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Dive into the research topics where Andrew McQuillin is active.

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Featured researches published by Andrew McQuillin.


Nature | 2009

Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Shaun Purcell; Naomi R. Wray; Jennifer Stone; Peter M. Visscher; Michael Conlon O'Donovan; Patrick F. Sullivan; Pamela Sklar; Douglas M. Ruderfer; Andrew McQuillin; Derek W. Morris; Colm O’Dushlaine; Aiden Corvin; Peter Holmans; Michael C. O’Donovan; Stuart MacGregor; Hugh Gurling; Douglas Blackwood; Nicholas John Craddock; Michael Gill; Christina M. Hultman; George Kirov; Paul Lichtenstein; Walter J. Muir; Michael John Owen; Carlos N. Pato; Edward M. Scolnick; David St Clair; Nigel Melville Williams; Lyudmila Georgieva; Ivan Nikolov

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%. 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.


Nature Genetics | 2009

Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease.

Denise Harold; Richard Abraham; Paul Hollingworth; Rebecca Sims; Amy Gerrish; Marian Lindsay Hamshere; Jaspreet Singh Pahwa; Valentina Moskvina; Kimberley Dowzell; Amy Williams; Nicola L. Jones; Charlene Thomas; Alexandra Stretton; Angharad R. Morgan; Simon Lovestone; John Powell; Petroula Proitsi; Michelle K. Lupton; Carol Brayne; David C. Rubinsztein; Michael Gill; Brian A. Lawlor; Aoibhinn Lynch; Kevin Morgan; Kristelle Brown; Peter Passmore; David Craig; Bernadette McGuinness; Stephen Todd; Clive Holmes

We undertook a two-stage genome-wide association study (GWAS) of Alzheimers 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 × 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 × 10−9) and 5′ to the PICALM gene (rs3851179, P = 1.9 × 10−8). These associations were replicated in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with Alzheimers disease in the combined dataset (rs11136000, P = 8.5 × 10−10, odds ratio = 0.86; rs3851179, P = 1.3 × 10−9, odds ratio = 0.86).


Archive | 2009

Letter abstract - Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's Disease

Denise Harold; Richard Abraham; Paul Hollingworth; Rebecca Sims; Amy Gerrish; Marian Lindsay Hamshere; Jaspreet Sing Pahwa; Valentina Moskvina; Kimberley Dowzell; Amy Williams; Nicola L. Jones; Charlene Thomas; Alexandra Stretton; Angharad R. Morgan; Simon Lovestone; John Powell; Petroula Proitsi; Michelle K. Lupton; Carol Brayne; David C. Rubinsztein; Michael Gill; Brian A. Lawlor; Aoibhinn Lynch; Kevin Morgan; Kristelle Brown; Peter Passmore; David Craig; Bernadette McGuinness; Stephen Todd; Clive Holmes

We undertook a two-stage genome-wide association study (GWAS) of Alzheimers 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 × 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 × 10−9) and 5′ to the PICALM gene (rs3851179, P = 1.9 × 10−8). These associations were replicated in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with Alzheimers disease in the combined dataset (rs11136000, P = 8.5 × 10−10, odds ratio = 0.86; rs3851179, P = 1.3 × 10−9, odds ratio = 0.86).


Nature | 2008

Rare chromosomal deletions and duplications increase risk of schizophrenia

Jennifer Stone; Michael C. O’Donovan; Hugh Gurling; George Kirov; Douglas Blackwood; Aiden Corvin; Nicholas John Craddock; Michael Gill; Christina M. Hultman; Paul Lichtenstein; Andrew McQuillin; Carlos N. Pato; Douglas M. Ruderfer; Michael John Owen; David St Clair; Patrick F. Sullivan; Pamela Sklar; Shaun Purcell; Joshua M. Korn; Stuart Macgregor; Derek W. Morris; Colm O’Dushlaine; Mark J. Daly; Peter M. Visscher; Peter Holmans; Edward M. Scolnick; Nigel Melville Williams; Lucy Georgieva; Ivan Nikolov; Nadine Norton

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 and also in neurodevelopmental disorders, 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. 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.


