MétaCan
Menu
Back to cohort
Record W2903416893 · doi:10.1038/s41467-018-07340-5

GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes

2018· review· en· W2903416893 on OpenAlexaff
Nora Franceschini, Claudia Giambartolomei, Paul S. de Vries, Chris Finan, Joshua C. Bis, Rachael P. Huntley, Ruth C. Lovering, Salman M. Tajuddin, Thomas W. Winkler, Misa Graff, Maryam Kavousi, Caroline Dale, Albert V. Smith, Edith Hofer, Ilja M. Nolte, Lingyi Lu, Markus Scholz, Muralidharan Sargurupremraj, Niina Pitkänen, Oscar Franzén, Peter K. Joshi, Raymond Noordam, Riccardo E. Marioni, Shih‐Jen Hwang, Solomon K. Musani, Ulf Schminke, Walter Palmas, Aaron Isaacs, Adolfo Correa, Alan B. Zonderman, Albert Hofman, Alexander Teumer, Amanda J. Cox, André G. Uitterlinden, Andrew Wong, Andries J. Smit, Anne B. Newman, Annie Britton, Arno Ruusalepp, Bengt Sennblad, Bo Hedblad, Bogdan Paşaniuc, Brenda W.J.H. Penninx, Carl D. Langefeld, Christina L. Wassel, Christophe Tzourio, Cristiano Fava, Damiano Baldassarre, Daniel H. O’Leary, Daniel Teupser, Diana Kuh, Elena Tremoli, Elmo Mannarino, Enzo Grossi, E BOERWINKLE, Eric E. Schadt, Erik Ingelsson, Fabrizio Veglia, Fernando Rivadeneira, Frank Beutner, Ganesh Chauhan, Gerardo Heiss, Harry Campbell, Henry Völzke, Hugh S. Markus, Ian J. Deary, J. Wouter Jukema, Jacqueline de Graaf, Janne Pott, Jemma C. Hopewell, Jingjing Liang, Joachim Thiery, Jorgen Engmann, Karl Gertow, Kenneth Rice, Kent D. Taylor, Klodian Dhana, Lambertus A. Kiemeney, Lars Lind, Laura M. Raffield, Lenore J. Launer, Lesca M. Holdt, Marcus Dörr, Martin Dichgans, Matthew Traylor, Matthias Sitzer, Meena Kumari, Mika Kivimäki, Mike A. Nalls, Olle Melander, Olli T. Raitakari, Oscar H. Franco, Oscar L. Rueda‐Ochoa, Panos Roussos, Peter H. Whincup, Philippe Amouyel, Philippe Giral, Pramod Anugu, Quenna Wong, Rainer Malik, Rainer Rauramaa, Ralph Burkhardt, Rebecca Hardy, R. Schmidt, Renée de Mutsert, Richard Morris, Rona J. Strawbridge, S. Goya Wannamethee, Sara Hägg, Sonia Shah, Stela McLachlan, Stella Trompet, Sudha Seshadri, Sudhir Kurl, Susan R. Heckbert, Susan M. Ring, Tamara B. Harris, Terho Lehtimäki, Tessel E. Galesloot, Tina Shah, Ulf dé Fairé, Vincent Plagnol, Wayne D. Rosamond, Wendy S. Post, Xiaofeng Zhu, Xiaoling Zhang, Xiuqing Guo, Yasaman Saba, Yukinori Okada, Aniket Mishra, Loes C.A. Rutten‐Jacobs, Anne-Katrin Giese, Sander W. van der Laan, Sólveig Grétarsdóttir, Christopher D. Anderson, Michael Chong, Hieab H.H. Adams, Tetsuro Ago, Peter Almgren, Hakan Ay, Traci M. Bartz, Oscar Benavente, Steve Bevan, Giorgio B. Boncoraglio, Robert D. Brown, Adam S. Butterworth, Caty Carrera, Cara L. Carty, Daniel I. Chasman, Wei‐Min Chen, John W. Cole, Ioana Cotlarciuc, Carlos Cruchaga, John Danesh, P. Bakker, Anita L. DeStefano, Marcel den Hoed, Qing Duan, Stefan T. Engelter, Guido J. Falcone, Rebecca F. Gottesman, Raji P. Grewal, Stefan Gustafsson, Jeffrey Haessler, Ahamad Hassan, Aki S. Havulinna, George Howard, Fang‐Chi Hsu, Hyacinth I. Hyacinth, M. Arfan Ikram, Marguerite R. Irvin, Xueqiu Jian, Jordi Jiménez-Conde, Julie A. Johnson, Masahiro Kanai, Keith L. Keene, Brett Kissela, Dawn Kleindorfer, Charles Kooperberg, Michiaki Kubo, Leslie Lange, Claudia Langenberg, Jin‐Moo Lee, Robin Lemmens, Didier Leys, Cathryn M. Lewis, Wei‐Yu Lin, Arne Lindgren, Erik Lorentzen, Patrik K. E. Magnusson, Jane Maguire, Ani Manichaikul, Patrick F. McArdle, James F. Meschia, Thomas H. Mosley, Toshiharu Ninomiya, Martin O’Donnell, Sara L. Pulit, Kristiina Rannikmäe, Alex P. Reiner, Kathryn M. Rexrode, Stephen S. Rich, Paul M. Ridker, Natalia S. Rost, Peter M. Rothwell, Tatjana Rundek, Ralph L. Sacco, Saori Sakaue, Michèle M. Sale, Veikko Salomaa, Bishwa R. Sapkota, Carsten Oliver Schmidt, Pankaj Sharma, Agnieszka Slowik, Cathie Sudlow, Christian Tanislav, Turgut Tatlisumak, Vincent Thijs, Guðmar Þorleifsson, Unnur Thorsteinsdottir, Steffen Tiedt, James Walters, Nicholas J. Wareham, Sylvia Wassertheil‐Smoller, Kerri L. Wiggins, Qiong Yang, Salim Yusuf, Tomi Pastinen, Simon Koplev, Veronica Codoni, Mete Civelek, Nick Smith, David‐Alexandre Trégouët, Ingrid E. Christophersen, Carolina Roselli, Steven A. Lubitz, Patrick T. Ellinor, E Shyong Tai, Jaspal S. Kooner, Norihiro Kato, Jiang He, Pim van der Harst, Paul Elliott, John C. Chambers, Fumihiko Takeuchi, Andrew D. Johnson, Dharambir K. Sanghera, Christina Jern, Daniel Strbian, Israel Fernández‐Cadenas, W.T. Longstreth, Arndt Rolfs, Jun Hata, Daniel Woo, Jonathan Rosand, Guillaume Paré, Danish Saleheen, Kari Stefansson, Bradford B. Worrall, Steven J. Kittner, Joanna M. M. Howson, Abbas Dehghan, Adrie Seldenrijk, Alanna C. Morrison, Anders Hamsten, Bruce M. Psaty, Cornelia M. van Duijn, Debbie A. Lawlor, Dennis O. Mook‐Kanamori, Donald W. Bowden, Helena Schmidt, James F. Wilson, James G. Wilson, Jerome I. Rotter, Joanna M. Wardlaw, John Deanfield, Julian Halcox, Leo‐Pekka Lyytikäinen, Markus Loeffler, Michele K. Evans, Stéphanie Debette, Steve E. Humphries, Uwe Völker, Vilmundur Guðnason, Aroon D. Hingorani, Johan Björkegren, Juan P. Casas, Christopher J. O’Donnell

