Uric Acid and Gluconic Acid as Predictors of Hyperglycemia and Cytotoxic Injury after Stroke.
Uric Acid and Gluconic Acid as Predictors of Hyperglycemia and Cytotoxic Injury after Stroke.
复制标题
DOI：
10.1007/s12975-020-00862-5
复制
发表时间：
2021-04
影响因子：
6.9
通讯作者：
Acharjee A
中科院分区：
文献类型：
--
作者：
Ament Z;Bevers MB;Wolcott Z;Kimberly WT;Acharjee A
高血压是急性缺血性脑卒中后严重脑损伤的一个特征，但其潜在的代谢变化及其与细胞毒性脑损伤的联系尚不完全清楚。在这项观察性研究中，我们应用回归，机器学习分类分析来识别与高血糖症相关的代谢物和细胞毒性脑损伤的神经影像学代理。采用液相色谱-串联质谱法对381例急性卒中患者的入院血浆样本进行代谢组学和脂质组学研究。由中心临床实验室测量葡萄糖，一个亚组的患者（n=201）在磁共振成像（MRI）上进行表观扩散系数（ADC）成像定量，以估计细胞毒性损伤。在高血糖（OR 19.6，95% CI 8.6 - 44.7，P=1.44x10−12）和ADC（OR 5.3，95% CI 2.2 - 13.0，P=2.42x10−4）的单变量分析中，尿酸是主要代谢物。为了进一步对模型特征进行优先级排序并考虑非线性相关结构，应用随机森林机器学习算法分别对高血糖症和ADC进行建模。所使用的统计技术已将尿酸和葡萄糖酸确定为所有模型共同的主要候选标记物（尿酸的R2= 68%，P=2.2 x 10−10;葡萄糖酸的R2= 15%，P=8.09 x 10−10）。尿酸和葡萄糖酸都与高血糖和细胞毒性脑损伤有关。这两种代谢物都与氧化应激有关，这突出了限制中风后脑损伤的两个候选目标。
Hyperglycemia is a feature of worse brain injury after acute ischemic stroke, but the underlying metabolic changes and the link to cytotoxic brain injury is not fully understood. In this observational study, we applied regression, machine learning classification analyses to identify metabolites associated with hyperglycemia and a neuroimaging proxy for cytotoxic brain injury. Metabolomics and lipidomics was carried out using liquid chromatography-tandem mass spectrometry in admission plasma samples from 381 patients presenting with an acute stroke. Glucose was measured by a central clinical laboratory, and a subgroup of patients (n=201) had apparent diffusion coefficient (ADC) imaging quantified on magnetic resonance imaging (MRI) to estimate cytotoxic injury. Uric acid was the leading metabolite in univariate analysis of both hyperglycemia (OR 19.6, 95% CI 8.6 – 44.7, P=1.44x10−12) and ADC (OR 5.3, 95% CI 2.2 – 13.0, P=2.42x10−4). To further prioritize model features and account for nonlinear correlation structure, a random forest machine learning algorithm was applied to separately model hyperglycemia and ADC. The statistical techniques used, have identified uric acid and gluconic acids as leading candidate markers common to all models (R2=68%, P=2.2 x 10−10 for uric acid; R2=15%, P=8.09 x 10−10 for gluconic acid). Both uric acid and gluconic acid were associated with hyperglycemia and cytotoxic brain injury. Both metabolites are linked to oxidative stress, which highlights two candidate targets for limiting brain injury after stroke.
登录
查看更多内容
影响因子：
7.6
作者：
BARON, RM;KENNY, DA
通讯作者：
KENNY, DA
影响因子：
3
作者：
Acharjee A;Ament Z;West JA;Stanley E;Griffin JL
通讯作者：
Griffin JL
影响因子：
8.3
作者：
ONEILL, PA;DAVIES, I;BENNETT, D
通讯作者：
BENNETT, D
影响因子：
48
作者：
Gray, Christopher S.;Hildreth, Anthony J.;Alberti, K. George M. M.
通讯作者：
Alberti, K. George M. M.
影响因子：
13.6
作者：
Floegel A;Kühn T;Sookthai D;Johnson T;Prehn C;Rolle-Kampczyk U;Otto W;Weikert C;Illig T;von Bergen M;Adamski J;Boeing H;Kaaks R;Pischon T
通讯作者：
Pischon T