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Your search keyword '"Anne O’Donnell‐Luria"' showing total 5 results
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5 results on '"Anne O’Donnell‐Luria"'

1. Centers for Mendelian Genomics: A decade of facilitating gene discovery

Author

Samantha M. Baxter, Jennifer E. Posey, Nicole J. Lake, Nara Sobreira, Jessica X. Chong, Steven Buyske, Elizabeth E. Blue, Lisa H. Chadwick, Zeynep H. Coban-Akdemir, Kimberly F. Doheny, Colleen P. Davis, Monkol Lek, Christopher Wellington, Shalini N. Jhangiani, Mark Gerstein, Richard A. Gibbs, Richard P. Lifton, Daniel G. MacArthur, Tara C. Matise, James R. Lupski, David Valle, Michael J. Bamshad, Ada Hamosh, Shrikant Mane, Deborah A. Nickerson, Heidi L. Rehm, Anne O’Donnell-Luria, Marcia Adams, François Aguet, Gulsen Akay, Peter Anderson, Corina Antonescu, Harindra M. Arachchi, Mehmed M. Atik, Christina A. Austin-Tse, Larry Babb, Tamara J. Bacus, Vahid Bahrambeigi, Suganthi Balasubramanian, Yavuz Bayram, Arthur L. Beaudet, Christine R. Beck, John W. Belmont, Jennifer E. Below, Kaya Bilguvar, Corinne D. Boehm, Eric Boerwinkle, Philip M. Boone, Sara J. Bowne, Harrison Brand, Kati J. Buckingham, Alicia B. Byrne, Daniel Calame, Ian M. Campbell, Xiaolong Cao, Claudia Carvalho, Varuna Chander, Jaime Chang, Katherine R. Chao, Ivan K. Chinn, Declan Clarke, Ryan L. Collins, Beryl Cummings, Zain Dardas, Moez Dawood, Kayla Delano, Stephanie P. DiTroia, Harshavardhan Doddapaneni, Haowei Du, Renqian Du, Ruizhi Duan, Mohammad Eldomery, Christine M. Eng, Eleina England, Emily Evangelista, Selin Everett, Jawid Fatih, Adam Felsenfeld, Laurent C. Francioli, Christian D. Frazar, Jack Fu, Emmanuel Gamarra, Tomasz Gambin, Weiniu Gan, Mira Gandhi, Vijay S. Ganesh, Kiran V. Garimella, Laura D. Gauthier, Danielle Giroux, Claudia Gonzaga-Jauregui, Julia K. Goodrich, William W. Gordon, Sean Griffith, Christopher M. Grochowski, Shen Gu, Sanna Gudmundsson, Stacey J. Hall, Adam Hansen, Tamar Harel, Arif O. Harmanci, Isabella Herman, Kurt Hetrick, Hadia Hijazi, Martha Horike-Pyne, Elvin Hsu, Jianhong Hu, Yongqing Huang, Jameson R. Hurless, Steve Jahl, Gail P. Jarvik, Yunyun Jiang, Eric Johanson, Angad Jolly, Ender Karaca, Michael Khayat, James Knight, J. Thomas Kolar, Sushant Kumar, Seema Lalani, Kristen M. Laricchia, Kathryn E. Larkin, Suzanne M. Leal, Gabrielle Lemire, Richard A. Lewis, He Li, Hua Ling, Rachel B. Lipson, Pengfei Liu, Alysia Kern Lovgren, Francesc López-Giráldez, Melissa P. MacMillan, Brian E. Mangilog, Stacy Mano, Dana Marafi, Beth Marosy, Jamie L. Marshall, Renan Martin, Colby T. Marvin, Michelle Mawhinney, Sean McGee, Daniel J. McGoldrick, Michelle Mehaffey, Betselote Mekonnen, Xiaolu Meng, Tadahiro Mitani, Christina Y. Miyake, David Mohr, Shaine Morris, Thomas E. Mullen, David R. Murdock, Mullai Murugan, Donna M. Muzny, Ben Myers, Juanita Neira, Kevin K. Nguyen, Patrick M. Nielsen, Natalie Nudelman, Emily O’Heir, Melanie C. O’Leary, Chrissie Ongaco, Jordan Orange, Ikeoluwa A. Osei-Owusu, Ingrid S. Paine, Lynn S. Pais, Justin Paschall, Karynne Patterson, Davut Pehlivan, Benjamin Pelle, Samantha Penney, Jorge Perez de Acha Chavez, Emma Pierce-Hoffman, Cecilia M. Poli, Jaya Punetha, Aparna Radhakrishnan, Matthew A. Richardson, Eliete Rodrigues, Gwendolin T. Roote, Jill A. Rosenfeld, Erica L. Ryke, Aniko Sabo, Alice Sanchez, Isabelle Schrauwen, Daryl A. Scott, Fritz Sedlazeck, Jillian Serrano, Chad A. Shaw, Tameka Shelford, Kathryn M. Shively, Moriel Singer-Berk, Joshua D. Smith, Hana Snow, Grace Snyder, Matthew Solomonson, Rachel G. Son, Xiaofei Song, Pawel Stankiewicz, Taylorlyn Stephan, V. Reid Sutton, Abigail Sveden, Diana Cornejo Sánchez, Monica Tackett, Michael Talkowski, Machiko S. Threlkeld, Grace Tiao, Miriam S. Udler, Laura Vail, Zaheer Valivullah, Elise Valkanas, Grace E. VanNoy, Qingbo S. Wang, Gao Wang, Lu Wang, Michael F. Wangler, Nicholas A. Watts, Ben Weisburd, Jeffrey M. Weiss, Marsha M. Wheeler, Janson J. White, Clara E. Williamson, Michael W. Wilson, Wojciech Wiszniewski, Marjorie A. Withers, Dane Witmer, Lauren Witzgall, Elizabeth Wohler, Monica H. Wojcik, Isaac Wong, Jordan C. Wood, Nan Wu, Jinchuan Xing, Yaping Yang, Qian Yi, Bo Yuan, Jordan E. Zeiger, Chaofan Zhang, Peng Zhang, Yan Zhang, Xiaohong Zhang, Yeting Zhang, Shifa Zhang, Huda Zoghbi, and Igna van den Veyver

