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Contains fulltext : 248656.pdf (Publisher’s version ) (Closed access) BACKGROUND: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. METHODS: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. RESULTS: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10(-8)), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10(-6)) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10(-7); rs73033497, p = 8.8 × 10(-7); rs7914279, p = 6.4 × 10(-7)), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10(-7)) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10(-7)), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10(-7)) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). CONCLUSIONS: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.

Schizophrenia is a common, clinically heterogeneous disorder associated with lifelong morbidity and early mortality. Several genetic variants associated with schizophrenia have been identified, but the majority of the heritability remains unknown. In this study, we report on a case-control sample of Ashkenazi Jews (AJ), a founder population that may provide additional insights into genetic etiology of schizophrenia. We performed a genome-wide association analysis (GWAS) of 592 cases and 505 controls of AJ ancestry ascertained in the US. Subsequently, we performed a meta-analysis with an Israeli AJ sample of 913 cases and 1640 controls, followed by a meta-analysis and polygenic risk scoring using summary results from Psychiatric GWAS Consortium 2 schizophrenia study. The U.S. AJ sample showed strong evidence of polygenic inheritance (pseudo-R2 ∼9.7%) and a SNP-heritability estimate of 0.39 (P = 0.00046). We found no genome-wide significant associations in the U.S. sample or in the combined US/Israeli AJ meta-analysis of 1505 cases and 2145 controls. The strongest AJ specific associations (P-values in 10−6–10−7 range) were in the 22q 11.2 deletion region and included the genes TBX1, GLN1, and COMT. Supportive evidence (meta P

Schizophrenia is a brain disorder with high heritability. Recent studies have implicated genes involved in the immune response pathway in the pathogenesis of schizophrenia. Interferon regulatory factor 3 (IRF3), a virus-immune-related gene, activates the transcription of several interferon-induced genes, and functionally interacts with several schizophrenia susceptibility genes. To test whether IRF3 is a schizophrenia susceptibility gene, we analyzed the associations of its SNPs with schizophrenia in independent population samples as well as reported data from expression quantitative trait loci (eQTL) in healthy individuals. We observed multiple independent SNPs in IRF3 showing nominally significant associations with schizophrenia (P < 0.05); more intriguingly, a SNP (rs11880923), which is significantly correlated with IRF3 expression in independent samples (P < 0.05), is also consistently associated with schizophrenia across different cohorts and in combined samples (odds ratio = 1.075, Pmeta = 2.08 × 10(-5)), especially in Caucasians (odds ratio = 1.078, Pmeta = 2.46 × 10(-5)). These results suggested that IRF3 is likely a risk gene for schizophrenia, at least in Caucasians. Although the clinical associations of IRF3 with diagnosis did not achieve genome-wide level of statistical significance, the observed odds ratio is comparable with other susceptibility loci identified through large-scale genetic association studies on schizophrenia, which could be regarded simply as small but detectable effects.

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R-2 increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase. Refereed/Peer-reviewed

Interpretation of complex DNA mixtures is an ongoing challenge in the field of forensic genetics. Commonly used STR markers are quite polymorphic, enabling very high statistical association between a single source DNA profile from a crime scene and a matching suspect. STR typing of low order mixtures with two and three contributors also commonly produces high statistical association for a contributor, using current interpretation software. However higher order mixtures, with four contributors or more, are more challenging. Shared alleles among the many contributors may complicate the correct assessment of the number of contributors to a mixture and decreases the statistical support for inclusion of contributors. Recently, there is a rising use of massively parallel sequencing for forensic applications, and markers such as SNPs and short haplotypes are receiving more attention. However, these markers are even less polymorphic than autosomal STRs and are not suitable for complex mixture interpretation. We propose to use a different panel of haplotype markers, which contain many SNPs and are very polymorphic. These markers can be sequenced either by standard sequencing technologies or by a new instrument called MinION that sequences DNA as it passes through a nanopore. This instrument is very small and can sequence long stretches of DNA, but suffers from high error rate. We present a method for calling haplotype alleles facing high error rate, and use simulation to test its robustness. We also calculate likelihood ratio (LR) between propositions of contribution and non-contribution for individuals that do, and do not, contribute to various complex DNA mixtures. Our results indicate that the correct alleles can be identified in a mixture, despite the high sequencing error rate, and that contributors get high LR (>109) even in complex mixtures with up to five contributors. Non-contributors receive a very small LR, below 1 in most cases (>98%), which support their exclusion as possible donors to the complex DNA mixtures.

J. Lönnqvist on työryhmän Psychiat Genomics Consortium jäsen. Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on similar to 150,000 individuals give a higher accuracy than LDSC estimates based on similar to 400,000 individuals (from combinedmeta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.

We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05–21.6; P=1 × 10−4) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P=8.4 × 10−7). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08–1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies., Relatives of patients with amyotrophic lateral sclerosis have an unexpectedly high incidence of schizophrenia. Here, the authors show a genetic link between the two conditions, suggesting shared neurobiological mechanisms.

