Genetic variation within the pri-let-7f-2 in the X chromosome predicting stroke risk in a Chinese Han population from Liaoning, China: From a case-control study to a new predictive nomogram.
Genetic variation within the pri-let-7f-2 in the X chromosome predicting stroke risk in a Chinese Han population from Liaoning, China: From a case-control study to a new predictive nomogram.
复制标题
X 染色体 pri-let-7f-2 内的遗传变异可预测中国辽宁汉族人群的中风风险：从病例对照研究到新的预测列线图
DOI：
10.3389/fmed.2022.936249
复制
发表时间：
2022
影响因子：
3.9
通讯作者：
中科院分区：
文献类型：
--
作者：
背景和目的中风是世界范围内最常见的致残原因和第二大死亡原因。因此，有必要确定有发生中风风险的患者。本病例对照研究旨在创建和验证基于性别的遗传特征图，以便仅使用易于获得的临床变量来预测缺血性卒中（IS）风险。材料与方法采用R软件中的样本函数随机分为训练组（70%）和验证组（30%），共纳入中国辽宁省（汉族）IS患者1803例和健康对照1456例。分析了prilet -7f-2 rs17276588变异基因型的分布。在进行基因分型分析后，采用统计学分析确定相关特征。利用多元逻辑回归、最小绝对收缩和选择算子（LASSO）回归和单变量回归识别出的特征，建立多元预测nomogram模型。采用校准曲线确定模型在训练和验证队列中的识别精度。外部效度也进行了测试。结果基因分型分析确定A等位基因是男性和女性IS的潜在危险因素。nomogram发现rs17276588变异基因型和一些临床参数，包括年龄、糖尿病、体重指数（BMI）、高血压、饮酒史、吸烟史和高脂血症是发生IS的危险因素。男女模型的标定曲线具有较好的一致性和适用性。结论pri-let-7f-2 rs17276588变异基因型与中国北方汉族人群is发病率密切相关。我们设计的nomogram结合了遗传指纹和临床数据，在预测中国汉族人群患IS的风险方面有很大的前景。
Background and objectives Stroke is the most common cause of disability and the second cause of death worldwide. Therefore, there is a need to identify patients at risk of developing stroke. This case-control study aimed to create and verify a gender-specific genetic signature-based nomogram to facilitate the prediction of ischemic stroke (IS) risk using only easily available clinical variables. Materials and methods A total of 1,803 IS patients and 1,456 healthy controls from the Liaoning province in China (Han population) were included which randomly divided into training cohort (70%) and validation cohort (30%) using the sample function in R software. The distribution of the pri-let-7f-2 rs17276588 variant genotype was analyzed. Following genotyping analysis, statistical analysis was used to identify relevant features. The features identified from the multivariate logistic regression, the least absolute shrinkage and selection operator (LASSO) regression, and univariate regression were used to create a multivariate prediction nomogram model. A calibration curve was used to determine the discrimination accuracy of the model in the training and validation cohorts. External validity was also performed. Results The genotyping analysis identified the A allele as a potential risk factor for IS in both men and women. The nomogram identified the rs17276588 variant genotype and several clinical parameters, including age, diabetes mellitus, body mass index (BMI), hypertension, history of alcohol use, history of smoking, and hyperlipidemia as risk factors for developing IS. The calibration curves for the male and female models showed good consistency and applicability. Conclusion The pri-let-7f-2 rs17276588 variant genotype is highly linked to the incidence of IS in the northern Chinese Han population. The nomogram we devised, which combines genetic fingerprints and clinical data, has a lot of promise for predicting the risk of IS within the Chinese Han population.
影响因子：
3.4
作者：
Li J;Huang J;Pang T;Chen Z;Li J;Wu L;Hu Y;Chen W
通讯作者：
Chen W
构建基于 MicroRNA 的列线图来预测乳腺癌患者的肺转移
影响因子：
3.7
作者：
Zhang L;Pan J;Wang Z;Yang C;Huang J
通讯作者：
Huang J