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1. Author Correction: Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancer

Author

Mary L. Stackpole, Weihua Zeng, Shuo Li, Chun-Chi Liu, Yonggang Zhou, Shanshan He, Angela Yeh, Ziye Wang, Fengzhu Sun, Qingjiao Li, Zuyang Yuan, Asli Yildirim, Pin-Jung Chen, Paul Winograd, Benjamin Tran, Yi-Te Lee, Paul Shize Li, Zorawar Noor, Megumi Yokomizo, Preeti Ahuja, Yazhen Zhu, Hsian-Rong Tseng, James S. Tomlinson, Edward Garon, Samuel French, Clara E. Magyar, Sarah Dry, Clara Lajonchere, Daniel Geschwind, Gina Choi, Sammy Saab, Frank Alber, Wing Hung Wong, Steven M. Dubinett, Denise R. Aberle, Vatche Agopian, Steven-Huy B. Han, Xiaohui Ni, Wenyuan Li, and Xianghong Jasmine Zhou

Subjects
Science
Published
2024
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2. Author Correction: Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative

Author

Ruth Johnson, Yi Ding, Vidhya Venkateswaran, Arjun Bhattacharya, Kristin Boulier, Alec Chiu, Sergey Knyazev, Tommer Schwarz, Malika Freund, Lingyu Zhan, Kathryn S. Burch, Christa Caggiano, Brian Hill, Nadav Rakocz, Brunilda Balliu, Christopher T. Denny, Jae Hoon Sul, Noah Zaitlen, Valerie A. Arboleda, Eran Halperin, Sriram Sankararaman, Manish J. Butte, UCLA Precision Health Data Discovery Repository Working Group, UCLA Precision Health ATLAS Working Group, Clara Lajonchere, Daniel H. Geschwind, and Bogdan Pasaniuc

Subjects
Medicine, Genetics, QH426-470
Published
2022
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3. Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative

Author

Ruth Johnson, Yi Ding, Vidhya Venkateswaran, Arjun Bhattacharya, Kristin Boulier, Alec Chiu, Sergey Knyazev, Tommer Schwarz, Malika Freund, Lingyu Zhan, Kathryn S. Burch, Christa Caggiano, Brian Hill, Nadav Rakocz, Brunilda Balliu, Christopher T. Denny, Jae Hoon Sul, Noah Zaitlen, Valerie A. Arboleda, Eran Halperin, Sriram Sankararaman, Manish J. Butte, UCLA Precision Health Data Discovery Repository Working Group, UCLA Precision Health ATLAS Working Group, Clara Lajonchere, Daniel H. Geschwind, and Bogdan Pasaniuc

Subjects
Electronic health records, Biobank, Genetic ancestry, Genome-wide association studies, Phenome-wide association studies, Medicine, Genetics, QH426-470
Abstract

Abstract Background Large medical centers in urban areas, like Los Angeles, care for a diverse patient population and offer the potential to study the interplay between genetic ancestry and social determinants of health. Here, we explore the implications of genetic ancestry within the University of California, Los Angeles (UCLA) ATLAS Community Health Initiative—an ancestrally diverse biobank of genomic data linked with de-identified electronic health records (EHRs) of UCLA Health patients (N=36,736). Methods We quantify the extensive continental and subcontinental genetic diversity within the ATLAS data through principal component analysis, identity-by-descent, and genetic admixture. We assess the relationship between genetically inferred ancestry (GIA) and >1500 EHR-derived phenotypes (phecodes). Finally, we demonstrate the utility of genetic data linked with EHR to perform ancestry-specific and multi-ancestry genome and phenome-wide scans across a broad set of disease phenotypes. Results We identify 5 continental-scale GIA clusters including European American (EA), African American (AA), Hispanic Latino American (HL), South Asian American (SAA) and East Asian American (EAA) individuals and 7 subcontinental GIA clusters within the EAA GIA corresponding to Chinese American, Vietnamese American, and Japanese American individuals. Although we broadly find that self-identified race/ethnicity (SIRE) is highly correlated with GIA, we still observe marked differences between the two, emphasizing that the populations defined by these two criteria are not analogous. We find a total of 259 significant associations between continental GIA and phecodes even after accounting for individuals’ SIRE, demonstrating that for some phenotypes, GIA provides information not already captured by SIRE. GWAS identifies significant associations for liver disease in the 22q13.31 locus across the HL and EAA GIA groups (HL p-value=2.32×10−16, EAA p-value=6.73×10−11). A subsequent PheWAS at the top SNP reveals significant associations with neurologic and neoplastic phenotypes specifically within the HL GIA group. Conclusions Overall, our results explore the interplay between SIRE and GIA within a disease context and underscore the utility of studying the genomes of diverse individuals through biobank-scale genotyping linked with EHR-based phenotyping.

Published
2022
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4. Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancer

Author

Mary L. Stackpole, Weihua Zeng, Shuo Li, Chun-Chi Liu, Yonggang Zhou, Shanshan He, Angela Yeh, Ziye Wang, Fengzhu Sun, Qingjiao Li, Zuyang Yuan, Asli Yildirim, Pin-Jung Chen, Paul Winograd, Benjamin Tran, Yi-Te Lee, Paul Shize Li, Zorawar Noor, Megumi Yokomizo, Preeti Ahuja, Yazhen Zhu, Hsian-Rong Tseng, James S. Tomlinson, Edward Garon, Samuel French, Clara E. Magyar, Sarah Dry, Clara Lajonchere, Daniel Geschwind, Gina Choi, Sammy Saab, Frank Alber, Wing Hung Wong, Steven M. Dubinett, Denise R. Aberle, Vatche Agopian, Steven-Huy B. Han, Xiaohui Ni, Wenyuan Li, and Xianghong Jasmine Zhou

Subjects
Science
Abstract

Abstract Early cancer detection by cell-free DNA faces multiple challenges: low fraction of tumor cell-free DNA, molecular heterogeneity of cancer, and sample sizes that are not sufficient to reflect diverse patient populations. Here, we develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of the cell-free DNA methylome (with > 12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our approach to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, allowing us to learn new features and expand to other cancer types as training cohorts grow.

Published
2022
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5. Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

Author

Ying Wang, Shinichi Namba, Esteban Lopera, Sini Kerminen, Kristin Tsuo, Kristi Läll, Masahiro Kanai, Wei Zhou, Kuan-Han Wu, Marie-Julie Favé, Laxmi Bhatta, Philip Awadalla, Ben Brumpton, Patrick Deelen, Kristian Hveem, Valeria Lo Faro, Reedik Mägi, Yoshinori Murakami, Serena Sanna, Jordan W. Smoller, Jasmina Uzunovic, Brooke N. Wolford, Cristen Willer, Eric R. Gamazon, Nancy J. Cox, Ida Surakka, Yukinori Okada, Alicia R. Martin, Jibril Hirbo, Kuan-Han H. Wu, Humaira Rasheed, Jibril B. Hirbo, Arjun Bhattacharya, Huiling Zhao, Esteban A. Lopera-Maya, Sinéad B. Chapman, Juha Karjalainen, Mitja Kurki, Maasha Mutaamba, Juulia J. Partanen, Ben M. Brumpton, Sameer Chavan, Tzu-Ting Chen, Michelle Daya, Yi Ding, Yen-Chen A. Feng, Christopher R. Gignoux, Sarah E. Graham, Whitney E. Hornsby, Nathan Ingold, Ruth Johnson, Triin Laisk, Kuang Lin, Jun Lv, Iona Y. Millwood, Priit Palta, Anita Pandit, Michael H. Preuss, Unnur Thorsteinsdottir, Matthew Zawistowski, Xue Zhong, Archie Campbell, Kristy Crooks, Geertruida H. de Bock, Nicholas J. Douville, Sarah Finer, Lars G. Fritsche, Christopher J. Griffiths, Yu Guo, Karen A. Hunt, Takahiro Konuma, Riccardo E. Marioni, Jansonius Nomdo, Snehal Patil, Nicholas Rafaels, Anne Richmond, Jonathan A. Shortt, Peter Straub, Ran Tao, Brett Vanderwerff, Kathleen C. Barnes, Marike Boezen, Zhengming Chen, Chia-Yen Chen, Judy Cho, George Davey Smith, Hilary K. Finucane, Lude Franke, Andrea Ganna, Tom R. Gaunt, Tian Ge, Hailiang Huang, Jennifer Huffman, Jukka T. Koskela, Clara Lajonchere, Matthew H. Law, Liming Li, Cecilia M. Lindgren, Ruth J.F. Loos, Stuart MacGregor, Koichi Matsuda, Catherine M. Olsen, David J. Porteous, Jordan A. Shavit, Harold Snieder, Richard C. Trembath, Judith M. Vonk, David Whiteman, Stephen J. Wicks, Cisca Wijmenga, John Wright, Jie Zheng, Xiang Zhou, Michael Boehnke, Daniel H. Geschwind, Caroline Hayward, Eimear E. Kenny, Yen-Feng Lin, Hilary C. Martin, Sarah E. Medland, Aarno V. Palotie, Bogdan Pasaniuc, Kari Stefansson, David A. van Heel, Robin G. Walters, Sebastian Zöllner, Cristen J. Willer, Mark J. Daly, and Benjamin M. Neale

Subjects
Global-Biobank Meta-analysis Initiative, polygenic risk scores, multi-ancestry genetic prediction, accuracy heterogeneity, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract

Summary: Polygenic risk scores (PRSs) have been widely explored in precision medicine. However, few studies have thoroughly investigated their best practices in global populations across different diseases. We here utilized data from Global Biobank Meta-analysis Initiative (GBMI) to explore methodological considerations and PRS performance in 9 different biobanks for 14 disease endpoints. Specifically, we constructed PRSs using pruning and thresholding (P + T) and PRS-continuous shrinkage (CS). For both methods, using a European-based linkage disequilibrium (LD) reference panel resulted in comparable or higher prediction accuracy compared with several other non-European-based panels. PRS-CS overall outperformed the classic P + T method, especially for endpoints with higher SNP-based heritability. Notably, prediction accuracy is heterogeneous across endpoints, biobanks, and ancestries, especially for asthma, which has known variation in disease prevalence across populations. Overall, we provide lessons for PRS construction, evaluation, and interpretation using GBMI resources and highlight the importance of best practices for PRS in the biobank-scale genomics era.

Published
2023
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6. The UCLA ATLAS Community Health Initiative: Promoting precision health research in a diverse biobank

Author

Ruth Johnson, Yi Ding, Arjun Bhattacharya, Sergey Knyazev, Alec Chiu, Clara Lajonchere, Daniel H. Geschwind, and Bogdan Pasaniuc

Subjects
electronic health records, biobanks, multi-ancestry, Global-Biobank Meta-analysis Initiative, GWAS, PheWAS, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract

Summary: The UCLA ATLAS Community Health Initiative (ATLAS) has an initial target to recruit 150,000 participants from across the UCLA Health system with the goal of creating a genomic database to accelerate precision medicine efforts in California. This initiative includes a biobank embedded within the UCLA Health system that comprises de-identified genomic data linked to electronic health records (EHRs). The first freeze of data from September 2020 contains 27,987 genotyped samples imputed to 7.9 million SNPs across the genome and is linked with de-identified versions of the EHRs from UCLA Health. Here, we describe a centralized repository of the genotype data and provide tools and pipelines to perform genome- and phenome-wide association studies across a wide range of EHR-derived phenotypes and genetic ancestry groups. We demonstrate the utility of this resource through the analysis of 7 well-studied traits and recapitulate many previous genetic and phenotypic associations.

Published
2023
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7. Phenome-Wide Association Study of Polygenic Risk Score for Alzheimer’s Disease in Electronic Health Records

Author

Mingzhou Fu, UCLA Precision Health Data Discovery Repository Working Group, UCLA Precision Health ATLAS Working Group, Timothy S. Chang, Anna L. Antonio, Maryam Ariannejad, Angela M. Badillo, Brunilda Balliu, Yael Berkovich, Michael Broudy, Tony Dang, Chris Denny, Eleazar Eskin, Eran Halperin, Brian L. Hill, Ankur Jain, Vivek Katakwar, Clara Lajonchere, Clara Magyar, Sheila Minton, Ghouse Mohammed, Ariff Muhamed, Pabba Pavan, Michael A. Pfeffer, Nadav Rakocz, Akos Rudas, Rey Salonga, Timothy J. Sanders, Paul Tung, Vu Vu, Ailsa Zheng, Ruth Jhnson, Yi Ding, Alec Chiu, Jae-Hoon Sul, Sriram Sankraraman, and Bogdan Pasaniuc

Subjects
Alzheimer’s disease, polygenic risk score, phenome-wide association study, electronic health record, Mendelian randomization, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Alzheimer’s disease (AD) is the most common form of dementia and a growing public health burden in the United States. Significant progress has been made in identifying genetic risk for AD, but limited studies have investigated how AD genetic risk may be associated with other disease conditions in an unbiased fashion. In this study, we conducted a phenome-wide association study (PheWAS) by genetic ancestry groups within a large academic health system using the polygenic risk score (PRS) for AD. PRS was calculated using LDpred2 with genome-wide association study (GWAS) summary statistics. Phenotypes were extracted from electronic health record (EHR) diagnosis codes and mapped to more clinically meaningful phecodes. Logistic regression with Firth’s bias correction was used for PRS phenotype analyses. Mendelian randomization was used to examine causality in significant PheWAS associations. Our results showed a strong association between AD PRS and AD phenotype in European ancestry (OR = 1.26, 95% CI: 1.13, 1.40). Among a total of 1,515 PheWAS tests within the European sample, we observed strong associations of AD PRS with AD and related phenotypes, which include mild cognitive impairment (MCI), memory loss, and dementias. We observed a phenome-wide significant association between AD PRS and gouty arthropathy (OR = 0.90, adjusted p = 0.05). Further causal inference tests with Mendelian randomization showed that gout was not causally associated with AD. We concluded that genetic predisposition of AD was negatively associated with gout, but gout was not a causal risk factor for AD. Our study evaluated AD PRS in a real-world EHR setting and provided evidence that AD PRS may help to identify individuals who are genetically at risk of AD and other related phenotypes. We identified non-neurodegenerative diseases associated with AD PRS, which is essential to understand the genetic architecture of AD and potential side effects of drugs targeting genetic risk factors of AD. Together, these findings expand our understanding of AD genetic and clinical risk factors, which provide a framework for continued research in aging with the growing number of real-world EHR linked with genetic data.

