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Human Molecular Genetics Advance Access originally published online on December 21, 2006
Human Molecular Genetics 2007 16(5):453-462; doi:10.1093/hmg/ddl462
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© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Families with the risk allele of DISC1 reveal a link between schizophrenia and another component of the same molecular pathway, NDE1

William Hennah1, Liisa Tomppo1, Tero Hiekkalinna1, Outi M. Palo1, Helena Kilpinen1, Jesper Ekelund1,2, Annamari Tuulio-Henriksson2, Kaisa Silander1, Timo Partonen2, Tiina Paunio1,3, Joseph D. Terwilliger4,5,6, Jouko Lönnqvist2,3 and Leena Peltonen1,7,8,*

1 Department of Molecular Medicine and 2 Department of Mental Health and Alcohol Research, National Public Health Institute, Helsinki, Finland, 3 Department of Psychiatry, Helsinki University Central Hospital, Helsinki, Finland, 4 Department of Genetics and Development, Department of Psychiatry, Columbia Genome Center, Columbia University, New York, NY, USA, 5 Division of Medical Genetics, New York State Psychiatric Institute, New York, NY, USA, 6 Finnish Genome Center and 7 Department of Medical Genetics, University of Helsinki, Helsinki, Finland and 8 The Broad Institute, MIT, Boston, MA, USA

* To whom correspondence should be addressed at: Department of Molecular Medicine, National Public Health Institute, Helsinki, Finland. Tel: +1 358947448393; Fax: +1 358947448480; Email: leena.peltonen{at}ktl.fi

Received November 20, 2006; Accepted December 4, 2006


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
We have previously reported a robust association between an allelic haplotype of ‘Disrupted in Schizophrenia 1’ (DISC1) and schizophrenia in a nationwide collection of Finnish schizophrenia families. This specific DISC1 allele was later identified to associate with visual working memory, selectively in males. DISC1 association to schizophrenia has since been replicated in multiple independent study samples from different populations. In this study, we conditioned our sample of Finnish families for the presence of the Finnish tentative risk allele for DISC1 and re-analyzed our genome-wide scan data of 443 markers on the basis of this stratification. Two additional loci displayed an evidence of linkage (LOD > 3) and included a locus on 16p13, proximal to the gene encoding NDE1, which has been shown to biologically interact with DISC1. Although none of the observed linkages remained significant after multiple test correction through simulation, further analysis of NDE1 revealed an association between a tag-haplotype and schizophrenia (P = 0.00046) specific to females, which proved to be significant (P = 0.011) after multiple test correction. Our finding would support the concept that initial gene findings in multifactorial diseases will assist in the identification of other components of complex genetic etiology. Notably, this and other converging lines of evidence underline the importance of DISC1-related functional pathways in the etiology of schizophrenia.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Schizophrenia is a severe mental disorder with a global morbid risk of ~1%, with a strong genetic component in etiology (1). Research on the characteristics of this genetic etiology has been ongoing for years, but only recently has converging evidence emerged for the involved genes (2). Since schizophrenia is a polygenic disorder, it has been hypothesized that identification of the first candidate genes would greatly facilitate the identification of others. One such candidate gene was assigned as ‘Disrupted in Schizophrenia 1’ (DISC1), first identified as a potential susceptibility gene for schizophrenia in a large Scottish family, demonstrating the co-segregation of a balanced (1;11) (q42.1;q14.3) translocation with schizophrenia and related psychiatric disorders (3,4). We have previously identified an allelic haplotype of DISC1, HEP3, which was originally observed to be significantly under-transmitted to affected females in Finnish families ascertained for schizophrenia (5). Later, this observed transmission mechanism was found to be an epiphenomenon of over-transmission to affected males, which was originally masked by the high frequency of HEP3 in the sample population. Further statistical analysis of HEP3 indicates that it confers increased risk to schizophrenia through a negative effect on visual working memory in males (6). Association with DISC1 has since been replicated in independent study samples for schizophrenia and related disorders (7–10) as well as with neurocognitive endophenotypes (11,12) and neuroimaging endophenotypes (10,13). These combine to suggest that DISC1 is most likely to be related to the poorer cognitive ability observed in individuals with schizophrenia and their families (14,15). Recent evidence on DISC1 is consistent with this, in showing that the truncated form of DISC1 impairs cerebral cortical development (16) and that normal DISC1 binds to PDE4B in a cAMP-dependent manner (17). The latter also shows that the PDE4B gene is disrupted in two related individuals with psychiatric disorders (17), as well as notes the biological relevance of PDE4B to the processes governing learning and memory.