American Journal of Human Genetics | 2003

Genome Scan Meta-Analysis of Schizophrenia and Bipolar Disorder, Part II: Schizophrenia

Cathryn M. Lewis; Douglas F. Levinson; Lesley H. Wise; Lynn E. DeLisi; Richard E. Straub; Iiris Hovatta; Nigel Melville Williams; Sibylle G. Schwab; Ann E. Pulver; Stephen V. Faraone; Linda M. Brzustowicz; Charles A. Kaufmann; David L. Garver; Hugh Gurling; Eva Lindholm; Hilary Coon; Hans W. Moises; William Byerley; Sarah H. Shaw; Andrea Mesén; Robin Sherrington; F. Anthony O'Neill; Dermot Walsh; Kenneth S. Kendler; Jesper Ekelund; Tiina Paunio; Jouko Lönnqvist; Leena Peltonen; Michael Conlon O'Donovan; Michael John Owen

Schizophrenia is a common disorder with high heritability and a 10-fold increase in risk to siblings of probands. Replication has been inconsistent for reports of significant genetic linkage. To assess evidence for linkage across studies, rank-based genome scan meta-analysis (GSMA) was applied to data from 20 schizophrenia genome scans. Each marker for each scan was assigned to 1 of 120 30-cM bins, with the bins ranked by linkage scores (1 = most significant) and the ranks averaged across studies (R(avg)) and then weighted for sample size (N(sqrt)[affected casess]). A permutation test was used to compute the probability of observing, by chance, each bins average rank (P(AvgRnk)) or of observing it for a bin with the same place (first, second, etc.) in the order of average ranks in each permutation (P(ord)). The GSMA produced significant genomewide evidence for linkage on chromosome 2q (PAvgRnk<.000417). Two aggregate criteria for linkage were also met (clusters of nominally significant P values that did not occur in 1,000 replicates of the entire data set with no linkage present): 12 consecutive bins with both P(AvgRnk) and P(ord)<.05, including regions of chromosomes 5q, 3p, 11q, 6p, 1q, 22q, 8p, 20q, and 14p, and 19 consecutive bins with P(ord)<.05, additionally including regions of chromosomes 16q, 18q, 10p, 15q, 6q, and 17q. There is greater consistency of linkage results across studies than has been previously recognized. The results suggest that some or all of these regions contain loci that increase susceptibility to schizophrenia in diverse populations.


Nature Genetics | 2008

Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder

Manuel A. Ferreira; Michael Conlon O'Donovan; Ian Richard Jones; Douglas M. Ruderfer; Lisa Jones; Jinbo Fan; George Kirov; Roy H. Perlis; Elaine K. Green; Jordan W. Smoller; Detelina Grozeva; Jennifer Stone; Ivan Nikolov; Marian Lindsay Hamshere; Vishwajit L. Nimgaonkar; Valentina Moskvina; Michael E. Thase; Sian Caesar; Gary S. Sachs; Jennifer Franklin; Katherine Gordon-Smith; Kristin Ardlie; Stacey Gabriel; Christine Fraser; Brendan Blumenstiel; Matthew DeFelice; Gerome Breen; Michael Gill; Derek W. Morris; Amanda Elkin

To identify susceptibility loci for bipolar disorder, we tested 1.8 million variants in 4,387 cases and 6,209 controls and identified a region of strong association (rs10994336, P = 9.1 × 10−9) in ANK3 (ankyrin G). We also found further support for the previously reported CACNA1C (alpha 1C subunit of the L-type voltage-gated calcium channel; combined P = 7.0 × 10−8, rs1006737). Our results suggest that ion channelopathies may be involved in the pathogenesis of bipolar disorder.


