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Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation
Norihiro Kato, Marie Loh, Fumihiko Takeuchi, Niek Verweij, Xu Wang, Weihua Zhang, Tanika N Kelly, Danish Saleheen, Benjamin Lehne, Irene Mateo Leach, Alexander Drong, James Abbott, Simone Wahl, Sian-Tsung Tan, William R. Scott, Gianluca Campanella, Marc Chadeau‐Hyam, Uzma Afzal, Tarunveer S. Ahluwalia, Marc Jan Bonder, Peng Chen, Abbas Dehghan, Todd L. Edwards, Tõnu Esko, Min Jin Go, Sarah E. Harris, Jaana Hartiala, Silva Kasela, Anuradhani Kasturiratne, Chiea Chuen Khor, Marcus E. Kleber, Huaixing Li, Zuan Yu Mok, Masahiro Nakatochi, Nur Sabrina Sapari, Richa Saxena, Alexandre F.R. Stewart, Lisette Stolk, Yasuharu Tabara, Ai Ling Teh, Ying Wu, Jer-Yuarn Wu, Yi Zhang, Imke Aits, Alexessander Couto Alves, Shikta Das, Rajkumar Dorajoo, Jemma C. Hopewell, Yun Kyoung Kim, Robert W. Koivula, Jian’an Luan, Leo‐Pekka Lyytikäinen, Quang N Nguyen, Mark A. Pereira, Iris Postmus, Olli T Raitakari, Molly Scannell Bryan, Robert A. Scott, Rossella Sorice, Vinicius Tragante, Michela Traglia, Jon White, Ken Yamamoto, Yonghong Zhang, Linda S. Adair, Alauddin Ahmed, Koichi Akiyama, Rasheed Asif, Tin Aung, Inês Barroso, Andrew Bjonnes, Timothy R. Braun, Hui Cai, Li-Ching Chang, Chien‐Hsiun Chen, Ching‐Yu Cheng, Yap Seng Chong, Rory Collins, Regina Courtney, Gail Davies, Graciela Delgado, Loi D., Pieter A. Doevendans, Ron T. Gansevoort, Yu-Tang Gao, Tanja B. Grammer, Niels Grarup, Jagvir Grewal, Dongfeng Gu, Gurpreet S Wander, Anna-Liisa Hartikainen, Stanley L. Hazen, Jing He, Chew‐Kiat Heng, James E. Hixson, Albert Hofman, Chris Hsu, Wei Huang, Lise Lotte N. Husemoen, Joo‐Yeon Hwang, Sahoko Ichihara, Michiya Igase, Masato Isono, Johanne Marie Justesen, Tomohiro Katsuya, Muhammad G Kibriya, Young Jin Kim, Miyako Kishimoto, Woon‐Puay Koh, Katsuhiko Kohara, Meena Kumari, Kenneth Kwek, Sang Lee, Jeannette Lee, Jiemin Liao, Wolfgang Lieb, David C. Liewald, Tatsuaki Matsubara, Yumi Matsushita, Thomas Meitinger, Evelin Mihailov, Lili Milani, Rebecca Mills, Nina Mononen, Martina Müller‐Nurasyid, Toru Nabika, Eitaro Nakashima, Hong Kiat Ng, Kjell Nikus, Teresa Nutile, Takayoshi Ohkubo, Keizo Ohnaka, Sarah Parish, Lavinia Paternoster, Hao Peng, Annette Peters, Son T Pham, Mahfuzar Rahman, Hiromi Rakugi, Olov Rolandsson, Michelle Ann Rozario, Daniela Ruggiero, Cinzia Sala, Sarju Ralhan, Kazuro Shimokawa, Harold Snieder, Thomas Sparsø, Wilko Spiering, John M. Starr, David J. Stott, Daniel O. Stram, Takao Sugiyama, Silke Szymczak, W.H. Wilson Tang, Tong Lin, Stella Trompet, Väinö Turjanmaa, Hirotsugu Ueshima, André G. Uitterlinden, Satoshi Umemura, Marja Vääräsmäki, Rob M. van Dam, Wiek H. van Gilst, Dirk J. van Veldhuisen, Jorma Viikari, Mélanie Waldenberger, Yiqin Wang, Aili Wang, Rory Wilson, Tien Yin Wong, Yong-Bing Xiang, Shuhei Yamaguchi, Xingwang Ye, Robin Young, Terri L. Young, Jian‐Min Yuan, Xueya Zhou, Folkert W. Asselbergs, Marina Ciullo, Robert B. Clarke, Panos Deloukas, André Franke, Paul W. Franks, Steve Franks, Yechiel Friedlander, Myron D. Gross, Zhirong Guo, Torben Hansen, Marjo‐Riitta Järvelin, Torben Jørgensen, J. Wouter Jukema, Mika Kähönen, Hiroshi Kajio, Mika Kivimäki, Jong‐Young Lee, Terho Lehtimäki, Allan Linneberg, Tetsuro Miki, Oluf Pedersen, Nilesh J. Samani, Thorkild I. A. Sørensen, Ryoichi Takayanagi, Daniela Toniolo, Habibul Ahsan, Hooman Allayee, Yuan-Tsong Chen, John Danesh, Ian J. Deary, Oscar H. Franco, Lude Franke, Bastiaan T Heijman, Joanna D. Holbrook, Aaron Isaacs, Bong‐Jo Kim, Xu Lin, Jianjun Liu, Winfried März, Andres Metspalu, Karen L. Mohlke, Dharambir K. Sanghera, Xiao‐Ou Shu, Joyce B. J. van Meurs, Eranga N. Vithana, Ananda R. Wickremasinghe, Cisca Wijmenga, Bruce H. R. Wolffenbuttel, Mitsuhiro Yokota, Wei Zheng, Dingliang Zhu, Paolo Vineis, Soterios Α. Kyrtopoulos, Jos Kleinjans, Mark I. McCarthy, Richie Soong, Christian Gieger, Yik‐Ying Teo, Jiang He, Paul Elliott, E Shyong Tai, Pim van der Harst, Jaspal S. Kooner, John C. Chambers
Bibliographic record
VenueNature Genetics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversity of Ottawa
FundersNational Center for Research ResourcesU.S. National Library of MedicineNational Institute of Environmental Health SciencesNational Center for Advancing Translational SciencesWellcome TrustNederlandse Organisatie voor Wetenschappelijk OnderzoekNational Human Genome Research InstituteFogarty International CenterNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteNational Institute on AgingNational Institute of Diabetes and Digestive and Kidney DiseasesBiotechnology and Biological Sciences Research CouncilMedical Research CouncilAgency for Healthcare Research and QualityNational Institute for Health and Care ResearchNational Cancer InstituteBritish Heart Foundation
KeywordsBiologyDNA methylationGeneticsGenome-wide association studyMethylationGenetic associationGenomeGenetic genealogyDNAComputational biologySingle-nucleotide polymorphismGeneGenotypePopulationGene expression
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 head0.014
GPT teacher head0.282
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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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Citations376
Published2015
Admission routes1
Has abstractno