Yu Wuhan, Chen Lihua, Li Xuebing, Han Tingli, Yang Yang, Hu Cheng, Yu Weihua, Lü Yang
Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Department of Obsetric and Gyncology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Brain Sci. 2023 Oct 13;13(10):1459. doi: 10.3390/brainsci13101459.
(1) Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that threatens the population health of older adults. However, the mechanisms of the altered metabolism involved in AD pathology are poorly understood. The aim of the study was to identify the potential biomarkers of AD and discover the metabolomic changes produced during the progression of the disease. (2) Methods: Gas chromatography-mass spectrometry (GC-MS) was used to measure the concentrations of the serum metabolites in a cohort of subjects with AD (n = 88) and a cognitively normal control (CN) group (n = 85). The patients were classified as very mild (n = 25), mild (n = 27), moderate (n = 25), and severe (n = 11). The serum metabolic profiles were analyzed using multivariate and univariate approaches. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied to identify the potential biomarkers of AD. Biofunctional enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes. (3) Results: Our results revealed considerable separation between the AD and CN groups. Six metabolites were identified as potential biomarkers of AD (AUC > 0.85), and the diagnostic model of three metabolites could predict the risk of AD with high accuracy (AUC = 0.984). The metabolic enrichment analysis revealed that carbohydrate metabolism deficiency and the disturbance of amino acid, fatty acid, and lipid metabolism were involved in AD progression. Especially, the pathway analysis highlighted that l-glutamate participated in four crucial nervous system pathways (including the GABAergic synapse, the glutamatergic synapse, retrograde endocannabinoid signaling, and the synaptic vesicle cycle). (4) Conclusions: Carbohydrate metabolism deficiency and amino acid dysregulation, fatty acid, and lipid metabolism disorders were pivotal events in AD progression. Our study may provide novel insights into the role of metabolic disorders in AD pathogenesis and identify new markers for AD diagnosis.
(1) 背景：阿尔茨海默病（AD）是一种渐进性神经退行性疾病，威胁着老年人的群体健康。然而，AD病理过程中代谢改变的机制尚不清楚。本研究的目的是识别AD的潜在生物标志物，并发现疾病进展过程中产生的代谢组学变化。(2) 方法：采用气相色谱 - 质谱联用（GC - MS）技术测量一组AD患者（n = 88）和认知正常对照组（CN，n = 85）血清代谢物的浓度。患者被分为极轻度（n = 25）、轻度（n = 27）、中度（n = 25）和重度（n = 11）。使用多变量和单变量方法分析血清代谢谱。应用最小绝对收缩和选择算子（LASSO）逻辑回归来识别AD的潜在生物标志物。使用京都基因与基因组百科全书进行生物功能富集分析。(3) 结果：我们的结果显示AD组和CN组之间有明显差异。六种代谢物被确定为AD的潜在生物标志物（曲线下面积> 0.85），三种代谢物的诊断模型能够高精度地预测AD风险（曲线下面积= 0.984）。代谢富集分析表明，碳水化合物代谢缺陷以及氨基酸、脂肪酸和脂质代谢紊乱与AD进展有关。特别是，通路分析突出显示L - 谷氨酸参与了四个关键的神经系统通路（包括γ-氨基丁酸能突触、谷氨酸能突触、逆行内源性大麻素信号传导和突触小泡循环）。(4) 结论：碳水化合物代谢缺陷以及氨基酸失调、脂肪酸和脂质代谢紊乱是AD进展中的关键事件。我们的研究可能为代谢紊乱在AD发病机制中的作用提供新的见解，并识别AD诊断的新标志物。