The recent series of large genome-wide association studies in European and Japanese cohorts established that Parkinson disease (PD) has a substantial genetic component. To further investigate the genetic landscape of PD, we performed a genome-wide scan in the largest to date Ashkenazi Jewish cohort of 1130 Parkinson patients and 2611 pooled controls. Motivated by the reduced disease allele heterogeneity and a high degree of identical-by-descent (IBD) haplotype sharing in this founder population, we conducted a haplotype association study based on mapping of shared IBD segments. We observed significant haplotype association signals at three previously implicated Parkinson loci: LRRK2 (OR = 12.05, P = 1.23 × 10(-56)), MAPT (OR = 0.62, P = 1.78 × 10(-11)) and GBA (multiple distinct haplotypes, OR > 8.28, P = 1.13 × 10(-11) and OR = 2.50, P = 1.22 × 10(-9)). In addition, we identified a novel association signal on chr2q14.3 coming from a rare haplotype (OR = 22.58, P = 1.21 × 10(-10)) and replicated it in a secondary cohort of 306 Ashkenazi PD cases and 2583 controls. Our results highlight the power of our haplotype association method, particularly useful in studies of founder populations, and reaffirm the benefits of studying complex diseases in Ashkenazi Jewish cohorts.

Sex differences in schizophrenia are well known, but their genetic basis has not been identified. We performed a genome-wide association scan for schizophrenia in an Ashkenazi Jewish population using DNA pooling. We found a female-specific association with rs7341475, a SNP in the fourth intron of the reelin (RELN) gene (p = 2.9 × 10−5 in women), with a significant gene-sex effect (p = 1.8 × 10−4). We studied rs7341475 in four additional populations, totaling 2,274 cases and 4,401 controls. A significant effect was observed only in women, replicating the initial result (p = 2.1 × 10−3 in women; p = 4.2 × 10−3 for gene-sex interaction). Based on all populations the estimated relative risk of women carrying the common genotype is 1.58 (p = 8.8 × 10−7; p = 1.6 × 10−5 for gene-sex interaction). The female-specific association between RELN and schizophrenia is one of the few examples of a replicated sex-specific genetic association in any disease., Author Summary Schizophrenia is a complex mental disease, which includes symptoms of delusions, hallucinations, disorganized speech, aberrant behavior, lack of emotional expression, diminished motivation, and social withdrawal. The cause of schizophrenia is unknown, but there is extensive evidence that genetics play a significant role in its aetiology. We studied the genetic basis of schizophrenia by analyzing around 500,000 genetic variants distributed across the whole human genome in DNA from schizophrenic patients and controls. We analyzed separately the DNA from men and women, and identified a genetic variant that increases the risk of developing schizophrenia in women only. The genetic variant is estimated to increase the risk of schizophrenia for women carrying the risk variant by 1.4-fold. The genetic variant is in a gene called reelin, which is known to play a part in brain development. However, it is still unclear how this genetic variant predisposes to schizophrenia nor why it is specific to women only.

The Ashkenazi Jewish (AJ) population is important in genetics due to its high rate of Mendelian disorders. AJ appeared in Europe in the 10th century, and their ancestry is thought to comprise European (EU) and Middle-Eastern (ME) components. However, both the time and place of admixture are subject to debate. Here, we attempt to characterize the AJ admixture history using a careful application of new and existing methods on a large AJ sample. Our main approach was based on local ancestry inference, in which we first classified each AJ genomic segment as EU or ME, and then compared allele frequencies along the EU segments to those of different EU populations. The contribution of each EU source was also estimated using GLOBETROTTER and haplotype sharing. The time of admixture was inferred based on multiple statistics, including ME segment lengths, the total EU ancestry per chromosome, and the correlation of ancestries along the chromosome. The major source of EU ancestry in AJ was found to be Southern Europe (≈60–80% of EU ancestry), with the rest being likely Eastern European. The inferred admixture time was ≈30 generations ago, but multiple lines of evidence suggest that it represents an average over two or more events, pre- and post-dating the founder event experienced by AJ in late medieval times. The time of the pre-bottleneck admixture event, which was likely Southern European, was estimated to ≈25–50 generations ago., Author summary The Ashkenazi Jewish population has resided in Europe for much of its 1000-year existence. However, its ethnic and geographic origins are controversial, due to the scarcity of reliable historical records. Previous genetic studies have found links to Middle-Eastern and European ancestries, but the admixture history has not been studied in detail yet, partly due to technical difficulties in disentangling signals from multiple admixture events. Here, we present an in-depth analysis of the sources of European gene flow and the time of admixture events by using multiple new and existing methods and extensive simulations. Our results suggest a model of at least two events of European admixture. One event slightly pre-dated a late medieval founder event and was likely from a Southern European source. Another event post-dated the founder event and likely occurred in Eastern Europe. These results, as well as the methods introduced, will be highly valuable for geneticists and other researchers interested in Ashkenazi Jewish origins.

