Bipolar disorder I (BD-I) and bipolar disorder II (BD-II) have specific characteristics and clear diagnostic criteria, but quite different treatment guidelines. In clinical practice, BD-II is commonly mistaken as a mild form of BD-I. This study uses data science technique to identify the important Single Nucleotide Polymorphisms (SNPs) significantly affecting the classifications of BD-I and BD-II, and develops a set of complementary diagnostic classifiers to enhance the diagnostic process. Screening assessments and SNP genotypes of 316 Han Chinese were performed with the Affymetrix Axiom Genome-Wide TWB Array Plate. The results show that the classifier constructed by 23 SNPs reached the area under curve of ROC (AUC) level of 0.939, while the classifier constructed by 42 SNPs reached the AUC level of 0.9574, which is a mere addition of 1.84 percent. The accuracy rate of classification increased by 3.46 percent. This study also uses Gene Ontology (GO) and Pathway to conduct a functional analysis and identify significant items, including calcium ion binding, GABA-A receptor activity, Rap1 signaling pathway, ECM proteoglycans, IL12-mediated signaling events, Nicotine addiction), and PI3K-Akt signaling pathway. The study can address time-consuming SNPs identification and also quantify the effect of SNP-SNP interactions.

中文翻译：

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用于双相情感障碍 I 和双相情感障碍 II 分类的 SNP 数据科学

双相情感障碍 I（BD-I）和双相情感障碍 II（BD-II）具有特定的特征和明确的诊断标准，但治疗指南却截然不同。在临床实践中，BD-II 通常被误认为是 BD-I 的一种温和形式。本研究使用数据科学技术识别显着影响 BD-I 和 BD-II 分类的重要单核苷酸多态性 (SNP)，并开发了一组互补的诊断分类器以增强诊断过程。使用 Affymetrix Axiom Genome-Wide TWB Array Plate 对 316 名汉族人进行筛选评估和 SNP 基因型。结果表明，23个SNP构建的分类器的ROC曲线下面积（AUC）水平为0.939，而42个SNP构建的分类器的AUC水平为0.9574，仅增加了1.84%。分类准确率提高了3.46%。本研究还使用 Gene Ontology (GO) 和 Pathway 进行功能分析并确定重要项目，包括钙离子结合、GABA-A 受体活性、Rap1 信号通路、ECM 蛋白聚糖、IL12 介导的信号事件、尼古丁成瘾），以及PI3K-Akt 信号通路。该研究可以解决耗时的 SNP 识别问题，还可以量化 SNP-SNP 相互作用的影响。