Not unexpectedly, and similar to other candidate genes for schizophrenia, the observed DISC1 associations have been to different allelic variants in different populations. In the samples collected from the Finnish population, the region spanning 62 kb of intron 1 to exon 2 of DISC1 represented by the allelic haplotype HEP3 (alleles T and A of rs751229 and rs3738401, respectively) is the most consistently and robustly associated and can be referred to as the ‘risk allele’ for schizophrenia.

Here, we have analyzed the genome-wide scan data from our sample of 458 Finnish families, taking into consideration the presence of the DISC1 HEP3 allelic haplotype in each family. The families with the risk allele of DISC1 and those without were treated as two separate sample sets. We hypothesized that since locus heterogeneity certainly exists between families, this ascertainment strategy could provide some added power to identify genes involved in the molecular pathogenesis of schizophrenia.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Linkage analysis in a large family sample from Finland ascertained for schizophrenia
The study sample used here primarily consists of families that were used for the previous published Finnish genome-wide scans for schizophrenia (18–21). However, since new families have since been added to this sample collection, we first report the genome-wide linkage findings for this large data set (n = 458). When the genome-wide marker data were analyzed using linkage analysis across the eight models tested, evidence for linkage (LOD > 3) emerged for two genomic loci: D1S2709 (LOD = 3.64) located at 1q42 intragenic of the DISC1 gene and D5S647 (LOD = 3.05) on 5q12.3. The 1q42 locus is a previously observed linkage region in the Finnish sample (19,22), and here the most significant linkage was also displayed under the dominant model of LC3, as observed in the original analyses with 168 families (19). The marker D5S647 is located 71 cM from a previously observed linkage on 5q33 in the Finnish population (18), but is within the chromosome 5q11–q13 region originally implicated in Icelandic, UK and Canadian study samples in 1988 (23,24). Four other loci (1q32, 4q28, 8q24 and 11q24) displayed linkage with LOD scores > 2 in this whole data set under different models and liability classes (LCs), of which only 1q32 (D1S1723; LOD = 2.20) represents a shared locus with any previously observed linkage to schizophrenia in the Finnish study material, originally noted in a geographical sub-sample of this complete data set (21) (Table 1).


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  		Table 1. Two-point linkage results for markers under the dominant and recessive models where LOD scores > 2 were observed in any of the four LCs and any of the three samples

 
Linkage analysis after stratification for a DISC1 schizophrenia-associating haplotype
After we conditioned the study sample for the HEP3 allelic haplotype, three loci provided evidence for linkage (LOD > 3): 1q42 (D1S2709; LOD = 3.31), 10q21 (GATA101E02; LOD = 3.58) and 16p13 (D16S764; LOD = 3.17) (Table 1), all three within the sub-sample of families carrying the DISC1 risk allele (n = 145 families). It was expected that D1S2709 would display a high LOD score, since this marker showed the initial significant linkage in Finnish families and led to the discovery of the HEP3 haplotype, which was used here as the ascertainment criterion. On chromosome 16p13, two neighboring markers displayed LOD > 2 for the dominant model using the most restricted diagnostic class, LC1, with one of them showing LOD > 3. Most interestingly, this region of the genome contains a gene encoding a known DISC1-binding protein, NDE1 (25,26), located 0.8 Mb from the linked marker D16S764. Furthermore, linkage to this locus has also been observed in Finnish bipolar disorder families (27), implying some relevance for this genomic region not just to schizophrenia but also other mental disorders. The GATA101E02 marker on chromosome 10 displayed its evidence for linkage under the dominant model using the broadest diagnostic class, LC4. The linkage peak on 10q21 is located in virtually the same region previously found to display significant linkage to schizophrenia in Ashkenazi Jews (28) and suggested in other studies (29,30).

Markers displaying linkage LOD > 2 were located at 1p13, 2q32, 6p21, 7q22, 8p22, 11q22 and 12q21 in families with the HEP3 allele and at 5q12 and 8q24 in families negative for HEP3 (Table 1). Of all these twelve loci, eight are located at or around 20 cM from genomic regions previously identified in linkage studies of schizophrenia (Table 2) and include the genome regions containing the most promising candidate genes associated with schizophrenia in multiple study samples: dysbindin (6p21) [first reported by Straub et al. (31)], neuregulin (8p22) [first reported by Stefansson et al. (32)], GRM3 (33) and RELN (34) (7q22) (Table 2; Fig. 1; reviewed in 2).


