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Many medical treatments, from oncology to psychiatry, can lower white blood cell counts and thus access to these treatments can be restricted to individuals with normal levels of white blood cells, principally in order to minimize risk of serious infection. This adversely affects individuals of African or Middle Eastern ancestries who have on average a reduced number of circulating white blood cells, because of the Duffy-null (CC) genotype at rs2814778 in the ACKR1 gene. Here, we investigate whether the Duffy-null genotype is associated with the risk of infection using the UK Biobank sample and the iPSYCH Danish case-cohort study, two population-based samples from different countries and age ranges. We found that a high proportion of those with the Duffy-null genotype (21%) had a neutrophil count below the threshold often used as a cut-off for access to relevant treatments, compared with 1% of those with the TC/TT genotype. In addition we found that despite its strong association with lower average neutrophil counts, the Duffy-null genotype was not associated with an increased risk of infection, viral or bacterial. These results have widespread implications for the clinical treatment of individuals of African ancestry and indicate that neutrophil thresholds to access treatments could be lowered in individuals with the Duffy-null genotype without an increased risk of infection., (© The Author(s) 2020. Published by Oxford University Press.)

Schizophrenia is a debilitating psychiatric disorder with approximately 1% lifetime risk globally. Large-scale schizophrenia genetic studies have reported primarily on European ancestry samples, potentially missing important biological insights. Here, we report the largest study to date of East Asian participants (22,778 schizophrenia cases and 35,362 controls), identifying 21 genome-wide-significant associations in 19 genetic loci. Common genetic variants that confer risk for schizophrenia have highly similar effects between East Asian and European ancestries (genetic correlation = 0.98 ± 0.03), indicating that the genetic basis of schizophrenia and its biology are broadly shared across populations. A fixed-effect meta-analysis including individuals from East Asian and European ancestries identified 208 significant associations in 176 genetic loci (53 novel). Trans-ancestry fine-mapping reduced the sets of candidate causal variants in 44 loci. Polygenic risk scores had reduced performance when transferred across ancestries, highlighting the importance of including sufficient samples of major ancestral groups to ensure their generalizability across populations.

Background: Genetic influences on gene expression in the human fetal brain plausibly impact upon a variety of postnatal brain-related traits, including susceptibility to neuropsychiatric disorders. However, to date, there have been no studies that have mapped genome-wide expression quantitative trait loci (eQTL) specifically in the human prenatal brain., Results: We performed deep RNA sequencing and genome-wide genotyping on a unique collection of 120 human brains from the second trimester of gestation to provide the first eQTL dataset derived exclusively from the human fetal brain. We identify high confidence cis-acting eQTL at the individual transcript as well as whole gene level, including many mapping to a common inversion polymorphism on chromosome 17q21. Fetal brain eQTL are enriched among risk variants for postnatal conditions including attention deficit hyperactivity disorder, schizophrenia, and bipolar disorder. We further identify changes in gene expression within the prenatal brain that potentially mediate risk for neuropsychiatric traits, including increased expression of C4A in association with genetic risk for schizophrenia, increased expression of LRRC57 in association with genetic risk for bipolar disorder, and altered expression of multiple genes within the chromosome 17q21 inversion in association with variants influencing the personality trait of neuroticism., Conclusions: We have mapped eQTL operating in the human fetal brain, providing evidence that these confer risk to certain neuropsychiatric disorders, and identifying gene expression changes that potentially mediate susceptibility to these conditions.

Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide insights. We report a new genome-wide association study of schizophrenia (11,260 cases and 24,542 controls), and through meta-analysis with existing data we identify 50 novel associated loci and 145 loci in total. Through integrating genomic fine-mapping with brain expression and chromosome conformation data, we identify candidate causal genes within 33 loci. We also show for the first time that the common variant association signal is highly enriched among genes that are under strong selective pressures. These findings provide new insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation-intolerant genes and suggest a mechanism by which common risk variants persist in the population.

Studies have suggested that Research Diagnostic Criteria for Schizoaffective Disorder Bipolar type (RDC-SABP) might identify a more genetically homogenous subgroup of bipolar disorder. Aiming to identify loci associated with RDC-SABP, we have performed a replication study using independent RDC-SABP cases (n = 144) and controls (n = 6,559), focusing on the 10 loci that reached a p-value <10 -5 for RDC-SABP in the Wellcome Trust Case Control Consortium (WTCCC) bipolar disorder sample. Combining the WTCCC and replication datasets by meta-analysis (combined RDC-SABP, n = 423, controls, n = 9,494), we observed genome-wide significant association at one SNP, rs2352974, located within the intron of the gene TRAIP on chromosome 3p21.31 (p-value, 4.37 × 10 -8 ). This locus did not reach genome-wide significance in bipolar disorder or schizophrenia large Psychiatric Genomic Consortium datasets, suggesting that it may represent a relatively specific genetic risk for the bipolar subtype of schizoaffective disorder., (© 2017 Wiley Periodicals, Inc.)

Risk of schizophrenia is conferred by alleles occurring across the full spectrum of frequencies from common SNPs of weak effect through to ultra rare alleles, some of which may be moderately to highly penetrant. Previous studies have suggested that some of the risk of schizophrenia is attributable to uncommon alleles represented on Illumina exome arrays. Here, we present the largest study of exomic variation in schizophrenia to date, using samples from the United Kingdom and Sweden (10,011 schizophrenia cases and 13,791 controls). Single variants, genes, and gene sets were analyzed for association with schizophrenia. No single variant or gene reached genome-wide significance. Among candidate gene sets, we found significant enrichment for rare alleles (minor allele frequency [MAF] < 0.001) in genes intolerant of loss-of-function (LoF) variation and in genes whose messenger RNAs bind to fragile X mental retardation protein (FMRP). We further delineate the genetic architecture of schizophrenia by excluding a role for uncommon exomic variants (0.01 ≤ MAF ≥ 0.001) that confer a relatively large effect (odds ratio [OR] > 4). We also show risk alleles within this frequency range exist, but confer smaller effects and should be identified by larger studies., (© 2017 Wiley Periodicals, Inc.)

