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Record W2061194981 · doi:10.1126/science.aaa3650

Exome sequencing in amyotrophic lateral sclerosis identifies risk genes and pathways

2015· article· en· W2061194981 on OpenAlexaff
Elizabeth T. Cirulli, Brittany N. Lasseigne, Slavé Petrovski, Peter C. Sapp, Patrick A. Dion, Claire S. Leblond, Julien Couthouis, Yifan Lu, Quanli Wang, Brian J. Krueger, Zhong Ren, Jonathan Keebler, Yujun Han, Shawn Levy, Braden Boone, Jack R. Wimbish, Lindsay L. Waite, John P. Carulli, Kelly L. Williams, John F. Staropoli, Winnie Xin, Alessandra Chesi, Alya R. Raphael, Diane McKenna‐Yasek, Janet Cady, J.M.B.V. de Jong, Kevin P. Kenna, Bradley Smith, Simon Topp, Jack W. Miller, Soragia Athina Gkazi, Ammar Al‐Chalabi, Leonard H. van den Berg, Jan H. Veldink, Vincenzo Silani, Nicola Ticozzi, Christopher E. Shaw, Robert H. Baloh, Stanley H. Appel, Ericka Simpson, Clotilde Lagier‐Tourenne, Stefan M. Pulst, Summer Gibson, John Q. Trojanowski, Lauren Elman, Leo McCluskey, Murray Grossman, Neil A. Shneider, Wendy K. Chung, John Ravits, Jonathan D. Glass, Katherine B. Sims, Vivianna M. Van Deerlin, Tom Maniatis, Sebastian Hayes, Alban Ordureau, Sharan Swarup, John E. Landers, Frank Baas, Andrew S. Allen, Richard Bedlack, J. Wade Harper, Aaron D. Gitler, Guy A. Rouleau, Robert H. Brown, Matthew B. Harms, Gregory M. Cooper, Tim Harris, R Myers, David B. Goldstein

Bibliographic record

VenueScience · 2015
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Center for Advancing Translational SciencesNational Institute on AgingMotor Neurone Disease AssociationNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesMedical Research CouncilNational Institute for Health and Care ResearchWellcome Trust
KeywordsOptineurinAmyotrophic lateral sclerosisExome sequencingGeneSequestosome 1TANK-binding kinase 1ExomeBiologyGeneticsRefSeqInnate immune systemAutophagyDiseaseMutationBioinformaticsMedicineGenomePathologyImmune system

Abstract

fetched live from OpenAlex

Amyotrophic lateral sclerosis (ALS) is a devastating neurological disease with no effective treatment. We report the results of a moderate-scale sequencing study aimed at increasing the number of genes known to contribute to predisposition for ALS. We performed whole-exome sequencing of 2869 ALS patients and 6405 controls. Several known ALS genes were found to be associated, and TBK1 (the gene encoding TANK-binding kinase 1) was identified as an ALS gene. TBK1 is known to bind to and phosphorylate a number of proteins involved in innate immunity and autophagy, including optineurin (OPTN) and p62 (SQSTM1/sequestosome), both of which have also been implicated in ALS. These observations reveal a key role of the autophagic pathway in ALS and suggest specific targets for therapeutic intervention.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.122
GPT teacher head0.309
Teacher spread0.187 · 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

Citations981
Published2015
Admission routes1
Has abstractyes

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