基于高通量测序技术下的心脑血管疾病患病风险评估模型研究

心脑血管疾病是一种严重威胁人类健康的常见疾病,且在中等发达国家的患病率正处于逐年上升的趋势,针对无症状个体患者进行全面可靠的风险评估是预防该疾病的关键.基于高通量测序平台,以高通量测序数据为基础,通过使用多元线性回归模型来预测与心脑血管疾病高度相关的基因和SNP位点的odds ratio(OR)值信息,以此构建心脑血管风险评估模型.将这一模型预测所得到的风险评估结果与临床诊断结果进行比较,两者具有高度的一致性.

A study of the risk model of cardiovascular and cerebrovascular diseases based on high-throughput sequencing techniques

Cardiovascular and cerebrovascular diseases are common diseases that seriously threaten human health and are becoming prevalent year by year in middle-developed countries,whose prevention relies on the comprehensive and reliable risk assessment for asymptomatic individuals. With the help of the high throughput sequencing platform,this research uses the multiple-linear regression prediction model to predict the OR value of all the SNPs in an individual to reconstruct the cardiovascular risk assessment model. The comparison of the results of the risk assessment with the relevant clinical diagnosis reveals that the two have a high degree of consistency.