Bibliographic record

VenueNature Communications · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMcGill UniversityUniversity of British ColumbiaMcMaster UniversityPopulation Health Research Institute
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of General Medical SciencesNational Human Genome Research InstituteMedical Research CouncilNational Cancer InstituteUniversitat Autònoma de BarcelonaSchool of Medicine, Emory UniversityNovo Nordisk FondenScience for Life LaboratoryTerveyden ja hyvinvoinnin laitosFondazione I.R.C.C.S. Istituto Neurologico Carlo BestaJohns Hopkins UniversityChildren's National HospitalUppsala UniversitetNational Institute on Minority Health and Health DisparitiesDeutsche ForschungsgemeinschaftBundesministerium für Bildung und ForschungNational Institute on AgingNational Institute for Health and Care ResearchAgence Nationale de la RechercheUniversity College LondonHope Center for Neurological DisordersWellcome TrustNational Institutes of HealthRosetrees TrustEuropean CommissionGeorge Washington UniversityHunter Medical Research InstituteAflacNational Institute of Neurological Disorders and StrokeBritish Heart FoundationEmory UniversityRoyal Holloway, University of LondonBrigham and Women's HospitalYale UniversityUniversity of Texas Health Science Center at HoustonNational Heart, Lung, and Blood InstituteChildren’s Hospital of Wisconsin Research InstituteAmerican Heart Association
KeywordsGenome-wide association studyColocalizationIntima-media thicknessMedicineCardiologyInternal medicineCarotid arteriesBiologyGeneticsSingle-nucleotide polymorphismGenotypeNeuroscienceGene

Abstract

fetched live from OpenAlex

Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.058
GPT teacher head0.384
Teacher spread0.326 · 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
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

Citations178
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicGenetic Associations and EpidemiologyFrench-language works237,207