Molecular Psychiatry | 2008

Whole-genome association study of bipolar disorder

Pamela Sklar; Jordan W. Smoller; Jinbo Fan; Manuel A. Ferreira; Roy H. Perlis; Vishwajit L. Nimgaonkar; Matthew B. McQueen; Stephen V. Faraone; Andrew Kirby; P. I. W. de Bakker; Matthew N. Ogdie; Michael E. Thase; Gary S. Sachs; Katherine E. O. Todd-Brown; Stacey Gabriel; Carrie Sougnez; Casey Gates; Brendan Blumenstiel; Matthew DeFelice; Kristin Ardlie; J Franklin; Walter J. Muir; Kevin A. McGhee; Donald J. MacIntyre; Alan W. McLean; M VanBeck; Andrew McQuillin; Nick Bass; Matthew Robinson; Jacob Lawrence

We performed a genome-wide association scan in 1461 patients with bipolar (BP) 1 disorder, 2008 controls drawn from the Systematic Treatment Enhancement Program for Bipolar Disorder and the University College London sample collections with successful genotyping for 372 193 single nucleotide polymorphisms (SNPs). Our strongest single SNP results are found in myosin5B (MYO5B; P=1.66 × 10−7) and tetraspanin-8 (TSPAN8; P=6.11 × 10−7). Haplotype analysis further supported single SNP results highlighting MYO5B, TSPAN8 and the epidermal growth factor receptor (MYO5B; P=2.04 × 10−8, TSPAN8; P=7.57 × 10−7 and EGFR; P=8.36 × 10−8). For replication, we genotyped 304 SNPs in family-based NIMH samples (n=409 trios) and University of Edinburgh case–control samples (n=365 cases, 351 controls) that did not provide independent replication after correction for multiple testing. A comparison of our strongest associations with the genome-wide scan of 1868 patients with BP disorder and 2938 controls who completed the scan as part of the Wellcome Trust Case–Control Consortium indicates concordant signals for SNPs within the voltage-dependent calcium channel, L-type, alpha 1C subunit (CACNA1C) gene. Given the heritability of BP disorder, the lack of agreement between studies emphasizes that susceptibility alleles are likely to be modest in effect size and require even larger samples for detection.


PLOS ONE | 2010

Genetic evidence implicates the immune system and cholesterol metabolism in the aetiology of Alzheimer's disease.

Lesley Jones; Peter Holmans; Marian Lindsay Hamshere; Denise Harold; Valentina Moskvina; Dobril Ivanov; Andrew Pocklington; Richard Abraham; Paul Hollingworth; Rebecca Sims; Amy Gerrish; Jaspreet Singh Pahwa; Nicola L. Jones; Alexandra Stretton; Angharad R. Morgan; Simon Lovestone; John Powell; Petroula Proitsi; Michelle K. Lupton; Carol Brayne; David C. Rubinsztein; Michael Gill; Brian A. Lawlor; Aoibhinn Lynch; Kevin Morgan; Kristelle Brown; Peter Passmore; David Craig; Bernadette McGuinness; Stephen Todd

Background Late Onset Alzheimers disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. Principal Findings We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimers disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches.


American Journal of Human Genetics | 2001

Genomewide Genetic Linkage Analysis Confirms the Presence of Susceptibility Loci for Schizophrenia, on Chromosomes 1q32.2, 5q33.2, and 8p21-22 and Provides Support for Linkage to Schizophrenia, on Chromosomes 11q23.3-24 and 20q12.1-11.23

Hugh Gurling; Gursharan Kalsi; Jon Brynjolfson; T. Sigmundsson; Robin Sherrington; Baljinder S. Mankoo; T Read; Patrice Murphy; E Blaveri; Andrew McQuillin; Hannes Petursson; David Curtis

