dual character of rs6336. Another explanation for the dual character may depend on the parental origin of the genetic variation. Recently, parental-origin-specific SNP associations with breast cancer, basal-cell carcinoma, and type 2 diabetes have been reported (Kong et al., 2009). Thus, TRKA SNP rs6336 may be a risk allele when inherited from the father and a protective allele when inherited from the mother or vice versa.

In conclusion, we find TRKA SNP rs6336 either as a risk allele or a protective factor for schizophrenia. However, further research on large, well-characterized cohorts is necessary to explore whether this TRKA SNP is linked to a certain endophenotype and/or interacts with another SNP(s) in the TRKA signaling pathway to explain its apparently dual association with schizophrenia.

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The authors thank the patients who participated and made this study possible. They also acknowledge expert assistance by numerous mental health professionals in the various clinical departments.

This study was supported by the Dutch Top Institute Pharma (Grant T5-209), the Danish Medical Research Council, the Novo Nordisk Foundation, the Villum Kann Rasmussen Foundation, the Hjerrild Foundation, and the Faculty of Health Sciences, Aarhus University. The Denmark I sample was supported by the Danish Research Council (Grant 271-06-0608, to T.W.). The research conducted within the Swedish samples was funded by the Swedish Research Council (Grants 2003-5158 and 2006-4472), The Medical Faculty, Umeå University and the County Councils of Västerbotten and Norrbotten, Sweden. Stephan Claes is a Senior Clinical Researcher of the Fund for Scientific Research Flanders (FWO Vlaanderen). TOP study group received support from the University of Oslo, the Research Council of Norway (♯167153/V50, ♯163070/V50), and the South-East Norway Health Authority (♯2004-123).

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case–control study; meta-analysis; neurotrophic tyrosine kinase receptor 1; protective factor; risk factor

© 2011 Lippincott Williams & Wilkins, Inc.


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