Recent studies have identified numerous single nucleotide polymorphisms (SNPs) that modify an individual's risk of developing prostate cancer (Amundadottir et al, 2006; Eeles et al, 2008; Gudmundsson et al, 2007a; Gudmundsson et al, 2008; Gudmundsson et al, 2007b; Haiman et al, 2007; Robbins et al, 2007; Thomas et al, 2008). Although some investigators have considered the possibility of heterogeneity between ethnic groups, where a SNP shows a different effect on prostate cancer risk depending on the population being studied, these studies only considered ethnic groups with different continents of ancestral origins (Haiman et al, 2007; Waters et al, 2009; Yamada et al, 2009; Hooker et al, 2010; Zheng et al, 2010). As alleles of numerous SNPs are known to vary in frequency across Europe (Bersaglieri et al, 2004), and population substructure is consistently observed in Americans with ancestry from different locations in Europe (Price et al, 2008; Tian et al, 2008), there is a possibility that prostate cancer risk alleles may have different effects in different populations of European ancestry. Ashkenazi Jews are Jews whose ancestors come primarily from central and eastern Europe; the majority of North American Jews and a large proportion of Israeli Jews are of Ashkenazi ancestry. The global linkage disequilibrium (LD) profiles of the Ashkenazi Jewish (AJ) population do not seem to differ significantly from that of other populations of European ancestry. However, it has been suggested that there may be significant local differences in allele frequencies and haplotype structure between the Ashkenazi population and other European populations, including at loci associated with common cancer (Gold et al, 2008; Olshen et al, 2008; Price et al, 2008; Tian et al, 2008). Therefore, examination of known prostate cancer risk SNPs in the AJ population provides a unique opportunity to test for genetic heterogeneity at these loci among individuals of European ancestry. Here, we report the results of a case–control association study in the AJ population of 29 previously identified prostate cancer SNPs. Our data argue against the hypothesis that risk alleles for prostate cancer generally have different effects in the Ashkenazi and non-Ashkenazi European ancestry populations.

In recent years in silico analysis of common laboratory mice has been introduced and subsequently applied, in slightly different ways, as a methodology for gene mapping. Previously we have demonstrated some limitation of the methodology due to sporadic genetic correlations across the genome. Here, we revisit the three main aspects that affect in silico analysis. First, we report on the use of marker maps: we compared our existing 20,000 SNP map to the newly released 140,000 SNP map. Second, we investigated the effect of varying strain numbers on power to map QTL. Third, we introduced a novel statistical approach: a cladistic analysis, which is well suited for mouse genetics and has increased flexibility over existing in silico approaches. We have found that in our examples of complex traits, in silico analysis by itself does fail to uniquely identify quantitative trait gene (QTG)-containing regions. However, when combined with additional information, it may significantly help to prioritize candidate genes. We therefore recommend using an integrated work flow that uses other genomic information such as linkage regions, regions of shared ancestry, and gene expression information to obtain a list of candidate genes from the genome.

Several lines of evidence have established the presence of an association between a 3-Mb deletion in chromosome 22q11 and schizophrenia. In this paper we present a complete high-density SNP scan of this segment using DNA pools, and demonstrate significant association between two distinct regions and schizophrenia in an Ashkenazi Jewish population. One of these regions contains the previously identified COMT gene. The pattern of association and linkage disequilibrium (LD) in the second region suggest that DGCR2, which encodes a putative adhesion receptor protein, is the susceptibility gene. We confirmed the association between DGCR2 and schizophrenia through individual genotyping of 1,400 subjects. In a gene expression analysis the risk allele of a coding SNP associated with schizophrenia was found to be associated with a reduced expression of DGCR2. Interestingly, the expression of DGCR2 was also found to be elevated in the dorsolateral prefrontal cortex of schizophrenic patients relative to matched controls. This increase is likely to be explained by exposure to antipsychotic drugs. To test that hypothesis, we looked at rats exposed to antipsychotic medication and found significantly elevated levels of DGCR2 transcripts. The genetic and functional evidences here reported suggest a possible role of the DGCR2 gene in the pathology of schizophrenia and also in the therapeutic effects of antipsychotic drugs.

Association studies are now primarily being conducted with single nucleotide polymorphisms because they are present everywhere in the genome and can be genotyped in "high throughput" formats. Microsatellite markers have a higher degree of polymorphism than single nucleotide polymorphisms and have been widely used in both linkage and association studies of disease. Polymorphic microsatellite markers with several alleles can readily detect linkage disequilibrium but at any given locus there may be differences between single nucleotide polymorphisms and microsatellites in their power to detect linkage disequilibrium because of the evolutionary history of the locus, especially the rate at which both the single nucleotide polymorphisms and microsatellite polymorphisms have mutated and the number of disease mutations and their history. In the current study, we examined the efficiency of microsatellite markers in association analysis by looking at all existent microsatellite markers in the catechol-O-methyltransferase gene region and by genotyping these microsatellites in a large cohort of schizophrenia patients and healthy controls, a subset of a sample where catechol-O-methyltransferase and schizophrenia were found to be associated. We also estimated the levels of linkage disequilibrium between these microsatellites and the previously reported single nucleotide polymorphisms (within the catechol-O-methyltransferase gene) found to be associated with schizophrenia. A modest allelic association of P=0.041 was found between schizophrenia and the microsatellite marker D22S944, which was not significant, however, when corrected for all microsatellites tested. Nevertheless, significant linkage disequilibrium was found between this marker and the three single nucleotide polymorphisms within the catechol-O-methyltransferase gene that displayed association with the disease in the previously published research on this sample. Significant linkage disequilibrium was also observed between microsatellites up to approximately 300 kb distant from those single nucleotide polymorphisms. Although significant, the extent of linkage disequilibrium in terms of r2 was small (in the order of 0.01).