We identified rare coding variants associated with Alzheimer's disease in a three-stage case-control study of 85,133 subjects. In stage 1, we genotyped 34,174 samples using a whole-exome microarray. In stage 2, we tested associated variants (P < 1 × 10 -4 ) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, we used an additional 14,997 samples to test the most significant stage 2 associations (P < 5 × 10 -8 ) using imputed genotypes. We observed three new genome-wide significant nonsynonymous variants associated with Alzheimer's disease: a protective variant in PLCG2 (rs72824905: p.Pro522Arg, P = 5.38 × 10 -10 , odds ratio (OR) = 0.68, minor allele frequency (MAF) cases = 0.0059, MAF controls = 0.0093), a risk variant in ABI3 (rs616338: p.Ser209Phe, P = 4.56 × 10 -10 , OR = 1.43, MAF cases = 0.011, MAF controls = 0.008), and a new genome-wide significant variant in TREM2 (rs143332484: p.Arg62His, P = 1.55 × 10 -14 , OR = 1.67, MAF cases = 0.0143, MAF controls = 0.0089), a known susceptibility gene for Alzheimer's disease. These protein-altering changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified risk genes in Alzheimer's disease. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to the development of Alzheimer's disease.

Importance: Schizophrenia is a highly heritable, polygenic condition characterized by a relatively diverse phenotype and frequent comorbid conditions, such as anxiety and depression. At present, limited evidence explains how genetic risk for schizophrenia is manifest in the general population., Objective: To investigate the extent to which genetic risk for schizophrenia is associated with different phenotypes during adolescence in a population-based birth cohort., Design, Setting, and Participants: This cohort study used data from the Avon Longitudinal Study of Parents and Children (ALSPAC). Of 14,062 children in the birth cohort, genetic data were available for 9912 adolescents. Data were collected periodically from September 6, 1990, and collection is ongoing. Data were analyzed from March 4 to August 13, 2015., Exposures: Polygenic risk scores (PRSs) for schizophrenia generated for individuals in the ALSPAC cohort using results of the second Psychiatric Genomics Consortium Schizophrenia genome-wide association study as a training set., Main Outcomes and Measures: Logistic regression was used to assess associations between the schizophrenia PRS and (1) psychotic experiences (Psychosis-Like Symptom Interview at 12 and 18 years of age), (2) negative symptoms (Community Assessment of Psychic Experiences at 16.5 years of age), (3) depressive disorder (Development and Well-Being Assessment at 15.5 years of age), and (4) anxiety disorder (Development and Well-Being Assessment at 15.5 years of age) in adolescence., Results: Of the 8230 ALSPAC participants whose genetic data passed quality control checks (51.2% male, 48.8% female), 3676 to 5444 participated in assessments from 12 to 18 years of age. The PRSs created using single-nucleotide polymorphisms with a training-set P ≤ .05 threshold were associated with negative symptoms (odds ratio [OR] per SD increase in PRS, 1.21; 95% CI, 1.08-1.36; R(2) = 0.007) and anxiety disorder (OR per SD increase in PRS, 1.17; 95% CI, 1.06- 1.29; R(2) = 0.005). No evidence was found of an association between schizophrenia PRS and psychotic experiences (OR per SD increase in PRS, 1.08; 95% CI, 0.98-1.19; R(2) = 0.001) or depressive disorder (OR per SD increase in PRS, 1.02; 95% CI, 0.91-1.13; R(2) = 0.00005). Results were mostly consistent across different training-set P value thresholds and using different cutoffs and measures of the psychopathological outcomes., Conclusions and Relevance: This study demonstrates polygenic overlaps between common genetic polymorphisms associated with schizophrenia and negative symptoms and anxiety disorder but not with psychotic experiences or depression. Because the genetic risk for schizophrenia appears to be manifest as anxiety and negative symptoms during adolescence, a greater focus on these phenotypes rather than on psychotic experiences might be required for prediction of transition in at-risk samples., Competing Interests: Disclosures: Dr O'Donovan received a consultancy fee from Roche in July 2015. No other disclosures were reported.

Most genetic studies assume that the function of a genetic variant is independent of the parent from which it is inherited, but this is not always true. The best known example of parent-of-origin effects arises with respect to alleles at imprinted loci. In classical imprinting, characteristically, either the maternal or paternal copy is expressed, but not both. Only alleles present in one of the parental copies of the gene, the expressed copy, is likely to contribute to disease. It has been postulated that imprinting is important in central nervous system development, and that consequently, imprinted loci may be involved in schizophrenia. If this is true, allowing for parent-of-origin effects might be important in genetic studies of schizophrenia. Here, we use genome-wide association data from one of the world's largest samples (N = 695) of parent schizophrenia-offspring trios to test for parent-of-origin effects. To maximise power, we restricted our analyses to test two main hypotheses. If imprinting plays a disproportionate role in schizophrenia susceptibility, we postulated a) that alleles showing robust evidence for association to schizophrenia from previous genome-wide association studies should be enriched for parent-of-origin effects and b) that genes at loci imprinted in humans or mice should be enriched both for genome-wide significant associations, and in our sample, for parent-of-origin effects. Neither prediction was supported in the present study. We have shown, that it is unlikely that parent-of-origin effects or imprinting play particularly important roles in schizophrenia, although our findings do not exclude such effects at specific loci nor do they exclude such effects among rare alleles.

Heritability analyses of genome-wide association study (GWAS) cohorts have yielded important insights into complex disease architecture, and increasing sample sizes hold the promise of further discoveries. Here we analyze the genetic architectures of schizophrenia in 49,806 samples from the PGC and nine complex diseases in 54,734 samples from the GERA cohort. For schizophrenia, we infer an overwhelmingly polygenic disease architecture in which ≥71% of 1-Mb genomic regions harbor ≥1 variant influencing schizophrenia risk. We also observe significant enrichment of heritability in GC-rich regions and in higher-frequency SNPs for both schizophrenia and GERA diseases. In bivariate analyses, we observe significant genetic correlations (ranging from 0.18 to 0.85) for several pairs of GERA diseases; genetic correlations were on average 1.3 tunes stronger than the correlations of overall disease liabilities. To accomplish these analyses, we developed a fast algorithm for multicomponent, multi-trait variance-components analysis that overcomes prior computational barriers that made such analyses intractable at this scale.

