基于 logistic 回归模型的中国北方 2 型糖尿病风险评估。
Risk assessment of type 2 diabetes in northern China based on the logistic regression model.
机构信息
Beijing Computing Center, Beijing Academy of Science and Technology, Beijing 100094, China.
The Key Laboratory of Beijing Cloud Computing Technology and Applicatio.
出版信息
Technol Health Care. 2021;29(S1):351-358. doi: 10.3233/THC-218033.
BACKGROUND
Type 2 diabetes mellitus (T2DM) is a complex disease with high incidence and serious harm associated with polygenic determination. This study aimed to develop a predictive model so as to assess the risk of T2DM and apply it to health care and disease prevention in northern China.
OBJECTIVE
Based on genotyping results, a risk warning model for type 2 diabetes was established.
METHODS
Blood samples of 1042 patients with T2DM in northern China were collected. Multiplex polymerase chain reaction and high-throughput sequencing (NGS) techniques were used to design the amplification-based targeted sequencing panel to sequence the 21 T2DM susceptibility genes.
RESULT
The related key gene KQT-like subfamily member 1 played an important role in the T2DM risk model, and single-nucleotide polymorphism rs2237892 was highly significant, with a P value of 1.2 × 10-5.
CONCLUSIONS
Susceptibility genes in different populations were examined, and a model was developed to assess the risk-based genetic analysis. The performance of the model reached 92.8%.
背景
2 型糖尿病（T2DM）是一种具有高发病率和严重危害的复杂疾病，与多基因决定有关。本研究旨在建立一个预测模型，以评估 T2DM 的风险，并将其应用于中国北方的医疗保健和疾病预防。
目的
基于基因分型结果，建立 2 型糖尿病风险预警模型。
方法
收集中国北方 1042 例 T2DM 患者的血样。采用多重聚合酶链反应和高通量测序（NGS）技术设计基于扩增的靶向测序面板，对 21 个 2 型糖尿病易感性基因进行测序。
结果
相关关键基因 KQT 样亚家族成员 1 在 T2DM 风险模型中发挥重要作用，单核苷酸多态性 rs2237892 高度显著，P 值为 1.2×10-5。
结论
对不同人群的易感基因进行了检测，并建立了一个基于遗传分析的风险评估模型。该模型的性能达到了 92.8%。
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