Common forensic and mass disaster scenarios present DNA evidence that comprises a mixture of several contributors. Identifying the presence of an individual in such mixtures has proven difficult. In the current study, we evaluate the practical usefulness of currently available "off-the-shelf" SNP microarrays for such purposes. We found that a set of 3000 SNPs specifically selected for this purpose can accurately identify the presence of an individual in complex DNA mixtures of various compositions. For example, individuals contributing as little as 5% to a complex DNA mixture can be robustly identified even if the starting DNA amount was as little as 5.0ng and had undergone whole-genome amplification (WGA) prior to SNP analysis. The work presented in this study represents proof-of-principle that our previously proposed approach, can work with real "forensic-type" samples. Furthermore, in the absence of a low-density focused forensic SNP microarray, the use of standard, currently available high-density SNP microarrays can be similarly used and even increase statistical power due to the larger amount of available information.

The Ashkenazi Jewish (AJ) population is a genetic isolate close to European and Middle Eastern groups, with genetic diversity patterns conducive to disease mapping. Here we report high-depth sequencing of 128 complete genomes of AJ controls. Compared with European samples, our AJ panel has 47% more novel variants per genome and is eightfold more effective at filtering benign variants out of AJ clinical genomes. Our panel improves imputation accuracy for AJ SNP arrays by 28%, and covers at least one haplotype in ≈67% of any AJ genome with long, identical-by-descent segments. Reconstruction of recent AJ history from such segments confirms a recent bottleneck of merely ≈350 individuals. Modelling of ancient histories for AJ and European populations using their joint allele frequency spectrum determines AJ to be an even admixture of European and likely Middle Eastern origins. We date the split between the two ancestral populations to ≈12–25 Kyr, suggesting a predominantly Near Eastern source for the repopulation of Europe after the Last Glacial Maximum., Ashkenazi Jews are a genetically isolated population with distinct patterns of genetic diversity. Here, the authors sequence the genomes of 128 Ashkenazi Jewish individuals and use the sequence information to provide insight into the population's European and Middle Eastern origins.

Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia. ispartof: Nature vol:511 issue:7510 pages:421-7 ispartof: location:England status: published

Schizophrenia and bipolar disorder are major psychiatric disorders with high heritability and overlapping genetic variance. Here we perform a genome-wide association study in an ethnically homogeneous cohort of 904 schizophrenia cases and 1,640 controls drawn from the Ashkenazi Jewish population. We identify a novel genome-wide significant risk locus at chromosome 4q26, demonstrating the potential advantages of this founder population for gene discovery. The top single-nucleotide polymorphism (SNP; rs11098403) demonstrates consistent effects across 11 replication and extension cohorts, totalling 23, 191 samples across multiple ethnicities, regardless of diagnosis (schizophrenia or bipolar disorder), resulting in Pmeta=9.49 × 10−12 (odds ratio (OR)=1.13, 95% confidence interval (CI): 1.08–1.17) across both disorders and Pmeta=2.67 × 10−8 (OR=1.15, 95% CI: 1.08–1.21) for schizophrenia alone. In addition, this intergenic SNP significantly predicts postmortem cerebellar gene expression of NDST3, which encodes an enzyme critical to heparan sulphate metabolism. Heparan sulphate binding is critical to neurite outgrowth, axon formation and synaptic processes thought to be aberrant in these disorders., Schizophrenia and bipolar disorder are important psychiatric disorders with overlapping genetic components. Here, the authors identify and replicate a genome-wide significant risk locus for the two disorders, and suggest a role for NDST3 in severe psychiatric disease.

Copy number variants (CNVs) are risk factors in neurodevelopmental disorders, including autism, epilepsy, intellectual disability (ID) and schizophrenia. Childhood onset schizophrenia (COS), defined as onset before the age of 13 years, is a rare and severe form of the disorder, with more striking array of prepsychotic developmental disorders and abnormalities in brain development. Because of the well-known phenotypic variability associated with pathogenic CNVs, we conducted whole genome genotyping to detect CNVs and then focused on a group of 46 rare CNVs that had well-documented risk for adult onset schizophrenia (AOS), autism, epilepsy and/or ID. We evaluated 126 COS probands, 69 of which also had a healthy full sibling. When COS probands were compared with their matched related controls, significantly more affected individuals carried disease-related CNVs (P=0.017). Moreover, COS probands showed a higher rate than that found in AOS probands (P

