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Record W3020879553 · doi:10.3389/fphar.2020.00486

Long-Distance Phasing of a Tentative “Enhancer” Single-Nucleotide Polymorphism With CYP2D6 Star Allele Definitions

2020· article· en· W3020879553 on OpenAlexaff
Erin C. Boone, Wendy Y. Wang, Roger Gaedigk, Mariana Cherner, Anick Bérard, J. Steven Leeder, Neil Miller, Andrea Gaedigk

Bibliographic record

VenueFrontiers in Pharmacology · 2020
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentNational Institute on Drug AbuseNational Institutes of Health
KeywordsEnhancerGeneticsSingle-nucleotide polymorphismBiologySNPLocus (genetics)HaplotypeAlleleTag SNPPopulationComputational biologyGeneGenotypeGene expressionMedicine

Abstract

fetched live from OpenAlex

Background: The CYP2D6 gene locus has been extensively studied over decades, yet a portion of variability in CYP2D6 activity cannot be explained by known sequence variations within the gene, copy number variation or structural rearrangements. It was proposed that rs5758550 located 116 kb downstream of the CYP2D6 gene locus increases gene expression and thus contributes to variability in CYP2D6 activity. This finding has, however, not been validated. The purpose of the study was to address a major technological barrier, i.e. experimentally linking rs5758550, also referred to as the ‘enhancer’ SNP, to CYP2D6 haplotypes >100 kb away. To overcome this challenge is essential to ultimately determine the contribution of the ‘enhancer’ SNP to interindividual variability in CYP2D6 activity. Methods: A large ethnically mixed population sample (n=3162) was computationally phased to determine linkage between the ‘enhancer’ SNP and CYP2D6 haplotypes (or star alleles). To experimentally validate predicted linkages, DropPhase2D6, a digital droplet PCR (ddPCR)-based method was developed. 10X Genomics Linked-Reads were utilized as a proof of concept. Results: Phasing predicted that the ‘enhancer’ SNP can occur on numerous CYP2D6 haplotypes including CYP2D6 *1, *2, *5 and *41 and suggested that linkage is incomplete, i.e. a portion of these alleles do not have the ‘enhancer’ SNP. Phasing also revealed differences amongst the European and African ancestry data sets regarding the proportion of alleles with and without the ‘enhancer’ SNP. DropPhase2D6 was utilized to confirm or refute the predicted ‘enhancer’ SNP location for individual samples, e.g. of n=3 samples genotyped as *1/*41, rs5758550 was on the *41 allele of two samples and on *1 allele of one sample. Our findings highlights that the location of the ‘enhancer’ SNP must not be assigned by ‘default’. Furthermore, linkage between the ‘enhancer’ SNP and CYP2D6 star allele haplotypes was confirmed with 10X Genomics technology. We were unable, however, to verify selected haplotypes predicted by Ray et al (PMID 30520769). Conclusions: Since the ‘enhancer’ SNP can be present on a portion of normal, decreased, or no function alleles, the phase of the ‘enhancer’ SNP must be considered when investigating the impact of the ‘enhancer’ SNP on CYP2D6 activity.

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)0.003
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.115
GPT teacher head0.373
Teacher spread0.258 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

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