Author
James A. Knowles
Other affiliations: Zilkha Neurogenetic Institute
Bio: James A. Knowles is an academic researcher from University of Southern California. The author has contributed to research in topics: Genome-wide association study & Population. The author has an hindex of 49, co-authored 111 publications receiving 22785 citations. Previous affiliations of James A. Knowles include Zilkha Neurogenetic Institute.
Papers published on a yearly basis
Papers
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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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Harvard University1, Broad Institute2, 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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TL;DR: Empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.
Abstract: 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.
2,058 citations
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Broad Institute1, Harvard University2, Massachusetts Institute of Technology3, 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: An anatomically comprehensive atlas of the mid-gestational human brain is described, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions.
Abstract: The anatomical and functional architecture of the human brain is mainly determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and post-mitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and outer subventricular zones even though the outer zone is expanded in humans. Both germinal and post-mitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in the frontal lobe. Finally, many neurodevelopmental disorder and human-evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development.
1,114 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, Princeton University10, Howard Hughes Medical Institute11, 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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TL;DR: In this paper, the authors defined the following terms: ALAT, alanine aminotransferase, ASAT, aspartate AMINOTE, and APAH, associated pulmonary arterial hypertension.
Abstract: ALAT
: alanine aminotransferase
ASAT
: aspartate aminotransferase
APAH
: associated pulmonary arterial hypertension
BAS
: balloon atrial septostomy
BMPR2
: bone morphogenetic protein receptor 2
BNP
: brain natriuretic peptide
BPA
: balloon pulmonary angioplasty
BREATHE
: Bosentan
5,224 citations
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TL;DR: Canu, a successor of Celera Assembler that is specifically designed for noisy single-molecule sequences, is presented, demonstrating that Canu can reliably assemble complete microbial genomes and near-complete eukaryotic chromosomes using either Pacific Biosciences or Oxford Nanopore technologies.
Abstract: Long-read single-molecule sequencing has revolutionized de novo genome assembly and enabled the automated reconstruction of reference-quality genomes. However, given the relatively high error rates of such technologies, efficient and accurate assembly of large repeats and closely related haplotypes remains challenging. We address these issues with Canu, a successor of Celera Assembler that is specifically designed for noisy single-molecule sequences. Canu introduces support for nanopore sequencing, halves depth-of-coverage requirements, and improves assembly continuity while simultaneously reducing runtime by an order of magnitude on large genomes versus Celera Assembler 8.2. These advances result from new overlapping and assembly algorithms, including an adaptive overlapping strategy based on tf-idf weighted MinHash and a sparse assembly graph construction that avoids collapsing diverged repeats and haplotypes. We demonstrate that Canu can reliably assemble complete microbial genomes and near-complete eukaryotic chromosomes using either Pacific Biosciences (PacBio) or Oxford Nanopore technologies and achieves a contig NG50 of >21 Mbp on both human and Drosophila melanogaster PacBio data sets. For assembly structures that cannot be linearly represented, Canu provides graph-based assembly outputs in graphical fragment assembly (GFA) format for analysis or integration with complementary phasing and scaffolding techniques. The combination of such highly resolved assembly graphs with long-range scaffolding information promises the complete and automated assembly of complex genomes.
4,806 citations