Data-driven studies of identity by descent (IBD) were recently enabled by high-resolution genomic data from large cohorts and scalable algorithms for IBD detection. Yet, haplotype sharing currently represents an underutilized source of information for population-genetics research. We present analytical results on the relationship between haplotype sharing across purportedly unrelated individuals and a population’s demographic history. We express the distribution of IBD sharing across pairs of individuals for segments of arbitrary length as a function of the population’s demography, and we derive an inference procedure to reconstruct such demographic history. The accuracy of the proposed reconstruction methodology was extensively tested on simulated data. We applied this methodology to two densely typed data sets: 500 Ashkenazi Jewish (AJ) individuals and 56 Kenyan Maasai (MKK) individuals (HapMap 3 data set). Reconstructing the demographic history of the AJ cohort, we recovered two subsequent population expansions, separated by a severe founder event, consistent with previous analysis of lower-throughput genetic data and historical accounts of AJ history. In the MKK cohort, high levels of cryptic relatedness were detected. The spectrum of IBD sharing is consistent with a demographic model in which several small-sized demes intermix through high migration rates and result in enrichment of shared long-range haplotypes. This scenario of historically structured demographies might explain the unexpected abundance of runs of homozygosity within several populations.

Homologous long segments along the genomes of close or remote relatives that are identical by descent (IBD) from a common ancestor provide clues for recent events in human genetics. We set out to extensively map such IBD segments in large cohorts and investigate their distribution within and across different populations. We report analysis of several data sets, demonstrating that IBD is more common than expected by naive models of population genetics. We show that the frequency of IBD pairs is population dependent and can be used to cluster individuals into populations, detect a homogeneous subpopulation within a larger cohort, and infer bottleneck events in such a subpopulation. Specifically, we show that Ashkenazi Jewish individuals are all connected through transitive remote family ties evident by sharing of 50 cM IBD to a publicly available data set of less than 400 individuals. We further expose regions where long-range haplotypes are shared significantly more often than elsewhere in the genome, observed across multiple populations, and enriched for common long structural variation. These are inconsistent with recent relatedness and suggest ancient common ancestry, with limited recombination between haplotypes.

We conducted data-mining analyses using the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and molecular genetics of schizophrenia genome-wide association study supported by the genetic association information network (MGS-GAIN) schizophrenia data sets and performed bioinformatic prioritization for all the markers with P-values ≤0.05 in both data sets. In this process, we found that in the CMYA5 gene, there were two non-synonymous markers, rs3828611 and rs10043986, showing nominal significance in both the CATIE and MGS-GAIN samples. In a combined analysis of both the CATIE and MGS-GAIN samples, rs4704591 was identified as the most significant marker in the gene. Linkage disequilibrium analyses indicated that these markers were in low LD (3 828 611–rs10043986, r2 = 0.008; rs10043986–rs4704591, r2 = 0.204). In addition, CMYA5 was reported to be physically interacting with the DTNBP1 gene, a promising candidate for schizophrenia, suggesting that CMYA5 may be involved in the same biological pathway and process. On the basis of this information, we performed replication studies for these three single-nucleotide polymorphisms. The rs3828611 was found to have conflicting results in our Irish samples and was dropped out without further investigation. The other two markers were verified in 23 other independent data sets. In a meta-analysis of all 23 replication samples (family samples, 912 families with 4160 subjects; case–control samples, 11 380 cases and 15 021 controls), we found that both markers are significantly associated with schizophrenia (rs10043986, odds ratio (OR) = 1.11, 95% confidence interval (CI) = 1.04–1.18, P = 8.2 × 10−4 and rs4704591, OR = 1.07, 95% CI = 1.03–1.11, P = 3.0 × 10−4). The results were also significant for the 22 Caucasian replication samples (rs10043986, OR = 1.11, 95% CI = 1.03–1.17, P = 0.0026 and rs4704591, OR = 1.07, 95% CI = 1.02–1.11, P = 0.0015). Furthermore, haplotype conditioned analyses indicated that the association signals observed at these two markers are independent. On the basis of these results, we concluded that CMYA5 is associated with schizophrenia and further investigation of the gene is warranted.

The identification of a suspect in a complex DNA mixture typed with standard short tandem repeat (STR) kits has proved difficult. In the current study we present the theoretical framework of a method aimed to resolve this problem in forensic cases. The method suggests genotyping a specially designed panel of 1000-3000 single nucleotide polymorphisms (SNPs), each with a relatively low (

We carried out a genome-wide association study of schizophrenia (479 cases, 2,937 controls) and tested loci with P < 10-5 in up to 16,726 additional subjects. Of 12 loci followed up, 3 had strong independent support (P < 5 × 10-4), and the overall pattern of replication was unlikely to occur by chance (P = 9 × 10-8). Meta-analysis provided strongest evidence for association around ZNF804A (P = 1.61 × 10-7) and this strengthened when the affected phenotype included bipolar disorder (P = 9.96 × 10-9). © 2008 Nature Publishing Group.

