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Patrick Bolton

Bio: Patrick Bolton is an academic researcher from King's College London. The author has contributed to research in topics: Autism & Autism spectrum disorder. The author has an hindex of 78, co-authored 218 publications receiving 31415 citations. Previous affiliations of Patrick Bolton include Centre for Mental Health & King's College.


Papers
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Journal ArticleDOI
TL;DR: The findings indicate that autism is under a high degree of genetic control and suggest the involvement of multiple genetic loci.
Abstract: Two previous epidemiological studies of autistic twins suggested that autism was predominantly genetically determined, although the findings with regard to a broader phenotype of cognitive, and possibly social, abnormalities were contradictory. Obstetric and perinatal hazards were also invoked as environmentally determined aetiological factors. The first British twin sample has been re-examined and a second total population sample of autistic twins recruited. In the combined sample 60% of monozygotic (MZ) pairs were concordant for autism versus no dizygotic (DZ) pairs; 92% of MZ pairs were concordant for a broader spectrum of related cognitive or social abnormalities versus 10% of DZ pairs. The findings indicate that autism is under a high degree of genetic control and suggest the involvement of multiple genetic loci. Obstetric hazards usually appear to be consequences of genetically influenced abnormal development, rather than independent aetiological factors. Few new cases had possible medical aetiologies, refuting claims that recognized disorders are common aetiological influences.

2,378 citations

Journal ArticleDOI
Silvia De Rubeis1, Xin-Xin He2, Arthur P. Goldberg1, Christopher S. Poultney1, Kaitlin E. Samocha3, A. Ercument Cicek2, Yan Kou1, Li Liu2, Menachem Fromer1, Menachem Fromer3, R. Susan Walker4, Tarjinder Singh5, Lambertus Klei6, Jack A. Kosmicki3, Shih-Chen Fu1, Branko Aleksic7, Monica Biscaldi8, Patrick Bolton9, Jessica M. Brownfeld1, Jinlu Cai1, Nicholas G. Campbell10, Angel Carracedo11, Angel Carracedo12, Maria H. Chahrour3, Andreas G. Chiocchetti, Hilary Coon13, Emily L. Crawford10, Lucy Crooks5, Sarah Curran9, Geraldine Dawson14, Eftichia Duketis, Bridget A. Fernandez15, Louise Gallagher16, Evan T. Geller17, Stephen J. Guter18, R. Sean Hill3, R. Sean Hill19, Iuliana Ionita-Laza20, Patricia Jiménez González, Helena Kilpinen, Sabine M. Klauck21, Alexander Kolevzon1, Irene Lee22, Jing Lei2, Terho Lehtimäki, Chiao-Feng Lin17, Avi Ma'ayan1, Christian R. Marshall4, Alison L. McInnes23, Benjamin M. Neale24, Michael John Owen25, Norio Ozaki7, Mara Parellada26, Jeremy R. Parr27, Shaun Purcell1, Kaija Puura, Deepthi Rajagopalan4, Karola Rehnström5, Abraham Reichenberg1, Aniko Sabo28, Michael Sachse, Stephen Sanders29, Chad M. Schafer2, Martin Schulte-Rüther30, David Skuse22, David Skuse31, Christine Stevens24, Peter Szatmari32, Kristiina Tammimies4, Otto Valladares17, Annette Voran33, Li-San Wang17, Lauren A. Weiss29, A. Jeremy Willsey29, Timothy W. Yu19, Timothy W. Yu3, Ryan K. C. Yuen4, Edwin H. Cook18, Christine M. Freitag, Michael Gill16, Christina M. Hultman34, Thomas Lehner35, Aarno Palotie3, Aarno Palotie24, Aarno Palotie36, Gerard D. Schellenberg17, Pamela Sklar1, Matthew W. State29, James S. Sutcliffe10, Christopher A. Walsh3, Christopher A. Walsh19, Stephen W. Scherer4, Michael E. Zwick37, Jeffrey C. Barrett5, David J. Cutler37, Kathryn Roeder2, Bernie Devlin6, Mark J. Daly3, Mark J. Daly24, Joseph D. Buxbaum1 
13 Nov 2014-Nature
TL;DR: Using exome sequencing, it is shown that analysis of rare coding variation in 3,871 autism cases and 9,937 ancestry-matched or parental controls implicates 22 autosomal genes at a false discovery rate of < 0.05, plus a set of 107 genes strongly enriched for those likely to affect risk (FDR < 0.30).
Abstract: The genetic architecture of autism spectrum disorder involves the interplay of common and rare variants and their impact on hundreds of genes. Using exome sequencing, here we show that analysis of rare coding variation in 3,871 autism cases and 9,937 ancestry-matched or parental controls implicates 22 autosomal genes at a false discovery rate (FDR) < 0.05, plus a set of 107 autosomal genes strongly enriched for those likely to affect risk (FDR < 0.30). These 107 genes, which show unusual evolutionary constraint against mutations, incur de novo loss-of-function mutations in over 5% of autistic subjects. Many of the genes implicated encode proteins for synaptic formation, transcriptional regulation and chromatin-remodelling pathways. These include voltage-gated ion channels regulating the propagation of action potentials, pacemaking and excitability-transcription coupling, as well as histone-modifying enzymes and chromatin remodellers-most prominently those that mediate post-translational lysine methylation/demethylation modifications of histones.