Subjects
Phenotype, Exome Sequencing, Humans, Exome, Genomics, Article, Genetic Association Studies, Genetics (clinical)
Abstract

PURPOSE: Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. METHODS: Over the past 10 years, the National Institutes of Health–supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. RESULTS: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. CONCLUSION: The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.

Published
2022
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2. Diagnostic capabilities of nanopore long-read sequencing in muscular dystrophy

Author

Christine C. Bruels, Hannah R. Littel, Audrey L. Daugherty, Seth Stafki, Elicia A. Estrella, Emily S. McGaughy, Don Truong, Jonathan P. Badalamenti, Lynn Pais, Vijay S. Ganesh, Anne O'Donnell‐Luria, Heather J. Stalker, Yang Wang, Christin Collins, Andrea Behlmann, Richard J. L. F. Lemmers, Silvère M. van der Maarel, Regina Laine, Partha S. Ghosh, Basil T. Darras, Carla D. Zingariello, Christina A. Pacak, Louis M. Kunkel, and Peter B. Kang

Subjects
Muscular Dystrophy, Duchenne, Nanopore Sequencing, Nanopores, General Neuroscience, Exome Sequencing, Humans, Neurology (clinical)
Abstract

Many individuals with muscular dystrophies remain genetically undiagnosed despite clinical diagnostic testing, including exome sequencing. Some may harbor previously undetected structural variants (SVs) or cryptic splice sites. We enrolled 10 unrelated families: nine had muscular dystrophy but lacked complete genetic diagnoses and one had an asymptomatic DMD duplication. Nano-pore genomic long-read sequencing identified previously undetected pathogenic variants in four individuals: an SV in DMD, an SV in LAMA2, and two single nucleotide variants in DMD that alter splicing. The DMD duplication in the asymptomatic individual was in tandem. Nanopore sequencing may help streamline genetic diagnostic approaches for muscular dystrophy.