Published
2022
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8. An Integrated, Scalable, Electronic Video Consent Process to Power Precision Health Research: Large, Population-Based, Cohort Implementation and Scalability Study

Author

Clara Lajonchere, Arash Naeim, Sarah Dry, Neil Wenger, David Elashoff, Sitaram Vangala, Antonia Petruse, Maryam Ariannejad, Clara Magyar, Liliana Johansen, Gabriela Werre, Maxwell Kroloff, and Daniel Geschwind

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundObtaining explicit consent from patients to use their remnant biological samples and deidentified clinical data for research is essential for advancing precision medicine. ObjectiveWe aimed to describe the operational implementation and scalability of an electronic universal consent process that was used to power an institutional precision health biobank across a large academic health system. MethodsThe University of California, Los Angeles, implemented the use of innovative electronic consent videos as the primary recruitment tool for precision health research. The consent videos targeted patients aged ≥18 years across ambulatory clinical laboratories, perioperative settings, and hospital settings. Each of these major areas had slightly different workflows and patient populations. Sociodemographic information, comorbidity data, health utilization data (ambulatory visits, emergency room visits, and hospital admissions), and consent decision data were collected. ResultsThe consenting approach proved scalable across 22 clinical sites (hospital and ambulatory settings). Over 40,000 participants completed the consent process at a rate of 800 to 1000 patients per week over a 2-year time period. Participants were representative of the adult University of California, Los Angeles, Health population. The opt-in rates in the perioperative (16,500/22,519, 73.3%) and ambulatory clinics (2308/3390, 68.1%) were higher than those in clinical laboratories (7506/14,235, 52.7%; P

Published
2021
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10. Electronic Video Consent to Power Precision Health Research: A Pilot Cohort Study

Author

Arash Naeim, Sarah Dry, David Elashoff, Zhuoer Xie, Antonia Petruse, Clara Magyar, Liliana Johansen, Gabriela Werre, Clara Lajonchere, and Neil Wenger

Subjects
Medicine
Abstract

BackgroundDeveloping innovative, efficient, and institutionally scalable biospecimen consent for remnant tissue that meets the National Institutes of Health consent guidelines for genomic and molecular analysis is essential for precision medicine efforts in cancer. ObjectiveThis study aims to pilot-test an electronic video consent that individuals could complete largely on their own. MethodsThe University of California, Los Angeles developed a video consenting approach designed to be comprehensive yet fast (around 5 minutes) for providing universal consent for remnant biospecimen collection for research. The approach was piloted in 175 patients who were coming in for routine services in laboratory medicine, radiology, oncology, and hospital admissions. The pilot yielded 164 completed postconsent surveys. The pilot assessed the usefulness, ease, and trustworthiness of the video consent. In addition, we explored drivers for opting in or opting out. ResultsThe pilot demonstrated that the electronic video consent was well received by patients, with high scores for usefulness, ease, and trustworthiness even among patients that opted out of participation. The revised more animated video pilot test in phase 2 was better received in terms of ease of use (P=.005) and the ability to understand the information (P

Published
2021
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11. Pre-existing conditions in Hispanics/Latinxs that are COVID-19 risk factors

Author

Timothy S. Chang, Yi Ding, Malika K. Freund, Ruth Johnson, Tommer Schwarz, Julie M. Yabu, Chad Hazlett, Jeffrey N. Chiang, David A. Wulf, Daniel H. Geschwind, Manish J. Butte, Bogdan Pasaniuc, Anna L. Antonio, Maryam Ariannejad, Angela M. Badillo, Brunilda Balliu, Yael Berkovich, Michael Broudy, Tony Dang, Chris Denny, Eleazar Eskin, Eran Halperin, Brian L. Hill, Ankur Jain, Vivek Katakwar, Clara Lajonchere, Clara Magyar, Sheila Minton, Ghouse Mohammed, Ariff Muhamed, Pabba Pavan, Michael A. Pfeffer, Nadav Rakocz, Akos Rudas, Rey Salonga, Timothy J. Sanders, Paul Tung, Vu Vu, and Ailsa Zheng

Subjects
public health, virology, Science
Abstract

Summary: Coronavirus disease 2019 (COVID-19) has exposed health care disparities in minority groups including Hispanics/Latinxs (HL). Studies of COVID-19 risk factors for HL have relied on county-level data. We investigated COVID-19 risk factors in HL using individual-level, electronic health records in a Los Angeles health system between March 9, 2020, and August 31, 2020. Of 9,287 HL tested for SARS-CoV-2, 562 were positive. HL constituted an increasing percentage of all COVID-19 positive individuals as disease severity escalated. Multiple risk factors identified in Non-Hispanic/Latinx whites (NHL-W), like renal disease, also conveyed risk in HL. Pre-existing nonrheumatic mitral valve disorder was a risk factor for HL hospitalization but not for NHL-W COVID-19 or HL influenza hospitalization, suggesting it may be a specific HL COVID-19 risk. Admission laboratory values also suggested that HL presented with a greater inflammatory response. COVID-19 risk factors for HL can help guide equitable government policies and identify at-risk populations.

Published
2021
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12. Meta-analysis fine-mapping is often miscalibrated at single-variant resolution

Author

Masahiro Kanai, Roy Elzur, Wei Zhou, Mark J. Daly, Hilary K. Finucane, Kuan-Han H. Wu, Humaira Rasheed, Kristin Tsuo, Jibril B. Hirbo, Ying Wang, Arjun Bhattacharya, Huiling Zhao, Shinichi Namba, Ida Surakka, Brooke N. Wolford, Valeria Lo Faro, Esteban A. Lopera-Maya, Kristi Läll, Marie-Julie Favé, Juulia J. Partanen, Sinéad B. Chapman, Juha Karjalainen, Mitja Kurki, Mutaamba Maasha, Ben M. Brumpton, Sameer Chavan, Tzu-Ting Chen, Michelle Daya, Yi Ding, Yen-Chen A. Feng, Lindsay A. Guare, Christopher R. Gignoux, Sarah E. Graham, Whitney E. Hornsby, Nathan Ingold, Said I. Ismail, Ruth Johnson, Triin Laisk, Kuang Lin, Jun Lv, Iona Y. Millwood, Sonia Moreno-Grau, Kisung Nam, Priit Palta, Anita Pandit, Michael H. Preuss, Chadi Saad, Shefali Setia-Verma, Unnur Thorsteinsdottir, Jasmina Uzunovic, Anurag Verma, Matthew Zawistowski, Xue Zhong, Nahla Afifi, Kawthar M. Al-Dabhani, Asma Al Thani, Yuki Bradford, Archie Campbell, Kristy Crooks, Geertruida H. de Bock, Scott M. Damrauer, Nicholas J. Douville, Sarah Finer, Lars G. Fritsche, Eleni Fthenou, Gilberto Gonzalez-Arroyo, Christopher J. Griffiths, Yu Guo, Karen A. Hunt, Alexander Ioannidis, Nomdo M. Jansonius, Takahiro Konuma, Ming Ta Michael Lee, Arturo Lopez-Pineda, Yuta Matsuda, Riccardo E. Marioni, Babak Moatamed, Marco A. Nava-Aguilar, Kensuke Numakura, Snehal Patil, Nicholas Rafaels, Anne Richmond, Agustin Rojas-Muñoz, Jonathan A. Shortt, Peter Straub, Ran Tao, Brett Vanderwerff, Manvi Vernekar, Yogasudha Veturi, Kathleen C. Barnes, Marike Boezen, Zhengming Chen, Chia-Yen Chen, Judy Cho, George Davey Smith, Lude Franke, Eric R. Gamazon, Andrea Ganna, Tom R. Gaunt, Tian Ge, Hailiang Huang, Jennifer Huffman, Nicholas Katsanis, Jukka T. Koskela, Clara Lajonchere, Matthew H. Law, Liming Li, Cecilia M. Lindgren, Ruth J.F. Loos, Stuart MacGregor, Koichi Matsuda, Catherine M. Olsen, David J. Porteous, Jordan A. Shavit, Harold Snieder, Tomohiro Takano, Richard C. Trembath, Judith M. Vonk, David C. Whiteman, Stephen J. Wicks, Cisca Wijmenga, John Wright, Jie Zheng, Xiang Zhou, Philip Awadalla, Michael Boehnke, Carlos D. Bustamante, Nancy J. Cox, Segun Fatumo, Daniel H. Geschwind, Caroline Hayward, Kristian Hveem, Eimear E. Kenny, Seunggeun Lee, Yen-Feng Lin, Hamdi Mbarek, Reedik Mägi, Hilary C. Martin, Sarah E. Medland, Yukinori Okada, Aarno V. Palotie, Bogdan Pasaniuc, Daniel J. Rader, Marylyn D. Ritchie, Serena Sanna, Jordan W. Smoller, Kari Stefansson, David A. van Heel, Robin G. Walters, Sebastian Zöllner, null Biobank of the Americas, null Biobank Japan Project, null BioMe, null BioVU, null CanPath - Ontario Health Study, null China Kadoorie Biobank Collaborative Group, null Colorado Center for Personalized Medicine, null deCODE Genetics, null Estonian Biobank, FinnGen, null Generation Scotland, null Genes & Health Research Team, null LifeLines, null Mass General Brigham Biobank, null Michigan Genomics Initiative, null National Biobank of Korea, null Penn Medicine BioBank, null Qatar Biobank, null The Qskin Sun and Health Study, null Taiwan Biobank, null The Hunt Study, null Ucla Atlas Community Health Initiative, null Uganda Genome Resource, null Uk Biobank, Alicia R. Martin, Cristen J. Willer, Benjamin M. Neale, Institute for Molecular Medicine Finland, Samuli Olli Ripatti / Principal Investigator, Complex Disease Genetics, Genomics of Neurological and Neuropsychiatric Disorders, Data Science Genetic Epidemiology Lab, Research Programs Unit, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, and University of Helsinki

Subjects
biobank, meta-analysis, genome-wide association study, fine-mapping, Genetics, 1184 Genetics, developmental biology, physiology, GWAS, 3111 Biomedicine, heterogeneity, summary statistics, Biochemistry, Genetics and Molecular Biology (miscellaneous), linkage disequilibrium, miscalibration
Abstract

Funding Information: We acknowledge all the participants and researchers of the 23 biobanks that have contributed to the GBMI. Biobank-specific acknowledgments are included in the Data S3 . We thank H. Huang, A.R. Martin, B.M. Neale, Y. Okada, K. Tsuo, J.C. Ulirsch, Y. Wang, and all the members of Finucane and Daly labs for their helpful feedback. M.K. was supported by a Nakajima Foundation Fellowship and the Masason Foundation . H.K.F. was funded by NIH grant DP5 OD024582 . Publisher Copyright: © 2022 The Author(s) Meta-analysis is pervasively used to combine multiple genome-wide association studies (GWASs). Fine-mapping of meta-analysis studies is typically performed as in a single-cohort study. Here, we first demonstrate that heterogeneity (e.g., of sample size, phenotyping, imputation) hurts calibration of meta-analysis fine-mapping. We propose a summary statistics-based quality-control (QC) method, suspicious loci analysis of meta-analysis summary statistics (SLALOM), that identifies suspicious loci for meta-analysis fine-mapping by detecting outliers in association statistics. We validate SLALOM in simulations and the GWAS Catalog. Applying SLALOM to 14 meta-analyses from the Global Biobank Meta-analysis Initiative (GBMI), we find that 67% of loci show suspicious patterns that call into question fine-mapping accuracy. These predicted suspicious loci are significantly depleted for having nonsynonymous variants as lead variant (2.7×; Fisher's exact p = 7.3 × 10−4). We find limited evidence of fine-mapping improvement in the GBMI meta-analyses compared with individual biobanks. We urge extreme caution when interpreting fine-mapping results from meta-analysis of heterogeneous cohorts.

Published
2022

13. The UCLA ATLAS Community Health Initiative: promoting precision health research in a diverse biobank

Author

Ruth Johnson, Yi Ding, Arjun Bhattacharya, Alec Chiu, Clara Lajonchere, Daniel H. Geschwind, and Bogdan Pasaniuc

Abstract

The UCLA ATLAS Community Health Initiative (ATLAS) has an initial target to recruit 150,000 participants from across the UCLA Health system, with the goal of creating a genomic database to accelerate precision medicine efforts in California. This initiative includes a biobank embedded within the UCLA Health system that comprises de-identified genomic data linked to electronic health records (EHR). The first freeze of data from September 2020 contains 27,987 genotyped samples imputed to 7.9 million SNPs across the genome and is linked with a de-identified EHR extract. This database enables the study of numerous clinically-related phenotypes within the same medical system. Here we describe a centralized repository of the genotype data and provide tools and pipelines to perform genome-wide and phenome-wide association studies across a wide range of EHR-derived phenotypes and genetic ancestry groups. We demonstrate the utility of this resource through the analysis of 7 well-studied traits and recapitulate many previous genetic and phenotypic associations.

Published
2022

14. Global Biobank Meta-analysis Initiative: powering genetic discovery across human diseases

Author

Sarah Finer, Yen-Feng Lin, Michigan Genomics Initiative, Valeria Lo Faro, Benjamin M. Neale, Nathan Ingold, Estonian Biobank, Peter Straub, Jasmina Uzunovic, Triin Laisk, Whitney E. Hornsby, Sebastian Zoellner, Takahiro Konuma, Jordan A. Shavit, Masahiro Kanai, Xue Zhong, Stephen J. Wicks, Taiwan Biobank, Arjun Bhattacharya, Nicholas J. Douville, Yi Ding, BioVU, Jennifer E. Huffman, Christopher R. Gignoux, Kristian Hveem, Serena Sanna, Brooke N. Wolford, Mitja I. Kurki, Aarno Palotie, Yukinori Okada, FinnGen, Clara Lajonchere, Ida Surakka, Mass General Brigham Biobank, Jie Zheng, Caroline Hayward, Riccardo E. Marioni, Chris Griffiths, Lars G. Fritsche, Rasheed Humaira, Ben Michael Brumpton, Kristi Läll, Kuang Lin, Jordan W. Smoller, Lude Franke, Michelle Daya, David C. Whiteman, Karen A. Hunt, Harold Snieder, Jun Lv, Stuart MacGregor, Alicia R. Martin, Juha Karjalainen, Jonathan A. Shortt, Kuan-Han H. Wu, Jibril B Hirbo, Sameer Chavan, Marie-Julie Favé, Snehal Patil, Kristy Crooks, Sarah E. Graham, Tzu-Ting Chen, Michael Preuss, Matthew Zawistowski, Yen-Chen Anne Feng, Iona Y Millwood, Cisca Wijmenga, Cristen J. Willer, Jansonius Nomdo, Kristin Tsuo, Qimr Berghofer Biobank, Koichi Matsuda, LifeLines, Shinichi Namba, Nicholas M. Rafaels, Priit Palta, Unnur Thorsteinsdottir, Chia-Yen Chen, Generation Scotland, Cecilia M. Lindgren, Huiling Zhao, Andrea Ganna, Bogdan Pasaniuc, Maasha Mutaamba, Nancy J. Cox, Zhengming Chen, George Davey Smith, Mark J. Daly, Sarah E. Medland, Yu Guo, Daniel H. Geschwind, Matthew Law, Judith M. Vonk, Eimear E. Kenny, David J. Porteous, Tian Ge, Judy H. Cho, UK Biobank, Ruth J. F. Loos, Eric R. Gamazon, Wei Zhou, Richard C. Trembath, Philip Awadalla, Kathleen C. Barnes, David A. van Heel, Kari Stefansson, Archie Campbell, Hilary C. Martin, Tom R. Gaunt, Ruth E. Johnson, Sinéad B. Chapman, Esteban A Lopera-Maya, Michael Boehnke, Brett Vanderwerff, Catherine M. Olsen, Marike Boezen, Anita Pandit, BioMe, Ran Tao, Hilary K. Finucane, Anne Richmond, Ying Wang, Liming Li, Geertruida H. de Bock, John Wright, Xiang Zhou, Robin G. Walters, Reedik Mägi, and Hailiang Huang

Subjects
Disease gene, 0303 health sciences, South asia, Collaborative network, Genome-wide association study, Computational biology, Biology, Biobank, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Baseline characteristics, Meta-analysis, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract

SummaryBiobanks are being established across the world to understand the genetic, environmental, and epidemiological basis of human diseases with the goal of better prevention and treatments. Genome-wide association studies (GWAS) have been very successful at mapping genomic loci for a wide range of human diseases and traits, but in general, lack appropriate representation of diverse ancestries - with most biobanks and preceding GWAS studies composed of individuals of European ancestries. Here, we introduce the Global Biobank Meta-analysis Initiative (GBMI) -- a collaborative network of 19 biobanks from 4 continents representing more than 2.1 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWAS generated using harmonized genotypes and phenotypes from member biobanks. GBMI brings together results from GWAS analysis across 6 main ancestry groups: approximately 33,000 of African ancestry either from Africa or from admixed-ancestry diaspora (AFR), 18,000 admixed American (AMR), 31,000 Central and South Asian (CSA), 341,000 East Asian (EAS), 1.4 million European (EUR), and 1,600 Middle Eastern (MID) individuals. In this flagship project, we generated GWASs from across 14 exemplar diseases and endpoints, including both common and less prevalent diseases that were previously understudied. Using the genetic association results, we validate that GWASs conducted in biobanks worldwide can be successfully integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics between biobanks. We demonstrate the value of this collaborative effort to improve GWAS power for diseases, increase representation, benefit understudied diseases, and improve risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of the studied traits.

