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Record W4396578590 · doi:10.1016/j.neuron.2024.04.002

Genome sequence analyses identify novel risk loci for multiple system atrophy

2024· article· en· W4396578590 on OpenAlexfundno aff
Ruth Chia, Anindita Ray, Zalak Shah, Jinhui Ding, Paola Ruffo, Masashi Fujita, Vilas Menon, Sara Sáez-Atiénzar, Paolo Reho, Karri Kaivola, Ronald L. Walton, Regina H. Reynolds, Ramita Karra, S.S.J. Sait, Fulya Akçimen, Mónica Díez-Fairén, Ignacio Álvarez, Alessandra Fanciulli, Nadia Stefanova, Klaus Seppi, Susanne Duerr, Fabian Leys, Florian Krismer, Victoria Sidoroff, Alexander Zimprich, Walter Pirker, Olivier Rascol, Alexandra Foubert‐Samier, Wassilios G. Meissner, François Tison, Anne Pavy‐Le Traon, Maria Teresa Pellecchia, Paolo Barone, Maria Claudia Russillo, Juan Marín‐Lahoz, Jaime Kulisevsky, Soraya Torres, Pablo Mir, María Teresa Periñán, Christos Proukakis, Viorica Chelban, Lesley Wu, Yee Yen Goh, Laura Parkkinen, Christopher Kobylecki, Jennifer A. Saxon, Sara Rollinson, Emily M. Garland, Italo Biaggioni, Irene Litvan, Ileana Gabriela Sanchez Rubio, Roy N. Alcalay, Kimberly Kwei, Steven Lubbe, Qinwen Mao, Margaret E. Flanagan, Rudolph J. Castellani, Vikram Khurana, Alain Ndayisaba, Andrea Calvo, Gabriele Mora, Antonio Canosa, Gianluca Floris, Ryan C. Bohannan, Anni Moore, Lucy Norcliffe‐Kaufmann, Jose‐Alberto Palma, Horacio Kaufmann, Changyoun Kim, Michiyo Iba, Eliezer Masliah, Ted M. Dawson, Liana S. Rosenthal, Alexander Pantelyat, Marilyn S. Albert, Olga Pletniková, Juan C. Troncoso, Jon Infante, Carmen Lage, Pascual Sánchez‐Juan, Geidy E. Serrano, Thomas G. Beach, Pau Pástor, Huw R. Morris, Diego Albani, Jordi Clarimón, Gregor K. Wenning, John Hardy, Mina Ryten, Eric Topol, Ali Torkamani, Adriano Chiò, David A. Bennett, Philip L. De Jager, Philip Low, Wolfgang Singer, William P. Cheshire, Zbigniew K. Wszołek, Dennis W. Dickson, Bryan J. Traynor, J. Raphael Gibbs, Clifton L. Dalgard, Owen A. Ross, Henry Houlden, Sonja W. Scholz

Bibliographic record

VenueNeuron · 2024
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersCommon FundNational Institute of Neurological Disorders and StrokeNIH Office of the DirectorNational Heart, Lung, and Blood InstituteNational Human Genome Research InstituteInstitut de Recherches ServierBrigham Research InstituteArizona Biomedical Research CommissionAustrian Science FundH. Lundbeck A/SAlzheimer’s Research UKBrigham and Women's HospitalParkinson's UKMultiple System Atrophy CoalitionTheravance Biopharma USWellcome TrustNational Institutes of HealthRegeneron PharmaceuticalsNational Cancer InstituteServierCurePSPJohns Hopkins UniversityMichael J. Fox Foundation for Parkinson's ResearchUniversität InnsbruckArizona Department of Health ServicesParkinson's FoundationDemensförbundetBiogenNorthwestern UniversityNational Institute on AgingNational Institute for Health and Care ResearchMedical Research CouncilTeva Pharmaceutical IndustriesLouisiana Transportation Research CenterMayo ClinicMedizinische Universität InnsbruckAbbVieAlzheimer SocietyEli Lilly and CompanyNational Institute of Mental HealthTakeda Pharmaceuticals U.S.A.Sanofi
KeywordsSequence (biology)GenomeGeneticsBiologyComputational biologyAtrophyGeneEvolutionary biologyNeuroscience

Abstract

fetched live from OpenAlex

Multiple system atrophy (MSA) is an adult-onset, sporadic synucleinopathy characterized by parkinsonism, cerebellar ataxia, and dysautonomia. The genetic architecture of MSA is poorly understood, and treatments are limited to supportive measures. Here, we performed a comprehensive analysis of whole genome sequence data from 888 European-ancestry MSA cases and 7,128 controls to systematically investigate the genetic underpinnings of this understudied neurodegenerative disease. We identified four significantly associated risk loci using a genome-wide association study approach. Transcriptome-wide association analyses prioritized USP38-DT, KCTD7, and lnc-KCTD7-2 as novel susceptibility genes for MSA within these loci, and single-nucleus RNA sequence analysis found that the associated variants acted as cis-expression quantitative trait loci for multiple genes across neuronal and glial cell types. In conclusion, this study highlights the role of genetic determinants in the pathogenesis of MSA, and the publicly available data from this study represent a valuable resource for investigating synucleinopathies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

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

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 head0.081
GPT teacher head0.357
Teacher spread0.276 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations42
Published2024
Admission routes1
Has abstractyes

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