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Polymorphisms of Multidrug Resistance Gene (MDR1) and Cyclosporine Absorption in De Novo Renal Transplant Patients

2007· article· en· W2018353645 on OpenAlexaff
Clary J. Foote, Wenda Greer, Bryce Kiberd, Albert D. Fraser, Joseph Lawen, Björn Nashan, P Belitsky

Bibliographic record

VenueTransplantation · 2007
Typearticle
Languageen
FieldMedicine
TopicDrug Transport and Resistance Mechanisms
Canadian institutionsQueen Elizabeth II Health Sciences Centre
Fundersnot available
KeywordsSingle-nucleotide polymorphismLinkage disequilibriumMedicineTransplantationHaplotypePharmacokineticsInternal medicineGastroenterologyPopulationPharmacologyBiologyAlleleGeneticsGenotypeGene

Abstract

fetched live from OpenAlex

BACKGROUND: Several single nucleotide polymorphisms (SNPs) in the multidrug resistance (MDR1) gene may play a role in the interindividual variation of cyclosporine A (CsA) absorption in renal transplant patients. METHODS: An analysis of CsA absorption measured by the dose- and weight-adjusted 4 hr area under the time-concentration curve, AUC(0-4)/mg doseCsA/kg, was conducted on day 3 after transplantation, in 69 de novo renal transplant patients who were genotyped for MDR1 SNPs. Follow-up pharmacogenomic analysis at 1 month posttransplant was performed utilizing dose- and weight-adjusted 2-hour postdose CsA concentration (C2). RESULTS: AUC(0-4)/mg doseCsA/kg was significantly higher (P=0.024) in (C/C)3435 individuals than in a grouped population of (C/T)3435 and (T/T)3435 patients on postoperative day 3. G2677T variants were not significantly correlated with CsA absorption (P=0.084). The number of C3435-G2677 haplotypes was the best predictor of CsA exposure. At 1 month posttransplant, no correlation was seen between MDR1 SNPs and CsA exposure. The frequency of wild-type variants for C3435T and G2677T were 61% and 77.6%, respectively. SNPs at G2677T and C3435T loci were found to be in linkage disequilibrium. CONCLUSIONS: MDR1 polymorphisms are associated with differences in CsA exposure only in the first posttransplant week.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.567

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 studies0.0000.000
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 head0.006
GPT teacher head0.231
Teacher spread0.224 · 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

Citations29
Published2007
Admission routes1
Has abstractyes

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