Department of Computer Engineering & Applications, Institute of Engineering & Technology, GLA University, Mathura 281406, India.
Department of Medicine, Sawai Man Singh Medical College and Hospital, Jaipur 302004, India.
Biomolecules. 2023 Feb 24;13(3):432. doi: 10.3390/biom13030432.
Insulin resistance (IR) is considered the precursor and the key pathophysiological mechanism of type 2 diabetes (T2D) and metabolic syndrome (MetS). However, the pathways that IR shares with T2D are not clearly understood. Meta-analysis of multiple DNA microarray datasets could provide a robust set of metagenes identified across multiple studies. These metagenes would likely include a subset of genes (key metagenes) shared by both IR and T2D, and possibly responsible for the transition between them. In this study, we attempted to find these key metagenes using a feature selection method, LASSO, and then used the expression profiles of these genes to train five machine learning models: LASSO, SVM, XGBoost, Random Forest, and ANN. Among them, ANN performed well, with an area under the curve (AUC) > 95%. It also demonstrated fairly good performance in differentiating diabetics from normal glucose tolerant (NGT) persons in the test dataset, with 73% accuracy across 64 human adipose tissue samples. Furthermore, these core metagenes were also enriched in diabetes-associated terms and were found in previous genome-wide association studies of T2D and its associated glycemic traits HOMA-IR and HOMA-B. Therefore, this metagenome deserves further investigation with regard to the cardinal molecular pathological defects/pathways underlying both IR and T2D.
胰岛素抵抗（IR）被认为是 2 型糖尿病（T2D）和代谢综合征（MetS）的前体和关键病理生理机制。然而，IR 与 T2D 之间的途径尚不清楚。对多个 DNA 微阵列数据集的荟萃分析可以提供一组经过多个研究验证的稳健的元基因。这些元基因可能包括 IR 和 T2D 共有的一组基因（关键元基因），并可能负责它们之间的转变。在这项研究中，我们试图使用特征选择方法 LASSO 找到这些关键元基因，然后使用这些基因的表达谱来训练五个机器学习模型：LASSO、SVM、XGBoost、随机森林和 ANN。其中，ANN 表现良好，曲线下面积（AUC）>95%。它在区分糖尿病患者和正常葡萄糖耐量（NGT）个体的测试数据集方面也表现出相当好的性能，在 64 个人体脂肪组织样本中准确率为 73%。此外，这些核心元基因在与糖尿病相关的术语中也得到了富集，并在以前的 T2D 及其相关血糖特征 HOMA-IR 和 HOMA-B 的全基因组关联研究中被发现。因此，这个元基因组值得进一步研究，以了解 IR 和 T2D 背后的主要分子病理缺陷/途径。
