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Record W3040473777 · doi:10.1101/2020.07.06.185066

Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into the complex genetic architecture

2020· preprint· en· W3040473777 on OpenAlexafffund
Ruth Chia, Marya S. Sabir, Sara Bandrés‐Ciga, Sara Sáez-Atiénzar, Regina H. Reynolds, Emil K. Gustavsson, Ronald L. Walton, Sarah Ahmed, Coralie Viollet, Jinhui Ding, Mary B. Makarious, Mónica Díez-Fairén, Makayla Portley, Zalak Shah, Yevgeniya Abramzon, Dena Hernández, Cornelis Blauwendraat, David J. Stone, John D. Eicher, Laura Parkkinen, Olaf Ansorge, Lorraine N. Clark, Lawrence S. Honig, Karen Marder, Afina W. Lemstra, Peter St George‐Hyslop, Elisabet Londos, Kevin Morgan, Tammaryn Lashley, Thomas T. Warner, Zane Jaunmuktane, Douglas Galasko, Isabel Santana, Pentti J. Tienari, Liisa Myllykangas, Minna Oinas, Nigel J. Cairns, John C. Morris, Glenda M. Halliday, Vivianna M. Van Deerlin, John Q. Trojanowski, Maurizio Grassano, Andrea Calvo, Gabriele Mora, Antonio Canosa, Gianluca Floris, Ryan C. Bohannan, Francesca Brett, Ziv Gan‐Or, Joshua T. Geiger, Anni Moore, Patrick May, Rejko Krüger, David S. Goldstein, Grisel Lopez, Nahid Tayebi, Ellen Sidransky, Jose‐Alberto Palma, Horacio Kaufmann, Vikram G. Shakkottai, Matthew Perkins, Kathy L. Newell, Thomas Gasser, Claudia Schulte, Francesco Landi, Erika Salvi, Daniele Cusi, Eliezer Masliah, Ronald C. Kim, Chad A. Caraway, Ed Monuki, Maura Brunetti, Ted M. Dawson, Liana S. Rosenthal, Marilyn S. Albert, Olga Pletnikova, Juan C. Troncoso, Margaret E. Flanagan, Qinwen Mao, Eileen H. Bigio, Eloy Rodríguez‐Rodríguez, Jon Infante, Carmen Lage, Isabel González Aramburu, Pascual Sánchez‐Juan, Bernardino Ghetti, Julia Keith, Sandra E. Black, Mario Masellis, Ekaterina Rogaeva, Charles Duyckaerts, Alexis Brice, Suzanne Lesage, Georgia Xiromerisiou, Matthew J. Barrett, Bension S. Tilley, Steve Gentleman, Giancarlo Logroscino, Geidy E. Serrano, Thomas G. Beach, Ian G. McKeith, Alan Thomas, Johannes Attems, Christopher M. Morris, Seth Love, Claire Troakes, Safa Al‐Sarraj, Angela Hodges, Dag Aarsland, Gregory Klein, Scott M. Kaiser, Randy Woltjer, Pau Pástor, Lynn M. Bekris, James B. Leverenz, Lilah M. Besser, Amanda Kuzma, Alan E. Renton, Alison Goate, David A. Bennett, Clemens R. Scherzer, Huw R. Morris, Raffaele Ferrari, Diego Albani, Stuart Pickering‐Brown, Kelley Faber, Walter A. Kukull, Estrella Morenas‐Rodríguez, Alberto Lleó, Juan Fortea, Daniel Alcolea, Jordi Clarimón, Michael A. Nalls, Luigi Ferrucci, Susan M. Resnick, Toshiko Tanaka, Tatiana Foroud, Caroline Graff, Zbigniew K. Wszołek, Tanis J. Ferman, Bradley F. Boeve, John Hardy, Eric Topol, Ali Torkamani, Andrew Singleton, Mina Ryten, Dennis W. Dickson, Adriano Chiò, Owen A. Ross, J. Raphael Gibbs, Clifton L. Dalgard, Bryan J. Traynor, Sonja W. Scholz

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsHeart and Stroke FoundationSunnybrook Health Science CentreOccupational Cancer Research CentreHealth Sciences CentreMcGill UniversityMontreal Neurological Institute and HospitalUniversity of Toronto
FundersNational Center for Advancing Translational SciencesDemensförbundetNational Heart, Lung, and Blood InstituteInstituto de Salud Carlos IIIAlzheimer's SocietyCanadian Institutes of Health ResearchNational Institutes of HealthUniversity of TorontoCharles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St. LouisNewcastle UniversityEuropean Regional Development FundKing's College LondonNational Institute on AgingNational Institute for Health and Care ResearchMedical Research CouncilVerily Life SciencesMinistero della SaluteSol Goldman Charitable TrustCollege of Pharmacy, University of MichiganNational Institute of Neurological Disorders and StrokeSunovionArizona Biomedical Research CommissionGeorgia Clinical and Translational Science AllianceWellcome TrustBroad InstituteSanofiSouth London and Maudsley NHS Foundation TrustCOPD FoundationMayo ClinicUniversity of MichiganMassachusetts General HospitalLittle Family FoundationMinistero dell’Istruzione, dell’Università e della RicercaJohns Hopkins UniversityBrigham and Women's HospitalArizona Department of Health ServicesNational Human Genome Research InstituteCelgeneNational Institute on Minority Health and Health DisparitiesAstraZenecaJackson State UniversityMississippi State Department of HealthMichael J. Fox Foundation for Parkinson's ResearchConsortium canadien en neurodégénérescence associée au vieillissementAmerican Parkinson Disease AssociationNorthwestern UniversityPfizerFoundation for the National Institutes of HealthAmerican Heart AssociationCenter for Individualized Medicine, Mayo ClinicLewy Body Dementia Association
KeywordsGenetic architectureLewy bodyDementiaGenome-wide association studyBiologyDiseaseGeneticsGenomeDementia with Lewy bodiesGenetic associationComputational biologyGeneEvolutionary biologyQuantitative trait locusMedicineSingle-nucleotide polymorphismGenotypePathology

Abstract

fetched live from OpenAlex

Abstract The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA . Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer’s and Parkinson’s disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.205
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2020
Admission routes2
Has abstractyes

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