Published
2021

15. Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Author

Wei Zhou, Masahiro Kanai, Kuan-Han H. Wu, Humaira Rasheed, Kristin Tsuo, Jibril B. Hirbo, Ying Wang, Arjun Bhattacharya, Huiling Zhao, Shinichi Namba, Ida Surakka, Brooke N. Wolford, Valeria Lo Faro, Esteban A. Lopera-Maya, Kristi Läll, Marie-Julie Favé, Juulia J. Partanen, Sinéad B. Chapman, Juha Karjalainen, Mitja Kurki, Mutaamba Maasha, Ben M. Brumpton, Sameer Chavan, Tzu-Ting Chen, Michelle Daya, Yi Ding, Yen-Chen A. Feng, Lindsay A. Guare, Christopher R. Gignoux, Sarah E. Graham, Whitney E. Hornsby, Nathan Ingold, Said I. Ismail, Ruth Johnson, Triin Laisk, Kuang Lin, Jun Lv, Iona Y. Millwood, Sonia Moreno-Grau, Kisung Nam, Priit Palta, Anita Pandit, Michael H. Preuss, Chadi Saad, Shefali Setia-Verma, Unnur Thorsteinsdottir, Jasmina Uzunovic, Anurag Verma, Matthew Zawistowski, Xue Zhong, Nahla Afifi, Kawthar M. Al-Dabhani, Asma Al Thani, Yuki Bradford, Archie Campbell, Kristy Crooks, Geertruida H. de Bock, Scott M. Damrauer, Nicholas J. Douville, Sarah Finer, Lars G. Fritsche, Eleni Fthenou, Gilberto Gonzalez-Arroyo, Christopher J. Griffiths, Yu Guo, Karen A. Hunt, Alexander Ioannidis, Nomdo M. Jansonius, Takahiro Konuma, Ming Ta Michael Lee, Arturo Lopez-Pineda, Yuta Matsuda, Riccardo E. Marioni, Babak Moatamed, Marco A. Nava-Aguilar, Kensuke Numakura, Snehal Patil, Nicholas Rafaels, Anne Richmond, Agustin Rojas-Muñoz, Jonathan A. Shortt, Peter Straub, Ran Tao, Brett Vanderwerff, Manvi Vernekar, Yogasudha Veturi, Kathleen C. Barnes, Marike Boezen, Zhengming Chen, Chia-Yen Chen, Judy Cho, George Davey Smith, Hilary K. Finucane, Lude Franke, Eric R. Gamazon, Andrea Ganna, Tom R. Gaunt, Tian Ge, Hailiang Huang, Jennifer Huffman, Nicholas Katsanis, Jukka T. Koskela, Clara Lajonchere, Matthew H. Law, Liming Li, Cecilia M. Lindgren, Ruth J.F. Loos, Stuart MacGregor, Koichi Matsuda, Catherine M. Olsen, David J. Porteous, Jordan A. Shavit, Harold Snieder, Tomohiro Takano, Richard C. Trembath, Judith M. Vonk, David C. Whiteman, Stephen J. Wicks, Cisca Wijmenga, John Wright, Jie Zheng, Xiang Zhou, Philip Awadalla, Michael Boehnke, Carlos D. Bustamante, Nancy J. Cox, Segun Fatumo, Daniel H. Geschwind, Caroline Hayward, Kristian Hveem, Eimear E. Kenny, Seunggeun Lee, Yen-Feng Lin, Hamdi Mbarek, Reedik Mägi, Hilary C. Martin, Sarah E. Medland, Yukinori Okada, Aarno V. Palotie, Bogdan Pasaniuc, Daniel J. Rader, Marylyn D. Ritchie, Serena Sanna, Jordan W. Smoller, Kari Stefansson, David A. van Heel, Robin G. Walters, Sebastian Zöllner, Alicia R. Martin, Cristen J. Willer, Mark J. Daly, Benjamin M. Neale, Samuli Olli Ripatti / Principal Investigator, University of Helsinki, Institute for Molecular Medicine Finland, Complex Disease Genetics, Genomics of Neurological and Neuropsychiatric Disorders, Data Science Genetic Epidemiology Lab, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, ​Basic and Translational Research and Imaging Methodology Development in Groningen (BRIDGE), Life Course Epidemiology (LCE), Damage and Repair in Cancer Development and Cancer Treatment (DARE), Perceptual and Cognitive Neuroscience (PCN), Groningen Research Institute for Asthma and COPD (GRIAC), Stem Cell Aging Leukemia and Lymphoma (SALL), and Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI)

Subjects
biobank, meta-analysis, genetic association studies, 1184 Genetics, developmental biology, physiology, GWAS, 3111 Biomedicine, biobank meta-analysis, ancestry diversity, phenotype harmonization
Abstract

Funding Information: The work of the contributing biobanks was supported by numerous grants from governmental and charitable bodies. Biobank-specific acknowledgments and more detailed acknowledgments are included in Data S2. Initiative management, S.B.C. J.C. N.J.C. M.J.D. E.E.K. A.R.M. B.M.N. Y.O. A.V.P. D.A.v.H. R.G.W. C.J.W. W.Z. and S.Z.; individual biobank analysis, A.B. Y.B. B.M.B. C.D.B. S.C. T.-T.C. K.C. S.M.D. M.D. G.H.d.B. Y.D. N.J.D. M.-J.F. Y.-C.A.F. S.F. V.L.F. L.G.F. E.R.G. T.R.G. D.H.G. C.R.G. G.G.-A. S.E.G. L.A.G. C.H. J.B.H. W.E.H. H.H. K.H. N.I. A.I. R.J. M. Kurki, J.K. N.K. E.E.K. J.T.K. M. Kanai, T.L. K.L. M.H.L. S.L. K.L. Y.-F.L. V.L.F. R.J.F.L. E.A.L.-M. A.R.-M. S.M.-G. R.M. R.E.M. H.C.M. A.R.M. Y.M. H.M. S.E.M. I.Y.M. B.M. S.M. K.N. S.N. M.A.N.-A. K.N. Y.O. P.P. A.L.-P. A.P. B.P. S.P. M.H.P. D.J.R. N.R. M.D.R. A.R. C.S. S.S. S.S.S. J.A.S. P.S. I.S. T.T. R.T. K.T. J.U. D.A.v.H. B.V. M.V. Y.V. J.M.V. R.G.W. Y.W. S.J.W. B.N.W. K.-H.H.W. M.Z. X.Z. and S.Z.; individual biobank management, N.A. A.A.T. K.M.A.-D. P.A. K.C.B. M. Boehnke, M. Boezen, C.D.B. A.C. Z.C. C.-Y.C. J.C. N.J.C. S.M.D. S.F. Y.-C.A.F. S.F. E.F. T.G. C.R.G. C.J.G. Y.G. H.H. K.A.H. K.H. S.I.I. N.M.J. N.K. E.E.K. J.T.K. C.L. M.H.L. M.T.M.L. L.L. K.L. Y.-F.L. R.J.F.L. J.L. S.M. Y.M. K.M. I.Y.M. Y.O. C.M.O. A.V.P. B.P. D.J.P. D.J.R. M.D.R. S.S. J.W.S. H.S. K.S. T.T. U.T. R.C.T. D.A.v.H. M.V. R.G.W. D.C.W. C.W. J.W. M.Z. X.Z. and S.Z.; study design and interpretation of results, A.B. M. Boehnke, M. Boezen, B.M.B. T.-T.C. C.-Y.C. M.J.D. G.D.S. N.J.D. S.F. M.-J.F. H.K.F. E.R.G. A.G. T.G. J.B.H. J.H. K.H. R.J. M.K. E.E.K. T.K. C.M.L. V.L.F. E.A.L.-M. A.R.M. S.N. B.M.N. C.M.O. J.J.P. B.P. N.R. H.R. J.A.S. I.S. K.T. D.A.v.H. R.G.W. Y.W. D.C.W. S.J.W. C.J.W. B.N.W. J.W. K.-H.H.W. M.Z. H.Z. J.Z. W.Z. X.Z. and S.Z.; drafted and edited the paper, A.B. M. Boehnke, M. Boezen, M.J.D. G.H.d.B. N.J.D. T.R.G. J.B.H. N.I. N.M.J. M.K. V.L.F. S.M. A.R.M. H.M. S.N. B.M.N. C.M.O. B.P. H.R. C.S. J.A.S. J.W.S. K.T. Y.W. D.C.W. C.J.W. K.-H.H.W. H.Z. J.Z. W.Z. and S.Z.; primary meta-analysis and quality control, M.J.D. H.K.F. M. Kanai, J.K. J.T.K. M. Kurki, M.M. B.M.N. C.J.W. K.-H.H.W. and W.Z.; drug discovery: S.N. T.K. K.-H.H.W. W.Z. and Y.O.; fine mapping, M. Kanai, W.Z. M.J.D. and H.K.F.; polygenic risk score, Y.W. S.N. E.A.L.-M. S.K. K.T. K.L. M. Kanai, W.Z. K.W. M.-J.F. L.B. P.A. P.D. V.L.F. R.M. Y.M. B.B. S.S. J.U. E.R.G. N.J.C. I.S. Y.O. A.R.M. and J.B.H.; proteome-wide Mendelian randomization, H.Z. H.R. A.B. G.H. G.D.S. B.M.B. W.Z. B.M.N. T.R.G. and J.Z.; transcriptome-wide association study, A.B. J.B.H. W.Z. J.Z. M. Kanai, B.P. E.R.G. and N.J.C.; asthma, K.T. W.Z. Y.W. M. Kanai, S.N. Y.O. B.M.N. M.J.D. and A.R.M.; heart failure, K.-H.H.W. N.J.D. B.N.W. I.S. S.E.G. J.B.H. N.J.C. M.P. R.J.F.L. M.J.D. B.M.N. W.Z. W.E.H. and C.J.W.; idiopathic pulmonary fibrosis, J.J.P. W.Z. M.J.D. J.T.K. N.J.C. and J.B.H.; primary open-angle glaucoma, V.L.F. A.B. W.Z. Y.W. K.L. M. Kanai, E.A.L.-M. P.S. R.T. X.Z. S.N. S.S. Y.O. N.I. S.M. H.S. I.S. C.W. A.R.M. E.R.G. N.M.J. N.J.C. and J.B.H.; stroke, I.S. K.-H.H.W. W.H. B.N.W. W.Z. J.E.H. A.P. B.B. A.H.S. M.E.G. R.G.W. K.H. C.K. S.Z. M.J.D. B.M.N. and C.J.W.; venous thromboembolism, B.N.W. I.S. K.-H.H.W. B.B. V.L.F. K.T. M.D. B.N. W.Z. J.A.S. and C.J.W. All authors reviewed the manuscript. M.J.D. is a founder of Maze Therapeutics. B.M.N. is a member of the scientific advisory board at Deep Genomics and a consultant for Camp4 Therapeutics, Takeda Pharmaceutical, and Biogen. The spouse of C.J.W. works at Regeneron Pharmaceuticals. C.-Y.C. is employed by Biogen. C.R.G. owns stock in 23andMe, Inc. T.R.G. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. E.E.K. has received speaker fees from Regeneron, Illumina, and 23andMe and is a member of the advisory board for Galateo Bio. R.E.M. has received speaker fees from Illumina and is a scientific advisor to the Epigenetic Clock Development Foundation. G.D.S. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. K.S. and U.T. are employed by deCODE Genetics/Amgen, Inc. J.Z. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. S.M. is a co-founder of and holds stock in Seonix Bio. Publisher Copyright: © 2022 Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)—a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.

Published
2022

16. Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative

Author

Ruth, Johnson, Yi, Ding, Vidhya, Venkateswaran, Arjun, Bhattacharya, Kristin, Boulier, Alec, Chiu, Sergey, Knyazev, Tommer, Schwarz, Malika, Freund, Lingyu, Zhan, Kathryn S, Burch, Christa, Caggiano, Brian, Hill, Nadav, Rakocz, Brunilda, Balliu, Christopher T, Denny, Jae Hoon, Sul, Noah, Zaitlen, Valerie A, Arboleda, Eran, Halperin, Sriram, Sankararaman, Manish J, Butte, Clara, Lajonchere, Daniel H, Geschwind, and Bogdan, Pasaniuc

Subjects
Asian People, Electronic Health Records, Humans, Genomics, Public Health, Biological Specimen Banks
Abstract

Large medical centers in urban areas, like Los Angeles, care for a diverse patient population and offer the potential to study the interplay between genetic ancestry and social determinants of health. Here, we explore the implications of genetic ancestry within the University of California, Los Angeles (UCLA) ATLAS Community Health Initiative-an ancestrally diverse biobank of genomic data linked with de-identified electronic health records (EHRs) of UCLA Health patients (N=36,736).We quantify the extensive continental and subcontinental genetic diversity within the ATLAS data through principal component analysis, identity-by-descent, and genetic admixture. We assess the relationship between genetically inferred ancestry (GIA) and1500 EHR-derived phenotypes (phecodes). Finally, we demonstrate the utility of genetic data linked with EHR to perform ancestry-specific and multi-ancestry genome and phenome-wide scans across a broad set of disease phenotypes.We identify 5 continental-scale GIA clusters including European American (EA), African American (AA), Hispanic Latino American (HL), South Asian American (SAA) and East Asian American (EAA) individuals and 7 subcontinental GIA clusters within the EAA GIA corresponding to Chinese American, Vietnamese American, and Japanese American individuals. Although we broadly find that self-identified race/ethnicity (SIRE) is highly correlated with GIA, we still observe marked differences between the two, emphasizing that the populations defined by these two criteria are not analogous. We find a total of 259 significant associations between continental GIA and phecodes even after accounting for individuals' SIRE, demonstrating that for some phenotypes, GIA provides information not already captured by SIRE. GWAS identifies significant associations for liver disease in the 22q13.31 locus across the HL and EAA GIA groups (HL p-value=2.32×10Overall, our results explore the interplay between SIRE and GIA within a disease context and underscore the utility of studying the genomes of diverse individuals through biobank-scale genotyping linked with EHR-based phenotyping.

Published
2021

17. Leveraging genomic diversity for discovery in an EHR-linked biobank: the UCLA ATLAS Community Health Initiative

Author

Sriram Sankararaman, Arjun Bhattacharya, Daniel H. Geschwind, Kathryn S. Burch, Eran Halperin, Brian L. Hill, Jae Hoon Sul, Brunilda Balliu, Noah Zaitlen, Manish J. Butte, Vidhya Venkateswaran, Clara Lajonchere, Bogdan Pasaniuc, Yi Ding, Christa Caggiano, Malika K. Freund, Valerie A. Arboleda, Lingyu Zhan, Alec M. Chiu, Ruth E. Johnson, Tommer Schwarz, and Nadav Rakocz

Subjects
Race (biology), Geography, Evolutionary biology, Genetic genealogy, media_common.quotation_subject, Community health, Context (language use), Disease, Social determinants of health, Biobank, Diversity (politics), media_common
Abstract

Large medical centers located in urban areas such as Los Angeles care for a diverse patient population and offer the potential to study the interplay between genomic ancestry and social determinants of health within a single medical system. Here, we introduce the UCLA ATLAS Community Health Initiative – a biobank of genomic data linked with de-identified electronic health records (EHRs) of UCLA Health patients. We leverage the unique genomic diversity of the patient population in ATLAS to explore the interplay between self-reported race/ethnicity and genetic ancestry within a disease context using phenotypes extracted from the EHR. First, we identify an extensive amount of continental and subcontinental genomic diversity within the ATLAS data that is consistent with the global diversity of Los Angeles; this includes clusters of ATLAS individuals corresponding to individuals with Korean, Japanese, Filipino, and Middle Eastern genomic ancestries. Most importantly, we find that common diseases and traits stratify across genomic ancestry clusters, thus suggesting their utility in understanding disease biology across diverse individuals. Next, we showcase the power of genetic data linked with EHR to perform ancestry-specific genome and phenome-wide scans to identify genetic factors for a variety of EHR-derived phenotypes (phecodes). For example, we find ancestry-specific associations for liver disease, and link the genetic variants with neurological and neoplastic phenotypes primarily within individuals of admixed ancestries. Overall, our results underscore the utility of studying the genomes of diverse individuals through biobank-scale genotyping efforts linked with EHR-based phenotyping.