Figure 1
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  		Figure 1. Schematic diagrams to highlight the primary regions of interest indicated by performing a genome-wide scan conditional on a DISC1 haplotype. Downward pointing arrows represent the locations of our linkage findings, and thick black lines above each schematic represent previous linkage findings and thick black lines below the schematic represent previous association findings. (A) The schematic shows 1 Mb; (B) all schematics show 40 Mb, and relevant candidate genes are illustrated for each chromosome.

 


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  		Table 2. Significance of the LOD scores > 2 observed in the two stratified sub-samples and additionally showing the locations of the nearest previous schizophrenia linkage findings where appropriate

 
Association analysis of the NDE1 locus
The linkage on 16p13 immediately implicated the potential involvement of the NDE1 gene, since the corresponding polypeptide has been shown to bind to the DISC1 protein (25,26). We wanted to analyze this gene for association to schizophrenia spectrum disorders. Seven single nucleotide polymorphisms (SNPs) over the 75 kb of the NDE1 gene (Fig. 2) were genotyped and analyzed in our nationwide study sample of 458 schizophrenia families using the pseudomarker program (35). Linkage disequilibrium (LD) analysis using the solid spine of LD criterion (D' > 0.8) in the Haploview program (36) demonstrated that all seven SNPs were located in the same haploblock, with analysis of four SNPs in a haplotype being able to ‘tag’ for this block (Fig. 2). This tag-haplotype was analyzed using the TRANSMIT program (37). Two individual SNPs (Table 3) and the tag-haplotype (Table 4) displayed association < 0.05 after 100 000 permutations, although neither the SNPs nor the haplotype was significant after the conservative Bonferroni correction for the eight total tests performed at this stage.


Figure 2
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  		Figure 2. Illustration of the NDE1 exonic structure to show the positions of the SNPs used in the association analysis. Those labeled with an asterisk are the component SNPs of the haplotype that was shown to tag for the region through the LD analysis. This LD region is illustrated below the SNPs for the founders of the Finnish sample population used here and for the CEPH HapMap individuals.

 


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  		Table 3. Observed P-values before multiple test correction, for the seven analyzed SNPs located within the NDE1 gene, from the pseudomarker program for the LD given linkage statistic

 


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  		Table 4. Empirical P-values from the analysis of the NDE1 tag-haplotype (tag) with end-state diagnosis and the neurocognitive variable representing visual working memory

 
Since our initial observation of association to DISC1 had displayed sex-dependent effects, we wanted to test whether such effects may also affect the association with the NDE1 gene, since it is encoding a protein with an established biological connection with DISC1. Such an effect was observed, with all individual SNPs (Table 3) and the tag-haplotype (Table 4) displaying P-values < 0.05 only for the analysis monitoring transmission to female offspring. After a conservative correction for multiple testing, the association to the tag-haplotype (permutated P-value = 0.00046; observed transmissions = 237; expected transmissions = 208) remained significant (P = 0.011) for the total 24 tests performed. Linkage analysis, to test whether this NDE1 tag-haplotype explains the observed linkage in 16p13, showed that the haplotype provides greater evidence for linkage than the nearby microsatellites in the whole sample (LOD = 1.00, compared to LOD = 0.78), but not in the HEP3 positive families (LOD = 1.26, compared to LOD = 3.17), suggesting that other nearby variants may have also partially contributed to the observed linkage signal. The risk allele of the NDE1 tag-haplotype comprises the CGCC alleles of the SNPs rs4781678, rs2242549, rs881803 and rs2075512, respectively, and is present in the founders of the schizophrenia families at a frequency of 30%, whereas in the population control sample from Finland, it has a frequency of 19%. As in our original observation of association to schizophrenia with DISC1 haplotypes (5), we performed a validating analysis that only used one affected offspring per family to completely remove any confounding effects caused by linkage in our family material. The tag-haplotype remained significant after this test only for transmission distortion to affected females (P = 0.0024), but was no longer significant in the whole sample (P = 0.072), although again this could be due to the reduction in power from the decreased sample size in the analysis (n = 1494 individuals compared with 2756 in the whole sample).