We have performed genetic linkage analysis in 13 large multiply affected families, to test the hypothesis that there is extensive heterogeneity of linkage for genetic subtypes of schizophrenia. Our strategy consisted of selecting 13 kindreds containing multiple affected cases in three or more generations, an absence of bipolar affective disorder, and a single progenitor source of schizophrenia with unilineal transmission into the branch of the kindred sampled. DNA samples from these families were genotyped with 365 microsatellite markers spaced at approximately 10-cM intervals across the whole genome. We observed LOD scores >3.0 at five distinct loci, either in the sample as a whole or within single families, strongly suggesting etiological heterogeneity. Heterogeneity LOD scores >3.0 in the sample as a whole were found at 1q33.2 (LOD score 3.2; P=.0003), 5q33.2 (LOD score 3.6; P=.0001), 8p22.1-22 (LOD score 3.6; P=.0001), and 11q21 (LOD score 3.1; P=.0004). LOD scores >3.0 within single pedigrees were found at 4q13-31 (LOD score 3.2; P=.0003) and at 11q23.3-24 (LOD score 3.2; P=.0003). A LOD score of 2.9 was also found at 20q12.1-11.23 within in a single family. The fact that other studies have also detected LOD scores >3.0 at 1q33.2, 5q33.2, 8p21-22 and 11q21 suggests that these regions do indeed harbor schizophrenia-susceptibility loci. We believe that the weight of evidence for linkage to the chromosome 1q22, 5q33.2, and 8p21-22 loci is now sufficient to justify intensive investigation of these regions by methods based on linkage disequilibrium. Such studies will soon allow the identification of mutations having a direct effect on susceptibility to schizophrenia.


Molecular Psychiatry | 2009

Meta-analysis of 32 genome-wide linkage studies of schizophrenia

M Y M Ng; Douglas F. Levinson; Stephen V. Faraone; Brian K. Suarez; Lynn E. DeLisi; Tadao Arinami; Brien P. Riley; Tiina Paunio; Ann E. Pulver; Irmansyah; Peter Holmans; Michael A. Escamilla; Dieter B. Wildenauer; Nigel Melville Williams; Claudine Laurent; Bryan J. Mowry; Linda M. Brzustowicz; M. Maziade; Pamela Sklar; David L. Garver; Gonçalo R. Abecasis; Bernard Lerer; M D Fallin; H M D Gurling; Pablo V. Gejman; Eva Lindholm; Hans W. Moises; William Byerley; Ellen M. Wijsman; Paola Forabosco

A genome scan meta-a nalysis (GSMA) was carried out on 32 independent genome-wide linkage scan analyses that included 3255 pedigrees with 7413 genotyped cases affected with schizophrenia (SCZ) or related disorders. The primary GSMA divided the autosomes into 120 bins, rank-ordered the bins within each study according to the most positive linkage result in each bin, summed these ranks (weighted for study size) for each bin across studies and determined the empirical probability of a given summed rank (PSR) by simulation. Suggestive evidence for linkage was observed in two single bins, on chromosomes 5q (142–168 Mb) and 2q (103–134 Mb). Genome-wide evidence for linkage was detected on chromosome 2q (119–152 Mb) when bin boundaries were shifted to the middle of the previous bins. The primary analysis met empirical criteria for ‘aggregate’ genome-wide significance, indicating that some or all of 10 bins are likely to contain loci linked to SCZ, including regions of chromosomes 1, 2q, 3q, 4q, 5q, 8p and 10q. In a secondary analysis of 22 studies of European-ancestry samples, suggestive evidence for linkage was observed on chromosome 8p (16–33 Mb). Although the newer genome-wide association methodology has greater power to detect weak associations to single common DNA sequence variants, linkage analysis can detect diverse genetic effects that segregate in families, including multiple rare variants within one locus or several weakly associated loci in the same region. Therefore, the regions supported by this meta-analysis deserve close attention in future studies.

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David Curtis

University College London

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Jacob Lawrence

University College London

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Nick Bass

University College London

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Nicholas Bass

University College London

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Hmd Gurling

University College London

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G Kalsi

University College London

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