Background: A long-standing epidemiological puzzle is the reduced rate of rheumatoid arthritis (RA) in those with schizophrenia (SZ) and vice versa. Traditional epidemiological approaches to determine if this negative association is underpinned by genetic factors would test for reduced rates of one disorder in relatives of the other, but sufficiently powered data sets are difficult to achieve. The genomics era presents an alternative paradigm for investigating the genetic relationship between two uncommon disorders., Methods: We use genome-wide common single nucleotide polymorphism (SNP) data from independently collected SZ and RA case-control cohorts to estimate the SNP correlation between the disorders. We test a genotype X environment (GxE) hypothesis for SZ with environment defined as winter- vs summer-born., Results: We estimate a small but significant negative SNP-genetic correlation between SZ and RA (-0.046, s.e. 0.026, P = 0.036). The negative correlation was stronger for the SNP set attributed to coding or regulatory regions (-0.174, s.e. 0.071, P = 0.0075). Our analyses led us to hypothesize a gene-environment interaction for SZ in the form of immune challenge. We used month of birth as a proxy for environmental immune challenge and estimated the genetic correlation between winter-born and non-winter born SZ to be significantly less than 1 for coding/regulatory region SNPs (0.56, s.e. 0.14, P = 0.00090)., Conclusions: Our results are consistent with epidemiological observations of a negative relationship between SZ and RA reflecting, at least in part, genetic factors. Results of the month of birth analysis are consistent with pleiotropic effects of genetic variants dependent on environmental context.

Objective: Twin studies and genome-wide complex trait analysis (GCTA) are not in agreement regarding heritability estimates for behavioral traits in children from the general population. This has sparked a debate on the possible difference in genetic architecture between behavioral traits and psychiatric disorders. In this study, we test whether polygenic risk scores associated with variation in attention-deficit/hyperactivity disorder (ADHD) trait levels in children from the general population predict ADHD diagnostic status and severity in an independent clinical sample., Method: Single nucleotide polymorphisms (SNPs) with p < .5 from a genome-wide association study of ADHD traits in 4,546 children (mean age, 7 years 7 months) from the Avon Longitudinal Study of Parents and Children (ALSPAC; general population sample) were selected to calculate polygenic risk scores in 508 children with an ADHD diagnosis (independent clinical sample) and 5,081 control participants. Polygenic scores were tested for association with case-control status and severity of disorder in the clinical sample., Results: Increased polygenic score for ADHD traits predicted ADHD case-control status (odds ratio = 1.17 [95% CI = 1.08-1.28], p = .0003), higher ADHD symptom severity (β = 0.29 [95% CI = 0.04-0.54], p = 0.02), and symptom domain severity in the clinical sample., Conclusion: This study highlights the relevance of additive genetic variance in ADHD, and provides evidence that shared genetic factors contribute to both behavioral traits in the general population and psychiatric disorders at least in the case of ADHD., (Copyright © 2015 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

Recent results indicate that genome-wide association studies (GWAS) have the potential to explain much of the heritability of common complex phenotypes, but methods are lacking to reliably identify the remaining associated single nucleotide polymorphisms (SNPs). We applied stratified False Discovery Rate (sFDR) methods to leverage genic enrichment in GWAS summary statistics data to uncover new loci likely to replicate in independent samples. Specifically, we use linkage disequilibrium-weighted annotations for each SNP in combination with nominal p-values to estimate the True Discovery Rate (TDR = 1-FDR) for strata determined by different genic categories. We show a consistent pattern of enrichment of polygenic effects in specific annotation categories across diverse phenotypes, with the greatest enrichment for SNPs tagging regulatory and coding genic elements, little enrichment in introns, and negative enrichment for intergenic SNPs. Stratified enrichment directly leads to increased TDR for a given p-value, mirrored by increased replication rates in independent samples. We show this in independent Crohn's disease GWAS, where we find a hundredfold variation in replication rate across genic categories. Applying a well-established sFDR methodology we demonstrate the utility of stratification for improving power of GWAS in complex phenotypes, with increased rejection rates from 20% in height to 300% in schizophrenia with traditional FDR and sFDR both fixed at 0.05. Our analyses demonstrate an inherent stratification among GWAS SNPs with important conceptual implications that can be leveraged by statistical methods to improve the discovery of loci., Competing Interests: The authors have declared that no competing interests exist.

Several lines of evidence suggest that genome-wide association studies (GWASs) have the potential to explain more of the "missing heritability" of common complex phenotypes. However, reliable methods for identifying a larger proportion of SNPs are currently lacking. Here, we present a genetic-pleiotropy-informed method for improving gene discovery with the use of GWAS summary-statistics data. We applied this methodology to identify additional loci associated with schizophrenia (SCZ), a highly heritable disorder with significant missing heritability. Epidemiological and clinical studies suggest comorbidity between SCZ and cardiovascular-disease (CVD) risk factors, including systolic blood pressure, triglycerides, low- and high-density lipoprotein, body mass index, waist-to-hip ratio, and type 2 diabetes. Using stratified quantile-quantile plots, we show enrichment of SNPs associated with SCZ as a function of the association with several CVD risk factors and a corresponding reduction in false discovery rate (FDR). We validate this "pleiotropic enrichment" by demonstrating increased replication rate across independent SCZ substudies. Applying the stratified FDR method, we identified 25 loci associated with SCZ at a conditional FDR level of 0.01. Of these, ten loci are associated with both SCZ and CVD risk factors, mainly triglycerides and low- and high-density lipoproteins but also waist-to-hip ratio, systolic blood pressure, and body mass index. Together, these findings suggest the feasibility of using genetic-pleiotropy-informed methods for improving gene discovery in SCZ and identifying potential mechanistic relationships with various CVD risk factors., (Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Although the association of common genetic variation in the extended MHC region with schizophrenia is the most significant yet discovered, the MHC region is one of the more complex regions of the human genome, with unusually high gene density and long-range linkage disequilibrium. The statistical test on which the MHC association is based is a relatively simple, additive model which uses logistic regression of SNP genotypes to predict case-control status. However, it is plausible that more complex models underlie this association. Using a well-characterized sample of trios, we evaluated more complex models by looking for evidence for: (a) non-random mating for HLA alleles, schizophrenia risk profiles, and ancestry; (b) parent-of-origin effects for HLA alleles; and (c) maternal-fetal genotype incompatibility in the HLA. We found no evidence for non-random mating in the parents of individuals with schizophrenia in terms of MHC genotypes or schizophrenia risk profile scores. However, there was evidence of non-random mating that appeared mostly to be driven by ancestry. We did not detect over-transmission of HLA alleles to affected offspring via the general TDT test (without regard to parent of origin) or preferential transmission via paternal or maternal inheritance. We evaluated the hypothesis that maternal-fetal HLA incompatibility may increase risk for schizophrenia using eight classical HLA loci. The most significant alleles were in HLA-B, HLA-C, HLA-DQB1, and HLA-DRB1 but none was significant after accounting for multiple comparisons. We did not find evidence to support more complex models of gene action, but statistical power may have been limiting., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Additional information about risk genes or risk pathways for diseases can be extracted from genome-wide association studies through analyses of groups of markers. The most commonly employed approaches involve combining individual marker data by adding the test statistics, or summing the logarithms of their P-values, and then using permutation testing to derive empirical P-values that allow for the statistical dependence of single-marker tests arising from linkage disequilibrium (LD). In the present study, we use simulated data to show that these approaches fail to reflect the structure of the sampling error, and the effect of this is to give undue weight to correlated markers. We show that the results obtained are internally inconsistent in the presence of strong LD, and are externally inconsistent with the results derived from multi-locus analysis. We also show that the results obtained from regression and multivariate Hotelling T(2) (H-T2) testing, but not those obtained from permutations, are consistent with the theoretically expected distributions, and that the H-T2 test has greater power to detect gene-wide associations in real datasets. Finally, we show that while the results from permutation testing can be made to approximate those from regression and multivariate Hotelling T(2) testing through aggressive LD pruning of markers, this comes at the cost of loss of information. We conclude that when conducting multi-locus analyses of sets of single-nucleotide polymorphisms, regression or multivariate Hotelling T(2) testing, which give equivalent results, are preferable to the other more commonly applied approaches.