Published
2022

3. Landscape of multi-nucleotide variants in 125,748 human exomes and 15,708 genomes

Author

Ruth Loos, Qingbo Wang, Anne O'Donnell-Luria, Benjamin Glaser, James Ware, John D. Rioux, ROBERTO ELOSUA, Kristian Cibulskis, Laurent Francioli, E Shyong Tai, Terho Lehtimäki, Daniel MacArthur, Irina Armean, Matthew Bown, Tiinamaija Tuomi, Jeanette Erdmann, Matthew Solomonson, Harry Sokol, Aarno Palotie, Martti Färkkilä, Ronald Ma, Olle Melander, Emilia Solinas, Tampere University, Clinical Medicine, Department of Clinical Chemistry, Centre of Excellence in Complex Disease Genetics, HUS Abdominal Center, Institute for Molecular Medicine Finland, Helsinki Institute of Life Science HiLIFE, Department of Medicine, Clinicum, Gastroenterologian yksikkö, Helsinki University Hospital Area, Research Programs Unit, Aarno Palotie / Principal Investigator, Genomics of Neurological and Neuropsychiatric Disorders, Department of Public Health, Samuli Olli Ripatti / Principal Investigator, Complex Disease Genetics, Biostatistics Helsinki, Biosciences, and Rosetrees Trust

Subjects
0301 basic medicine, Mutation rate, Science, Nonsense mutation, General Physics and Astronomy, Computational biology, Genome, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Protein sequencing, 0302 clinical medicine, DNA Mutational Analysis, Genetic variation, ELEMENTS, lcsh:Science, Exome, SIGNATURES, Exome sequencing, Polymerase, 030304 developmental biology, 0303 health sciences, Multidisciplinary, biology, Haplotype, 1184 Genetics, developmental biology, physiology, Genome Aggregation Database Production Team, Genomics, General Chemistry, FRAMEWORK, EVOLUTION, SLIPPAGE, 030104 developmental biology, Haplotypes, CpG site, DE-NOVO MUTATIONS, Genome Aggregation Database Consortium, 030220 oncology & carcinogenesis, Mutation (genetic algorithm), WHOLE-GENOME, PATTERNS, biology.protein, DNA-POLYMERASE-ZETA, REPEATS, lcsh:Q, 3111 Biomedicine, 030217 neurology & neurosurgery
Abstract

Multi-nucleotide variants (MNVs), defined as two or more nearby variants existing on the same haplotype in an individual, are a clinically and biologically important class of genetic variation. However, existing tools typically do not accurately classify MNVs, and understanding of their mutational origins remains limited. Here, we systematically survey MNVs in 125,748 whole exomes and 15,708 whole genomes from the Genome Aggregation Database (gnomAD). We identify 1,792,248 MNVs across the genome with constituent variants falling within 2 bp distance of one another, including 18,756 variants with a novel combined effect on protein sequence. Finally, we estimate the relative impact of known mutational mechanisms - CpG deamination, replication error by polymerase zeta, and polymerase slippage at repeat junctions - on the generation of MNVs. Our results demonstrate the value of haplotype-aware variant annotation, and refine our understanding of genome-wide mutational mechanisms of MNVs., Multi-nucleotide variants (MNV) are genetic variants in close proximity of each other on the same haplotype whose functional impact is difficult to predict if they reside in the same codon. Here, Wang et al. use the gnomAD dataset to assemble a catalogue of MNVs and estimate their global mutation rate.

