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Record W4401322182 · doi:10.1159/000540741

Phenotypic Discordance among Siblings with Autosomal Recessive Polycystic Kidney Disease: Case Report and Review of the Literature

2024· review· en· W4401322182 on OpenAlexaff
M. Henein, Felicia Russo, Zachary T. Sentell, Rémi Goupil, Thomas M. Kitzler

Bibliographic record

Venue˜The œNephron journals/Nephron journals · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsMcGill UniversityHôpital du Sacré-Cœur de MontréalMcGill University Health Centre
Fundersnot available
KeywordsPhenotypeAutosomal dominant polycystic kidney diseaseGeneticsDiseaseAutosomal Recessive Polycystic Kidney DiseaseBiologyClinical phenotypePolycystic kidney diseasePolycystic diseasePolycystic kidneyMedicinePathologyKidneyGene

Abstract

fetched live from OpenAlex

Missense variants in the PKHD1 gene are associated with the full spectrum of autosomal recessive polycystic kidney disease severity and exhibit variable expressivity. The study of clinical expressivity is limited by the extensive allelic heterogeneity within the PKHD1 gene, which encodes a 4074-amino-acid protein. We report the case of adult siblings with biallelic missense PKHD1 variants, c.4870C>T (p.Arg1624Trp) and c.8206T>G (p.Trp2736Gly), who presented with discordant phenotypes. Patient A developed progressive chronic kidney disease and Caroli syndrome in childhood requiring combined liver and kidney transplantation, while patient B remains minimally affected in the fourth decade of life with normal kidney function and signs of medullary sponge kidney on imaging. We review previously reported cases of phenotypic discordance among siblings and suggest that genotypes composed of at least one hypomorphic missense variant are more likely to lead to phenotypic discordance.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0050.004
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.304
Teacher spread0.290 · 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 designCase report
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

Citations0
Published2024
Admission routes1
Has abstractyes

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