Furthermore, as DISC1 had been shown to be putatively associated to a neurocognitive measure of visual working memory in this sample, it would logically follow that a biologically interacting gene may also associate to the same endophenotype of schizophrenia. Analysis for association between the NDE1 tag-haplotype and visual working memory was performed by using the QTDT program (38), as used for the analysis of the DISC1 haplotype (6). We first analyzed for association to the end-state diagnosis to gage the effect of the reduced sample size for which neurocognitive information was available (n = 215 families out of 458 families of the complete study sample) and then followed with the association analysis in the sample with the quantitative endophenotype. We also divided the sample to address the potential sex difference and to confirm that any association is truly to the endophenotype being contributed by both affected and currently unaffected individuals from these families. In the analysis of DISC1, we hypothesized that association to the quantitative variable, if truly associated with clinical vulnerability, should be stronger than to the end-state diagnosis. Such an increase was not seen for the NDE1 tag-haplotype, yet the analysis of only female offspring approached the 0.05 level of statistical significance (Table 4).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 REFERENCES
 
Here, we have analyzed genome-wide marker data in 458 families ascertained for schizophrenia, making it one of the largest studies of its kind for psychiatric disorders and providing support for the 1q42 and 5q12 loci as being involved in the etiology of schizophrenia. We had already seen the 1q42 locus in previous genome-wide scans in sub-samples of the data set used here and identified that an allelic haplotype of DISC1, a regional candidate gene, spanning intron 1 to exon 2 is associated with schizophrenia. Following this observation, we stratified our large family sample on the basis of the presence of this DISC1 allelic haplotype, the tentative ‘risk allele’ in this study sample, with the assumption that this stratification would help us to define two genetically more homogeneous study samples, aiding the detection of further potential susceptibility loci. This seemed to be the case for the DISC1 positive families, since we could identify two loci displaying genome-wide evidence for linkage in addition to 1q42. Furthermore, seven other chromosomal regions showed some evidence for linkage, and interestingly, six of them were located in the immediate vicinity of genomic regions previously linked to schizophrenia, including 8p22–p11 and 6p22.3, the genomic loci containing the NRG1 and DTNBP1 genes. By controlling for DISC1 status in our large nationwide collection of schizophrenia families, we were thus able to detect linkage to several schizophrenia loci containing previously identified candidate genes, not detectable in the genetically more heterogeneous total sample. This finding would provide some support to the hypothesis that several of the associated candidate genes reported actually work in concert. Such an approach could guide the gene identification efforts in other study samples and hopefully facilitate the formulation of a comprehensive model of the complex genetic background of schizophrenia.

We characterized the linkage region on 16p13 further, since it contains a novel and highly interesting candidate gene, NDE1, encoding a protein which biologically interacts with the DISC1 protein (25,26). Association with schizophrenia was observed and found to be primarily contributed by affected females by over-transmission of an allelic haplotype of NDE1. This haplotype consists of four SNPs that were highlighted as being able to ‘tag’ for the entire NDE1 gene, since all SNPs genotyped were observed to be in the same haploblock in this Finnish sample population. The public access data available through the HapMap project (39) suggest that the NDE1 region in the CEPH population has more than one haplotype block spanning it, further demonstrating the increased amounts of LD that can be utilized from the analysis of isolated populations (40).