Published
2020
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4. Mendelian etiologies identified with whole exome sequencing in cerebral palsy

Author

Maya Chopra, Dustin L. Gable, Jamie Love‐Nichols, Alexa Tsao, Shira Rockowitz, Piotr Sliz, Elizabeth Barkoudah, Lucia Bastianelli, David Coulter, Emily Davidson, Claudio DeGusmao, David Fogelman, Kathleen Huth, Paige Marshall, Donna Nimec, Jessica Solomon Sanders, Benjamin J. Shore, Brian Snyder, Scellig S. D. Stone, Ana Ubeda, Colyn Watkins, Charles Berde, Jeffrey Bolton, Catherine Brownstein, Michael Costigan, Darius Ebrahimi‐Fakhari, Abbe Lai, Anne O'Donnell‐Luria, Alex R. Paciorkowski, Anna Pinto, John Pugh, Lance Rodan, Eugene Roe, Lindsay Swanson, Bo Zhang, Michael C. Kruer, Mustafa Sahin, Annapurna Poduri, and Siddharth Srivastava

Subjects
Cohort Studies, Male, Adolescent, General Neuroscience, Cerebral Palsy, Child, Preschool, Exome Sequencing, Humans, Female, Genetic Predisposition to Disease, Neurology (clinical), Child
Abstract

Cerebral palsy (CP) is the most common childhood motor disability, yet its link to single-gene disorders is under-characterized. To explore the genetic landscape of CP, we conducted whole exome sequencing (WES) in a cohort of patients with CP.We performed comprehensive phenotyping and WES on a prospective cohort of individuals with cryptogenic CP (who meet criteria for CP; have no risk factors), non-cryptogenic CP (who meet criteria for CP; have at least one risk factor), and CP masqueraders (who could be diagnosed with CP, but have regression/progressive symptoms). We characterized motor phenotypes, ascertained medical comorbidities, and classified brain MRIs. We analyzed WES data using an institutional pipeline.We included 50 probands in this analysis (20 females, 30 males). Twenty-four had cryptogenic CP, 20 had non-cryptogenic CP, five had CP masquerader classification, and one had unknown classification. Hypotonic-ataxic subtype showed a difference in prevalence across the classification groups (p = 0.01). Twenty-six percent of participants (13/50) had a pathogenic/likely pathogenic variant in 13 unique genes (ECHS1, SATB2, ZMYM2, ADAT3, COL4A1, THOC2, SLC16A2, SPAST, POLR2A, GNAO1, PDHX, ACADM, ATL1), including one patient with two genetic disorders (ACADM, PDHX) and two patients with a SPAST-related disorder. The CP masquerader category had the highest diagnostic yield (n = 3/5, 60%), followed by the cryptogenic CP category (n = 7/24, 29%). Fifteen percent of patients with non-cryptogenic CP (n = 3/20) had a Mendelian disorder on WES.WES demonstrated a significant prevalence of Mendelian disorders in individuals clinically diagnosed with CP, including in individuals with known CP risk factors.