Until last year, type 2 diabetes (T2D) susceptibility loci have hardly been identified, despite great effort. Recently, however, several whole-genome association (WGA) studies jointly uncovered 10 robustly replicated loci. Here, we examine these loci in the Ashkenazi Jewish (AJ) population in a sample of 1,131 cases versus 1,147 controls. Genetic predisposition to T2D in the AJ population was found similar to that established in the previous studies. One SNP, rs7754840 in the CDKAL1 gene, presented a significantly stronger effect in the AJ population as compared to the general Caucasian population. This may possibly be due to the increased homogeneity of the AJ population. The use of the SNPs considered in this study, to identify individuals at high (or low) risk to develop T2D, was found of limited value. Our study, however, strongly supports the robustness of WGA studies for the identification of genes affecting complex traits in general and T2D in particular.

Evidence both from animal and human studies suggests that common polymorphisms in the oxytocin receptor (OXTR) gene are likely candidates to confer risk for autism spectrum disorders (ASD). In lower mammals, oxytocin is important in a wide range of social behaviors, and recent human studies have shown that administration of oxytocin modulates behavior in both clinical and non-clinical groups. Additionally, two linkage studies and two recent association investigations also underscore a possible role for the OXTR gene in predisposing to ASD. We undertook a comprehensive study of all 18 tagged SNPs across the entire OXTR gene region identified using HapMap data and the Haploview algorithm. Altogether 152 subjects diagnosed with ASDs (that is, DSM IV autistic disorder or pervasive developmental disorder--NOS) from 133 families were genotyped (parents and affected siblings). Both individual SNPs and haplotypes were tested for association using family-based association tests as provided in the UNPHASED set of programs. Significant association with single SNPs and haplotypes (global P-values

Neuregulin 1 (NRG1) has been found to be associated with schizophrenia in several populations. Consistently, mutant mice heterozygous for either NRG1 or its receptor, ErbB4, show a behavioral phenotype that overlaps with mouse models for schizophrenia. These observations raised the hypothesis that impaired NRG1-ErbB4 signaling may contribute to schizophrenia susceptibility. Nineteen SNPs encompassing the ErbB4 gene were selected from the HapMap database and genotyped in genomic DNA isolated from 59 Ashkenazi schizophrenia patients and 130 matched controls. Expression analysis of ErbB4 splice variants was performed on postmortem DLPFC samples obtained from Caucasian patients and controls by real-time PCR. We found a highly significant difference between patient and control groups in three SNPs from one linkage disequilibrium (LD) block both in allele (P = 0.013, 0.0045, 0.0049) and genotype frequencies (P = 0.00013, 0.000021, 0.00018), as well as a risk haplotype (P = 0.00044). Expression analysis indicated that the CYT-1 isoform is overexpressed in patients (P = 0.047) and that juxtamembrane (JM)-a displays a similar trend (P = 0.081). This study provides a direct link between ErbB4 and the disease. We propose that NRG1 and its receptor ErbB4 are components of a biological pathway, involved in the pathophysiology of schizophrenia.

The shared ancestry of mouse inbred strains, together with the availability of sequence and phenotype information, is a resource that can be used to map quantitative trait loci (QTL). The difficulty in using only sequence information lies in the fact that in most instances the allelic state of the QTL cannot be unambiguously determined in a given strain. To overcome this difficulty, the performance of multiple crosses between various inbred strains has been proposed. Here we suggest and evaluate a general approach, which consists of crossing the two strains used initially to map the QTL and any new strain. We have termed these crosses “yin-yang,” because they are complementary in nature as shown by the fact that the QTL will necessarily segregate in only one of the crosses. We used the publicly available SNP database of chromosome 16 to evaluate the mapping resolution achievable through this approach. Although on average the improvement of mapping resolution using only four inbred strains was relatively small (i.e., reduction of the QTL-containing interval by half at most), we found a great degree of variability among different regions of chromosome 16 with regard to mapping resolution. This suggests that with a large number of strains in hand, selecting a small number of strains may provide a significant contribution to the fine mapping of QTL.

A variety of psychiatric illnesses, including schizophrenia and bipolar disorder, have been reported in patients with microdeletion on chromosome 22q11-a region which includes the catechol-O-methyltransferase (COMT) gene. The variety of psychiatric manifestations in patients with the 22q11 microdeletion and the role of COMT in the degradation of catecholamine neurotransmitters may thus suggest a general involvement of the COMT gene in psychiatric diseases. We have previously reported on a significant association between a COMT haplotype and schizophrenia. In this study, we attempt to test for association between bipolar disorder and the polymorphisms implicated in schizophrenia. The association between COMT and bipolar disorder was tested by examining the allele and haplotype found to be associated with schizophrenia. A significant association between bipolar disorder and COMT polymorphisms was found. The estimated relative risk is greater in women, a result consistent with our previous findings in schizophrenia. We suggest that polymorphisms in the COMT gene may influence susceptibility to both diseases--and probably also a wider range of behavioral traits.

