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Record W4384665253 · doi:10.1007/s00109-023-02341-4

Genotypic analysis of a large cohort of patients with suspected atypical hemolytic uremic syndrome

2023· article· en· W4384665253 on OpenAlexafffundabout
Dervla M. Connaughton, Pratibha Bhai, Paul Isenring, Mohammed Mahdi, Bekim Sadiković, Laila C. Schenkel

Bibliographic record

VenueJournal of Molecular Medicine · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsUniversité LavalLondon Health Sciences CentreWestern University
FundersAlexion PharmaceuticalsAcademic Medical Organization of Southwestern OntarioLondon Health Sciences CentreAstraZeneca
KeywordsAtypical hemolytic uremic syndromePenetranceGenetic testingMedicineMicroangiopathic hemolytic anemiaCopy-number variationMolecular diagnosticsGeneticsCohortBioinformaticsInternal medicineGeneBiologyImmunologyPhenotypeComplement systemThrombotic thrombocytopenic purpuraAntibody

Abstract

fetched live from OpenAlex

Atypical hemolytic uremic syndrome (aHUS) is characterized by microangiopathic hemolytic anemia, thrombocytopenia, and renal impairment. Complement and coagulation gene variants have been associated with aHUS susceptibility. We assessed the diagnostic yield of a next-generation sequencing (NGS) panel in a large cohort of Canadian patients with suspected aHUS. Molecular testing was performed on peripheral blood DNA samples from 167 patients, collected between May 2019 and December 2021, using a clinically validated NGS pipeline. Coding exons with 20 base pairs of flanking intronic regions for 21 aHUS-associated or candidate genes were enriched using a custom hybridization protocol. All sequence and copy number variants were assessed and classified following American College of Medical Genetics guidelines. Molecular diagnostic results were reported for four variants in three individuals (1.8%). Twenty-seven variants of unknown significance were identified in 25 (15%) patients, and 34 unique variants in candidate genes were identified in 28 individuals. An illustrative patient case describing two genetic alterations in complement genes is presented, highlighting that variable expressivity and incomplete penetrance must be considered when interpreting genetic data in patients with complement-mediated disease, alongside the potential additive effects of genetic variants on aHUS pathophysiology. In this cohort of patients with suspected aHUS, using clinical pipelines for genetic testing and variant classification, pathogenic/likely pathogenic variants occurred in a very small percentage of patients. Our results highlight the ongoing challenges in variant classification following NGS panel testing in patients with suspected aHUS, alongside the need for clear testing guidance in the clinical setting. KEY MESSAGES: • Clinical molecular testing for disease associated genes in aHUS is challenging. • Challenges include patient selection criteria, test validation, and interpretation. • Most variants were of uncertain significance (31.7% of patients; VUS + candidates). • Their clinical significance may be elucidated as more evidence becomes available. • Low molecular diagnostic rate (1.8%), perhaps due to strict classification criteria. • Case study identified two likely pathogenic variants; one each in MCP/CD46 and CFI.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.251
Teacher spread0.244 · 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 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

Citations6
Published2023
Admission routes3
Has abstractyes

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