The findings would implicate that two interactive proteins, DISC1 and NDE1, could work in concert in the genetic etiology of schizophrenia and tentatively suggests the potential mediation of some of their effect via deficits in working memory (6) or other cognitive functions (11,12). The currently available functional information for both DISC1 and NDE1 lends this hypothesis further credence and has the potential to expand the concept of ‘defective’ pathways in schizophrenia. Not only do the proteins of these two genes interact (25,26), but they also interact to form a complex of proteins with LIS1 (26), with NDE1 appearing to be interchangeable with its homolog NDEL (25). It is known that an LIS1/NDEL complex functions in neuronal migration regulated by signaling from another schizophrenia candidate gene, RELN (Fig. 3) (41). Furthermore, mouse models with differing LIS1 heterozygous mutations have been shown to have cortical and hippocampal disorganization and impaired spatial learning and coordination (42,43), whereas mouse models with NDE1 homozygous mutations have been shown to have less neurons in the cerebral cortex, with thin cortical layering (44). Both cortex and hippocampus are highly implicated in schizophrenia (45,46), with DISC1 having been shown to be additionally associated to reductions in gray matter in these two regions (10,13), further supported by recent evidence that the truncated form of DISC1 impairs cerebral cortical development (16). Additional recent observations have contributed to a broadening of these lines of evidence, when it was observed that DISC1 binds to PDE4B in a cAMP-dependent manner and that two related individuals with psychiatric disorders have a chromosomal aberration directly disrupting the PDE4B gene (17). The PDE4 genes are homologs of the Drosophila dunce gene, which when mutated cause learning and memory deficits (47), with a potential mechanism of action being through the disruption of the cAMP second messenger system that is involved in the processes of learning and memory (17). Although the Finnish family material has been ascertained on schizophrenia, both the DISC1 and the NDE1 observations of association were obtained using a broad diagnostic class that includes other forms of mental illness. Furthermore, the association with DISC1 has been independently observed to display association to bipolar disorder (9) and schizoaffective disorder (7) directly. This has led to the hypothesis that the predisposing effect of DISC1 is not specific to schizophrenia, and our data here suggest that the same may be shown for NDE1. It is important to note that two genes that have been previously shown to biologically interact now display association to schizophrenia in the same Finnish family sample, implying the possibility of genetic interaction between these two genes. Yet the testing of genetic interaction has not been performed here, as a meaningful test would require a sample size much greater than the one used, with the sex-dependent effects of the observed associations for these two genes being expected to complicate such an analysis in a small sample size.


Figure 3
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  		Figure 3. Illustration of the relationship between RELN signaling and the potential functions of DISC1 and NDE1 in neuronal migration with LIS1. Dashed arrows represent intermediate stages between the process of RELN signaling and its ultimate response.

 
This convergence of multiple lines of evidence starts to implicate not just DISC1 but a ‘DISC1 pathway’ that also incorporates NDE1 and PDE4B in the etiology of schizophrenia, potentially through underlying deficits in learning and memory. The components of this and related biological pathways would offer additional candidate genes for genetic studies aiming to characterize the genetic background of schizophrenia.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
REFERENCES
 
Sample materials
The sample used here is an extension of the samples previously used to perform linkage analysis for schizophrenia in Finland (18–22). The sample identification and collection has remained the same throughout the years, where all Finnish patients with schizophrenia born between 1940 and 1976 were identified through the hospital discharge, disability pension and the free medication registers. Close family members of each proband were then identified through the national population register, enabling the construction of pedigrees. This study now totals 458 families that contain 2756 individuals, of which 2059 have been genotyped. Of these genotyped individuals, 931 are classified as affected using increasingly inclusive LCs applying criteria from the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) (48), for the consensus lifetime diagnosis based on medical records, and in the case of those individuals for whom neuropsychological information was obtained, diagnosis is also based on interview. From this whole sample, 1034 offspring are male and 878 are female.

Owing to the extensive nature of the neurocognitive traits being measured for the quantitative analysis, it was only logistically feasible to test approximately half of the families from the entire sample. This sub-sample consists of 215 families containing 1437 individuals of which 400 are classified as affected and where 746 have undergone extensive neuropsychological assessment, including 356 offspring currently unaffected under LC4. Of those assessed in this sample, 390 are male and 356 are female.

In addition, a sample of 60 anonymous Finnish trios, representing a random sample of the population, was used in order to derive the unbiased frequencies of the NDE1 SNPs and tag-haplotype. For SNP and haplotype-association analysis of the end-state diagnosis, this control sample was combined with the ascertained families in order to have some provision for the bias in the schizophrenia sample by the addition of controls.

Clinical phenotype and neurocognitive traits
The diagnostic assessment used for the entire sample population is based on the analysis of all available inpatient and outpatient records for those individuals with a register-based diagnosis of psychosis between 1969 and 1998, who were born between 1940 and 1976. Two psychiatrists then independently determined the consensus best estimate lifetime diagnosis, according to the DSM-IV, blind to family structure and register diagnosis. If these two psychiatrists provided conflicting diagnoses, a third independent psychiatrist was used to reach the consensus; however, reviewer's agreement has been noted to be excellent, with kappa values ranging from 95–99% depending on the LC (49), meaning that the third reviewer was rarely used. The LCs used here applied criteria from the DSM-IV and comprised the following categories. LC1 constitutes schizophrenia only, LC2 added individuals affected with schizoaffective disorder, LC3 added individuals with schizophrenia spectrum disorder and LC4 added individuals with bipolar disorder or severe major depressive disorder. In order to reduce the potential multiple testing involved in the association analysis, only the broadest LC (LC4) was to be used, and this was also selected, as it would provide all possible phase information and statistical power available from this sample.