Published
2021

18. An Integrated, Scalable, Electronic Video Consent Process to Power Precision Health Research: Large, Population-Based, Cohort Implementation and Scalability Study (Preprint)

Author

Clara Lajonchere, Arash Naeim, Sarah Dry, Neil Wenger, David Elashoff, Sitaram Vangala, Antonia Petruse, Maryam Ariannejad, Clara Magyar, Liliana Johansen, Gabriela Werre, Maxwell Kroloff, and Daniel Geschwind

Abstract

BACKGROUND Obtaining explicit consent from patients to use their remnant biological samples and deidentified clinical data for research is essential for advancing precision medicine. OBJECTIVE We aimed to describe the operational implementation and scalability of an electronic universal consent process that was used to power an institutional precision health biobank across a large academic health system. METHODS The University of California, Los Angeles, implemented the use of innovative electronic consent videos as the primary recruitment tool for precision health research. The consent videos targeted patients aged ≥18 years across ambulatory clinical laboratories, perioperative settings, and hospital settings. Each of these major areas had slightly different workflows and patient populations. Sociodemographic information, comorbidity data, health utilization data (ambulatory visits, emergency room visits, and hospital admissions), and consent decision data were collected. RESULTS The consenting approach proved scalable across 22 clinical sites (hospital and ambulatory settings). Over 40,000 participants completed the consent process at a rate of 800 to 1000 patients per week over a 2-year time period. Participants were representative of the adult University of California, Los Angeles, Health population. The opt-in rates in the perioperative (16,500/22,519, 73.3%) and ambulatory clinics (2308/3390, 68.1%) were higher than those in clinical laboratories (7506/14,235, 52.7%; PPPP CONCLUSIONS This is one of the few large-scale, electronic video–based consent implementation programs that reports a 65.5% (26,314/40,144) average overall opt-in rate across a large academic health system. This rate is higher than those previously reported for email (3.6%) and electronic biobank (50%) informed consent rates. This study demonstrates a scalable recruitment approach for population health research.

Published
2021

19. Electronic Video Consent to Power Precision Research: A Pilot Cohort Study (Preprint)

Author

Arash Naeim, Sarah Dry, David Elashoff, Zhuoer Xie, Antonia Petruse, Clara Magyar, Lilliana Johansen, Gabriela Werre, Clara Lajonchere, and Neil Wenger

Abstract

BACKGROUND Developing innovative, efficient, and institutionally scalable biospecimen consent for remnant tissue that meets the National Institutes of Health consent guidelines for genomic and molecular analysis is essential for precision medicine efforts in cancer. OBJECTIVE This study aims to pilot-test an electronic video consent that individuals could complete largely on their own. METHODS The University of California, Los Angeles developed a video consenting approach designed to be comprehensive yet fast (around 5 minutes) for providing universal consent for remnant biospecimen collection for research. The approach was piloted in 175 patients who were coming in for routine services in laboratory medicine, radiology, oncology, and hospital admissions. The pilot yielded 164 completed postconsent surveys. The pilot assessed the usefulness, ease, and trustworthiness of the video consent. In addition, we explored drivers for opting in or opting out. RESULTS The pilot demonstrated that the electronic video consent was well received by patients, with high scores for usefulness, ease, and trustworthiness even among patients that opted out of participation. The revised more animated video pilot test in phase 2 was better received in terms of ease of use (P=.005) and the ability to understand the information (PP CONCLUSIONS Efforts to better educate the community may be needed to help overcome some of the barriers in engaging individuals to participate in precision health initiatives.

Published
2021

20. Electronic Video Consent to Power Precision Health Research: A Pilot Cohort Study

Author

Clara Lajonchere, Arash Naeim, Neil S. Wenger, Sarah M. Dry, Clara E. Magyar, Gabriela Werre, Zhuoer Xie, Liliana Johansen, David Elashoff, and Antonia Petruse

Subjects
precision medicine, Medical laboratory, Medicine (miscellaneous), Health Informatics, Sample (statistics), privacy, video, efficient, electronic consent, Power (social and political), biobanking, cancer, participation, Original Paper, education, Medical education, Opting out, business.industry, pilot study, Usability, Precision medicine, Biobank, innovation, Computer Science Applications, barrier, consent, precision, business, Psychology, engagement, Cohort study
Abstract

Background Developing innovative, efficient, and institutionally scalable biospecimen consent for remnant tissue that meets the National Institutes of Health consent guidelines for genomic and molecular analysis is essential for precision medicine efforts in cancer. Objective This study aims to pilot-test an electronic video consent that individuals could complete largely on their own. Methods The University of California, Los Angeles developed a video consenting approach designed to be comprehensive yet fast (around 5 minutes) for providing universal consent for remnant biospecimen collection for research. The approach was piloted in 175 patients who were coming in for routine services in laboratory medicine, radiology, oncology, and hospital admissions. The pilot yielded 164 completed postconsent surveys. The pilot assessed the usefulness, ease, and trustworthiness of the video consent. In addition, we explored drivers for opting in or opting out. Results The pilot demonstrated that the electronic video consent was well received by patients, with high scores for usefulness, ease, and trustworthiness even among patients that opted out of participation. The revised more animated video pilot test in phase 2 was better received in terms of ease of use (P=.005) and the ability to understand the information (P Conclusions Efforts to better educate the community may be needed to help overcome some of the barriers in engaging individuals to participate in precision health initiatives.

Published
2021

21. Abstract 24: Multi-feature ensemble learning on cell-free dna for accurately detecting and locating cancer

Author

Asli Yildirim, Qingjiao Li, Denise R. Aberle, Shize Li, Steven M. Dubinett, Zorawar S. Noor, Wing Hung Wong, Shuo Li, Chun-Chi Liu, Angela Yeh, Wenyuan Li, Xiaohui Ni, He Shanshan, Frank Alber, Fengzhu Sun, Clara Lajonchere, Pin Jung Chen, Sammy Saab, Daniel H. Geschwind, Vatche G. Agopian, Ziye Wang, Xianghong Jasmine Zhou, Steven-Huy B. Han, Edward B. Garon, Gina Choi, Weihua Zeng, Paul Winograd, Sarah M. Dry, Yonggang Zhou, Zuyang Yuan, Mary L. Stackpole, Clara E. Magyar, and Samuel Wheeler French

Subjects
Cancer Research, Multi feature, Oncology, Cell-free fetal DNA, business.industry, Computer science, medicine, Cancer, Pattern recognition, Artificial intelligence, business, medicine.disease, Ensemble learning
Abstract

Early cancer detection by cell-free DNA (cfDNA) faces multiple challenges: the low fraction of tumor DNA in cfDNA, the molecular heterogeneity of cancer, and sample sizes that are too small to reflect the heterogeneous patient population. We have developed an integrated cancer detection system, CancerRadar, that addresses all three challenges. It consists of (1) a cost-effective experimental assay, cfMethyl-Seq, for genome-wide methylation profiling of cfDNA, which provides >12-fold enrichment over Whole Genome Bisulfite Sequencing (WGBS) in CpG islands; and (2) a computational platform to extract information from cfMethyl-Seq data and diagnose the patient. The platform derives cfDNA methylations, cfDNA fragment sizes, copy number variations (CNV), and microbial composition from the raw cfMethyl-Seq data, and performs multi-feature ensemble learning. We demonstrate the power of CancerRadar by detecting and locating cancer in a cohort of 275 colon, liver, lung, and stomach cancer patients and 204 non-cancer individuals. For cancer detection, we achieve a sensitivity of 85.6%± 6.7% across all stages and 80.6%±9.1% for early stages (I and II), with a specificity of 99% in both cases. These metrics are derived using leave-one-out cross-validation. During independent validation on a reserved subsample, it achieves a sensitivity of 89.1%±11.3% across all stages and 85.7%±14.2% for early stages, with a specificity of 97% (one false positive). For locating a tumor's tissue of origin (TOO), CancerRadar achieved an accuracy of 91.5%±5.0% for all stages and 89.1%±7.3% for early stages, on an independent subsample. This study is the first to integrate cfDNA methylation, cfDNA fragment size, CNV, and microbial composition analyses for cancer detection on the same patient cohort. cfDNA methylation was the most useful for detecting cancer, but including features from other categories significantly increased the performance, especially for early-stage cancer. In contrast, with respect to TOO prediction, methylation-derived features were overwhelmingly important while including other features did not further improve performance. To fully exploit the power of cfDNA methylation, we identified four types of methylation markers with different characteristics. We have also improved our previous read-level deconvolution algorithm to more accurately identify trace tumor signals. Finally, our data show that as training sample sizes increase, the detection power of CancerRadar continues to increase. Although all existing cancer detection studies are limited by training sample sizes, the CancerRadar system uniquely and cost-effectively retains the genome-wide epigenetic and genetic profiles of cancer abnormalities, thereby permitting the classification models to learn and exploit newly significant features as training cohorts grow, as well as expanding their scope to other cancer types. Citation Format: Mary Stackpole, Weihua Zeng, Shuo Li, Chun-Chi Liu, Yonggang Zhou, Shanshan He, Angela Yeh, Ziye Wang, Fengzhu Sun, Qingjiao Li, Zuyang Yuan, Asli Yildirim, Pin Jung Chen, Paul Winograd, Shize Li, Zorawar Noor, Edward Garon, Samuel French, Clara Magyar, Sarah Dry, Clara Lajonchere, Daniel Geschwind, Gina Choi, Sammy Saab, Frank Alber, Wing Hung Wong, Steven Dubinett, Denise Aberle, Vatche Agopian, Steven-Huy Han, Xiaohui Ni, Wenyuan Li, Xianghong Jasmine Zhou. Multi-feature ensemble learning on cell-free dna for accurately detecting and locating cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 24.

Published
2021

22. Strategies for Disseminating Information on Biomedical Research on Autism to Hispanic Parents

Author

Aron Munson, Abe Kazemzadeh, Barbara Y. Wheeler, Shrikanth S. Narayanan, Roxana Cruz, Cary Kreutzer, Darryl Hwang, Tara Chklovski, Sheree M. Schrager, Thomas W. Valente, Lisa Schweitzer, Irene Martinez, and Clara Lajonchere

Subjects
Adult, Male, Parents, medicine.medical_specialty, Biomedical Research, Adolescent, Autism Spectrum Disorder, media_common.quotation_subject, Information Dissemination, Health literacy, Literacy, Article, 03 medical and health sciences, 0302 clinical medicine, Patient Education as Topic, Intervention (counseling), mental disorders, Developmental and Educational Psychology, medicine, Humans, 030212 general & internal medicine, Biomedicine, media_common, Language, 030505 public health, business.industry, Knowledge level, Public health, Hispanic or Latino, Middle Aged, medicine.disease, Health Literacy, Autism, Female, 0305 other medical science, business, Psychology, Clinical psychology
Abstract

Low income Hispanic families experience multiple barriers to accessing evidence-based information on Autism Spectrum Disorders (ASD). This study utilized a mixed-strategy intervention to create access to information in published bio-medical research articles on ASD by distilling the content into parent-friendly English- and Spanish-language ASD Science Briefs and presenting them to participants using two socially-oriented dissemination methods. There was a main effect for short-term knowledge gains associated with the Science Briefs but no effect for the dissemination method. After 5 months, participants reported utilizing the information learned and 90% wanted to read more Science Briefs. These preliminary findings highlight the potential benefits of distilling biomedical research articles on ASD into parent-friendly educational products for currently underserved Hispanic parents.

Published
2017

23. Detection of Clinically Relevant Genetic Variants in Autism Spectrum Disorder by Whole-Genome Sequencing

Author

Stephen W. Scherer, Andy Shih, Clara Lajonchere, Christian R. Marshall, Jieqin Liang, Xin Jin, Guangbiao Wang, Huanming Yang, Mingze He, Geraldine Dawson, Mingbang Wang, Jennifer L. Howe, Lynette Lau, Christina Chrysler, Mohammed Uddin, Yong-hui Jiang, Ann Thompson, Thomas Nalpathamkalam, Dandan Cao, Peter Szatmari, Yingrui Li, Junpu Mei, Bhooma Thiruvahindrapuram, Lonnie Zwaigenbaum, Melissa T. Carter, Susan Walker, Zhe Wang, J. Luo, Ryan K. C. Yuen, Robert H. Ring, Yujian Shi, Jian Wang, Jun Wang, Irene Drmic, Jia Ju, Nong Chen, Daniele Merico, Xueli Wu, and Evdokia Anagnostou

Subjects
Adult, Male, Proband, Biology, medicine.disease_cause, Article, Genetic Heterogeneity, 03 medical and health sciences, CHARGE syndrome, 0302 clinical medicine, mental disorders, Genetics, medicine, Humans, Genetics(clinical), Genetic Predisposition to Disease, Child, Genetics (clinical), 030304 developmental biology, Whole genome sequencing, 0303 health sciences, Mutation, Genome, Genetic heterogeneity, High-Throughput Nucleotide Sequencing, medicine.disease, FMR1, Pedigree, 3. Good health, Fragile X syndrome, Child Development Disorders, Pervasive, Autism spectrum disorder, Female, 030217 neurology & neurosurgery
Abstract

Autism Spectrum Disorder (ASD) demonstrates high heritability and familial clustering, yet the genetic causes remain only partially understood as a result of extensive clinical and genomic heterogeneity. Whole-genome sequencing (WGS) shows promise as a tool for identifying ASD risk genes as well as unreported mutations in known loci, but an assessment of its full utility in an ASD group has not been performed. We used WGS to examine 32 families with ASD to detect de novo or rare inherited genetic variants predicted to be deleterious (loss-of-function and damaging missense mutations). Among ASD probands, we identified deleterious de novo mutations in six of 32 (19%) families and X-linked or autosomal inherited alterations in ten of 32 (31%) families (some had combinations of mutations). The proportion of families identified with such putative mutations was larger than has been previously reported; this yield was in part due to the comprehensive and uniform coverage afforded by WGS. Deleterious variants were found in four unrecognized, nine known, and eight candidate ASD risk genes. Examples include CAPRIN1 and AFF2 (both linked to FMR1, which is involved in fragile X syndrome), VIP (involved in social-cognitive deficits), and other genes such as SCN2A and KCNQ2 (linked to epilepsy), NRXN1, and CHD7, which causes ASD-associated CHARGE syndrome. Taken together, these results suggest that WGS and thorough bioinformatic analyses for de novo and rare inherited mutations will improve the detection of genetic variants likely to be associated with ASD or its accompanying clinical symptoms.

Published
2013

24. Head Circumferences in Twins With and Without Autism Spectrum Disorders

Author

Clara Lajonchere, Andrea Torres, Brianne Cohen, Judith K. Grether, Sue C. Cleveland, Janet Miller, Wendy Froehlich, Angie Fedele, Jack Collins, Tiffany Torigoe, Jennifer M. Phillips, Karen Müller Smith, Joachim Hallmayer, Linda Lotspeich, Lisa A. Croen, and Sally J Ozonoff

Subjects
Male, medicine.medical_specialty, Adolescent, Cephalometry, Twins, Audiology, behavioral disciplines and activities, Article, mental disorders, Diseases in Twins, Developmental and Educational Psychology, medicine, Humans, Statistical analysis, Child, Psychiatry, Significant difference, Macrocephaly, Craniometry, medicine.disease, Megalencephaly, Head circumference, Child Development Disorders, Pervasive, Child, Preschool, Endophenotype, Autism, Female, medicine.symptom, Psychology, Head
Abstract

To determine the genetic relationship between head circumference (HC) and Autism Spectrum Disorders (ASDs). Twin pairs with at least one twin with an ASD were assessed. HCs in affected and unaffected individuals were compared, as were HC correlations in monozygotic and dizygotic pairs. 404 subjects, ages 4–18, were included. 20 % of males and 27 % of females with an ASD had macrocephaly. Unaffected co-twins showed similar rates (15 % of males and 22 % of females). Statistical analysis revealed no significant difference in HCs between affected and unaffected twins. Twins with ASDs and unaffected co-twins have similar HCs and increased rates of macrocephaly. Correlations demonstrated partial inheritance of HCs. Thus, macrocephaly may represent an endophenotype in ASDs.

