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Record W4224240370 · doi:10.1172/jci.insight.157035

Genome-wide studies reveal factors associated with circulating uromodulin and its relationships to complex diseases

2022· article· en· W4224240370 on OpenAlexafffund
Yong Li, Yurong Cheng, Francesco Consolato, Guglielmo Schiano, Michael Chong, Maik Pietzner, Ngoc Quynh Nguyen, Nora Scherer, Mary L. Biggs, Marcus E. Kleber, Stefan Haug, Burulça Göçmen, Marie Pigeyre, Peggy Sekula, Inga Steinbrenner, Pascal Schlosser, Christina B. Joseph, Jennifer A. Brody, Morgan E. Grams, Caroline Hayward, Ulla T. Schultheiß, Bernhard K. Krämer, Florian Kronenberg, Annette Peters, Jochen Seißler, Dominik Steubl, Cornelia Then, Matthias Wuttke, Winfried März, Kai‐Uwe Eckardt, Christian Gieger, Eric Boerwinkle, Bruce M. Psaty, Josef Coresh, Peter J. Oefner, Guillaume Paré, Claudia Langenberg, Jürgen E. Scherberich, Bing Yu, Shreeram Akilesh, Olivier Devuyst, Luca Rampoldi, Anna Köttgen

Bibliographic record

VenueJCI Insight · 2022
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsThrombosis and Atherosclerosis Research InstituteMcMaster UniversityPopulation Health Research Institute
FundersNational Center for Research ResourcesNational Human Genome Research InstituteNational Institute on AgingSwiss National Centre of Competence in Research Kidney Control of HomeostasisHelmholtz Zentrum MünchenCanadian Institutes of Health ResearchBayer VitalAbbott DiagnosticsAmgenSiemens HealthineersNational Center for Advancing Translational SciencesMedical Research CouncilUniversità di BolognaEuropean CommissionNovartis PharmaChina Scholarship CouncilVifor PharmaMinistero della SaluteNational Heart, Lung, and Blood InstituteDeutsche Diabetes GesellschaftAmryt PharmaAlbert-Ludwigs-Universität FreiburgBundesministerium für Bildung und ForschungDeutsche ForschungsgemeinschaftNational Institute of Diabetes and Digestive and Kidney DiseasesSanofiHorizon 2020 Framework ProgrammeNational Institute of Neurological Disorders and StrokeUniversity of CambridgeFresenius Medical Care North AmericaAstraZenecaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungYale UniversityMedizinische Fakultät der Albert-Ludwigs-Universität FreiburgNational Institutes of HealthU.S. Department of Health and Human ServicesNational Science Foundation
KeywordsTamm–Horsfall proteinBiologyKidneyKidney diseaseGeneGeneticsImmunologyComputational biologyEndocrinology

Abstract

fetched live from OpenAlex

Uromodulin (UMOD) is a major risk gene for monogenic and complex forms of kidney disease. The encoded kidney-specific protein uromodulin is highly abundant in urine and related to chronic kidney disease, hypertension, and pathogen defense. To gain insights into potential systemic roles, we performed genome-wide screens of circulating uromodulin using complementary antibody-based and aptamer-based assays. We detected 3 and 10 distinct significant loci, respectively. Integration of antibody-based results at the UMOD locus with functional genomics data (RNA-Seq, ATAC-Seq, Hi-C) of primary human kidney tissue highlighted an upstream variant with differential accessibility and transcription in uromodulin-synthesizing kidney cells as underlying the observed cis effect. Shared association patterns with complex traits, including chronic kidney disease and blood pressure, placed the PRKAG2 locus in the same pathway as UMOD. Experimental validation of the third antibody-based locus, B4GALNT2, showed that the p.Cys466Arg variant of the encoded N-acetylgalactosaminyltransferase had a loss-of-function effect leading to higher serum uromodulin levels. Aptamer-based results pointed to enzymes writing glycan marks present on uromodulin and to their receptors in the circulation, suggesting that this assay permits investigating uromodulin's complex glycosylation rather than its quantitative levels. Overall, our study provides insights into circulating uromodulin and its emerging functions.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.124
GPT teacher head0.299
Teacher spread0.175 · 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.

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

Citations23
Published2022
Admission routes2
Has abstractyes

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