The neuropsychological test battery, from where the quantitative neurocognitive trait was obtained, is a series of tests that uses well-validated, internationally used neuropsychological instruments to evaluate an individual's cognitive ability and includes the Wechsler Memory Scale—revised (50), the Wechsler Adult Intelligence Scale—revised (51) and the California Verbal Learning Test (52). They were administered to the subjects in a fixed order by experienced psychologists or psychiatric nurses who had received extensive training with the test battery, and all scoring was done by experienced psychologists (14). From this battery, only the variable for the test of visual working memory, as assessed through the Visual Span backward sub-test of the Wechsler Memory Scale—revised (50), was used because of the a priori hypothesis that NDE1 would associate to the same trait as DISC1. The descriptive statistics for the visual working memory variable used are similar to the variable used to test for association with DISC1 (6), the trait having a mean of 7.9 and a standard deviation of 1.8 in the whole sample.

Stratification of the sample
Although it is possible to hypothesize about the affecting mechanism represented by HEP3, we cannot be certain; therefore, we decided to be conservative in our criteria for dividing our sample population. The original study of 458 families was split into families where at least one family member carried the HEP3 haplotye ‘risk’ allele (n = 145 families) and families where no one in the family was predicted to carry the HEP3 haplotype (n = 313 families) (Table 5). Previous genome-wide analysis of this sample of Finnish families ascertained for schizophrenia has used a genealogical and geographical criterion for the separation of the sample (18–21), such a criterion was not additionally applied here.


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  		Table 5. Sample characteristics of the whole and two sub-samples, giving the number of families, individuals and individuals affected under the four LCs used in the analysis

 
Construction of haplotypes
For the analysis presented here, it was necessary to construct the haplotypes for each individual in the analysis. There is currently no gold standard for reliably performing this on data that consist of multiple tightly linked SNPs within family-based samples. The most reliable way to construct these haplotypes with this data set was to use the Simwalk2 program (53), a Markov chain Monte Carlo and simulated annealing program for haplotype analysis. This returned the most likely haplotypes for each individual, and in order to increase the reliability of the predicted haplotypes, we used all possible markers that had been genotyped on the 1q42 and 16p13 regions, which included 28 SNPs and four microsatellite markers for 1q42 and seven SNPs and two microsatellite markers for 16p13; the microsatellite markers used were those located next to the genes, not necessarily those that provided evidence of linkage. As an extra precaution for reliability, haplotypes assigned to individuals who had not been genotyped were not used in further analysis. The frequencies of the resulting haplotypes matched with those predicted by the TRANSMIT program (37).

Linkage analysis and simulation
A genome-wide linkage analysis was performed on the two stratified samples and the combined data set using genotypes from 443 microsatellite markers. These markers were all the microsatellites that had been previously genotyped and analyzed by this research group (18,19,22). Two-point linkage analysis was carried out using the heterogeneity model of the MLINK program (54). The scan was performed in all three samples for all four increasingly inclusive LCs and using both dominant and recessive models. Testing all of these models in each sample meant that 24 genome scans were being tested. Therefore, simulation of the data was essential in order to derive the significance of any results in the face of this multiple testing as well as the additional biasing contributed by the conditioning on DISC1. Such simulation of the linkage significance was carried out by randomly reassigning genotypes to individuals, but keeping the genotype frequencies identical to the original analysis, to create 100 random replicates of the sample. Linkage analysis, as performed for the original sample, was then performed on each of these replicates, with the derived P-values being calculated from the number of times the observed maximum LOD score was seen or exceeded in these simulations. The derivation of the P-value was performed across all 24 models and across all eight models in the three samples. None of our observed LOD scores was significant across all 24 models, and across all eight models for the individual samples, only the LOD scores > 3 are around the 0.05 level of significance. Therefore, we report the observed LOD scores in the text stating only that they provide evidence of linkage. The number of replicates performed for this analysis should ideally have been around 1000. However, due to the computational intensity of such analysis, it was first used for 100 replicates, since these already showed that none of our observed findings was significant over all tests performed, and it was decided that the remaining 900 replicates were not a necessary addition to the study. This simulation was also used to test the linkage information content of the two sub-samples and ensured that one sample was not liable to provide over-inflated LOD scores of no significance (Fig. 4).