We studied the patterns of linkage disequilibrium (LD) in the human genome among three populations: African Americans, Caucasians and Ashkenazi Jews. These three populations represent admixed, outbred and isolated populations, respectively. The study examined defined chromosomal regions across the whole genome. We found that SNP allele frequencies are highly correlated between Ashkenazi Jews and Caucasians and somewhat distinct in African Americans. In addition, Ashkenazi Jews have a modest increase in LD compared with Caucasians, and both have greater LD than African Americans. The three populations differed more significantly with regard to haplotype heterogeneity. We found, as expected, that Ashkenazi Jews display the greatest extent of homogeneity and African Americans the greatest extent of heterogeneity. We found that most of the variance in LD can be attributed to the difference between regions and markers rather than to that between different population types. The average recombination rates estimated by low-resolution genetic maps can only explain a small fraction of the variance between regions. We found that LD (in terms of r(2)) decreases as a function of distance even within the so-called 'haplotype blocks'. This has significant consequences when using LD mapping for the genetic dissection of complex traits, as higher density SNP maps will be required to scan the genome.

We have compared several genotyping methods to assess their applicability to single nucleotide polymorphism (SNP) allele frequency estimation in DNA pools. The accuracy of these methods (restriction fragment length polymorphism, real-time pyrophosphate DNA sequencing, single base extension with fluorescently labeled ddNTPs, homogeneous 5'-nuclease assay, and MALDI-TOF mass spectrometry) was tested by calculating the standard deviation among heterozygous individuals (which are natural DNA pools with 50% representation of each allele) and by estimating allele frequency in artificial pools. We show that although the methods differ in their accuracy, they can all serve for quantification of allele frequency in DNA pools with reasonable accuracy. We found that the influence of the error variance attributed to pool construction on quantification accuracy is insignificant and is SNP dependent.

Several lines of evidence have placed the catechol-O-methyltransferase (COMT) gene in the limelight as a candidate gene for schizophrenia. One of these is its biochemical function in metabolism of catecholamine neurotransmitters; another is the microdeletion, on chromosome 22q11, that includes the COMT gene and causes velocardiofacial syndrome, a syndrome associated with a high rate of psychosis, particularly schizophrenia. The interest in the COMT gene as a candidate risk factor for schizophrenia has led to numerous linkage and association analyses. These, however, have failed to produce any conclusive result. Here we report an efficient approach to gene discovery. The approach consists of ( i ) a large sample size—to our knowledge, the present study is the largest case-control study performed to date in schizophrenia; ( ii ) the use of Ashkenazi Jews, a well defined homogeneous population; and ( iii ) a stepwise procedure in which several single nucleotide polymorphisms (SNPs) are scanned in DNA pools, followed by individual genotyping and haplotype analysis of the relevant SNPs. We found a highly significant association between schizophrenia and a COMT haplotype ( P =9.5×10 −8 ). The approach presented can be widely implemented for the genetic dissection of other common diseases.

The complex genetic nature of many common diseases makes the identification of the genes that predispose to these ailments a difficult task. In this review we discuss the elements that contribute to the complexity of polygenic diseases and describe an experimental strategy for disease-related gene discovery that attempts to overcome these factors. This strategy involves a population-based case-control paradigm and makes use of a highly informative, homogeneous founder population, many of whose members presently reside in Israel. The properties of single nucleotide polymorphisms, which are presently the markers of choice, are discussed, and the technologies that are currently available for SNP genotyping are briefly presented.

Multiple studies have reported oligodendrocyte and myelin abnormalities, as well as dysregulation of their related genes, in brains of schizophrenia patients. One of these genes is the myelin-basic-protein (MBP) gene, which encodes two families of proteins: classic-MBPs and golli-MBPs. While the classic-MBPs are predominantly located in the myelin sheaths of the nervous system, the golli proteins are more widely expressed and are found in both the immune and the nervous systems. In the present study we performed a case-control association analysis of golli-MBP in two separate Jewish Ashkenazi cohorts (cohort I: 120 patients, 236 controls; cohort II: 379 patients, 380 controls). In addition we performed an expression analysis of golli-MBP mRNA in post-mortem dorsolateral prefrontal cortex samples of schizophrenia patients, and matched controls. In the first cohort we observed association between six (out of 26 genotyped) single nucleotide polymorphisms (SNPs) and the disease (p

Determination of haplotype frequencies (the joint distribution of genetic markers) in large population samples is a powerful tool for association studies. This is due to their greater extent of polymorphism since any two bi-allelic single nucleotide polymorphisms (SNPs) generate a potential four-allele genetic marker. Therefore, a haplotype may capture a given functional polymorphism with higher statistical power than its SNP components. The statistical estimation of haplotype frequencies, usually employed in linkage disequilibrium studies, requires individual genotyping for each SNP in the haplotype, thus making it an expensive process. In this study, we describe a new method for direct measurement of haplotype frequencies in DNA pools by allele-specific, long-range haplotype amplification. The proposed method allows the efficient determination of haplotypes composed of two SNPs in close vicinity (up to 20 kb).

