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Record W4229067085 · doi:10.1093/ndt/gfac062.029

MO048: Genome-wide studies reveal factors associated with circulating uromodulin and its relations with complex diseases

2022· article· en· W4229067085 on OpenAlexaff
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 Joseph, Jennifer A. Brody, Morgan E. Grams, Caroline Hayward, Ulla T. Schultheiß, Bernhard Kraemer, Florian Kronenberg, Annette Peters, Jochen Seißler, Dominik Steubl, Cornelia Then, Matthias Wuttke, Winfried Maerz, Kai‐Uwe Eckardt, Christian Gieger, Eric Boerwinkle, Bruce M. Psaty, Josef Coresh, Peter J. Oefner, Guillaume Paré, Claudia Langenberg, J E Scherberich, Bing Yu, Shreeram Akilesh, Olivier Devuyst, Luca Rampoldi, Anna Köttgen

Bibliographic record

VenueNephrology Dialysis Transplantation · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDigestive system and related health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTamm–Horsfall proteinBiologyGenome-wide association studyLocus (genetics)GeneticsKidney diseaseContext (archaeology)GenomeGeneKidneyGenotypeEndocrinologySingle-nucleotide polymorphism

Abstract

fetched live from OpenAlex

Abstract BACKGROUND AND AIMS UMOD is a major risk gene for monogenic and complex forms of kidney disease. The encoded kidney-specific protein uromodulin is the most abundant protein in urine and related to chronic kidney disease, hypertension and pathogen defense. Through basolateral release from kidney epithelial cells, uromodulin also reaches the blood, where its function is largely unknown. To gain insights into potential systemic roles, we performed genome-wide screens of circulating uromodulin in seven cohorts using two complementary assays. METHOD Separate genome-wide association study meta-analyses for circulating uromodulin were conducted for the antibody-based assay (five cohorts, N = 13 985) and the aptamer-based SOMAscan assay (two cohorts, N = 18 070). Genome-wide significant loci were placed into their functional genomic context using RNA-seq, ATAC-seq and Hi-C data generated from primary human kidney tissue. An array of downstream genetic analyses was then performed for significant loci, including fine-mapping, colocalization analyses and gene-by-gene interaction analyses. The B4GALNT2 p.Cys466Arg allele was expressed in MDCK cells and studied by immunofluorescence and Western blotting analyses. RESULTS We detected and replicated 13 genome-wide significant loci (P <5e−8; 12 novel). At the UMOD locus, functional genomics data of primary human kidney tissue highlighted an upstream regulatory variant with differential accessibility and UMOD transcription in uromodulin-synthesizing kidney cells. Shared association patterns with complex traits, including chronic kidney disease and blood pressure, placed the PRKAG2 locus in the same context as UMOD. Experimental validation of another locus, B4GALNT2, showed that the detected p.Cys466Arg variant of the encoded N-acetylgalactosaminyltransferase has a loss-of-function effect leading to higher serum uromodulin levels. Lastly, our results point to enzymes writing glycan marks present on uromodulin and to their receptors in the circulation. CONCLUSION This study provides human genetic evidence of new pathway members of uromodulin and delivers novel insights into its determinants and systemic role in the circulation.

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)0.000
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 score0.114
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.026
GPT teacher head0.259
Teacher spread0.233 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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