Author
Nicholas Walker
Bio: Nicholas Walker is an academic researcher from Aberdeen Royal Infirmary. The author has contributed to research in topics: Population & Single-nucleotide polymorphism. The author has an hindex of 13, co-authored 13 publications receiving 10519 citations.
Papers
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Broad Institute1, Harvard University2, QIMR Berghofer Medical Research Institute3, Cardiff University4, North Carolina State University5, Trinity College, Dublin6, University of Edinburgh7, Uppsala University8, Karolinska Institutet9, University of Southern California10, University of North Carolina at Chapel Hill11, University College London12, National Health Service13, University of Oxford14, University of Aberdeen15, Strathclyde Institute of Pharmacy and Biomedical Sciences16, State University of New York Upstate Medical University17, University of Coimbra18
TL;DR: The extent to which common genetic variation underlies the risk of schizophrenia is shown, using two analytic approaches, and the major histocompatibility complex is implicate, which is shown to involve thousands of common alleles of very small effect.
Abstract: Schizophrenia is a severe mental disorder with a lifetime risk of about 1%, characterized by hallucinations, delusions and cognitive deficits, with heritability estimated at up to 80%(1,2). We performed a genome-wide association study of 3,322 European individuals with schizophrenia and 3,587 controls. Here we show, using two analytic approaches, the extent to which common genetic variation underlies the risk of schizophrenia. First, we implicate the major histocompatibility complex. Second, we provide molecular genetic evidence for a substantial polygenic component to the risk of schizophrenia involving thousands of common alleles of very small effect. We show that this component also contributes to the risk of bipolar disorder, but not to several non-psychiatric diseases.
4,573 citations
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deCODE genetics1, Ludwig Maximilian University of Munich2, University of Bonn3, Utrecht University4, Copenhagen University Hospital5, University of Copenhagen6, GlaxoSmithKline7, Hammersmith Hospital8, Duke University9, Royal Cornhill Hospital10, King's College London11, University of Verona12, Sichuan University13, University of Oslo14, Glostrup Hospital15, Radboud University Nijmegen Medical Centre16, University of California, Los Angeles17, Heidelberg University18, Broad Institute19, Wellcome Trust Sanger Institute20, University of Iceland21
TL;DR: In a genome-wide search for CNVs associating with schizophrenia, a population-based sample was used to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring and three deletions significantly associate with schizophrenia and related psychoses in the combined sample.
Abstract: Reduced fecundity, associated with severe mental disorders, places negative selection pressure on risk alleles and may explain, in part, why common variants have not been found that confer risk of disorders such as autism, schizophrenia and mental retardation. Thus, rare variants may account for a larger fraction of the overall genetic risk than previously assumed. In contrast to rare single nucleotide mutations, rare copy number variations (CNVs) can be detected using genome-wide single nucleotide polymorphism arrays. This has led to the identification of CNVs associated with mental retardation and autism. In a genome-wide search for CNVs associating with schizophrenia, we used a population-based sample to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring. The 66 de novo CNVs identified were tested for association in a sample of 1,433 schizophrenia cases and 33,250 controls. Three deletions at 1q21.1, 15q11.2 and 15q13.3 showing nominal association with schizophrenia in the first sample (phase I) were followed up in a second sample of 3,285 cases and 7,951 controls (phase II). All three deletions significantly associate with schizophrenia and related psychoses in the combined sample. The identification of these rare, recurrent risk variants, having occurred independently in multiple founders and being subject to negative selection, is important in itself. CNV analysis may also point the way to the identification of additional and more prevalent risk variants in genes and pathways involved in schizophrenia.