Figure 4
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  		Figure 4. Graph to show the linkage information content of the three samples used here, showing the significance expected for a range of LOD scores, given the number of tests performed. The thick solid black line represents the significance across all 24 models performed. The thick dashed line represents the significance across the eight models performed on the whole sample. The thin solid line represents the significance across the eight models performed on the sample of families who did not carry the HEP3 allelic haplotype, and the thin dashed line represents the significance across the eight models performed on the sample of families with the HEP3 allelic haplotype.

 
Association and LD analysis
The genotypes for all the SNPs were corrected for Mendelian errors using the PedCheck program (55). Two-point analysis was performed using the Pseudomarker program, which performs joint linkage and LD analysis on a mixture of pedigrees and singletons. Pseudomarker is able to combine the power of linkage analysis with that of association and can test for LD in general pedigrees conditional on linkage (35). This latter option was used here, since it was known that the sample already displays linkage to this particular region. The LD between the seven SNPs covering the NDE1 gene was analyzed using the founder genotypes in the Haploview program with the solid spine of LD criterion (D' > 0.8) (36). This identified which SNPs would tag for the whole region when analyzed as a haplotype. Analysis of the tag-haplotype with the end-state diagnosis was performed using the TRANSMIT program, which can test for transmission of a haplotype even when phase is unknown and when parental genotypes are not complete. The TRANSMIT program is also able to compensate for the presence of linkage when using family data by the calculation of a robust variance estimate and by enabling the testing of one randomly affected offspring per family (37). Allelic haplotypes below a sample frequency of 5% were ignored as being too rare. TRANSMIT performed 100 000 permutations for all analyses, from which it derived the empirical P-values.Association analysis was performed only using the broadest diagnostic class (LC4), even though the maximum linkage signal was observed for LC1; this was so as to include all possible information afforded by our sample. Additionally, this strategy was implicated because of the previously observed linkage peak for bipolar disorder at 16p12, which suggested that the locus might be of importance to other psychiatric disorders and not just schizophrenia. For analysis of association with the neurocognitive test variable, the QTDT program was used (38). This is a variance component method for testing transmission distortion of an allele with a quantitative trait. In this analysis, age, sex and affection according to LC4 were used as covariates, and 100 000 permutations were performed to derive the empirical P-values.The predicted NDE1 haplotypes were recoded to form ‘bi-allelic markers’ so as to allow the hypothesized risk haplotype allele to be tested against all other possible haplotype alleles combined. Multiple testing was corrected using the Bonferroni correction; this method could be over conservative because all SNPs were to some degree in LD, meaning that the actual tests were not completely independent of one another. Therefore, we report the uncorrected observed P-values and state which ones remain significant at the 0.05 level after conservative correction. The haplotype analysis performed in TRANSMIT undertakes permutation analysis, which can be used to correct the multiple testing within the test for each haplotype. However, the Bonferroni correction is needed to be applied to the resulting P-value for the haplotype in order to account for the prior tests using the haplotypes component SNPs.


   ACKNOWLEDGEMENTS
 
The authors would like to acknowledge the efforts of Ms J. Meyer and Mr A. Parker for their contributing efforts in genotyping this sample, Mr K Sood for work in haplotyping and Mr P. Haimi for work with databases. Ms C. von Schantz is acknowledged for her assistance in protein and mouse model data mining. This work was partly funded by Wyeth Pharmaceuticals Inc., Millennium Pharmaceuticals Inc., Center of Excellence in Disease Genetics of the Academy of Finland and Biocentrum Helsinki Foundation for L.P., NIMH, Academy of Finland and Sigrid Juselius foundation grants for J.D.T., Academy of Finland grant for T.H. and Finnish Cultural Foundation Paavo Koskinen and Aili and Paul Pennanen grants for W.H. W.H. was a PhD student of the Helsinki Biomedical Graduate School. ‘Funding to pay the Open Access Publication charges for this article was provided by Center of Excellence in Disease Genetics of the Academy of Finland’.

Conflict of Interest statement. The authors declare that they have competing interests in this study.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
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