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Record W2907333597 · doi:10.1038/s41467-018-07867-7

Trans-ethnic kidney function association study reveals putative causal genes and effects on kidney-specific disease aetiologies

2018· review· en· W2907333597 on OpenAlexaff
Andrew P. Morris, Thu H Le, Hao Wu, Artur Akbarov, Peter J. van der Most, Gibran Hemani, George Davey Smith, Anubha Mahajan, Kyle J. Gaulton, Girish N. Nadkarni, Adán Valladares‐Salgado, Niels H. Wacher, Josyf C. Mychaleckyj, Nicole Dueker, Xiuqing Guo, Yang Hai, Jeffrey Haessler, Yoichiro Kamatani, Adrienne M. Stilp, Gu Zhu, James P. Cook, Johan Ärnlöv, Susan H. Blanton, Martin H. de Borst, Erwin P. Böttinger, Thomas A. Buchanan, Sylvia Cechova, Fadi J. Charchar, Pei‐Lun Chu, Jeffrey Damman, James Eales, Ali G. Gharavi, Vilmantas Giedraitis, Andrew C. Heath, Eli Ipp, Krzysztof Kiryluk, Holly Kramer, Michiaki Kubo, Anders Larsson, Cecilia M. Lindgren, Yingchang Lu, Pamela A. F. Madden, Grant W. Montgomery, George Papanicolaou, Leslie J. Raffel, Ralph L. Sacco, Elena Sánchez, Holger Stark, Johan Sundström, Kent D. Taylor, Anny H. Xiang, Aleksandra Živković, Lars Lind, Erik Ingelsson, Nicholas G. Martin, John B. Whitfield, Jianwen Cai, Cathy C. Laurie, Yukinori Okada, Koichi Matsuda, Charles Kooperberg, Yii-Der Ida Chen, Tatjana Rundek, Stephen S. Rich, Ruth J. F. Loos, Esteban J. Parra, Miguel Cruz, Jerome I. Rotter, Harold Snieder, Maciej Tomaszewski, Benjamin D. Humphreys, Nora Franceschini

Bibliographic record

VenueNature Communications · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Minority Health and Health DisparitiesNational Institute of Environmental Health SciencesNational Heart, Lung, and Blood InstituteDeutsche ForschungsgemeinschaftUniversity of BristolNational Institutes of HealthKidney Research UKNational Institute of Neurological Disorders and StrokeNational Institute for Health and Care ResearchNational Institute of Diabetes and Digestive and Kidney DiseasesLi Ka Shing FoundationBritish Heart FoundationNational Center for Advancing Translational SciencesWellcome TrustMedical Research CouncilMcKnight Foundation
KeywordsKidney diseaseRenal functionGenome-wide association studyPopulationBiologyMendelian randomizationGeneticsDiseaseMedicineGeneBioinformaticsInternal medicineGenetic variantsSingle-nucleotide polymorphismGenotype

Abstract

fetched live from OpenAlex

Chronic kidney disease (CKD) affects ~10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assemble genome-wide association studies of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals of diverse ancestry. We identify 127 distinct association signals with homogeneous effects on eGFR across ancestries and enrichment in genomic annotations including kidney-specific histone modifications. Fine-mapping reveals 40 high-confidence variants driving eGFR associations and highlights putative causal genes with cell-type specific expression in glomerulus, and in proximal and distal nephron. Mendelian randomisation supports causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure and hypertension. These results define novel molecular mechanisms and putative causal genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.489
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.048
GPT teacher head0.370
Teacher spread0.322 · 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 designNot applicable
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

Citations160
Published2018
Admission routes1
Has abstractyes

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