1,767 citations
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deCODE genetics1, Maastricht University Medical Centre2, Utrecht University3, University of California, Los Angeles4, University of Oslo5, University of Bonn6, Ludwig Maximilian University of Munich7, Copenhagen University Hospital8, Wellcome Trust Sanger Institute9, Aarhus University Hospital10, Aarhus University11, University of Iceland12, University of Helsinki13, Bispebjerg Hospital14, Glostrup Hospital15, Heidelberg University16, Semmelweis University17, University of Verona18, Radboud University Nijmegen Medical Centre19, Russian Academy20, University of Valencia21, King's College London22, Royal Cornhill Hospital23, Duke University24, University of Santiago de Compostela25, Hospital General Universitario Gregorio Marañón26, Karolinska Institutet27, Hammersmith Hospital28, GlaxoSmithKline29, Sichuan University30
TL;DR: Findings implicating the MHC region are consistent with an immune component to schizophrenia risk, whereas the association with NRGN and TCF4 points to perturbation of pathways involved in brain development, memory and cognition.
Abstract: Schizophrenia is a complex disorder, caused by both genetic and environmental factors and their interactions. Research on pathogenesis has traditionally focused on neurotransmitter systems in the brain, particularly those involving dopamine. Schizophrenia has been considered a separate disease for over a century, but in the absence of clear biological markers, diagnosis has historically been based on signs and symptoms. A fundamental message emerging from genome-wide association studies of copy number variations (CNVs) associated with the disease is that its genetic basis does not necessarily conform to classical nosological disease boundaries. Certain CNVs confer not only high relative risk of schizophrenia but also of other psychiatric disorders. The structural variations associated with schizophrenia can involve several genes and the phenotypic syndromes, or the 'genomic disorders', have not yet been characterized. Single nucleotide polymorphism (SNP)-based genome-wide association studies with the potential to implicate individual genes in complex diseases may reveal underlying biological pathways. Here we combined SNP data from several large genome-wide scans and followed up the most significant association signals. We found significant association with several markers spanning the major histocompatibility complex (MHC) region on chromosome 6p21.3-22.1, a marker located upstream of the neurogranin gene (NRGN) on 11q24.2 and a marker in intron four of transcription factor 4 (TCF4) on 18q21.2. Our findings implicating the MHC region are consistent with an immune component to schizophrenia risk, whereas the association with NRGN and TCF4 points to perturbation of pathways involved in brain development, memory and cognition.
1,625 citations
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Massachusetts Institute of Technology1, Harvard University2, Broad Institute3, Cardiff University4, University College London5, University of Edinburgh6, Trinity College, Dublin7, Karolinska Institutet8, Uppsala University9, University of Southern California10, University of Aberdeen11, University of North Carolina at Chapel Hill12, QIMR Berghofer Medical Research Institute13, Royal College of Surgeons in Ireland14, National Health Service15, University of Oxford16, Queen Mary University of London17, State University of New York System18, University of Coimbra19
TL;DR: A genome-wide survey of rare CNVs in 3,391 patients with schizophrenia and 3,181 ancestrally matched controls provides strong support for a model of schizophrenia pathogenesis that includes the effects of multiple rare structural variants, both genome- wide and at specific loci.
Abstract: Schizophrenia is a severe mental disorder marked by hallucinations, delusions, cognitive deficits and apathy, with a heritability estimated at 73 - 90% ( ref. 1). Inheritance patterns are complex, and the number and type of genetic variants involved are not understood. Copy number variants ( CNVs) have been identified in individual patients with schizophrenia(2-7) and also in neurodevelopmental disorders(8-11), but large- scale genome- wide surveys have not been performed. Here we report a genome- wide survey of rare CNVs in 3,391 patients with schizophrenia and 3,181 ancestrally matched controls, using high- density microarrays. For CNVs that were observed in less than 1% of the sample and were more than 100 kilobases in length, the total burden is increased 1.15- fold in patients with schizophrenia in comparison with controls. This effect was more pronounced for rarer, single- occurrence CNVs and for those that involved genes as opposed to those that did not. As expected, deletions were found within the region critical for velo- cardio- facial syndrome, which includes psychotic symptoms in 30% of patients(12). Associations with schizophrenia were also found for large deletions on chromosome 15q13.3 and 1q21.1. These associations have not previously been reported, and they remained significant after genome- wide correction. Our results provide strong support for a model of schizophrenia pathogenesis that includes the effects of multiple rare structural variants, both genome- wide and at specific loci.
