Effects and Interaction of Single Nucleotide Polymorphisms at the Pharmacokinetic/pharmacodynamic Site: Insights from the Rotterdam Study into Metformin Clinical Response and Dose Titration

Soroush Mohammadi Jouabadi,Payam Peymani,Mitra Nekouei Shahraki, Jeroen G. J. van Rooij,Linda Broer,Anton J. M. Roks,Bruno H. Stricker,Fariba Ahmadizar

PHARMACOGENOMICS JOURNAL（2024）

Erasmus MC

Cited 0|Views5

Abstract

Our study investigated the impact of genetic variations on metformin glycemic response in a cohort from the Rotterdam Study, comprising 14,926 individuals followed for up to 27 years. Among 1285 metformin users of European ancestry, using linear mixed models, we analyzed the association of single nucleotide polymorphisms (SNPs) and a Polygenic Risk Score (PRS) with glycemic response, measured by changes in metformin dosage or HbA1c levels. While individual genetic variants showed no significant association, rs622342 on SLC2A1 correlated with increased glycemic response only in metformin monotherapy patients (beta = -2.09, P-value < 0.001). The collective effect of variants, as represented by PRS, weakly correlated with changes in metformin dosage (beta = 0.023, P-value = 0.027). Synergistic interaction was observed between rs7124355 and rs8192675. Our findings suggest that while higher PRS correlates with increased metformin dosage, its modest effect size limits clinical utility, emphasizing the need for future research in diverse populations to refine genetic risk models.

Translated text

求助PDF

上传PDF

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Upload PDF to Generate Summary

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper

Data Disclaimer

The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn

Chat Paper

【要点】：本研究探讨了遗传变异对二甲双胍血糖反应的影响，发现单个核苷酸多态性（SNP）和多项遗传风险评分（PRS）与二甲双胍临床反应和剂量调整的关联性。

【方法】：利用线性混合模型分析来自 Rotterdam 研究的 14,926 名参与者的数据，对 1285 名欧洲血统的二甲双胍使用者的 SNP 和 PRS 与血糖反应（通过二甲双胍剂量变化或 HbA1c 水平变化衡量）的关联性进行评估。

【实验】：通过分析 Rotterdam 研究的数据，发现 rs622342 位点与二甲双胍单药治疗患者的血糖反应呈正相关，同时发现 rs7124355 和 rs8192675 位点之间存在协同作用，PRS 与二甲双胍剂量变化呈现弱相关性（数据集名称：Rotterdam Study）。