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Record W2175426329 · doi:10.1093/hmg/ddv454

A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration

2015· review· en· W2175426329 on OpenAlexaff
Paul S. de Vries, Daniel I. Chasman, Maria Sabater‐Lleal, Ming‐Huei Chen, Jennifer E. Huffman, Maristella Steri, Weihong Tang, Alexander Teumer, Riccardo E. Marioni, Vera Großmann, Jouke‐Jan Hottenga, Stella Trompet, Martina Müller‐Nurasyid, Wei Zhao, Jennifer A. Brody, Marcus E. Kleber, Xiuqing Guo, Jie Jin Wang, Paul L. Auer, John Attia, Lisa R. Yanek, Tarunveer S. Ahluwalia, Jari Lahti, Cristina Venturini, Toshiko Tanaka, Lawrence F. Bielak, Peter K. Joshi, Ares Rocañín-Arjó, Ivana Kolčić, Pau Navarro, Lynda M. Rose, Christopher Oldmeadow, Helene Riess, Johanna Mazur, Saonli Basu, Anuj Goel, Qiong Yang, Mohsen Ghanbari, Gonneke Willemsen, Ann Rumley, Edoardo Fiorillo, Anton J. M. de Craen, Anne Grotevendt, Robert A. Scott, Kent D. Taylor, Graciela E. Delgado, Jie Yao, Annette Kifley, Charles Kooperberg, Rehan Qayyum, Lorna M. Lopez, Tina Landsvig Berentzen, Katri Räikkönen, Massimo Mangino, Stefania Bandinelli, Patricia A. Peyser, Sarah H. Wild, David‐Alexandre Trégouët, Alan F. Wright, Jonathan Marten, Tatijana Zemunik, Alanna C. Morrison, Bengt Sennblad, Geoffrey H. Tofler, Moniek P.M. de Maat, Eco J. C. de Geus, Gordon Lowe, Magdalena Żołędziewska, Naveed Sattar, Harald Binder, Uwe Völker, Mélanie Waldenberger, Kay‐Tee Khaw, Barbara McKnight, Jie Huang, Nancy S. Jenny, Lihong Qi, Mark McEvoy, Diane M. Becker, John M. Starr, Antti‐Pekka Sarin, Pirro G. Hysi, Dena Hernández, Min A. Jhun, Harry Campbell, Anders Hamsten, Fernando Rivadeneira, Wendy L. McArdle, P. Eline Slagboom, Tanja Zeller, Wolfgang Köenig, Bruce M. Psaty, Talin Haritunians, Jingmin Liu, Aarno Palotie, André G. Uitterlinden, David J. Stott, Albert Hofman, Oscar H. Franco, Ozren Polašek, Igor Rudan, Pierre‐Emmanuel Morange, James F. Wilson, Sharon L. R. Kardia, Luigi Ferrucci, Tim D. Spector, Johan G. Eriksson, Torben Hansen, Ian J. Deary, Lewis C. Becker, Rodney J. Scott, Paul Mitchell, Winfried März, Annette Peters, Andreas Greinacher, Philipp S. Wild, J. Wouter Jukema, Dorret I. Boomsma, Caroline Hayward, Francesco Cucca, Russell P. Tracy, Hugh Watkins, Alex P. Reiner, Aaron R. Folsom, Paul M. Ridker, Christopher J. O’Donnell, Nicholas L. Smith, David P. Strachan, Abbas Dehghan

Bibliographic record

VenueHuman Molecular Genetics · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsCentre for Global Health ResearchInstitute of Population and Public Health
FundersNational Center for Research ResourcesNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteNational Institute on AgingNational Institute of Diabetes and Digestive and Kidney DiseasesZonMwBiotechnology and Biological Sciences Research CouncilVersus ArthritisMedical Research CouncilU.S. Public Health ServiceNational Institute of Neurological Disorders and StrokeNational Institute of Nursing ResearchNational Institute for Health and Care ResearchNational Center for Advancing Translational SciencesNational Human Genome Research InstituteNederlandse Organisatie voor Wetenschappelijk OnderzoekWellcome TrustNational Cancer InstituteBritish Heart FoundationNational Institutes of HealthCancer Research UK
KeywordsBiologyFibrinogenGeneticsMeta-analysisComputational biologyEvolutionary biologyInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Genome-wide association studies have previously identified 23 genetic loci associated with circulating fibrinogen concentration. These studies used HapMap imputation and did not examine the X-chromosome. 1000 Genomes imputation provides better coverage of uncommon variants, and includes indels. We conducted a genome-wide association analysis of 34 studies imputed to the 1000 Genomes Project reference panel and including ∼120 000 participants of European ancestry (95 806 participants with data on the X-chromosome). Approximately 10.7 million single-nucleotide polymorphisms and 1.2 million indels were examined. We identified 41 genome-wide significant fibrinogen loci; of which, 18 were newly identified. There were no genome-wide significant signals on the X-chromosome. The lead variants of five significant loci were indels. We further identified six additional independent signals, including three rare variants, at two previously characterized loci: FGB and IRF1. Together the 41 loci explain 3% of the variance in plasma fibrinogen concentration.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.583
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.240
GPT teacher head0.413
Teacher spread0.173 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations102
Published2015
Admission routes1
Has abstractyes

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