Published
2013

25. Microduplications of 16p11.2 are associated with schizophrenia

Author

Abhishek Bhandari, Patricia Roccanova, Virginia L. Willour, Shane McCarthy, Verena Krause, Ian D. Krantz, Clara Lajonchere, James S. Sutcliffe, Michael Conlon O'Donovan, Jeffrey A. Lieberman, D. Grozeva, James B. Potash, Markus M. Nöthen, Anil K. Malhotra, Layla Kassem, Olga Krastoshevsky, Jon McClellan, Elaine H. Zackai, Seungtai Yoon, Mary Claire King, Jo Steele, Vlad Kustanovich, Chad R. Haldeman-Englert, Michael Gill, Ellen Leibenluft, Jonathan Sebat, Michael John Owen, Sven Cichon, Nancy B. Spinner, Mary Kusenda, Jessica Wolff, Yoon-ha Lee, Ezra Susser, Vladimir Vacic, Nancy R. Mendell, Marcella Rietschel, Ravinesh A. Kumar, David Skuse, Nisha Chitkara, Thomas G. Schulze, Timothy J. Crow, Vladimir Makarov, Lilia M. Iakoucheva, Jaya Ganesh, B. Lakshmi, Lynn E. DeLisi, Jude Kendall, Tamim H. Shaikh, Kevin Pavon, Susan L. Christian, Kaija Puura, Sydney Gary, Anjené M. Addington, Nicholas John Craddock, Meredith Goodell, Terho Lehtimäki, T. Scott Stroup, Francis J. McMahon, Curtis K. Deutsch, George Kirov, Louise Gallagher, Patrick F. Sullivan, Tom Walsh, Diana O. Perkins, Pamela DeRosse, Justin Pearl, Paige Kaplan, Diane E. Dickel, Judith L. Rapoport, Anthony Leotta, Deborah L. Levy, and Dheeraj Malhotra

Subjects
medicine.medical_specialty, Psychosis, Biology, Article, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Gene Duplication, Internal medicine, Genetics, medicine, Humans, Genetic Predisposition to Disease, Copy-number variation, Bipolar disorder, 030304 developmental biology, 0303 health sciences, medicine.disease, Schizophrenia, Autism spectrum disorder, Meta-analysis, Cohort, Autism, Chromosomes, Human, Pair 16, 030217 neurology & neurosurgery
Abstract

Recurrent microdeletions and microduplications of a 600 kb genomic region of chromosome 16p11.2 have been implicated in childhood-onset developmental disorders1-3. Here we report the strong association of 16p11.2 microduplications with schizophrenia in two large cohorts. In the primary sample, the microduplication was detected in 12/1906 (0.63%) cases and 1/3971 (0.03%) controls (P=1.2×10-5, OR=25.8). In the replication sample, the microduplication was detected in 9/2645 (0.34%) cases and 1/2420 (0.04%) controls (P=0.022, OR=8.3). For the series combined, microduplication of 16p11.2 was associated with 14.5-fold increased risk of schizophrenia (95% C.I. [3.3, 62]). A meta-analysis of multiple psychiatric disorders showed a significant association of the microduplication with schizophrenia, bipolar disorder and autism. The reciprocal microdeletion was associated only with autism and developmental disorders. Analysis of patient clinical data showed that head circumference was significantly larger in patients with the microdeletion compared with patients with the microduplication (P = 0.0007). Our results suggest that the microduplication of 16p11.2 confers substantial risk for schizophrenia and other psychiatric disorders, whereas the reciprocal microdeletion is associated with contrasting clinical features.

Published
2009

26. A unified genetic theory for sporadic and inherited autism

Author

Jonathan Sebat, Clara Lajonchere, Vlad Kustanovich, Shanping Qiu, Xiaoyue Zhao, Catherine Lord, Paul A. Law, Michael Wigler, Anthony Leotta, Kiely Law, Daniel H. Geschwind, and Kenny Ye

Subjects
Male, Genetics, Sex Characteristics, Multidisciplinary, Databases, Factual, Models, Genetic, Offspring, Population genetics, Biological Sciences, Biology, medicine.disease, Penetrance, Risk Factors, mental disorders, Mutation (genetic algorithm), Genetic model, medicine, Humans, Autism, Female, Genetic Predisposition to Disease, Heritability of autism, Autistic Disorder, Sibling, Societies, Medical
Abstract

Autism is among the most clearly genetically determined of all cognitive-developmental disorders, with males affected more often than females. We have analyzed autism risk in multiplex families from the Autism Genetic Resource Exchange (AGRE) and find strong evidence for dominant transmission to male offspring. By incorporating generally accepted rates of autism and sibling recurrence, we find good fit for a simple genetic model in which most families fall into two types: a small minority for whom the risk of autism in male offspring is near 50%, and the vast majority for whom male offspring have a low risk. We propose an explanation that links these two types of families: sporadic autism in the low-risk families is mainly caused by spontaneous mutation with high penetrance in males and relatively poor penetrance in females; and high-risk families are from those offspring, most often females, who carry a new causative mutation but are unaffected and in turn transmit the mutation in dominant fashion to their offspring.

Published
2007

27. Attentional modulation of the gap effect

Author

Jay Pratt, Clara Lajonchere, and Richard A. Abrams

Subjects
Adult, medicine.medical_specialty, Gap effect, Adolescent, Fixation, Ocular, Stimulus (physiology), Audiology, 050105 experimental psychology, Developmental psychology, 03 medical and health sciences, 0302 clinical medicine, Attentional modulation, Reaction Time, Saccades, medicine, Humans, Attention, 0501 psychology and cognitive sciences, Disengagement theory, Disengagement, 05 social sciences, Eye movement, Sensory Systems, Fixation point, Ophthalmology, Saccade, Fixation (visual), Psychology, Photic Stimulation, 030217 neurology & neurosurgery
Abstract

The gap effect refers to a reduction in the latency of saccades to peripherally appearing targets when the fixation point disappears a short time before target appearance. The effect has been attributed to a number of potential mechanisms that function to assist in the maintenance of fixation. One such mechanism, attention, has been the focus of some disagreement in the literature regarding the gap effect. In the present study, we had subjects attend to a portion of a complex fixation stimulus. On some trials the attended portion was removed prior to onset of a saccade target whereas on other trials an unattended portion was removed. Subjects were faster to initiate saccades when the attended portion was removed, thus establishing a role of attention in the gap effect. The results have important implications for our understanding of eye movements and the gap effect.

Published
2006

28. Assessing behavioural and cognitive domains of autism spectrum disorders in rodents: current status and future perspectives

Author

Elodie Ey, Martien J H Kas, Jeffrey C. Glennon, Barbara Biemans, Frederic Esclassan, Jan K. Buitelaar, Clara Lajonchere, Robert H. Ring, Jacqueline N. Crawley, J. Peter H. Burbach, John Talpos, Lucas P. J. J. Noldus, Thomas Steckler, University Medical Center [Utrecht], Donders Institute for Brain, Cognition and Behaviour, Radboud university [Nijmegen], Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Institut Pasteur [Paris], Gènes, Synapses et Cognition, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Université Paris Diderot - Paris 7 (UPD7), Hoffmann-La Roche Ltd, Department of Psychiatry and Behavioral Sciences, University of California [Davis] (UC Davis), University of California-University of California-Center for neuroscience, Autism Genetic Resource Exchange, Autism Speaks, Keck School of Medicine [Los Angeles], University of Southern California (USC), Lilly Centre for Cognitive Neuroscience, Lilly Research Laboratories, Eli Lilly & Co. Ltd, Erl Wood Manor, Janssen Research & Development, Noldus Information Technology B.V., Institute of Neuroscience, The authors participate in the EU-AIMS project that receives support from the Innovative Medicines Initiative JointUndertaking under grant agreement no. 115300, resources of which are composed of financial contribution from the European Union 's Seventh Framework Programme (FP7/2007-2013), from the EFPIA companies in kind contribution and from Autism Speaks., European Project: 115300,EC:FP7:SP1-JTI,IMI-JU-03-2010,EU-AIMS(2012), Radboud University [Nijmegen], Institut Pasteur [Paris] (IP)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Gènes, Synapses et Cognition (CNRS - UMR3571 ), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), F. Hoffmann-La Roche [Basel], Center for neuroscience-University of California [Davis] (UC Davis), University of California (UC)-University of California (UC), Institut Pasteur [Paris]-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Animal Ecology, and Sub Animal Ecology

Subjects
Predictive validity, [SDV]Life Sciences [q-bio], Neuropsychological Tests, Developmental psychology, 03 medical and health sciences, Mice, 0302 clinical medicine, Cognition, Behavioural testing, mental disorders, medicine, Genetics, Animals, Humans, Ultrasonics, Behaviour, Animal model, Social Behavior, Food Dispensers, Automatic, 030304 developmental biology, Pharmacology, 0303 health sciences, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Social communication, Construct validity, medicine.disease, Social relation, Rats, Disease Models, Animal, Phenotype, International (English), Child Development Disorders, Pervasive, Models, Animal, Anxiety, Autism, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], medicine.symptom, Stereotyped Behavior, Vocalization, Animal, Psychology, Cognition Disorders, 030217 neurology & neurosurgery, Cognitive psychology
Abstract

Item does not contain fulltext The establishment of robust and replicable behavioural testing paradigms with translational value for psychiatric diseases is a major step forward in developing and testing etiology-directed treatment for these complex disorders. Based on the existing literature, we have generated an inventory of applied rodent behavioural testing paradigms relevant to autism spectrum disorders (ASD). This inventory focused on previously used paradigms that assess behavioural domains that are affected in ASD, such as social interaction, social communication, repetitive behaviours and behavioural inflexibility, cognition as well as anxiety behaviour. A wide range of behavioural testing paradigms for rodents were identified. However, the level of face and construct validity is highly variable. The predictive validity of these paradigms is unknown, as etiology-directed treatments for ASD are currently not on the market. To optimise these studies, future efforts should address aspects of reproducibility and take into account data about the neurodevelopmental underpinnings and trajectory of ASD. In addition, with the increasing knowledge of processes underlying ASD, such as sensory information processes and synaptic plasticity, phenotyping efforts should include multi-level automated analysis of, for example, representative task-related behavioural and electrophysiological read-outs.

Published
2014

29. Paternal age and autism are associated in a family-based sample

Author

Clara Lajonchere, Rita M. Cantor, J Furr, and J. Yoon

Subjects
Developmental disorder, Cellular and Molecular Neuroscience, Psychiatry and Mental health, medicine, Social environment, Paternal age, Autism, Sample (statistics), medicine.disease, Psychology, Family based, Molecular Biology, Developmental psychology
Published
2007

30. Individual common variants exert weak effects on the risk for autism spectrum disorderspi

Author

Naisha Shah, William M. McMahon, Barbara Parrini, Jeremy R. Parr, Thomas Bourgeron, Vanessa Hus, Gudrun Nygren, Sabine M. Klauck, John B. Vincent, Nadine M. Melhem, Jillian P. Casey, Christina Corsello, Jonathan L. Haines, Andrew D. Paterson, Raffaella Tancredi, Alistair T. Pagnamenta, Jonathan Green, Richard Delorme, Geraldine Dawson, Andrew Pickles, Carine Mantoulan, Alexander Kolevzon, Bridget A. Fernandez, Frederico Duque, Inês Sousa, Tara Paton, Kathryn Roeder, Joana Almeida, Richard Anney, Margaret A. Pericak-Vance, Joachim Hallmayer, Gerard D. Schellenberg, Sabata C. Lund, Rita M. Cantor, Daniel H. Geschwind, Janine A. Lamb, Annette Estes, Sven Bölte, Hakon Hakonarson, Gillian Hughes, Gillian Baird, John I. Nurnberger, Jessica Brian, Bernie Devlin, Roberta Igliozzi, Vera Stoppioni, Jiannis Ragoussis, Peter Szatmari, Ghazala Mirza, Eric Fombonne, Thomas H. Wassink, Emily L. Crawford, Nuala Sykes, Danielle Zurawiecki, Graham Kenny, David J. Posey, Elena Maestrini, Vlad Kustanovich, Elena Bacchelli, Veronica J. Vieland, Stephen W. Scherer, Guiomar Oliveira, Simon Wallace, John R. Gilbert, Latha Soorya, Sean Brennan, Tiago R. Magalhaes, Hilary Coon, Elizabeth A. Heron, Sabine Schlitt, Fritz Poustka, Astrid M. Vicente, Patrick Bolton, Linda Lotspeich, Nancy J. Minshew, Val C. Sheffield, Bennett L. Leventhal, Xiao-Qing Liu, Andrew Green, Joseph D. Buxbaum, Shawn Wood, Susan E. Folstein, Sean Ennis, Catarina Correia, James S. Sutcliffe, Carolyn Noakes, Ann Le Couteur, Marion Leboyer, Ann P. Thompson, Christine M. Freitag, Fred R. Volkmar, Katerina Papanikolaou, Dalila Pinto, Agatino Battaglia, Frances Lombard, Joseph Piven, Maretha de Jonge, Michael Rutter, Clara Lajonchere, Kerstin Wittemeyer, Herman van Engeland, Michael L. Cuccaro, Richard Holt, Lonnie Zwaigenbaum, Louise Gallagher, Jeff Munson, Ana Tryfon, John Tsiantis, Lambertus Klei, Christopher Gillberg, Penny Farrar, Joseph T. Glessner, Ellen M. Wijsman, Anthony P. Monaco, Wendy Roberts, Nadia Bolshakova, Cecilia Kim, Judith Miller, Stephen J. Guter, Susanne Thomson, Catherine Lord, Anthony J. Bailey, Miriam Law-Smith, Michael Gill, Christopher J. McDougle, Bernadette Rogé, Alison K. Merikangas, Jacob A. S. Vorstman, Suma Jacob, Judith Conroy, Kirsty Wing, Regina Regan, Jennifer L. Howe, Stanley F. Nelson, Edwin H. Cook, Catalina Betancur, Eftichia Duketis, Division of Mental Health and Addiction, Oslo University Hospital [Oslo], Department of Psychiatry [Pittsburgh], University of Pittsburgh School of Medicine, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), The Centre for Applied Genomics, Toronto, University of Toronto-The Hospital for sick children [Toronto] (SickKids)-Department of Molecular Genetics-McLaughlin Centre, Unidade de Neurodesenvolvimento e Autismo (UNDA), Hospital Pediatrico de Coimbra, Department of Pharmacy and Biotechnology, Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Newcomen Centre, Guy's Hospital [London], Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Goethe-Universität Frankfurt am Main, Department of Child and Adolescent Psychiatry, Institute of psychiatry, Molecular and Cellular Neurobiology, Autism Research Unit, The Hospital for sick children [Toronto] (SickKids)-University of Toronto, Academic Centre on Rare Diseases (ACoRD), University College Dublin [Dublin] (UCD), Instituto Nacional de Saùde Dr Ricardo Jorge [Portugal] (INSA), BioFIG, Center for Biodiversity, Functional and Integrative Genomics, Autism and Communicative Disorders Centre, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Department of Molecular Physiology & Biophysics and Psychiatry, Vanderbilt University [Nashville]-Centers for Human Genetics Research and Molecular Neuroscience, Vanderbilt Brain Institute, Vanderbilt University School of Medicine [Nashville], Department of Psychiatry, University Medical Center [Utrecht]-Brain Center Rudolf Magnus, Service de psychopathologie de l'enfant et de l'adolescent, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Robert Debré-Université Paris Diderot - Paris 7 (UPD7), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Department of Speech and Hearing Sciences [Washington], University of Washington [Seattle], The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], Disciplines of Genetics and Medicine, Memorial University of Newfoundland [St. John's], University of Miami School of Medicine, John P. Hussman Institute for Human Genomics, University of Miami [Coral Gables], Research Unit on Children's Psychosocial Maladjustment, Université Laval [Québec] (ULaval)-Department of Psychology, University of Gothenburg (GU), The Center for Applied Genomics, Children’s Hospital of Philadelphia (CHOP ), Manchester Academic Health Sciences Centre, Department of Disability and Human Development, University of Illinois [Chicago] (UIC), University of Illinois System-University of Illinois System, Program in Genetics and Genomic Biology, Hospital for Sick Children-University of Toronto McLaughlin Centre, Department of Psychiatry and Behavioral Sciences [Stanford], Stanford Medicine, Stanford University-Stanford University, Human Genetics Center, The University of Texas Health Science Center at Houston (UTHealth), Autism Genetic Resource Exchange, Autism Speaks, Centre for Integrated Genomic Medical Research, Manchester, University of Manchester [Manchester], Service de psychiatrie, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Hôpital Albert Chenevier, European Network of Bipolar Research Expert Centres (ENBREC), ENBREC, Newcastle University [Newcastle]-Institute of Health & Society (Child & Adolescent Psychiatry), New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU), Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse [Toulouse], Indiana University School of Medicine, Indiana University System-Indiana University System, Department of Psychiatry and Behavioral Sciences, University Department of Child Psychiatry, National and Kapodistrian University of Athens (NKUA), Department of Medicine, Manchester, University of Manchester [Manchester]-School of Epidemiology and Health Science, Department of Statistics, Carnegie Mellon University [Pittsburgh] (CMU), Octogone Unité de Recherche Interdisciplinaire (Octogone), Université Toulouse - Jean Jaurès (UT2J), Social, Genetic and Developmental Psychiatry Centre, Department of Pediatrics, University of Iowa [Iowa City]-Howard Hughes Medical-Institute Carver College of Medicine, Neuropsichiatria Infantile, Ospedale Santa Croce, Department of Psychiatry and Behavioural Neurosciences, McMaster University [Hamilton, Ontario]-Offord Centre for Child Studies, University of Toronto, Child Study Centre, Yale University School of Medicine, University of Oxford [Oxford]-Warneford Hospital, University of Alberta, MRC Social, Genetic and Developmental Psychiatry Centre (SGDP), The Institute of Psychiatry-King‘s College London, Department of Human Genetics, Los Angeles, David Geffen School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California-University of California-University of California [Los Angeles] (UCLA), University of California-University of California, Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris [Pisa], Autism Speaks and the Department of Psychiatry, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), Department of Neurology, University of California-University of California-David Geffen School of Medicine [Los Angeles], Division of Molecular Genome Analysis, German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Institutes of Neuroscience and Health and Society, Newcastle University [Newcastle], Carolina Institute for Developmental Disabilities, Pathology and Laboratory Medicine, University of Pennsylvania [Philadelphia], Carver College of Medicine [Iowa City], University of Iowa [Iowa City]-University of Iowa [Iowa City], Departments of Biostatistics and Medicine, Physiopathologie des Maladies du Système Nerveux Central, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Stanford School of Medicine [Stanford], Battelle Center for Mathematical Medicine, Ohio State University [Columbus] (OSU)-Nationwide Children's Hospital, Children’s Hospital of Philadelphia (CHOP )-Perelman School of Medicine, University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia], The Hospital for sick children [Toronto] (SickKids)-University of Toronto-Department of Molecular Genetics-McLaughlin Centre, Memorial University of Newfoundland = Université Memorial de Terre-Neuve [St. John's, Canada] (MUN), Yale School of Medicine [New Haven, Connecticut] (YSM), King‘s College London-The Institute of Psychiatry, University of California (UC)-University of California (UC)-University of California [Los Angeles] (UCLA), University of California (UC)-University of California (UC), University of California (UC)-University of California (UC)-David Geffen School of Medicine [Los Angeles], Perelman School of Medicine, University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia]-Children’s Hospital of Philadelphia (CHOP ), Anney R, Klei L, Pinto D, Almeida J, Bacchelli E, Baird G, Bolshakova N, Bölte S, Bolton PF, Bourgeron T, Brennan S, Brian J, Casey J, Conroy J, Correia C, Corsello C, Crawford EL, de Jonge M, Delorme R, Duketis E, Duque F, Estes A, Farrar P, Fernandez BA, Folstein SE, Fombonne E, Gilbert J, Gillberg C, Glessner JT, Green A, Green J, Guter SJ, Heron EA, Holt R, Howe JL, Hughes G, Hus V, Igliozzi R, Jacob S, Kenny GP, Kim C, Kolevzon A, Kustanovich V, Lajonchere CM, Lamb JA, Law-Smith M, Leboyer M, Le Couteur A, Leventhal BL, Liu XQ, Lombard F, Lord C, Lotspeich L, Lund SC, Magalhaes TR, Mantoulan C, McDougle CJ, Melhem NM, Merikangas A, Minshew NJ, Mirza GK, Munson J, Noakes C, Nygren G, Papanikolaou K, Pagnamenta AT, Parrini B, Paton T, Pickles A, Posey DJ, Poustka F, Ragoussis J, Regan R, Roberts W, Roeder K, Roge B, Rutter ML, Schlitt S, Shah N, Sheffield VC, Soorya L, Sousa I, Stoppioni V, Sykes N, Tancredi R, Thompson AP, Thomson S, Tryfon A, Tsiantis J, Van Engeland H, Vincent JB, Volkmar F, Vorstman J, Wallace S, Wing K, Wittemeyer K, Wood S, Zurawiecki D, Zwaigenbaum L, Bailey AJ, Battaglia A, Cantor RM, Coon H, Cuccaro ML, Dawson G, Ennis S, Freitag CM, Geschwind DH, Haines JL, Klauck SM, McMahon WM, Maestrini E, Miller J, Monaco AP, Nelson SF, Nurnberger JI Jr, Oliveira G, Parr JR, Pericak-Vance MA, Piven J, Schellenberg GD, Scherer SW, Vicente AM, Wassink TH, Wijsman EM, Betancur C, Buxbaum JD, Cook EH, Gallagher L, Gill M, Hallmayer J, Paterson AD, Sutcliffe JS, Szatmari P, Vieland VJ, Hakonarson H, Devlin B, University of Oxford, Pôle Enfants [CHU Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), University of Oxford-Warneford Hospital, University of Pennsylvania, University of Pennsylvania-University of Pennsylvania-Children’s Hospital of Philadelphia (CHOP ), Betancur, Catalina, and Université de Toulouse (UT)-Université de Toulouse (UT)

