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Association of CYP2C9*2 Allele with Sulfonylurea-Induced Hypoglycemia in Type 2 Diabetes Mellitus Patients: A Pharmacogenetic Study in Pakistani Pashtun Population

2023· preprint· en· W4383874757 on OpenAlexaff
Asif Jan, Muhammad Saeed, Ramzi A. Mothana, Tahir Muhammad, Naveed Rahman, Abdullah R. Alanzi, Rani Akbar

Bibliographic record

VenuePreprints.org · 2023
Typepreprint
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersKing Saud University
KeywordsSulfonylureaPharmacogeneticsAlleleCYP2C9PopulationHypoglycemiaType 2 Diabetes MellitusMedicineAllele frequencyInternal medicineCYP2C19GeneticsPharmacologyDiabetes mellitusGenotypeBiologyEndocrinologyGeneEnvironmental health

Abstract

fetched live from OpenAlex

Polymorphism in cytochrome P450 (CYP) 2C9 enzyme is known to cause significant inter-individual differences in drug response and occurrence of adverse drug reactions. Different alleles of the CYP2C9 gene have been identified but the notable alleles responsible for reduced enzyme activity are CYP2C9*2 and CYP2C9*3. No pharmacogenetic data is available on CYP2C9*2 and CYP2C9*3 alleles in Pakistani population. In Pakistan pharmacogenetics which examines the relationship between genetic factors and drug response, are in the early stages of development. We for the first time investigated the association between the CYP2C9 variant alleles CYP2C9*2 and CYP2C9*3 and the incidence of hypoglycemia in diabetic patients who were receiving the sulfonylurea medications. A total of n=400 individuals of Pashtun ethnicity were recruited from ten different districts of Khyber Pakhtunkhwa, Pakistan to participate in the study. The study participants were divided into two distinct groups: the case group (n=200) and the control group (n=200). The case group consisted of individuals with Type 2 Diabetes Mellitus (T2DM) who were receiving sulfonylurea medications and experience hypoglycaemia with it whereas the control group included individuals with T2DM who were receiving sulfonylurea medication but did not experience sulfonylurea-induced hypoglycaemia (SIH). Blood samples were obtained from study participants following informed consent. DNA was isolated from whole blood samples using Wiz-Prep DNA extraction kit. Following DNA isolation, CYP2C9 alleles were genotyped using MassARRAY sequencing platform at centre of genomics Rehman Medical Institute (RMI). The frequency of CYP2C9*2 (low activity allele) was more frequent in the diabetic patients with sulphonylurea-induced hypoglycaemia (SIH) compared to the control group (17.5% vs. 6.0%, p=0.021). The frequency of its corresponding genotype CYP2C9*1/*2 was higher in cases compared to control group (10% vs. 6% with P=0.036), same was true for genotype CYP2C9*2/*2 (7% vs. 3.5 % with P=0.028). Logistic regression analysis evident potential association of CYP2C9*2 allele and its genotypes with SIH. When adjusted for confounding factors such age, weight, sex, daily dose of sulphonylurea and triglyceride level the association between the CYP2C9*2 allele and hypoglycemia remains consistent. Confounding factors played no role in SIH because both groups (cases and controls) were closely matched in term of age, weight, sex, mean daily dose of sulphonylurea and trigyleride levels. Our study suggests that genetic information about a patient's CYP2C9 gene/enzyme can potentially assist physicians in prescribing the most suitable and safest drug based on their genetic make-up.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.201
GPT teacher head0.446
Teacher spread0.245 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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