Objective: A major motivation for seeking disease-associated genetic variation is to identify novel risk processes. Although rare copy number variants (CNVs) appear to contribute to attention deficit hyperactivity disorder (ADHD), common risk variants (single-nucleotide polymorphisms [SNPs]) have not yet been detected using genome-wide association studies (GWAS). This raises the concern as to whether future larger-scale, adequately powered GWAS will be worthwhile. The authors undertook a GWAS of ADHD and examined whether associated SNPs, including those below conventional levels of significance, influenced the same biological pathways affected by CNVs., Method: The authors analyzed genome-wide SNP frequencies in 727 children with ADHD and 5,081 comparison subjects. The gene sets that were enriched in a pathway analysis of the GWAS data (the top 5% of SNPs) were tested for an excess of genes spanned by large, rare CNVs in the children with ADHD., Results: No SNP achieved genome-wide significance levels. As previously reported in a subsample of the present study, large, rare CNVs were significantly more common in case subjects than comparison subjects. Thirteen biological pathways enriched for SNP association significantly overlapped with those enriched for rare CNVs. These included cholesterol-related and CNS development pathways. At the level of individual genes, CHRNA7, which encodes a nicotinic receptor subunit previously implicated in neuropsychiatric disorders, was affected by six large duplications in case subjects (none in comparison subjects), and SNPs in the gene had a gene-wide p value of 0.0002 for association in the GWAS., Conclusions: Both common and rare genetic variants appear to be relevant to ADHD and index-shared biological pathways.

Rare mutations in AβPP, PSEN1, and PSEN2 cause uncommon early onset forms of Alzheimer's disease (AD), and common variants in MAPT are associated with risk of other neurodegenerative disorders. We sought to establish whether common genetic variation in these genes confer risk to the common form of AD which occurs later in life (>65 years). We therefore tested single-nucleotide polymorphisms at these loci for association with late-onset AD (LOAD) in a large case-control sample consisting of 3,940 cases and 13,373 controls. Single-marker analysis did not identify any variants that reached genome-wide significance, a result which is supported by other recent genome-wide association studies. However, we did observe a significant association at the MAPT locus using a gene-wide approach (p = 0.009). We also observed suggestive association between AD and the marker rs9468, which defines the H1 haplotype, an extended haplotype that spans the MAPT gene and has previously been implicated in other neurodegenerative disorders including Parkinson's disease, progressive supranuclear palsy, and corticobasal degeneration. In summary common variants at AβPP, PSEN1, and PSEN2 and MAPT are unlikely to make strong contributions to susceptibility for LOAD. However, the gene-wide effect observed at MAPT indicates a possible contribution to disease risk which requires further study.

Large collaborative Genome-wide Association studies of schizophrenia have identified genes and genomic regions that are associated with the disorder at highly stringent levels of statistical significance. Among these, transcription factor 4 (TCF4) is one of the best supported although the associated SNP (rs9960767) is located within intron 3 and has no obvious function. Seeking the mechanism at TCF responsible for the association, we examined TCF4 for coding variants, and for cis regulated variation in TCF4 gene expression correlated with the associated SNP using an assay to detect differential allelic expression. Using data from the 1000 genomes project, we were unable to identify any nonsynonymous coding variants at the locus. Allele specific expression analysis using human post mortem brain samples revealed no evidence for cis-regulated mRNA expression related to genotype at the schizophrenia associated SNP. We conclude that association between schizophrenia and TCF4 is not mediated by a relatively common non-synonymous variant, or by a variant that alters mRNA expression as measured in adult human brain. It remains possible that the risk allele at this locus exerts effects on expression exclusively in a developmental context, in cell types or brain regions not adequately represented in our analysis, or through post-transcriptional effects, for example in the abundance of the protein or its sub-cellular distribution., (Copyright © 2011 Wiley-Liss, Inc.)

