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Record W4397044725 · doi:10.1681/asn.20233411s1215d

The Polygenic Burden of Rare Variants Predicts Onset of CKD in the UK Biobank

2023· article· en· W4397044725 on OpenAlexaff
Ricky Lali, Caitlyn Vlasschaert, Matthew B. Lanktree

Bibliographic record

VenueJournal of the American Society of Nephrology · 2023
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsMcMaster UniversityQueen's UniversityImpact
Fundersnot available
KeywordsBiobankMedicinePolygenic risk scoreInternal medicineGeneticsBiologyGenotypeSingle-nucleotide polymorphism

Abstract

fetched live from OpenAlex

Background: Genetic contributors to chronic kidney disease (CKD) have been explored through monogenic mechanisms by rare mutations and polygenic mechanisms through the aggregate impact of many small-effect common variants. In this work, we test whether a polygenic burden of rare variants across numerous genes contributes to CKD by constructing a rare variant polygenic risk score (rvPRS). Methods: We first conducted a discovery exome-wide association study (ExWAS) of rare protein-truncating variants with a calculated severe CKD phenotype based on eGFR below 30 ml/min/1.73m2 using a discovery set of 834 cases and 147,855 British European controls in the UK Biobank (UKB). After excluding known Mendelian CKD genes, an rvPRS was constructed of 124 nominally significant (P<0.05) risk genes associated with severe CKD. As such, the effect conferred through rvPRS124 would not be driven through underlying monogenic mechanisms. We then tested the predictive power of rvPRS124 using a validation set consisting of 688 independent CKD events in the UKB. Results: In the validation set, rvPRS124 conferred a 21% increase in hazard for incident CKD onset with one rare protein-truncating allele (HR=1.21; 95%CI, 1.01-1.46; P=0.045) after adjusting for age, sex, the first 5 principal components of ancestry, and pertinent clinical risk factors including obesity, myocardial infarction, and smoking. Individuals with 2 or more rvPRS124 alleles (N=1,352) had a 10-fold increase in hazard for CKD onset compared to individuals with no rvPRS124 variants (HR=10.0, 95% CI, 2.5-39.4; P=1.3 x 10-3). No single gene in rvPRS124 replicated an association with CKD after adjusting for multiple hypothesis testing (P<4x10-4; 0.05/124), which emphasizes the importance of rare variant polygenic mechanisms underlying CKD. Lastly, through 1000 permutations of random gene sets, we show that the association of rvPRS124 with CKD was specific to the selected genes used to construct the score and not solely due to the gene count (P<0.05). Conclusions: Using the UKB, we demonstrate a cumulative impact of rare proteintruncating variants in genes not known to have monogenic effects on CKD. An omnigenic score, incorporating established clinical risk factors and both Monogenic and common variant polygenic effects, should also include the polygenic burden of rare variants in non-Mendelian CKD-related genes.

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 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)0.002
metaresearch head score (Gemma)0.013
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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.282
Teacher spread0.267 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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