Subjects
Male, CNTNAP2, Genotype, Genome-wide association study, Single-nucleotide polymorphism, Nerve Tissue Proteins, [SDV.GEN] Life Sciences [q-bio]/Genetics, Biology, Language Development, Polymorphism, Single Nucleotide, 03 medical and health sciences, 0302 clinical medicine, autism spectrum disorders (ASDs), Gene Frequency, Risk Factors, mental disorders, Genetics, medicine, Humans, Genetic Predisposition to Disease, Copy-number variation, Allele, GENOME-WIDE ASSOCIATION, Child, Molecular Biology, Allele frequency, Genetics (clinical), Alleles, 030304 developmental biology, 0303 health sciences, [SDV.GEN]Life Sciences [q-bio]/Genetics, Association Studies Articles, Membrane Proteins, General Medicine, medicine.disease, Genetic architecture, Child Development Disorders, Pervasive, common variant, Perturbações do Desenvolvimento Infantil e Saúde Mental, Autism, Female, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

International audience; While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.

Published
2012

31. Genetic heritability and shared environmental factors among twin pairs with autism

Author

Joachim Hallmayer, Neil Risch, Janet Miller, Tiffany Torigoe, Lisa A. Croen, Andrea Torres, Karen S. Smith, Sally J Ozonoff, Linda Lotspeich, Jennifer M. Phillips, Clara Lajonchere, Angie Fedele, Jack Collins, Sue C. Cleveland, Brianne Cohen, and Judith K. Grether

Subjects
Adult, Male, Adolescent, Concordance, Context (language use), Epigenetics of autism, Environment, Risk Assessment, California, Article, Developmental psychology, Autism Diagnostic Observation Schedule, Sex Factors, Arts and Humanities (miscellaneous), mental disorders, medicine, Confidence Intervals, Prevalence, Humans, Genetic Predisposition to Disease, Child, Models, Genetic, Patient Selection, Twins, Monozygotic, Heritability, medicine.disease, Confidence interval, Psychiatry and Mental health, Socioeconomic Factors, Autism spectrum disorder, Child Development Disorders, Pervasive, Autism, Female, Gene-Environment Interaction, Psychology, Demography, Maternal Age
Abstract

Context: Autism is considered the most heritable of neurodevelopmental disorders, mainly because of the large difference in concordance rates between monozygotic and dizygotic twins. Objective: To provide rigorous quantitative estimates of genetic heritability of autism and the effects of shared environment. Design, Setting, and Participants: Twin pairs with at least 1 twin with an autism spectrum disorder (ASD) born between 1987 and 2004 were identified through the California Department of Developmental Services. Main Outcome Measures: Structured diagnostic assessments (Autism Diagnostic Interview–Revised and Autism Diagnostic Observation Schedule) were completed on 192 twin pairs. Concordance rates were calculated and parametric models were fitted for 2 definitions, 1 narrow (strict autism) and 1 broad (ASD). Results: For strict autism, probandwise concordance for male twins was 0.58 for 40 monozygotic pairs (95% confidence interval [CI], 0.42-0.74) and 0.21 for 31 dizygotic pairs (95% CI, 0.09-0.43); for female twins, the concordance was 0.60 for 7 monozygotic pairs (95% CI, 0.28-0.90) and 0.27 for 10 dizygotic pairs (95% CI, 0.090.69). For ASD, the probandwise concordance for male twins was 0.77 for 45 monozygotic pairs (95% CI, 0.650.86) and 0.31 for 45 dizygotic pairs (95% CI, 0.160.46); for female twins, the concordance was 0.50 for 9 monozygotic pairs (95% CI, 0.16-0.84) and 0.36 for 13 dizygotic pairs (95% CI, 0.11-0.60). A large proportion of the variance in liability can be explained by shared environmental factors (55%; 95% CI, 9%-81% for autism and 58%; 95% CI, 30%-80% for ASD) in addition to moderate genetic heritability (37%; 95% CI, 8%-84% for autism and 38%; 95% CI, 14%-67% for ASD). Conclusion: Susceptibility to ASD has moderate genetic heritability and a substantial shared twin environmental component.

Published
2011

32. Changing the Landscape of Autism Research: The Autism Genetic Resource Exchange

Author

Clara Lajonchere

Subjects
0303 health sciences, Biomedical Research, Extramural, Information Dissemination, Neuroscience(all), General Neuroscience, Computational Biology, Susceptibility gene, Biology, medicine.disease, behavioral disciplines and activities, Article, 3. Good health, Developmental psychology, 03 medical and health sciences, 0302 clinical medicine, Genetic resources, mental disorders, medicine, Autism, Humans, Genetic Predisposition to Disease, Autistic Disorder, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Autism Speaks' Autism Genetic Resource Exchange (AGRE) represents the largest private collection of genetic and phenotype data for families with ASD that is made available to qualified researchers worldwide. The availability of large and comprehensive registries that include detailed phenotype and genetic information for individuals affected with an ASD and family members is crucial for the discovery of autism susceptibility genes and the development and application of biologically based approaches to diagnosis and treatment. The model that AGRE has developed can be applied broadly to other disorders with complex etiologies.