We describe implementation of a set-based method to assess the significance of findings from genomewide association study data. Our method, implemented in PLINK, is based on theoretical approximation of Fisher's statistics such that the combination of P-vales at a gene or across a pathway is carried out in a manner that accounts for the correlation structure, or linkage disequilibrium, between single nucleotide polymorphisms. We compare our method to a permutation-based product of P-values approach and show a typical correlation in excess of 0.98 for a number of comparisons. The method gives Type I error rates that are less than or equal to the corresponding nominal significance levels, making it robust to the effects of false positives. We show that in broadly similar populations, reference data sets of markers are an appropriate substrate for deriving marker-marker linkage disequilibrium (LD), negating the need to access individual level genotypes, greatly facilitating its generic applicability. We show that the method is thus robust to LD-associated bias and has equivalent performance to permutation-based methods, with a significantly shorter runtime. This is particularly relevant at a time of increasing public availability of significantly larger genetic data sets and should go a long way to assist in the rapid analysis of these data sets., (© 2011 Wiley Periodicals, Inc.)

Common sequence variants have recently joined rare structural polymorphisms as genetic factors with strong evidence for association with schizophrenia. Here we extend our previous genome-wide association study and meta-analysis (totalling 7 946 cases and 19 036 controls) by examining an expanded set of variants using an enlarged follow-up sample (up to 10 260 cases and 23 500 controls). In addition to previously reported alleles in the major histocompatibility complex region, near neurogranin (NRGN) and in an intron of transcription factor 4 (TCF4), we find two novel variants showing genome-wide significant association: rs2312147[C], upstream of vaccinia-related kinase 2 (VRK2) [odds ratio (OR) = 1.09, P = 1.9 × 10(-9)] and rs4309482[A], between coiled-coiled domain containing 68 (CCDC68) and TCF4, about 400 kb from the previously described risk allele, but not accounted for by its association (OR = 1.09, P = 7.8 × 10(-9)).

Background: Given that genome-wide association studies (GWAS) of psychiatric disorders have identified only a small number of convincingly associated variants (single nucleotide polymorphism [SNP]), there is interest in seeking additional evidence for associated variants with tests of gene-gene interaction. Comprehensive pair-wise single SNP-SNP interaction analysis is computationally intensive, and the penalty for multiple testing is severe, given the number of interactions possible. Aiming to minimize these statistical and computational burdens, we have explored approaches to prioritize SNPs for interaction analyses., Methods: Primary interaction analyses were performed with the Wellcome Trust Case-Control Consortium bipolar disorder GWAS (1868 cases, 2938 control subjects). Replication analyses were performed with the Genetic Association Information Network bipolar disorder dataset (1001 cases, 1033 control subjects). The SNPs were prioritized for interaction analysis that showed evidence for association that surpassed a number of nominally significant thresholds, are within genome-wide significant genes, or are within genes that are functionally related., Results: For no set of prioritized SNPs did we obtain evidence to support the hypothesis that the selection strategy identified pairs of variants that were enriched for true (statistical) interactions., Conclusions: The SNPs prioritized according to a number of criteria do not have a raised prior probability for significant interaction that is detectable in samples of this size. We argue that the use of significance levels reflecting only the number of tests performed, as is now widely accepted for single SNP analysis, does not offer an appropriate degree of protection against the potential for GWAS studies to generate an enormous number of false positive interactions., (Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Variations in the signalling NRG1-ErbB4 pathway have been associated with genetic susceptibility for both bipolar disorder and schizophrenia, although the underlying neural mechanisms are still uncertain. Reduced integrity of the anterior limb of the internal capsule (ALIC) has been found in association with risk-associated genetic variation in the 5' region of the NRG1 gene. We hypothesised that variation in the gene encoding the NRG1 receptor, ErbB4, would also be associated with reduced ALIC integrity and with cognitive impairments characteristic of individuals with bipolar disorder and schizophrenia. Using diffusion tensor imaging (DTI), we examined the white matter integrity associations of the ErbB4 polymorphism rs4673628, which resides within intron 12 of the gene encoding ErbB4, in 36 healthy individuals. We also sought to clarify the cognitive effects of any findings. We found that genetic variation at the rs4673628 locus in the ErbB4 gene was significantly associated with ALIC white matter integrity which was also significantly and positively associated with mnemonic function. These findings provide further evidence to support a key role of NRG1-ErbB4 signalling in the pathophysiology of major mental disorders., (Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.)

The MAPT H1c haplotype is a risk factor for the neurodegenerative tauopathies progressive supranuclear palsy (PSP) and Alzheimer's disease. We hypothesise that the effect of the H1c haplotype relates to an increase in MAPT expression leading to an increase in tau neurofibrillary tangle deposition. We have evaluated the effect of the MAPT H1c haplotype on the expression of MAPT using allele specific expression, comparing the relative levels of MAPT H1 and H2 RNA derived from post-mortem human brain, unaffected by neurodegenerative disease. Using three assays spanning the MAPT gene we did not detect any effect of H1c on MAPT expression as compared with other haplotypes. We did, however, detect an effect of age on expression of MAPT H1 with a relative decrease in MAPT H1 expression with increased age. Our data suggest that there is an interaction between age and the expression of MAPT.

Context: Human and animal studies have implicated the gene NOS1 in both cognition and schizophrenia susceptibility., Objective: To investigate whether a potential schizophrenia risk single-nucleotide polymorphism (rs6490121) identified in a recent genome-wide association study negatively influences cognition in patients with schizophrenia and healthy control subjects., Design: A comparison of both cases and controls grouped according to NOS1 genotype (GG vs AG vs AA) on selected measures of cognition in 2 independent samples. We tested for association between NOS1 rs6490121 and cognitive functions known to be impaired in schizophrenia (IQ, episodic memory, working memory, and attentional control) in an Irish sample. We then sought to replicate the significant results in a German sample., Setting: Unrelated patients from general adult psychiatric inpatient and outpatient services and unrelated healthy volunteers from the general population were ascertained., Participants: Patients with DSM-IV-diagnosed schizophrenia and healthy control subjects from independent samples of Irish (cases, n = 349; controls, n = 230) and German (cases, n = 232; controls, n = 1344) nationality., Results: A main effect of NOS1 genotype on verbal IQ and working memory was observed in the Irish sample where the homozygous carriers of the schizophrenia risk G allele performed poorly compared with the other genotype groups. These findings were replicated in the German sample, again with the GG genotype carriers performing below other genotype groups. Post hoc analysis of additional IQ measures (full-scale and performance IQ) in the German sample revealed that NOS1 GG carriers underperformed on these measures also., Conclusions: NOS1 is associated with clinically significant variation in cognition. Whether this is a mechanism by which schizophrenia risk is increased (eg, via an influence on cognitive reserve) is yet to be confirmed.

