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Record W4409151023 · doi:10.1038/s41380-025-02954-w

A large-scale genome-wide study of gene-sleep duration interactions for blood pressure in 811,405 individuals from diverse populations

2025· article· en· W4409151023 on OpenAlexaff
Pavithra Nagarajan, Thomas W. Winkler, Amy R. Bentley, Clint L. Miller, Aldi T. Kraja, Karen Schwander, Songmi Lee, Wenyi Wang, Michael R. Brown, John L. Morrison, Ayush Giri, Jeffrey R. O’Connell, Traci M. Bartz, Lisa de las Fuentes, Valborg Guðmundsdóttir, Xiuqing Guo, Sarah E. Harris, Zhijie Huang, Mart Kals, Minjung Kho, Christophe Lefèvre, Jian’an Luan, Leo‐Pekka Lyytikäinen, Massimo Mangino, Yuri Milaneschi, Nicholette D. Allred, Varun Rao, Rainer Rauramaa, Botong Shen, Stefan Stadler, Quan Sun, Jingxian Tang, Sébastien Thériault, Adriaan van der Graaf, Peter J. van der Most, Yujie Wang, Stefan Weiß, Kenneth E. Westerman, Qian Yang, Yasuharu Tabara, Wei Zhao, Wanying Zhu, Drew Altschul, Md Abu Yusuf Ansari, Pramod Anugu, Anna D. Argoty-Pantoja, Michael Arzt, Hugues Aschard, John Attia, Lydia Bazzanno, Max Breyer, Jennifer A. Brody, Brian E. Cade, Hung‐Hsin Chen, Yii-Der Ida Chen, Zekai Chen, Paul S. de Vries, Latchezar Dimitrov, Anh Do, Jiawen Du, C. Dupont, Todd L. Edwards, Michele K. Evans, Tariq Faquih, Stephan B. Felix, Susan P. Fisher‐Hoch, James S. Floyd, Mariaelisa Graff, C. Charles Gu, Dongfeng Gu, Kristen G. Hairston, Anthony J. Hanley, Iris M. Heid, Sami Heikkinen, Heather M. Highland, Michelle M. Hood, Mika Kähönen, Carrie Karvonen‐Gutierrez, Takahisa Kawaguchi, Kazuya Setoh, Tanika N. Kelly, Pirjo Komulainen, Daniel Levy, Henry J. Lin, Peter Y. Liu, Pedro Marques‐Vidal, Joseph B. McCormick, Hao Mei, James B. Meigs, Cristina Menni, Kisung Nam, Ilja M. Nolte, Natasha L. Pacheco, Lauren E. Petty, Hannah G. Polikowsky, Michael A. Province, Bruce M. Psaty, Laura M. Raffield, Olli T. Raitakari, Stephen S. Rich, Renata L. Riha, Lorenz Risch, Martin Risch, Edward Ruiz-Narváez, Rodney J. Scott, Colleen M. Sitlani, Jennifer A. Smith, Tamar Sofer, Maris Teder‐Laving, Uwe Völker, Péter Vollenweider, Guanchao Wang, Ko Willems van Dijk, Otis D. Wilson, Rui Xia, Jie Yao, Kristin L. Young, Ruiyuan Zhang, Xiaofeng Zhu, Jennifer E Below, Carsten A. Böger, David Conen, Simon R. Cox, Marcus Dörr, Mary F. Feitosa, Ervin R. Fox, Nora Franceschini, Sina A. Gharib, Vilmundur Guðnason, Sioḃán D. Harlow, Jiang He, Zoltán Kutalik, Timo A. Lakka, Debbie A. Lawlor, Seunggeun Lee, Terho Lehtimäki, Changwei Li, Ching‐Ti Liu, Reedik Mägi, Fumihiko Matsuda, Alanna C. Morrison, Brenda W.J.H. Penninx, Patricia A. Peyser, Jerome I. Rotter, Harold Snieder, Tim D. Spector, Lynne E. Wagenknecht, Nicholas J. Wareham, Alan B. Zonderman, Kari E. North, Myriam Fornage

Bibliographic record

VenueMolecular Psychiatry · 2025
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsPopulation Health Research InstituteUniversity of TorontoUniversité Laval
FundersNational Human Genome Research InstituteNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteNational Institute on AgingU.S. Department of Health and Human ServicesNational Institutes of HealthU.S. Department of Veterans Affairs
KeywordsGeneSleep (system call)GenomeBlood pressureDuration (music)Scale (ratio)GeneticsPsychologyBiologyComputational biologyMedicineInternal medicineComputer scienceGeography

Abstract

fetched live from OpenAlex
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 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)0.001
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 score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.297
Teacher spread0.286 · 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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractno

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