2,228 citations

Journal ArticleDOI
Dalila Pinto1, Alistair T. Pagnamenta2, Lambertus Klei3, Richard Anney4  +178 moreInstitutions (46)
15 Jul 2010-Nature
TL;DR: The genome-wide characteristics of rare (<1% frequency) copy number variation in ASD are analysed using dense genotyping arrays to reveal many new genetic and functional targets in ASD that may lead to final connected pathways.
Abstract: The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviours. Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability. Although ASDs are known to be highly heritable ( approximately 90%), the underlying genetic determinants are still largely unknown. Here we analysed the genome-wide characteristics of rare (<1% frequency) copy number variation in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic copy number variants (CNVs) (1.19 fold, P = 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P = 3.4 x 10(-4)). Among the CNVs there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes such as SHANK2, SYNGAP1, DLGAP2 and the X-linked DDX53-PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene sets involved in cellular proliferation, projection and motility, and GTPase/Ras signalling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways.

1,919 citations

Journal ArticleDOI
22 Jun 2018-Science
TL;DR: It is demonstrated that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine, and it is shown that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures.
Abstract: Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

1,357 citations

Journal ArticleDOI
Peter Szatmari1, Andrew D. Paterson2, Lonnie Zwaigenbaum1, Wendy Roberts2, Jessica Brian2, Xiao-Qing Liu2, John B. Vincent2, Jennifer Skaug2, Ann P. Thompson1, Lili Senman2, Lars Feuk2, Cheng Qian2, Susan E. Bryson3, Marshall B. Jones4, Christian R. Marshall2, Stephen W. Scherer2, Veronica J. Vieland5, Christopher W. Bartlett5, La Vonne Mangin5, Rhinda Goedken6, Alberto M. Segre6, Margaret A. Pericak-Vance7, Michael L. Cuccaro7, John R. Gilbert7, Harry H. Wright8, Ruth K. Abramson8, Catalina Betancur9, Thomas Bourgeron10, Christopher Gillberg11, Marion Leboyer9, Joseph D. Buxbaum12, Kenneth L. Davis12, Eric Hollander12, Jeremy M. Silverman12, Joachim Hallmayer13, Linda Lotspeich13, James S. Sutcliffe14, Jonathan L. Haines14, Susan E. Folstein15, Joseph Piven16, Thomas H. Wassink6, Val C. Sheffield6, Daniel H. Geschwind17, Maja Bucan18, W. Ted Brown, Rita M. Cantor17, John N. Constantino19, T. Conrad Gilliam20, Martha R. Herbert21, Clara Lajonchere17, David H. Ledbetter22, Christa Lese-Martin22, Janet Miller17, Stan F. Nelson17, Carol A. Samango-Sprouse23, Sarah J. Spence17, Matthew W. State24, Rudolph E. Tanzi21, Hilary Coon25, Geraldine Dawson26, Bernie Devlin27, Annette Estes26, Pamela Flodman28, Lambertus Klei27, William M. McMahon25, Nancy J. Minshew27, Jeff Munson26, Elena Korvatska29, Elena Korvatska26, Patricia M. Rodier30, Gerard D. Schellenberg29, Gerard D. Schellenberg26, Moyra Smith28, M. Anne Spence28, Christopher J. Stodgell30, Ping Guo Tepper, Ellen M. Wijsman26, Chang En Yu29, Chang En Yu26, Bernadette Rogé31, Carine Mantoulan31, Kerstin Wittemeyer31, Annemarie Poustka32, Bärbel Felder32, Sabine M. Klauck32, Claudia Schuster32, Fritz Poustka33, Sven Bölte33, Sabine Feineis-Matthews33, Evelyn Herbrecht33, Gabi Schmötzer33, John Tsiantis34, Katerina Papanikolaou34, Elena Maestrini35, Elena Bacchelli35, Francesca Blasi35, Simona Carone35, Claudio Toma35, Herman van Engeland36, Maretha de Jonge36, Chantal Kemner36, Frederike Koop36, Marjolijn Langemeijer36, Channa Hijimans36, Wouter G. Staal36, Gillian Baird37, Patrick Bolton38, Michael Rutter38, Emma Weisblatt39, Jonathan Green40, Catherine Aldred40, Julie Anne Wilkinson40, Andrew Pickles40, Ann Le Couteur41, Tom Berney41, Helen McConachie41, Anthony J. Bailey42, Kostas Francis42, Gemma Honeyman42, Aislinn Hutchinson42, Jeremy R. Parr42, Simon Wallace42, Anthony P. Monaco42, Gabrielle Barnby42, Kazuhiro Kobayashi42, Janine A. Lamb42, Inês Sousa42, Nuala Sykes42, Edwin H. Cook43, Stephen J. Guter43, Bennett L. Leventhal43, Jeff Salt43, Catherine Lord44, Christina Corsello44, Vanessa Hus44, Daniel E. Weeks27, Fred R. Volkmar24, Maïté Tauber45, Eric Fombonne46, Andy Shih47 
TL;DR: Linkage and copy number variation analyses implicate chromosome 11p12–p13 and neurexins, respectively, among other candidate loci, highlighting glutamate-related genes as promising candidates for contributing to ASDs.
Abstract: Autism spectrum disorders (ASDs) are common, heritable neurodevelopmental conditions. The genetic architecture of ASDs is complex, requiring large samples to overcome heterogeneity. Here we broaden coverage and sample size relative to other studies of ASDs by using Affymetrix 10K SNP arrays and 1,181 [corrected] families with at least two affected individuals, performing the largest linkage scan to date while also analyzing copy number variation in these families. Linkage and copy number variation analyses implicate chromosome 11p12-p13 and neurexins, respectively, among other candidate loci. Neurexins team with previously implicated neuroligins for glutamatergic synaptogenesis, highlighting glutamate-related genes as promising candidates for contributing to ASDs.