We undertook a two-stage genome-wide association study (GWAS) of Alzheimer's disease (AD) involving over 16,000 individuals, the most powerful AD GWAS to date. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the apolipoprotein E (APOE) locus (most significant SNP, rs2075650, P = 1.8 x 10(-157)) and observed genome-wide significant association with SNPs at two loci not previously associated with the disease: at the CLU (also known as APOJ) gene (rs11136000, P = 1.4 x 10(-9)) and 5' to the PICALM gene (rs3851179, P = 1.9 x 10(-8)). These associations were replicated in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with Alzheimer's disease in the combined dataset (rs11136000, P = 8.5 x 10(-10), odds ratio = 0.86; rs3851179, P = 1.3 x 10(-9), odds ratio = 0.86).

Background: Bipolar affective disorder (BAD) is a psychiatric illness characterized by episodes of mania and depression. Although the etiology is not clear, epidemiological studies suggest it is a result of an interaction of genetic and environmental factors. Despite of enormous efforts and abundant studies conducted, none has yet been identified definitively a gene susceptible to bipolar disorder., Methods: Ninety-four Bulgarian patients diagnosed with bipolar disorder and 184 Bulgarian healthy individuals, were used for genotyping of 191 single nucleotide polymorphisms (SNPs) by TaqMan and/or Invader assays. Seventeen SNPs that revealed P value less than 0.05 in the first screening were genotyped using an additional independent set of samples, consisting of 78 BAD cases and 372 controls., Results: After applying the Bonferonni correction on genotyping results of 172 cases and 556 controls, only one SNP, rs1800883, in the HTR5A gene revealed a significant level of P value (P=0.000097; odds ratio=1.80 (95%CI, 1.27-2.54); corrected P=0.017)., Conclusions: Our findings suggest that HTR5A gene could play an important role in the pathogenesis of bipolar disorder in our population. However these findings should be viewed with caution and replication studies in other populations are necessary in support of these findings.

The development of molecular psychiatry in the last few decades identified a number of candidate genes that could be associated with schizophrenia. A great number of studies often result with controversial and non-conclusive outputs. However, it was determined that each of the implicated candidates would independently have a minor effect on the susceptibility to that disease. Herein we report results from our replication study for association using 255 Bulgarian patients with schizophrenia and schizoaffective disorder and 556 Bulgarian healthy controls. We have selected from the literatures 202 single nucleotide polymorphisms (SNPs) in 59 candidate genes, which previously were implicated in disease susceptibility, and we have genotyped them. Of the 183 SNPs successfully genotyped, only 1 SNP, rs6277 (C957T) in the DRD2 gene (P=0.0010, odds ratio=1.76), was considered to be significantly associated with schizophrenia after the replication study using independent sample sets. Our findings support one of the most widely considered hypotheses for schizophrenia etiology, the dopaminergic hypothesis.

A recent study reported significant association of late-onset Alzheimer's disease (LOAD) with multiple single nucleotide polymorphisms (SNPs) and haplotypes in SORL1, a neuronal sortilin-related receptor protein known to be involved in the trafficking and processing of amyloid precursor protein. Here we attempted to validate this finding in three large, well characterized case-control series. Approximately 2000 samples from the three series were individually genotyped for 12 SNPs, including the 10 reported significant SNPs and 2 that constitute the reported significant haplotypes. A total of 25 allelic and haplotypic association tests were performed. One SNP rs2070045 was marginally replicated in the three sample sets combined (nominal P=0.035); however, this result does not remain significant when accounting for multiple comparisons. Further validation in other sample sets will be required to assess the true effects of SORL1 variants in LOAD.

We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases.

This study sets out to identify novel susceptibility genes for late-onset Alzheimer's disease (LOAD) in a powerful set of samples from the UK and USA (1808 LOAD cases and 2062 controls). Allele frequencies of 17 343 gene-based putative functional single nucleotide polymorphisms (SNPs) were tested for association with LOAD in a discovery case-control sample from the UK. A tiered strategy was used to follow-up significant variants from the discovery sample in four independent sample sets. Here, we report the identification of several candidate SNPs that show significant association with LOAD. Three of the identified markers are located on chromosome 19 (meta-analysis: full sample P = 6.94E - 81 to 0.0001), close to the APOE gene and exhibit linkage disequilibrium (LD) with the APOEepsilon4 and epsilon2/3 variants (0.09 < D'<1). Two of the three SNPs can be regarded as study-wide significant (expected number of false positives reaching the observed significance level less than 0.05 per study). Sixteen additional SNPs show evidence for association with LOAD [P = 0.0010-0.00006; odds ratio (OR) = 1.07-1.45], several of which map to known linkage regions, biological candidate genes and novel genes. Four SNPs not in LD with APOE show a false positive rate of less than 2 per study, one of which shows study-wide suggestive evidence taking account of 17 343 tests. This is a missense mutation in the galanin-like peptide precursor gene (P = 0.00005, OR = 1.2, false positive rate = 0.87).

There is evidence to suggest a role for immune dysfunction in the pathogenesis of Alzheimer's disease, and it has previously been shown that blood plasma levels of the protein complement factor H, a member of the alternative complement pathway, was specifically elevated in people with late-onset Alzheimer's disease. We have genotyped the common complement factor H Y402H polymorphism in a large case-control cohort to investigate association with late-onset Alzheimer's disease susceptibility and find no evidence that this SNP is associated with disease risk. However, it remains possible that another variant in this gene may modify susceptibility for late-onset Alzheimer's disease.

Background: Genotyping technology has advanced such that genome-wide association studies of complex diseases based upon dense marker maps are now technically feasible. However, the cost of such projects remains high. Pooled DNA genotyping offers the possibility of applying the same technologies at a fraction of the cost, and there is some evidence that certain ultra-high throughput platforms also perform with an acceptable accuracy. However, thus far, this conclusion is based upon published data concerning only a small number of SNPs., Results: In the current study we prepared DNA pools from the parents and from the offspring of 30 parent-child trios that have been extensively genotyped by the HapMap project. We analysed the two pools with Affymetrix 10 K Xba 142 2.0 Arrays. The availability of the HapMap data allowed us to validate the performance of 6843 SNPs for which we had both complete individual and pooled genotyping data. Pooled analyses averaged over 5-6 microarrays resulted in highly reproducible results. Moreover, the accuracy of estimating differences in allele frequency between pools using this ultra-high throughput system was comparable with previous reports of pooling based upon lower throughput platforms, with an average error for the predicted allelic frequencies differences between the two pools of 1.37% and with 95% of SNPs showing an error of < 3.2%., Conclusion: Genotyping thousands of SNPs with DNA pooling using Affymetrix microarrays produces highly accurate results and can be used for genome-wide association studies.