Published
2021

5. Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Author

Julia K. Goodrich, Moriel Singer-Berk, Rachel Son, Abigail Sveden, Jordan Wood, Eleina England, Joanne B. Cole, Ben Weisburd, Nick Watts, Lizz Caulkins, Peter Dornbos, Ryan Koesterer, Zachary Zappala, Haichen Zhang, Kristin A. Maloney, Andy Dahl, Carlos A. Aguilar-Salinas, Gil Atzmon, Francisco Barajas-Olmos, Nir Barzilai, John Blangero, Eric Boerwinkle, Lori L. Bonnycastle, Erwin Bottinger, Donald W. Bowden, Federico Centeno-Cruz, John C. Chambers, Nathalie Chami, Edmund Chan, Juliana Chan, Ching-Yu Cheng, Yoon Shin Cho, Cecilia Contreras-Cubas, Emilio Córdova, Adolfo Correa, Ralph A. DeFronzo, Ravindranath Duggirala, Josée Dupuis, Ma Eugenia Garay-Sevilla, Humberto García-Ortiz, Christian Gieger, Benjamin Glaser, Clicerio González-Villalpando, Ma Elena Gonzalez, Niels Grarup, Leif Groop, Myron Gross, Christopher Haiman, Sohee Han, Craig L. Hanis, Torben Hansen, Nancy L. Heard-Costa, Brian E. Henderson, Juan Manuel Malacara Hernandez, Mi Yeong Hwang, Sergio Islas-Andrade, Marit E. Jørgensen, Hyun Min Kang, Bong-Jo Kim, Young Jin Kim, Heikki A. Koistinen, Jaspal Singh Kooner, Johanna Kuusisto, Soo-Heon Kwak, Markku Laakso, Leslie Lange, Jong-Young Lee, Juyoung Lee, Donna M. Lehman, Allan Linneberg, Jianjun Liu, Ruth J. F. Loos, Valeriya Lyssenko, Ronald C. W. Ma, Angélica Martínez-Hernández, James B. Meigs, Thomas Meitinger, Elvia Mendoza-Caamal, Karen L. Mohlke, Andrew D. Morris, Alanna C. Morrison, Maggie C. Y. Ng, Peter M. Nilsson, Christopher J. O’Donnell, Lorena Orozco, Colin N. A. Palmer, Kyong Soo Park, Wendy S. Post, Oluf Pedersen, Michael Preuss, Bruce M. Psaty, Alexander P. Reiner, Cristina Revilla-Monsalve, Stephen S. Rich, Jerome I. Rotter, Danish Saleheen, Claudia Schurmann, Xueling Sim, Rob Sladek, Kerrin S. Small, Wing Yee So, Timothy D. Spector, Konstantin Strauch, Tim M. Strom, E. Shyong Tai, Claudia H. T. Tam, Yik Ying Teo, Farook Thameem, Brian Tomlinson, Russell P. Tracy, Tiinamaija Tuomi, Jaakko Tuomilehto, Teresa Tusié-Luna, Rob M. van Dam, Ramachandran S. Vasan, James G. Wilson, Daniel R. Witte, Tien-Yin Wong, AMP-T2D-GENES Consortia, Noël P. Burtt, Noah Zaitlen, Mark I. McCarthy, Michael Boehnke, Toni I. Pollin, Jason Flannick, Josep M. Mercader, Anne O’Donnell-Luria, Samantha Baxter, Jose C. Florez, Daniel G. MacArthur, Miriam S. Udler, Institute for Molecular Medicine Finland, Clinicum, Centre of Excellence in Complex Disease Genetics, Leif Groop Research Group, HUS Abdominal Center, University of Helsinki, Department of Medicine, Tiinamaija Tuomi Research Group, Department of Public Health, NIH - National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (Estados Unidos), NIH - National Institute of Child Health and Human Development (NICHD) (Estados Unidos), and American Diabetes Association

Subjects
0301 basic medicine, Multifactorial Inheritance, LD SCORE REGRESSION, General Physics and Astronomy, MEDICAL GENETICS, Penetrance, Disease, DISEASE, 0302 clinical medicine, Genotype, Exome, Exome sequencing, Genetics, RISK, Multidisciplinary, Molecular medicine, Endocrine system and metabolic diseases, ASSOCIATION, RARE VARIANTS, LOW-FREQUENCY, Medical genomics, Adult, Science, Biology, AMERICAN-COLLEGE, Risk Assessment, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Diabetes mellitus, medicine, Humans, Genetic Predisposition to Disease, CLINICAL EXOME, Monogenic Diabetes, Dyslipidemias, MUTATIONS, Genetic variants, General Chemistry, medicine.disease, Biomarker (cell), 030104 developmental biology, Biological Variation, Population, Diabetes Mellitus, Type 2, 3121 General medicine, internal medicine and other clinical medicine, 030217 neurology & neurosurgery, Biomarkers
Abstract

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias., Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants.

Published
2021
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