1,338 citations


Cited by
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Journal ArticleDOI
Adam Auton1, Gonçalo R. Abecasis2, David Altshuler3, Richard Durbin4  +514 moreInstitutions (90)
01 Oct 2015-Nature
TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

12,661 citations

Journal ArticleDOI
TL;DR: Algorithm sensitivities and specificities for autism and PD DNOS relative to nonspectrum disorders were excellent, with moderate differentiation of autism from PDDNOS.
Abstract: The Autism Diagnostic Observation Schedule-Generic (ADOS-G) is a semistructured, standardized assessment of social interaction, communication, play, and imaginative use of materials for individuals suspected of having autism spectrum disorders. The observational schedule consists of four 30-minute modules, each designed to be administered to different individuals according to their level of expressive language. Psychometric data are presented for 223 children and adults with Autistic Disorder (autism), Pervasive Developmental Disorder Not Otherwise Specified (PDDNOS) or nonspectrum diagnoses. Within each module, diagnostic groups were equivalent on expressive language level. Results indicate substantial interrater and test-retest reliability for individual items, excellent interrater reliability within domains and excellent internal consistency. Comparisons of means indicated consistent differentiation of autism and PDDNOS from nonspectrum individuals, with some, but less consistent, differentiation of autism from PDDNOS. A priori operationalization of DSM-IV/ICD-10 criteria, factor analyses, and ROC curves were used to generate diagnostic algorithms with thresholds set for autism and broader autism spectrum/PDD. Algorithm sensitivities and specificities for autism and PDDNOS relative to nonspectrum disorders were excellent, with moderate differentiation of autism from PDDNOS.

7,012 citations

Journal ArticleDOI
TL;DR: The Autism-Spectrum Quotient is a valuable instrument for rapidly quantifying where any given individual is situated on the continuum from autism to normality, and its potential for screening for autism spectrum conditions in adults of normal intelligence remains to be fully explored.
Abstract: Currently there are no brief, self-administered instruments for measuring the degree to which an adult with normal intelligence has the traits associated with the autistic spectrum. In this paper, we report on a new instrument to assess this: the Autism-Spectrum Quotient (AQ). Individuals score in the range 0-50. Four groups of subjects were assessed: Group 1: 58 adults with Asperger syndrome (AS) or high-functioning autism (HFA); Group 2: 174 randomly selected controls. Group 3: 840 students in Cambridge University; and Group 4: 16 winners of the UK Mathematics Olympiad. The adults with AS/HFA had a mean AQ score of 35.8 (SD = 6.5), significantly higher than Group 2 controls (M = 16.4, SD = 6.3). 80% of the adults with AS/HFA scored 32+, versus 2% of controls. Among the controls, men scored slightly but significantly higher than women. No women scored extremely highly (AQ score 34+) whereas 4% of men did so. Twice as many men (40%) as women (21%) scored at intermediate levels (AQ score 20+). Among the AS/HFA group, male and female scores did not differ significantly. The students in Cambridge University did not differ from the randomly selected control group, but scientists (including mathematicians) scored significantly higher than both humanities and social sciences students, confirming an earlier study that autistic conditions are associated with scientific skills. Within the sciences, mathematicians scored highest. This was replicated in Group 4, the Mathematics Olympiad winners scoring significantly higher than the male Cambridge humanities students. 6% of the student sample scored 32+ on the AQ. On interview, 11 out of 11 of these met three or more DSM-IV criteria for AS/HFA, and all were studying sciences/mathematics, and 7 of the 11 met threshold on these criteria. Test-retest and interrater reliability of the AQ was good. The AQ is thus a valuable instrument for rapidly quantifying where any given individual is situated on the continuum from autism to normality. Its potential for screening for autism spectrum conditions in adults of normal intelligence remains to be fully explored.

4,988 citations