Background: Alzheimer's disease (AD) is a devastating neurodegeneration with a characteristic deficit in cholinergic neurotransmission. Treatment with acetylcholinesterase (AChE) inhibitors aims to reverse this deficit and does ameliorate the decline in cognition in some AD patients, although response is variable., Objective: To examine whether sequence variation in the gene encoding choline acetyltransferase (CHAT), which encodes the major catalytic enzyme of the cholinergic pathway, predicts response to AChE inhibitors., Methods: Alzheimer's disease patients (121) were treated with cholinesterase inhibitors and the effect of treatment on cognition was measured using the Mini Mental State Examination (MMSE). Six polymorphisms in CHAT were analysed for association with change in MMSE score., Results: After correction for multiple testing, we found one SNP, rs733722, in a promoter region of CHAT, is associated with response of AD patients to cholinesterase inhibitors (P = 0.03) and accounts for 6% of the variance in response to AChE inhibitors., Conclusion: Rs733722 represents a putative marker of response to AChE inhibitors in AD patients.

DNA sequence features were sought that could be used for the in silico ascertainment of the likely functional consequences of single nucleotide changes in human gene promoter regions. To identify relevant features of the local DNA sequence context, we transformed into consensus tables the nucleotide composition of sequences flanking 101 promoter SNPs of type C<-->T or A<-->G, defined empirically as being either 'functional' or 'non-functional' on the basis of a standardised reporter gene assay. The similarity of a given sequence to these consensus tables was then measured by means of the Shapiro-Senapathy score. A decision rule with the potential to discriminate between empirically ascertained functional and non-functional SNPs was proposed that potentiated discrimination between functional and non-functional SNPs with a sensitivity of 80% and a specificity of 20%. Two further datasets (viz. disease-associated SNPs of types A<-->G and C<-->T (N = 75) and pathological promoter mutations (transitions, N = 114)) were retrieved from the Human Gene Mutation Database (HGMD; http://www.hgmd.org/) and analyzed using consensus tables derived from the functional and non-functional promoter SNPs; approximately 70% were correctly recognized as being of probable functional significance. Complexity analysis was also used to quantify the regularity of the local DNA sequence environment. Functional SNPs/mutations of type C<-->T were found to occur in DNA regions characterized by lower average sequence complexity as measured with respect to symmetric elements; complexity values increased gradually from functional SNPs and pathological mutations to functional disease-associated SNPs and non-functional SNPs. This may reflect the internal axial symmetry that frequently characterizes transcription factor binding sites.

Linkage studies have suggested there is a susceptibility gene for late onset Alzheimer's disease (LOAD) in a broad region of chromosome 10. A strong positional and biological candidate is the gene encoding the insulin-degrading enzyme (IDE), a protease involved in the catabolism of Abeta. However, previous association studies have produced inconsistent results. To systematically evaluate the role of variation in IDE in the risk for LOAD, we genotyped 18 SNPs spanning a 276 kb region in and around IDE, including three "tagging" SNPs identified in an earlier study. We used four case-control series with a total of 1,217 cases and 1,257 controls. One SNP (IDE&#95;7) showed association in two samples (P-value = 0.0066, and P = 0.026, respectively), but this result was not replicated in the other two series. None of the other SNPs showed association with LOAD in any of the tested samples. Haplotypes, constructed from the three tagging SNPs, showed no globally significant association. In the UK2 series, the CTA haplotype was over-represented in cases (P = 0.046), and in the combined data set, the CCG haplotype was more frequent in controls (P = 0.015). However, these weak associations observed in our series were in the opposite direction to the results in previous studies. Although our results are not universally negative, we were unable to replicate the results of previous studies and conclude that common variants or haplotypes of these variants in IDE are not major risk factors for LOAD., (Copyright 2005 Wiley-Liss, Inc.)

Background: It has been recently reported that a functional variant in the ZDHHC8 gene encoding a putative palmitoyltransferase directly confers susceptibility to schizophrenia in females ()., Methods: We investigated the putative risk allele (rs175174) in four schizophrenia association samples including a Bulgarian proband and parent sample (474 trios) and three case-control panels of European origin (1028 patients/1253 control subjects) in an attempt to replicate these findings., Results: Our results do not support the hypothesis that genetic variation at rs175174 is associated with increased risk for schizophrenia nor do they suggest the presence of gender-specific differences., Conclusions: Our data suggest that the reported genetic association by either represents type I error resulting from sampling variance or that rs175174 is in linkage disequilibrium (LD) with the functional variant for schizophrenia and different LD patterns obscure the detection of association.

Background: Three studies have previously reported data that were interpreted by the authors as supportive of association between schizophrenia and polymorphisms in the gene encoding the metabotropic glutamate receptor GRM3., Methods: In a bid to examine this hypothesis, we examined seven SNPs spanning GRM3 in a UK case-control sample (schizophrenic cases n = 674, controls n = 716). These included all SNPs previously reported to be associated, alone or in haplotypes, with schizophrenia in European or European American samples., Results: Our data showed no evidence for association with single markers, or 2, 3, 4 and 5 marker haplotypes, nor did any specific haplotypes show evidence for association according to previously observed patterns., Conclusion: Examination of our own data and those of other groups leads us to conclude that at present, GRM3 should not be viewed as a gene for which there is replicated evidence for association with schizophrenia.