Published
2010

33. A genome-wide scan for common alleles affecting risk for autism

Author

Veronica J. Vieland, Stephen W. Scherer, Elizabeth A. Heron, Barbara Parrini, Jeremy R. Parr, Louise Gallagher, Jeff Munson, Annemarie Poustka, Susan E. Folstein, Irene Drmic, Gudrun Nygren, John P. Rice, Jeff Salt, Simon Wallace, Geraldine Dawson, Daniel H. Geschwind, Annette Estes, Sean Brennan, Alistair T. Pagnamenta, Nancy J. Minshew, Christina Corsello, Jonathan Green, William M. McMahon, Christopher Gillberg, Kathryn Roeder, Lambertus Klei, Anath C. Lionel, Bridget A. Fernandez, Thomas Bourgeron, Ellen M. Wijsman, Gerard D. Schellenberg, Wendy Roberts, Jeremy Goldberg, Frederico Duque, Ghazala Mirza, Sean Ennis, Joana Almeida, Nadine M. Melhem, Jillian P. Casey, Roberta Igliozzi, Ricardo Segurado, Carine Mantoulan, Katy Renshaw, Kai Wang, Andrew D. Paterson, Raffaella Tancredi, Matthew Nicholas Hill, Richard Anney, Christian R. Marshall, Anthony P. Monaco, Linda Lotspeich, Marion Leboyer, Richard Holt, Andrew Pickles, Vlad Kustanovich, William M. Mahoney, Jessica Brian, Inês Sousa, Peter Szatmari, Vanessa Hus, Janine A. Lamb, Hakon Hakonarson, Lonnie Zwaigenbaum, John Tsiantis, David J. Posey, Olena Korvatska, Guillermo Casallo, Rita M. Cantor, Bhooma Thiruvahindrapduram, Nadia Bolshakova, Sven Bölte, Alison K. Merikangas, Brian L. Yaspan, Cecilia Kim, Andrew Crossett, Fritz Poustka, Danielle Zurawiecki, Agatino Battaglia, Sabata C. Lund, Ann P. Thompson, Bennett L. Leventhal, Jessica Rickaby, Zhouzhi Wang, John I. Nurnberger, Astrid M. Vicente, Maretha de Jonge, Tiago R. Magalhaes, Michael L. Cuccaro, Val C. Sheffield, Nuala Sykes, Elena Maestrini, Guiomar Oliveira, Joseph D. Buxbaum, Fred R. Volkmar, Shawn Wood, Magdalena Laskawiec, Katherine Sansom, Herman van Engeland, Jane McGrath, Thomas H. Wassink, Su H. Chu, Elena Bacchelli, Carolyn Noakes, Ann Le Couteur, Catarina Correia, Ohsuke Migita, Bernie Devlin, Hilary Coon, Gillian Baird, Joseph Piven, Tom Berney, Ana Tryfon, Abdul Noor, Patrick Bolton, Latha Soorya, Vera Stoppioni, Stephen J. Guter, Joseph T. Glessner, Michael Gill, Christopher J. McDougle, Anthony J. Bailey, Margaret A. Pericak-Vance, Joachim Hallmayer, Christine M. Freitag, Penny Farrar, Kirsty Wing, Katherine E. Tansey, Bernadette Rogé, Michael Rutter, Christina Strawbridge, Brett S. Abrahams, Kerstin Wittemeyer, Laura J. Bierut, Tara Paton, Emily L. Crawford, Jonathan L. Haines, Alexander Kolevzon, Gillian Hughes, Lili Senman, James S. Sutcliffe, John B. Gilbert, Katerina Papanikolaou, Andrew R. Carson, Lynne E Cochrane, Regina Regan, Judith Miller, Susanne Thomson, Helen McConachie, Daisuke Sato, Richard Delorme, Jiannis Ragoussis, Eric Fombonne, Clara Lajonchere, Judith Conroy, Dalila Pinto, Aparna Prasad, Naisha Shah, Stanley F. Nelson, Sabine M. Klauck, Catalina Betancur, John B. Vincent, Eftichia Duketis, Jennifer L. Howe, Edwin H. Cook, Xiao-Qing Liu, Catherine Lord, Division of Mental Health and Addiction, Oslo University Hospital [Oslo], Department of Psychiatry [Pittsburgh], University of Pittsburgh School of Medicine, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), Program in Genetics and Genomic Biology, Hospital for Sick Children-University of Toronto McLaughlin Centre, Academic Centre on Rare Diseases (ACoRD), University College Dublin [Dublin] (UCD), Instituto Nacional de Saùde Dr Ricardo Jorge [Portugal] (INSA), BioFIG, Center for Biodiversity, Functional and Integrative Genomics, Department of Neurology, University of California [Los Angeles] (UCLA), University of California-University of California-David Geffen School of Medicine [Los Angeles], University of California-University of California, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], Unidade de Neurodesenvolvimento e Autismo (UNDA), Hospital Pediatrico de Coimbra, Department of Pharmacy and Biotechnology, Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Department of Psychiatry, University of Oxford [Oxford]-Warneford Hospital, Newcomen Centre, Guy's Hospital [London], Department of Psychiatry and Behavioral Sciences [Stanford], Stanford Medicine, Stanford University-Stanford University, Child and Adolescent Mental Health, Newcastle University [Newcastle], Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Goethe-Universität Frankfurt am Main, Department of Child and Adolescent Psychiatry, Institute of psychiatry, Génétique Humaine et Fonctions Cognitives, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Autism Research Unit, University of Toronto-The Hospital for sick children [Toronto] (SickKids), Autism and Communicative Disorders Centre, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Department of Molecular Physiology & Biophysics and Psychiatry, Vanderbilt University [Nashville]-Centers for Human Genetics Research and Molecular Neuroscience, Department of Statistics, Carnegie Mellon University [Pittsburgh] (CMU), Scientific Affairs, Autism Speaks, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), University Medical Center [Utrecht]-Brain Center Rudolf Magnus, Service de psychopathologie de l'enfant et de l'adolescent, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Robert Debré-Université Paris Diderot - Paris 7 (UPD7), Department of Speech and Hearing Sciences [Washington], University of Washington [Seattle], Disciplines of Genetics and Medicine, Memorial University of Newfoundland [St. John's], John P. Hussman Institute for Human Genomics, University of Miami [Coral Gables], Department of Child Psychiatry, McGill University = Université McGill [Montréal, Canada]-Montreal Children's Hospital, McGill University Health Center [Montreal] (MUHC)-McGill University Health Center [Montreal] (MUHC), University of Gothenburg (GU), The Center for Applied Genomics, Children’s Hospital of Philadelphia (CHOP ), Department of Psychiatry and Behavioural Neurosciences, McMaster University [Hamilton, Ontario], Manchester Academic Health Sciences Centre, Institute for Juvenile Research-University of Illinois [Chicago] (UIC), University of Illinois System-University of Illinois System, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia]-Children’s Hospital of Philadelphia (CHOP ), Division of Molecular Genome Analysis, German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Human Genetics Center, The University of Texas Health Science Center at Houston (UTHealth), Department of Medicine, Autism Genetic Resource Exchange, Centre for Integrated Genomic Medical Research, Manchester, University of Manchester [Manchester], Institut Universitaire d'Hématologie (IUH), Université Paris Diderot - Paris 7 (UPD7), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Nathan Kline Institute for Psychiatric Research (NKI), Nathan Kline Institute for Psychiatric Research, New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU)-NYU Child Study Center, Centre d'Etudes et de Recherches en PsychoPathologie, Université Toulouse - Jean Jaurès (UT2J), Indiana University School of Medicine, Indiana University System-Indiana University System, Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris [Pisa], Departments of Psychiatry and Neurology, Department of Psychiatry and Behavioral Sciences, Department of Human Genetics, Los Angeles, David Geffen School of Medicine [Los Angeles], University of California-University of California-University of California [Los Angeles] (UCLA), Centre for Addiction and Mental Health, Clarke Institute, University Department of Child Psychiatry, National and Kapodistrian University of Athens (NKUA), Institutes of Neuroscience and Health and Society, Department of Medicine, Manchester, University of Manchester [Manchester]-School of Epidemiology and Health Science, Carolina Institute for Developmental Disabilities, Social, Genetic and Developmental Psychiatry Centre, Washington University in Saint Louis (WUSTL), Howard Hughes Medical-Institute Carver College of Medicine-University of Iowa [Iowa City], Neuropsichiatria Infantile, Ospedale Santa Croce, Child Study Centre, Yale University School of Medicine, Carver College of Medicine [Iowa City], University of Iowa [Iowa City]-University of Iowa [Iowa City], University of Alberta, Physiopathologie des Maladies du Système Nerveux Central, Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), Vanderbilt Brain Institute, Vanderbilt University School of Medicine [Nashville], Pathology and Laboratory Medicine, University of Pennsylvania [Philadelphia], Battelle Center for Mathematical Medicine, Ohio State University [Columbus] (OSU)-Nationwide Children's Hospital, Departments of Biostatistics and Medicine, This research was primarily supported by Autism Speaks (USA), the Health Research Board (HRB, Ireland), The Medical Research Council (MRC, UK), Genome Canada/Ontario Genomics Institute, and the Hilibrand Foundation (USA). Additional support for individual groups was provided by the US National Institutes of Health [HD055751, HD055782, HD055784, HD35465, MH52708, MH55284, MH057881, MH061009, MH06359, MH066673, MH077930, MH080647, MH081754, MH66766, NS026630, NS042165, NS049261], the Canadian Institutes for Health Research (CIHR), Assistance Publique-Hôpitaux de Paris (France), Autistica, Canada Foundation for Innovation/Ontario Innovation Trust, Deutsche Forschungsgemeinschaft (grant: Po 255/17-4) (Germany), EC Sixth FP AUTISM MOLGEN, Fundação Calouste Gulbenkian (Portugal), Fondation de France, Fondation FondaMental (France), Fondation Orange (France), Fondation pour la Recherche Médicale (France), Fundação para a Ciência e Tecnologia (Portugal), GlaxoSmithKline-CIHR Pathfinder Chair (Canada), the Hospital for Sick Children Foundation and University of Toronto (Canada), INSERM (France), Institut Pasteur (France), the Italian Ministry of Health [convention 181 of 19.10.2001], the John P Hussman Foundation (USA), McLaughlin Centre (Canada), Netherlands Organization for Scientific Research [Rubicon 825.06.031], Ontario Ministry of Research and Innovation (Canada), Royal Netherlands Academy of Arts and Sciences [TMF/DA/5801], the Seaver Foundation (USA), the Swedish Science Council, The Centre for Applied Genomics (Canada), the Utah Autism Foundation (USA) and the Wellcome Trust core award [075491/Z/04 UK]. Funding support for the Study of Addiction: Genetics and Environment (SAGE) was provided through the NIH Genes, Environment and Health Initiative [GEI] (U01 HG004422)., University of California (UC)-University of California (UC)-David Geffen School of Medicine [Los Angeles], University of California (UC)-University of California (UC), The Hospital for sick children [Toronto] (SickKids)-University of Toronto, Memorial University of Newfoundland = Université Memorial de Terre-Neuve [St. John's, Canada] (MUN), University of California (UC)-University of California (UC)-University of California [Los Angeles] (UCLA), University of Iowa [Iowa City]-Howard Hughes Medical-Institute Carver College of Medicine, Yale School of Medicine [New Haven, Connecticut] (YSM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), University of Oxford, University of Oxford-Warneford Hospital, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania-University of Pennsylvania-Children’s Hospital of Philadelphia (CHOP ), Université de Toulouse (UT)-Université de Toulouse (UT), University of Pennsylvania, Betancur, Catalina, Anney R, Klei L, Pinto D, Regan R, Conroy J, Magalhaes TR, Correia C, Abrahams BS, Sykes N, Pagnamenta AT, Almeida J, Bacchelli E, Bailey AJ, Baird G, Battaglia A, Berney T, Bolshakova N, Bölte S, Bolton PF, Bourgeron T, Brennan S, Brian J, Carson AR, Casallo G, Casey J, Chu SH, Cochrane L, Corsello C, Crawford EL, Crossett A, Dawson G, de Jonge M, Delorme R, Drmic I, Duketis E, Duque F, Estes A, Farrar P, Fernandez BA, Folstein SE, Fombonne E, Freitag CM, Gilbert J, Gillberg C, Glessner JT, Goldberg J, Green J, Guter SJ, Hakonarson H, Heron EA, Hill M, Holt R, Howe JL, Hughes G, Hus V, Igliozzi R, Kim C, Klauck SM, Kolevzon A, Korvatska O, Kustanovich V, Lajonchere CM, Lamb JA, Laskawiec M, Leboyer M, Le Couteur A, Leventhal BL, Lionel AC, Liu XQ, Lord C, Lotspeich L, Lund SC, Maestrini E, Mahoney W, Mantoulan C, Marshall CR, McConachie H, McDougle CJ, McGrath J, McMahon WM, Melhem NM, Merikangas A, Migita O, Minshew NJ, Mirza GK, Munson J, Nelson SF, Noakes C, Noor A, Nygren G, Oliveira G, Papanikolaou K, Parr JR, Parrini B, Paton T, Pickles A, Piven J, Posey DJ, Poustka A, Poustka F, Prasad A, Ragoussis J, Renshaw K, Rickaby J, Roberts W, Roeder K, Roge B, Rutter ML, Bierut LJ, Rice JP, Salt J, Sansom K, Sato D, Segurado R, Senman L, Shah N, Sheffield VC, Soorya L, Sousa I, Stoppioni V, Strawbridge C, Tancredi R, Tansey K, Thiruvahindrapduram B, Thompson AP, Thomson S, Tryfon A, Tsiantis J, Van Engeland H, Vincent JB, Volkmar F, Wallace S, Wang K, Wang Z, Wassink TH, Wing K, Wittemeyer K, Wood S, Yaspan BL, Zurawiecki D, Zwaigenbaum L, Betancur C, Buxbaum JD, Cantor RM, Cook EH, Coon H, Cuccaro ML, Gallagher L, Geschwind DH, Gill M, Haines JL, Miller J, Monaco AP, Nurnberger JI Jr, Paterson AD, Pericak-Vance MA, Schellenberg GD, Scherer SW, Sutcliffe JS, Szatmari P, Vicente AM, Vieland VJ, Wijsman EM, Devlin B, Ennis S, and Hallmayer J.

Subjects
Genome-wide association study, [SDV.GEN] Life Sciences [q-bio]/Genetics, MESH: Genotype, 0302 clinical medicine, Risk Factors, MESH: Risk Factors, Databases, Genetic, Copy-number variation, MESH: Genetic Variation, Genetics (clinical), MESH: Databases, Genetic, Genetics, 0303 health sciences, education.field_of_study, MESH: Polymorphism, Single Nucleotide, Association Studies Articles, MESH: Genetic Predisposition to Disease, General Medicine, MESH: European Continental Ancestry Group, Autism spectrum disorders, MESH: DNA Copy Number Variations, Genotyping, DNA Copy Number Variations, Genotype, Population, MESH: Autistic Disorder, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, White People, 03 medical and health sciences, Genetic variation, Humans, Genetic Predisposition to Disease, ddc:610, Allele, Autistic Disorder, SNP association, education, Molecular Biology, Alleles, MESH: Genome, Human, 030304 developmental biology, [SDV.GEN]Life Sciences [q-bio]/Genetics, MESH: Humans, Genome, Human, MESH: Alleles, Haplotype, Genetic Variation, Genetic architecture, Perturbações do Desenvolvimento Infantil e Saúde Mental, MESH: Genome-Wide Association Study, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C. Author has checked copyright TS 14.06.13 The subscript characters from the abstract have not copied across properly. TS

Published
2010

34. Genome-wide analyses of exonic copy number variants in a family-based study point to novel autism susceptibility genes

Author

Nicole B. Gidaya, Thomas Owley, Dexter Hadley, Ted Hutman, John A. Sweeney, Ana I. Alvarez Retuerto, Joseph T. Glessner, Mingyao Li, Rita M. Cantor, Edward I. Herman, James S. Sutcliffe, Struan F.A. Grant, Vlad Kustanovich, Lisa I. Sonnenblick, Gerard D. Schellenberg, Clara Lajonchere, Cecilia Kim, Marian Sigman, Kai Wang, Brett S. Abrahams, Joseph D. Buxbaum, Ingrid E. Lindquist, Daniel H. Geschwind, Maja Bucan, Marcin Imielinski, Junhyong Kim, Edwin H. Cook, John I. Nurnberger, Thomas H. Wassink, Andrew B. Singleton, Jonathan P. Bradfield, Geraldine Dawson, Hakon Hakonarson, Nancy J. Minshew, Hilary Coon, William M. McMahon, and Gibson, Greg

Subjects
Male, Cancer Research, Neuronal, Autism, Gene Dosage, Genome-wide association study, QH426-470, Genome, Cohort Studies, 0302 clinical medicine, Gene Duplication, Gene duplication, 2.1 Biological and endogenous factors, Copy-number variation, Aetiology, Child, Neural Cell Adhesion Molecules, Genetics (clinical), Genetics and Genomics/Genetics of Disease, Sequence Deletion, Genetics, 0303 health sciences, Exons, Pedigree, Mental Health, Child, Preschool, Medical genetics, Female, Research Article, medicine.medical_specialty, Adolescent, Cell Adhesion Molecules, Neuronal, Ubiquitin-Protein Ligases, Intellectual and Developmental Disabilities (IDD), Nerve Tissue Proteins, Biology, Gene dosage, Structural variation, 03 medical and health sciences, Young Adult, medicine, Humans, Genetic Predisposition to Disease, Autistic Disorder, Preschool, Molecular Biology, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, Comparative genomics, Calcium-Binding Proteins, Human Genome, Brain Disorders, Case-Control Studies, Cell Adhesion Molecules, 030217 neurology & neurosurgery, Genome-Wide Association Study, Developmental Biology
Abstract

The genetics underlying the autism spectrum disorders (ASDs) is complex and remains poorly understood. Previous work has demonstrated an important role for structural variation in a subset of cases, but has lacked the resolution necessary to move beyond detection of large regions of potential interest to identification of individual genes. To pinpoint genes likely to contribute to ASD etiology, we performed high density genotyping in 912 multiplex families from the Autism Genetics Resource Exchange (AGRE) collection and contrasted results to those obtained for 1,488 healthy controls. Through prioritization of exonic deletions (eDels), exonic duplications (eDups), and whole gene duplication events (gDups), we identified more than 150 loci harboring rare variants in multiple unrelated probands, but no controls. Importantly, 27 of these were confirmed on examination of an independent replication cohort comprised of 859 cases and an additional 1,051 controls. Rare variants at known loci, including exonic deletions at NRXN1 and whole gene duplications encompassing UBE3A and several other genes in the 15q11–q13 region, were observed in the course of these analyses. Strong support was likewise observed for previously unreported genes such as BZRAP1, an adaptor molecule known to regulate synaptic transmission, with eDels or eDups observed in twelve unrelated cases but no controls (p = 2.3×10−5). Less is known about MDGA2, likewise observed to be case-specific (p = 1.3×10−4). But, it is notable that the encoded protein shows an unexpectedly high similarity to Contactin 4 (BLAST E-value = 3×10−39), which has also been linked to disease. That hundreds of distinct rare variants were each seen only once further highlights complexity in the ASDs and points to the continued need for larger cohorts., Author Summary Autism spectrum disorders (ASDs) are common neurodevelopmental syndromes with a strong genetic component. ASDs are characterized by disturbances in social behavior, impaired verbal and nonverbal communication, as well as repetitive behaviors and/or a restricted range of interests. To identify genes likely to contribute to ASD etiology, we performed high density genotyping in 912 multiplex families from the Autism Genetics Resource Exchange (AGRE) collection and contrasted results to those obtained for 1,488 healthy controls. To enrich for variants most likely to interfere with gene function, we restricted our analyses to deletions and gains encompassing exons. Of the many genomic regions highlighted, 27 were seen to harbor rare variants in cases and not controls, both in the first phase of our analysis, and also in an independent replication cohort comprised of 859 cases and 1,051 controls. More work in a larger number of individuals will be required to determine which of the rare alleles highlighted here are indeed related to the ASDs and how they act to shape risk.

Published
2009

35. Common genetic variants on 5p14.1 associate with autism spectrum disorders

Author

Robert T. Schultz, John A. Sweeney, Rita M. Cantor, Ami Klin, Clara Lajonchere, Brett S. Abrahams, Michael L. Cuccaro, William M. McMahon, Haitao Zhang, Ted Hutman, Cecilia E. Kim, Joseph T. Glessner, Nagahide Takahashi, James S. Sutcliffe, Geraldine Dawson, Olena Korvatska, Daniel H. Geschwind, Gerard D. Schellenberg, Annette Estes, Marcin Imielinski, Marian Sigman, Susan E. Levy, Lisa I. Sonnenblick, Judith Miller, Joseph D. Buxbaum, Kai Wang, Edward I. Herman, Hakon Hakonarson, Nancy J. Minshew, Daria Salyakina, Rosetta M. Chiavacci, Edwin H. Cook, Cuiping Hou, Maja Bucan, Eric F. Rappaport, Joseph Piven, Margaret A. Pericak-Vance, Patrick M. A. Sleiman, John R. Gilbert, Edward C. Frackelton, Sally J Ozonoff, Raphael Bernier, Hilary Coon, Deqiong Ma, Matthew W. State, Hongmei Dong, Camille W. Brune, Jonathan L. Haines, John I. Nurnberger, Thomas H. Wassink, Jonathan P. Bradfield, Jeffrey Munson, Thomas Owley, Ana I. Alvarez Retuerto, Takeshi Sakurai, and Struan F.A. Grant

Subjects
Genetic Markers, Genotype, Cell Adhesion Molecules, Neuronal, Epigenetics of autism, Genome-wide association study, Biology, Polymorphism, Single Nucleotide, Article, Cohort Studies, mental disorders, Genetic variation, Pervasive developmental disorder, medicine, Cell Adhesion, Humans, Heritability of autism, Genetic Predisposition to Disease, Copy-number variation, Autistic Disorder, Genetics, Multidisciplinary, Brain, Genetic Variation, Reproducibility of Results, medicine.disease, Cadherins, Developmental disorder, Case-Control Studies, Autism, Chromosomes, Human, Pair 5, Genome-Wide Association Study
Abstract

Autism spectrum disorders (ASDs) represent a group of childhood neurodevelopmental and neuropsychiatric disorders characterized by deficits in verbal communication, impairment of social interaction, and restricted and repetitive patterns of interests and behaviour. To identify common genetic risk factors underlying ASDs, here we present the results of genome-wide association studies on a cohort of 780 families (3,101 subjects) with affected children, and a second cohort of 1,204 affected subjects and 6,491 control subjects, all of whom were of European ancestry. Six single nucleotide polymorphisms between cadherin 10 (CDH10) and cadherin 9 (CDH9)-two genes encoding neuronal cell-adhesion molecules-revealed strong association signals, with the most significant SNP being rs4307059 (P = 3.4 x 10(-8), odds ratio = 1.19). These signals were replicated in two independent cohorts, with combined P values ranging from 7.4 x 10(-8) to 2.1 x 10(-10). Our results implicate neuronal cell-adhesion molecules in the pathogenesis of ASDs, and represent, to our knowledge, the first demonstration of genome-wide significant association of common variants with susceptibility to ASDs.

