Alzheimer's disease (AD) represents the main form of dementia; however, valid diagnosis and treatment measures are lacking. The discovery of valuable biomarkers through omics technologies can help solve this problem. For this reason, metabolomic analysis using ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS) was carried out on plasma, hippocampus, and cortex samples of an AD rat model. Based on the metabolomic data, we report a multi-factor combined biomarker screening strategy to rapidly and accurately identify potential biomarkers. Compared with the usual procedure, our strategy can identify fewer biomarkers with higher diagnostic specificity and sensitivity. In addition to diagnosis, the potential biomarkers identified using our strategy were also beneficial for drug evaluation. Multi-factor combined biomarker screening strategy was used to identify differential metabolites from a rat model of amyloid beta peptide 1–40 (Aβ₁₋₄₀) plus ibotenic acid-induced AD (compared with the controls) for the first time; lysophosphatidylcholine (LysoPC) and intermediates of sphingolipid metabolism were screened as potential biomarkers. Subsequently, the effects of donepezil and pine nut were successfully reflected by regulating the levels of the abovementioned biomarkers and metabolic profile distribution in partial least squares-discriminant analysis (PLS-DA). This novel biomarker screening strategy can be used to analyze other metabolomic data to simultaneously enable disease diagnosis and drug evaluation.

阿尔茨海默病（AD）代表痴呆的主要形式；然而，缺乏有效的诊断和治疗措施。通过组学技术发现有价值的生物标志物可以帮助解决这个问题。为此，使用超高效液相色谱结合四极杆飞行时间串联质谱 (UPLC-Q-TOF-MS) 对 AD 大鼠模型的血浆、海马和皮层样本进行代谢组学分析。基于代谢组学数据，我们报告了一种多因素组合的生物标志物筛选策略，以快速准确地识别潜在的生物标志物。与通常的程序相比，我们的策略可以识别更少的生物标志物，具有更高的诊断特异性和敏感性。除了诊断，使用我们的策略确定的潜在生物标志物也有利于药物评估。多因素联合生物标志物筛选策略用于鉴定来自淀粉样蛋白 β 肽 1-40（Aβ_1-40 ) 首次加上鹅膏菌酸诱导的 AD (与对照相比); 溶血磷脂酰胆碱 (LysoPC) 和鞘脂代谢中间体被筛选为潜在的生物标志物。随后，通过在偏最小二乘判别分析（PLS-DA）中调节上述生物标志物的水平和代谢谱分布，成功地反映了多奈哌齐和松子的作用。这种新颖的生物标志物筛选策略可用于分析其他代谢组学数据，以同时实现疾病诊断和药物评估。