Several groups have developed methods for estimating allele frequencies in DNA pools as a fast and cheap way for detecting allelic association between genetic markers and disease. To obtain accurate estimates of allele frequencies, a correction factor k for the degree to which measurement of allele-specific products is biased is generally applied. Factor k is usually obtained as the ratio of the two allele-specific signals in samples from heterozygous individuals, a step that can significantly impair throughput and increase cost. We have systematically investigated the properties of k through the use of empirical and simulated data. We show that for the dye terminator primer extension genotyping method we have applied, the correction factor k is substantially influenced by the dye terminators incorporated, but also by the terminal 3' base of the extension primer. We also show that the variation in k is large enough to result in unacceptable error rates if association studies are conducted without regard to k. We show that the impact of ignoring k can be neutralized by applying a correction factor k(max) that can be easily derived, but this at the potential cost of an increase in type I error. Finally, based upon observed distributions for k we derive a method allowing the estimation of the probability pooled data reflects significant differences in the allele frequencies between the subjects comprising the pools. By controlling the error rates in the absence of knowledge of the appropriate SNP-specific correction factors, each approach enhances the performance of DNA pooling, while considerably streamlining the method by reducing time and cost., ((c) 2005 Wiley-Liss, Inc.)

Background: Several studies support the dysbindin (dystrobrevin binding protein 1) gene (DTNBP1) as a susceptibility gene for schizophrenia. We previously reported that variation at a specific 3-locus haplotype influences susceptibility to schizophrenia in a large United Kingdom (UK) Caucasian case-control sample., Methods: Using similar methodology to our schizophrenia study, we have investigated this same 3-locus haplotype in a large, well-characterized bipolar sample (726 Caucasian UK DSM-IV bipolar I patients; 1407 ethnically matched controls)., Results: No significant differences were found in the distribution of the 3-locus haplotype in the full sample. Within the subset of bipolar I cases with predominantly psychotic episodes of mood disturbance (n = 133) we found nominally significant support for association at this haploptype (p < .042) and at SNP rs2619538 (p = .003), with a pattern of findings similar to that in our schizophrenia sample. This finding was not significant after correction for multiple testing., Conclusions: Our data suggest that variation at the polymorphisms examined does not make a major contribution to susceptibility to bipolar disorder in general. They are consistent with the possibility that DTNBP1 influences susceptibility to a subset of bipolar disorder cases with psychosis. However, our subset sample is small and the hypothesis requires testing in independent, adequately powered samples.

Alzheimer disease (AD) is a complex neurodegenerative disorder predisposed by multiple genetic factors. Mutations in amyloid beta precursor protein (APP) are known to be associated with autosomal dominant, early onset familial AD and possibly also late onset AD (LOAD). A number of genes encoding proteins capable of binding to APP have been identified, but their contribution to AD pathobiology remains unclear. Conceivably, mutations in these genes may play a role in affecting AD susceptibility, which appears to be substantiated by some genetic studies. Here we report results of the first genetic association study with APBB2, an APP binding protein (also known as FE65L), and LOAD, in three independently collected case-control series totaling approximately 2,000 samples. Two SNPs were significantly associated with LOAD in two sample series and in meta-analyses of all three sample sets (for rs13133980: odds ratio [OR](hom)=1.36 [95% CI: 1.05-1.75], OR(het)=1.32 [95% CI: 1.04-1.67], minor allele frequency=43%, P=0.041; and for hCV1558625: OR(hom)=1.37 [95% CI: 1.06-1.77], OR(het)=1.02 [95% CI: 0.82-1.26], minor allele frequency=48%, P=0.026). One of these SNPs, located in a region conserved between the human and mouse genome, showed a significant interaction with age of disease onset. For this marker, the association with LOAD was most pronounced in subjects with disease onset before 75 years of age (OR(hom)=2.43 [95% CI: 1.61-3.67]; OR(het)=2.15 [95% CI: 1.46-3.17]; P=0.00006) in the combined sample set. Our data raise the possibility that genetic variations in APBB2 may affect LOAD susceptibility.

There is substantial evidence for a susceptibility gene for late-onset Alzheimer's disease (AD) on chromosome 10. One of the characteristic features of AD is the degeneration and dysfunction of the cholinergic system. The genes encoding choline acetyltransferase (ChAT) and its vesicular transporter (VAChT), CHAT and SLC18A3 respectively, map to the linked region of chromosome 10 and are therefore both positional and obvious functional candidate genes for late-onset AD. We have screened both genes for sequence variants and investigated each for association with late-onset AD in up to 500 late-onset AD cases and 500 control DNAs collected in the UK. We detected a total of 17 sequence variants. Of these, 14 were in CHAT, comprising three non-synonymous variants (D7N in the S exon, A120T in exon 5 and L243F in exon 8), one synonymous change (H547H), nine single-nucleotide polymorphisms in intronic, untranslated or promoter regions, and a variable number of tandem repeats in intron 7. Three non-coding SNPs were detected in SLC18A3. None demonstrated any reproducible association with late-onset AD in our samples. Levels of linkage disequilibrium were generally low across the CHAT locus but two of the coding variants, D7N and A120T, proved to be in complete linkage disequilibrium.

DNA pooling is a practical way to reduce the cost of large-scale association studies to identify susceptibility loci for common diseases. Pooling allows allele frequencies in groups of individuals to be measured using far fewer PCR reactions and genotyping assays than are used when genotyping individuals. Here, we discuss recent developments in quantitative genotyping assays and in the design and analysis of pooling studies. Sophisticated pooling designs are being developed that can take account of hidden population stratification, confounders and inter-loci interactions, and that allow the analysis of haplotypes.

Detecting alleles that confer small increments in susceptibility to disease will require large-scale allelic association studies of single-nucleotide polymorphisms (SNPs) in candidate, or positional candidate, genes. However, current genotyping technologies are one to two orders of magnitude too expensive to permit the analysis of thousands of SNPs in large samples. We have developed and thoroughly validated a highly accurate protocol for SNP allele frequency estimation in DNA pools based upon the SNaPshot (Applied Biosystems) chemistry adaptation of primer extension. Using this assay, we were able to estimate the difference in allele frequencies between pooled cases and controls (Delta) with a mean error of 0.01. Moreover, when we genotyped seven different SNPs in a single multiplex reaction, the results were similar, with a mean error for Delta of 0.008. The assay performed well for alleles of low frequency alleles (f approximately 0.05) and was accurate even with relatively poor quality DNA template extracted from mouthwashes. Our assay conditions are generalisable, universal, robust and, therefore, for the first time, permit high-throughput association analysis at a realistic cost.