1,465 citations
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TL;DR: This direct replication of haplotype association in a second population further implicates NRG1 as a factor that contributes to the etiology of schizophrenia.
Abstract: Recently, we identified neuregulin 1 (NRG1) as a susceptibility gene for schizophrenia in the Icelandic population, by a combined linkage and association approach. Here, we report the first study evaluating the relevance of NRG1 to schizophrenia in a population outside Iceland. Markers representing a core at-risk haplotype found in Icelanders at the 5′ end of the NRG1 gene were genotyped in 609 unrelated Scottish patients and 618 unrelated Scottish control individuals. This haplotype consisted of five SNP markers and two microsatellites, which all appear to be in strong linkage disequilibrium. For the Scottish patients and control subjects, haplotype frequencies were estimated by maximum likelihood, using the expectation-maximization algorithm. The frequency of the seven-marker haplotype among the Scottish patients was significantly greater than that among the control subjects (10.2% vs. 5.9%, P=.00031). The estimated risk ratio was 1.8, which is in keeping with our report of unrelated Icelandic patients (2.1). Three of the seven markers in the haplotype gave single-point P values ranging from .000064 to .0021 for the allele contributing to the at-risk haplotype. This direct replication of haplotype association in a second population further implicates NRG1 as a factor that contributes to the etiology of schizophrenia.
569 citations
Cited by
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National Institutes of Health1, University of Chicago2, Duke University3, Harvard University4, University of Oxford5, GlaxoSmithKline6, Johns Hopkins University7, Yale University8, deCODE genetics9, Howard Hughes Medical Institute10, Princeton University11, Washington University in St. Louis12, University of California, Berkeley13, Stanford University14, University of Michigan15, Cornell University16, University of Washington17, University of Queensland18, Vanderbilt University19, North Carolina State University20, QIMR Berghofer Medical Research Institute21
TL;DR: This paper examined potential sources of missing heritability and proposed research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
Abstract: Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
7,797 citations
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TL;DR: 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.
Abstract: 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.
6,809 citations
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TL;DR: The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets and focuses on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation.
Abstract: For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the “missing heritability” problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.
5,867 citations
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5,173 citations
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Harvard University1, Broad Institute2, QIMR Berghofer Medical Research Institute3, Cardiff University4, North Carolina State University5, Trinity College, Dublin6, University of Edinburgh7, Karolinska Institutet8, Uppsala University9, University of Southern California10, University of North Carolina at Chapel Hill11, University College London12, National Health Service13, University of Oxford14, University of Aberdeen15, Strathclyde Institute of Pharmacy and Biomedical Sciences16, State University of New York Upstate Medical University17, University of Coimbra18
TL;DR: The extent to which common genetic variation underlies the risk of schizophrenia is shown, using two analytic approaches, and the major histocompatibility complex is implicate, which is shown to involve thousands of common alleles of very small effect.
Abstract: Schizophrenia is a severe mental disorder with a lifetime risk of about 1%, characterized by hallucinations, delusions and cognitive deficits, with heritability estimated at up to 80%(1,2). We performed a genome-wide association study of 3,322 European individuals with schizophrenia and 3,587 controls. Here we show, using two analytic approaches, the extent to which common genetic variation underlies the risk of schizophrenia. First, we implicate the major histocompatibility complex. Second, we provide molecular genetic evidence for a substantial polygenic component to the risk of schizophrenia involving thousands of common alleles of very small effect. We show that this component also contributes to the risk of bipolar disorder, but not to several non-psychiatric diseases.
4,573 citations