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Record W3175546635 · doi:10.1101/2021.06.15.21258641

Sequencing of over 100,000 individuals identifies multiple genes and rare variants associated with Crohns disease susceptibility

2021· preprint· en· W3175546635 on OpenAlexaff
Aleksejs Sazonovs, Christine Stevens, Guhan Venkataraman, Kai Yuan, Brandon E. Avila, María T. Abreu, Tariq Ahmad, Matthieu Allez, Ashwin N. Ananthakrishnan, Gil Atzmon, Aris Baras, Jeffrey C. Barrett, Nir Barzilai, Laurent Beaugerie, Ashley Beecham, Çharles N. Bernstein, Alain Bitton, Bernd Bokemeyer, Andrew Chan, Daniel C. Chung, Isabelle Cleynen, Jacques Cosnes, David J. Cutler, Allan Daly, Oriana M. Damas, Lisa W. Datta, Noor Dawany, Marcella Devoto, Sheila Dodge, Eva Ellinghaus, Laura Fachal, Martti Färkkilâ, William A. Faubion, Manuel A. R. Ferreira, Denis Franchimont, Stacey Gabriel, Michel Georges, Kyle Gettler, Mamta Giri, Benjamin Gläser, Siegfried Goerg, Philippe Goyette, Daniel B. Graham, Eija Hämäläinen, Talin Haritunians, Graham Heap, Mikko Hiltunen, Marc Hoeppner, Julie Horowitz, Peter M. Irving, Vivek Iyer, Chaim Jalas, Judith R. Kelsen, Hamed Khalili, Barbara S. Kirschner, Kimmo Kontula, Jukka Koskela, Subra Kugathasan, Juozas Kupčinskas, Christopher A Lamb, Matthias Laudes, Adam P. Levine, James D. Lewis, Claire Liefferinckx, Britt-Sabina Loescher, Édouard Louis, John Mansfield, Sandra May, Jacob L. McCauley, Emebet Mengesha, Myriam Mni, Paul Moayyedi, Christopher J. Moran, Rodney D. Newberry, Sirimon O’Charoen, David T. Okou, Bas Oldenburg, Harry Ostrer, Aarno Palotie, Joel Pekow, Inga Peter, Marieke Pierik, Cyriel Y. Ponsioen, Nikolas Pontikos, Natalie J. Prescott, Ann E. Pulver, Souad Rahmouni, Daniel L Rice, Päivi Saavalainen, Bruce E. Sands, R. Balfour Sartor, Elena Schiff, Stefan Schreiber, L. Philip Schuum, Anthony W. Segal, Philippe Seksik, Rasha Shawky, Shehzad Z. Sheikh, Mark S. Silverberg, Alison Simmons, Jurgita Skeiceviciene, Harry Sokol, Matthew Solomonson, Hari K. Somineni, Dylan Sun, Stephan Targan, Dan Turner, Holm H. Uhlig, Andrea E. van der Meulen‐de Jong, Séverine Vermeire, Sare Verstockt, Michiel Voskuil, Harland S. Winter, Justine Young, Richard H. Duerr, André Franke, Steven R. Brant, Judy H. Cho, Rinse K. Weersma, Miles Parkes, Ramnik J. Xavier, Manuel A. Rivas, John D. Rioux, Dermot McGovern, Hailiang Huang, Carl A. Anderson, Mark J. Daly

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsMcMaster UniversityMontreal Heart InstituteMcGill University Health CentreMount Sinai HospitalUniversity of Manitoba
FundersNational Institute of Mental HealthMedical Research CouncilNational Institutes of HealthNIHR Newcastle Biomedical Research CentreFonds De La Recherche Scientifique - FNRSInflammatory Bowel and Immunobiology Research InstituteNational Institute of Diabetes and Digestive and Kidney DiseasesStanley Center for Psychiatric Research, Broad InstituteCedars-Sinai Medical CenterDeutsche ForschungsgemeinschaftLeona M. and Harry B. Helmsley Charitable TrustNational Institute for Health and Care ResearchEuropean Regional Development FundEuropean CommissionBroad InstituteNational Human Genome Research InstituteNIHR Oxford Biomedical Research CentreWellcome Trust
KeywordsGenome-wide association studyBiologyGeneGeneticsGenetic associationDiseaseGenomeComputational biologyPopulationSingle-nucleotide polymorphismGenotypeMedicinePathology

Abstract

fetched live from OpenAlex

Abstract Genome-wide association studies (GWAS) have identified hundreds of loci associated with Crohns disease (CD), however, as with all complex diseases, deriving pathogenic mechanisms from these non-coding GWAS discoveries has been challenging. To complement GWAS and better define actionable biological targets, we analysed sequenced data from more than 30,000 CD patients and 80,000 population controls. We observe rare coding variants in established CD susceptibility genes as well as ten genes where coding variation directly implicates the gene in disease risk for the first time.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
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 head0.017
GPT teacher head0.248
Teacher spread0.232 · 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.

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

Citations11
Published2021
Admission routes1
Has abstractyes

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