Type 2 diabetes (T2D) is a common, polygenic chronic disease with high heritability. The purpose of this whole-genome association study was to discover novel T2D-associated genes. We genotyped 500 familial cases and 497 controls with >300,000 HapMap-derived tagging single-nucleotide-polymorphism (SNP) markers. When a stringent statistical correction for multiple testing was used, the only significant SNP was at TCF7L2, which has already been discovered and confirmed as a T2D-susceptibility gene. For a replication study, we selected 10 SNPs in six chromosomal regions with the strongest association (singly or as part of a haplotype) for retesting in an independent case-control set including 2,573 T2D cases and 2,776 controls. The most significant replicated result was found at the AHI1-LOC441171 gene region.

Pemphigus vulgaris (PV) is a severe autoimmune blistering disease caused by anti-epithelial antibodies, leading to disruption of cell–cell adhesion. Although the disease is exceedingly rare worldwide, it is known to be relatively prevalent in Jewish populations. The low prevalence of the disease represents a significant obstacle to a genome-wide approach to the mapping of susceptibility genes. We reasoned that the study of a genetically homogeneous cohort characterized by a high prevalence of PV may help exposing associated signals while reducing spurious results due to population sub-structure. We performed a genome-wide association study using 300K single-nucleotide polymorphisms (SNPs) in a case–control study of 100 PV patients of Jewish descent and 397 matched control individuals, followed by replication of significantly associated SNPs in three additional cohorts of Jewish, Egyptian, and German origin. In addition to the major histocompatibility complex locus, a genomic segment on 8q11.23 that spans the ST18 gene was also found to be significantly associated with PV. This association was confirmed in the Jewish and Egyptian replication sets but not in the German sample, suggesting that ST18-associated variants may predispose to PV in a population-specific manner. ST18 regulates apoptosis and inflammation, two processes of direct relevance to the pathogenesis of PV. Further supporting the relevance of ST18 to PV, we found this gene to be overexpressed in the skin of PV patients as compared with healthy individuals.

It has long been recognized that generalized deficits in cognitive ability represent a core component of schizophrenia, evident prior to full illness onset and independent of medication. The possibility of genetic overlap between risk for schizophrenia and cognitive phenotypes has been suggested by the presence of cognitive deficits in first-degree relatives of patients with schizophrenia; however, until recently, molecular genetic approaches to test this overlap have been lacking. Within the last few years, large-scale genome-wide association studies (GWAS) of schizophrenia have demonstrated that a substantial proportion of the heritability of the disorder is explained by a polygenic component consisting of many common SNPs of extremely small effect. Similar results have been reported in GWAS of general cognitive ability. The primary aim of the present study is to provide the first molecular genetic test of the classic endophenotype hypothesis, which states that alleles associated with reduced cognitive ability should also serve to increase risk for schizophrenia. We tested the endophenotype hypothesis by applying polygenic SNP scores derived from a large-scale cognitive GWAS meta-analysis (~5000 individuals from 9 non-clinical cohorts comprising the COGENT consortium) to four schizophrenia case-control cohorts. As predicted, cases had significantly lower cognitive polygenic scores compared to controls. In parallel, polygenic risk scores for schizophrenia were associated with lower general cognitive ability. Additionally, using our large cognitive meta-analytic dataset, we identified nominally significant cognitive associations for several SNPs that have previously been robustly associated with schizophrenia susceptibility. Results provide molecular confirmation of the genetic overlap between schizophrenia and general cognitive ability, and may provide additional insight into pathophysiology of the disorder.

Background Relatively small, reproductively isolated populations with reduced genetic diversity may have advantages for genomewide association mapping in disease genetics. The Ashkenazi Jewish population represents a unique population for study based on its recent (< 1,000 year) history of a limited number of founders, population bottlenecks and tradition of marriage within the community. We genotyped more than 1,300 Ashkenazi Jewish healthy volunteers from the Hebrew University Genetic Resource with the Illumina HumanOmni1-Quad platform. Comparison of the genotyping data with that of neighboring European and Asian populations enabled the Ashkenazi Jewish-specific component of the variance to be characterized with respect to disease-relevant alleles and pathways. Results Using clustering, principal components, and pairwise genetic distance as converging approaches, we identified an Ashkenazi Jewish-specific genetic signature that differentiated these subjects from both European and Middle Eastern samples. Most notably, gene ontology analysis of the Ashkenazi Jewish genetic signature revealed an enrichment of genes functioning in transepithelial chloride transport, such as CFTR, and in equilibrioception, potentially shedding light on cystic fibrosis, Usher syndrome and other diseases over-represented in the Ashkenazi Jewish population. Results also impact risk profiles for autoimmune and metabolic disorders in this population. Finally, residual intra-Ashkenazi population structure was minimal, primarily determined by class 1 MHC alleles, and not related to host country of origin. Conclusions The Ashkenazi Jewish population is of potential utility in disease-mapping studies due to its relative homogeneity and distinct genomic signature. Results suggest that Ashkenazi-associated disease genes may be components of population-specific genomic differences in key functional pathways.