Published
2008

36. Offering to Share: How to Put Heads Together in Autism Neuroimaging

Author

Stephen R. Dager, Eric Courchesne, David G. Amaral, John C. Mazziotta, Alan C. Evans, Declan G. Murphy, Robert T. Schultz, Clara Lajonchere, Martha R. Herbert, Elizabeth Aylward, Rita M. Cantor, Anders M. Dale, Matthew K. Belmonte, Guido Gerig, Christos Davatzikos, Janet E. Lainhart, Susan Levi-Pearl, Allan L. Reiss, Diane C. Chugani, Thomas A. Zeffiro, Sophia A. Colamarino, Joseph Piven, Susan Y. Bookheimer, and Nancy J. Minshew

Subjects
Scheme (programming language), Male, Interprofessional Relations, Neuropsychological Tests, Article, Developmental psychology, Developmental and Educational Psychology, medicine, Humans, Autistic Disorder, Cooperative Behavior, Child, computer.programming_language, Protocol (science), Data collection, Comparability, Brain, medicine.disease, Data science, Magnetic Resonance Imaging, Shared resource, Data sharing, Phenotype, Social Perception, Positron-Emission Tomography, Autism, Female, Raw data, Psychology, Cognition Disorders, computer
Abstract

Data sharing in autism neuroimaging presents scientific, technical, and social obstacles. We outline the desiderata for a data-sharing scheme that combines imaging with other measures of phenotype and with genetics, defines requirements for comparability of derived data and recommendations for raw data, outlines a core protocol including multispectral structural and diffusion-tensor imaging and optional extensions, provides for the collection of prospective, confound-free normative data, and extends sharing and collaborative development not only to data but to the analytical tools and methods applied to these data. A theme in these requirements is the need to preserve creative approaches and risk-taking within individual laboratories at the same time as common standards are provided for these laboratories to build on.

Published
2008
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37. Mapping autism risk loci using genetic linkage and chromosomal rearrangements

Author

Peter, Szatmari, Andrew D, Paterson, Lonnie, Zwaigenbaum, Wendy, Roberts, Jessica, Brian, Xiao-Qing, Liu, John B, Vincent, Jennifer L, Skaug, Ann P, Thompson, Lili, Senman, Lars, Feuk, Cheng, Qian, Susan E, Bryson, Marshall B, Jones, Christian R, Marshall, Stephen W, Scherer, Veronica J, Vieland, Christopher, Bartlett, La Vonne, Mangin, Rhinda, Goedken, Alberto, Segre, Margaret A, Pericak-Vance, Michael L, Cuccaro, John R, Gilbert, Harry H, Wright, Ruth K, Abramson, Catalina, Betancur, Thomas, Bourgeron, Christopher, Gillberg, Marion, Leboyer, Joseph D, Buxbaum, Kenneth L, Davis, Eric, Hollander, Jeremy M, Silverman, Joachim, Hallmayer, Linda, Lotspeich, James S, Sutcliffe, Jonathan L, Haines, Susan E, Folstein, Joseph, Piven, Thomas H, Wassink, Val, Sheffield, Daniel H, Geschwind, Maja, Bucan, W Ted, Brown, Rita M, Cantor, John N, Constantino, T Conrad, Gilliam, Martha, Herbert, Clara, Lajonchere, David H, Ledbetter, Christa, Lese-Martin, Janet, Miller, Stan, Nelson, Carol A, Samango-Sprouse, Sarah, Spence, Matthew, State, Rudolph E, Tanzi, Hilary, Coon, Geraldine, Dawson, Bernie, Devlin, Annette, Estes, Pamela, Flodman, Lambertus, Klei, William M, McMahon, Nancy, Minshew, Jeff, Munson, Elena, Korvatska, Patricia M, Rodier, Gerard D, Schellenberg, Moyra, Smith, M Anne, Spence, Chris, Stodgell, Ping Guo, Tepper, Ellen M, Wijsman, Chang-En, Yu, Bernadette, Rogé, Carine, Mantoulan, Kerstin, Wittemeyer, Annemarie, Poustka, Bärbel, Felder, Sabine M, Klauck, Claudia, Schuster, Fritz, Poustka, Sven, Bölte, Sabine, Feineis-Matthews, Evelyn, Herbrecht, Gabi, Schmötzer, John, Tsiantis, Katerina, Papanikolaou, Elena, Maestrini, Elena, Bacchelli, Francesca, Blasi, Simona, Carone, Claudio, Toma, Herman, Van Engeland, Maretha, de Jonge, Chantal, Kemner, Frederieke, Koop, Frederike, Koop, Marjolein, Langemeijer, Marjolijn, Langemeijer, Channa, Hijmans, Channa, Hijimans, Wouter G, Staal, Gillian, Baird, Patrick F, Bolton, Michael L, Rutter, Emma, Weisblatt, Jonathan, Green, Catherine, Aldred, Julie-Anne, Wilkinson, Andrew, Pickles, Ann, Le Couteur, Tom, Berney, Helen, McConachie, Anthony J, Bailey, Kostas, Francis, Gemma, Honeyman, Aislinn, Hutchinson, Jeremy R, Parr, Simon, Wallace, Anthony P, Monaco, Gabrielle, Barnby, Kazuhiro, Kobayashi, Janine A, Lamb, Ines, Sousa, Nuala, Sykes, Edwin H, Cook, Stephen J, Guter, Bennett L, Leventhal, Jeff, Salt, Catherine, Lord, Christina, Corsello, Vanessa, Hus, Daniel E, Weeks, Fred, Volkmar, Maïté, Tauber, Eric, Fombonne, Andy, Shih, Kacie J, Meyer, Department of Psychiatry and Behavioural Neurosciences, McMaster University [Hamilton, Ontario]-Offord Centre for Child Studies, The Centre for Applied Genomics, Toronto, University of Toronto-The Hospital for sick children [Toronto] (SickKids)-Department of Molecular Genetics-McLaughlin Centre, Department of Pediatrics, University of Alberta, Autism Research Unit, The Hospital for sick children [Toronto] (SickKids)-University of Toronto, Department of Psychiatry, University of Toronto, Departments of Pediatrics and Psychology, Dalhousie University [Halifax], Department of Neural and Behavioral Sciences, Pennsylvania State University (Penn State), Penn State System-Penn State System, Department of Molecular Genetics [Toronto], Battelle Center for Mathematical Medicine, Ohio State University [Columbus] (OSU)-Nationwide Children's Hospital, Department of Pathology and Laboratory Medicine, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), Department of Computer Science, University of Iowa [Iowa City], John P. Hussman Institute for Human Genomics, University of Miami [Coral Gables], W.S. Hall Psychiatric Institute, University of South Carolina [Columbia], Physiopathologie des Maladies du Système Nerveux Central, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Génétique Humaine et Fonctions Cognitives, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Gillberg Neuropsychiatry Centre [Göteborg, Sueden], Institute of Neuroscience and Physiology [Göteborg]-University of Gothenburg (GU), Institute of Child Health, University College of London [London] (UCL), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Friedman Brain Institute, Mount Sinai, Icahn School of Medicine at Mount Sinai [New York] (MSSM), Department of Neuroscience, PennState Meteorology Department, Department of Psychiatry [Pittsburgh], University of Pittsburgh School of Medicine, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), Stanford School of Medicine [Stanford], Stanford Medicine, Stanford University-Stanford University, Department of Psychiatry and Behavioral Sciences [Stanford], Vanderbilt Brain Institute, Vanderbilt University School of Medicine [Nashville], Department of Molecular Physiology & Biophysics and Psychiatry, Vanderbilt University [Nashville]-Centers for Human Genetics Research and Molecular Neuroscience, Johns Hopkins University (JHU), Carolina Institute for Developmental Disabilities, Carver College of Medicine [Iowa City], University of Iowa [Iowa City]-University of Iowa [Iowa City], University of Iowa [Iowa City]-Howard Hughes Medical-Institute Carver College of Medicine, Department of Neurology, UCLA School of Medicine, Department of Genetics, University of Pennsylvania [Philadelphia]-School of Medicine, N.Y.S. Institute for Basic Research in Developmental Disabilities, Department of Human Genetics, UCLA, University of California [Los Angeles] (UCLA), University of California-University of California-Semel Institute, Washington University in Saint Louis (WUSTL), University of Chicago, Harvard Medical School [Boston] (HMS), Autism Genetic Resource Exchange, Autism Speaks, Emory University [Atlanta, GA], Developmental Brain and Behaviour Unit, University of Southampton, Cure Autism Now, Institute of Human Genetics, Rheinische Friedrich-Wilhelms-Universität Bonn, Children's National Medical Center, The George Washington University (GW), Massachusetts General Hospital, Massachusetts General Hospital [Boston], Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris [Pisa], Autism Speaks and the Department of Psychiatry, Department of Speech and Hearing Sciences [Washington], University of Washington [Seattle], University of California [Irvine] (UCI), University of California-University of California, Department of Psychiatry and Behavioral Sciences, Department of OB/GYN, University of Rochester Medical Center, Pathology and Laboratory Medicine, University of Pennsylvania [Philadelphia], Department of Epidemiology, University of Pittsburgh (PITT), Departments of Biostatistics and Medicine, Department of Medicine, Octogone Unité de Recherche Interdisciplinaire (Octogone), Université Toulouse - Jean Jaurès (UT2J), Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse [Toulouse], University of Oxford [Oxford]-Warneford Hospital, Division of Molecular Genome Analysis, German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Goethe-Universität Frankfurt am Main, University Department of Child Psychiatry, National and Kapodistrian University of Athens (NKUA), Department of Pharmacy and Biotechnology, Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Medical Genetics Laboratory, Policlinico S. Orsola-Malpighi, University Medical Center [Utrecht]-Brain Center Rudolf Magnus, Department of Neurocognition, Maastricht University [Maastricht], Newcomen Centre, Guy's Hospital [London], Department of Child and Adolescent Psychiatry, Institute of psychiatry, MRC Social, Genetic and Developmental Psychiatry Centre (SGDP), The Institute of Psychiatry-King‘s College London, University of Cambridge Clinical School, University of Cambridge [UK] (CAM), Manchester Academic Health Sciences Centre, Department of Medicine, Manchester, University of Manchester [Manchester]-School of Epidemiology and Health Science, Newcastle University [Newcastle]-Institute of Health & Society (Child & Adolescent Psychiatry), Child and Adolescent Mental Health, Newcastle University [Newcastle], Institutes of Neuroscience and Health and Society, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], Centre for Integrated Genomic Medical Research, Manchester, University of Manchester [Manchester], Institute for Juvenile Research-University of Illinois [Chicago] (UIC), University of Illinois System-University of Illinois System, Institute for Juvenile Research, University of Illinois [Chicago] (UIC), Department of Disability and Human Development, New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU), Autism and Communicative Disorders Centre, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Human Genetics Department, SFU Discrete Mathematics Group (SFU-DMG), Simon Fraser University (SFU.ca), Child Study Centre, Yale University School of Medicine, Centre d'Endocrinologie, Maladies Osseuses, Génétique et Gynécologie Médicale, Hôpital des Enfants, CHU Toulouse [Toulouse]-CHU Toulouse [Toulouse], Department of Child Psychiatry, McGill University = Université McGill [Montréal, Canada]-Montreal Children's Hospital, McGill University Health Center [Montreal] (MUHC)-McGill University Health Center [Montreal] (MUHC), Scientific Affairs, Autism Genome Project Consortium, RS: FPN CN II, Cognitive Neuroscience, MUMC+: HZC Klinische Neurofysiologie (5), The Hospital for sick children [Toronto] (SickKids)-University of Toronto-Department of Molecular Genetics-McLaughlin Centre, University of California (UC)-University of California (UC)-Semel Institute, University of California [Irvine] (UC Irvine), University of California (UC)-University of California (UC), King‘s College London-The Institute of Psychiatry, Yale School of Medicine [New Haven, Connecticut] (YSM), Betancur, Catalina, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania-School of Medicine, University of Pennsylvania, Pôle Enfants [CHU Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), University of Oxford-Warneford Hospital, University of Oxford, Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Université de Toulouse (UT)-Université de Toulouse (UT), Szatmari P, Paterson AD, Zwaigenbaum L, Roberts W, Brian J, Liu XQ, Vincent JB, Skaug JL, Thompson AP, Senman L, Feuk L, Qian C, Bryson SE, Jones MB, Marshall CR, Scherer SW, Vieland VJ, Bartlett C, Mangin LV, Goedken R, Segre A, Pericak-Vance MA, Cuccaro ML, Gilbert JR, Wright HH, Abramson RK, Betancur C, Bourgeron T, Gillberg C, Leboyer M, Buxbaum JD, Davis KL, Hollander E, Silverman JM, Hallmayer J, Lotspeich L, Sutcliffe JS, Haines JL, Folstein SE, Piven J, Wassink TH, Sheffield V, Geschwind DH, Bucan M, Brown WT, Cantor RM, Constantino JN, Gilliam TC, Herbert M, Lajonchere C, Ledbetter DH, Lese-Martin C, Miller J, Nelson S, Samango-Sprouse CA, Spence S, State M, Tanzi RE, Coon H, Dawson G, Devlin B, Estes A, Flodman P, Klei L, McMahon WM, Minshew N, Munson J, Korvatska E, Rodier PM, Schellenberg GD, Smith M, Spence MA, Stodgell C, Tepper PG, Wijsman EM, Yu CE, Roge B, Mantoulan C, Wittemeyer K, Poustka A, Felder B, Klauck SM, Schuster C, Poustka F, Bolte S, Feineis-Matthews S, Herbrecht E, Schmotzer G, Tsiantis J, Papanikolaou K, Maestrini E, Bacchelli E, Blasi F, Carone S, Toma C, Van Engeland H, de Jonge M, Kemner C, Koop F, Langemeijer M, Hijimans C, Staal WG, Baird G, Bolton PF, Rutter ML, Weisblatt E, Green J, Aldred C, Wilkinson JA, Pickles A, Le Couteur A, Berney T, McConachie H, Bailey AJ, Francis K, Honeyman G, Hutchinson A, Parr JR, Wallace S, Monaco AP, Barnby G, Kobayashi K, Lamb JA, Sousa I, Sykes N, Cook EH, Guter SJ, Leventhal BL, Salt J, Lord C, Corsello C, Hus V, Weeks DE, Volkmar F, Tauber M, Fombonne E, and Shih A.

Subjects
Male, genetic structures, Genetic Linkage, Neurexin, [SDV.GEN] Life Sciences [q-bio]/Genetics, 0302 clinical medicine, Risk Factors, MESH: Risk Factors, Heritability of autism, Copy-number variation, MESH: Genetic Variation, Genetics, 0303 health sciences, medicine.diagnostic_test, MESH: Genetic Testing, MESH: Genetic Predisposition to Disease, Chromosome Mapping, 3. Good health, Female, MESH: Genetic Linkage, MESH: Autistic Disorder, Epigenetics of autism, Biology, Article, 03 medical and health sciences, Genetic linkage, mental disorders, medicine, Humans, MESH: Chromosome Aberrations, Family, Genetic Predisposition to Disease, Genetic Testing, Autistic Disorder, MESH: Family, 030304 developmental biology, Genetic testing, Chromosome Aberrations, [SDV.GEN]Life Sciences [q-bio]/Genetics, MESH: Humans, Genetic Variation, medicine.disease, Genetic architecture, MESH: Male, MESH: Lod Score, Autism, Lod Score, MESH: Chromosome Mapping, MESH: Female, 030217 neurology & neurosurgery
Abstract

International audience; 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.

Published
2007

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