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Record W2600130431 · doi:10.1101/110833

Novel blood pressure locus and gene discovery using GWAS and expression datasets from blood and the kidney

2017· preprint· en· W2600130431 on OpenAlexaff
Louise V. Wain, Ahmad Vaez, Rick Jansen, Roby Joehanes, Peter J. van der Most, A. Mesut Erzurumluoglu, Paul F. O’Reilly, Claudia P. Cabrera, Helen R. Warren, Lynda M. Rose, Germaine C. Verwoert, Jouke‐Jan Hottenga, Rona J. Strawbridge, Tõnu Esko, Dan E. Arking, Shih-Jen Hwang, Xiuqing Guo, Zoltán Kutalik, Stella Trompet, Nick Shrine, Alexander Teumer, Janina S. Ried, Joshua C. Bis, Albert V. Smith, Najaf Amin, Ilja M. Nolte, Leo‐Pekka Lyytikäinen, Anubha Mahajan, Nicholas J. Wareham, Edith Hofer, Peter K. Joshi, Kati Kristiansson, Michela Traglia, Aki S. Havulinna, Anuj Goel, Mike A. Nalls, Siim Sõber, Dragana Vuckovic, Jian’an Luan, Fabiola Del Greco M, Kristin L. Ayers, Jaume Marrugat, Daniela Ruggiero, Lorna M. Lopez, Teemu Niiranen, Stefan Enroth, Anne Jackson, Christopher P. Nelson, Jennifer E. Huffman, Weihua Zhang, Jonathan Marten, Ilaria Gandin, Sarah E. Harris, Tatijana Zemonik, Yingchang Lu, Εvangelos Εvangelou, Nabi Shah, Martin H. de Borst, Massimo Mangino, Bram P. Prins, Archie Campbell, Ruifang Li‐Gao, Ganesh Chauhan, Christopher Oldmeadow, Gonçalo Abecasis, Maryam Abedi, Caterina Barbieri, Michael R. Barnes, Chiara Batini, John Beilby, Tineka Blake, Michael Boehnke, Erwin P. Böttinger, Peter S. Braund, Morris J. Brown, Marco Brumat, Harry Campbell, John C. Chambers, Massimiliano Cocca, Francis S. Collins, John Connell, Heather J. Cordell, Jeffrey Damman, Gail Davies, Eco J. C. de Geus, Renée de Mutsert, Joris Deelen, Yusuf Demirkale, Alex S. F. Doney, Marcus Dörr, Martin Farrall, Teresa Ferreira, Mattias Frånberg, He Gao, Vilmantas Giedraitis, Christian Gieger, Franco Giulianini, Alan J. Gow, Anders Hamsten, Tamara B. Harris, Albert Hofman, Jennie Hui, Marjo‐Riitta Järvelin, Åsa Johansson, Andrew D. Johnson, Antti Jula, Mika Kähönen, Sekar Kathiresan, Kay‐Tee Khaw, Ivana Kolčić, Seppo Koskinen, Claudia Langenberg, Marty Larson, Lenore J. Launer, Benjamin Lehne, David C. Liewald, Li Lin, Lars Lind, François Mach, Chrysovalanto Mamasoula, Cristina Menni, Borbála Mifsud, Yuri Milaneschi, Anna Morgan, Andrew D. Morris, Alanna C. Morrison, Peter J. Munson, Priyanka Nandakumar, Quang Tri Nguyen, Teresa Nutile, Albertine J. Oldehinkel, Ben A. Oostra, Elin Org, Sandosh Padmanabhan, Aarno Palotie, Guillaume Paré, Alison Pattie, Brenda W.J.H. Penninx, Neil R Poulter, Peter P. Pramstaller, Olli T. Raitakari, Meixia Ren, Kenneth Rice, Paul M. Ridker, Harriëtte Riese, Samuli Ripatti, Antonietta Robino, Jerome I. Rotter, Igor Rudan, Yasaman Saba, Aude Saint Pierre, Cinzia Sala, Antti-Pekka Sarin, Reinhold Schmidt, Rodney J. Scott, Marc A. Seelen, Denis C. Shields, David S. Siscovick, Rossella Sorice, Alice Stanton, David J. Stott, Johan Sundström, Morris A. Swertz, Kent D. Taylor, Simon Thom, Ioanna Tzoulaki, Christophe Tzourio, André G. Uitterlinden, Uwe Vöker, Péter Vollenweider, Gonneke Willemsen, Alan F. Wright, Jie Yao, Sébastien Thériault, David Conen, Attia John, Peter Sever, Stéphanie Debette, Dennis O. Mook‐Kanamori, Eleftheria Zeggini, Tim D. Spector, Pim van der Harst, Anne‐Claire Vergnaud, Ruth J. F. Loos, Ozren Polašek, John M. Starr, Giorgia Girotto, Caroline Hayward, Jaspal S. Kooner, Cecila M. Lindgren, Véronique Vitart, Nilesh J. Samani, Jaakko Tuomilehto, Ulf Gyllensten, Paul Knekt, Ian J. Deary, Marina Ciullo, Roberto Elosúa, Bernard Keavney, Andrew A. Hicks, Robert A. Scott, Paolo Gasparini, Maris Laan, YongMei Liu, Hugh Watkins, Catharina A. Hartman, Veikko Salomaa, Daniela Toniolo, Markus Perola, James F. Wilson, Helena Schmidt, Jing Hua Zhao, Terho Lehtimäki, Cornelia M. van Duijn, Vilmundur Guðnason, Bruce M. Psaty, Annette Peters, Rainer Rettig, J. Wouter Jukema, David P. Strachan, Walter Palmas, Andres Metspalu, Erik Ingelsson, Dorret I. Boomsma, Oscar H. Franco, Murielle Bochud, Christopher Newton‐Cheh, Patricia B. Munroe, Paul Elliott, Daniel I. Chasman, Aravinda Chakravarti, Jo Knight, Andrew P. Morris, Daniel Levy, Martin D. Tobin, Harold Snieder, Mark J. Caulfield, Georg Ehret

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2017
Typepreprint
Languageen
FieldMedicine
TopicHormonal Regulation and Hypertension
Canadian institutionsMcMaster University
FundersMedical Research Council
KeywordsGenome-wide association studyImputation (statistics)Blood pressureBiologyExpression quantitative trait lociGeneLocus (genetics)Kidney diseaseGenetic association1000 Genomes ProjectGeneticsCandidate geneComputational biologyGenetic variationBioinformaticsSingle-nucleotide polymorphismGenotypeEndocrinologyMissing data

Abstract

fetched live from OpenAlex

ABSTRACT Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150,134 European ancestry individuals and sought significant evidence for independent replication in a further 228,245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9 and AKT2 , and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA . Combining large whole-blood gene expression resources totaling 12,607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in BP regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.241
Teacher spread0.218 · 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".

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Citations1
Published2017
Admission routes1
Has abstractyes

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Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicHormonal Regulation and HypertensionFrench-language works237,207