He Shan, Granot-Hershkovitz Einat, Zhang Ying, Bressler Jan, Tarraf Wassim, Yu Bing, Huang Tianyi, Zeng Donglin, Wassertheil-Smoller Sylvia, Lamar Melissa, Daviglus Martha, Marquine Maria J, Cai Jianwen, Mosley Thomas, Kaplan Robert, Boerwinkle Eric, Fornage Myriam, DeCarli Charles, Kristal Bruce, Gonzalez Hector M, Sofer Tamar
Department of Biostatistics Harvard T.H Chan School of Public Health Boston Massachusetts USA.
Division of Sleep and Circadian Disorders Brigham and Women's Hospital Boston Massachusetts USA.
Alzheimers Dement (Amst). 2022 Feb 23;14(1):e12259. doi: 10.1002/dad2.12259. eCollection 2022.
Blood metabolomics-based biomarkers may be useful to predict measures of neurocognitive aging.
We tested the association between 707 blood metabolites measured in 1451 participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), with mild cognitive impairment (MCI) and global cognitive change assessed 7 years later. We further used Lasso penalized regression to construct a metabolomics risk score (MRS) that predicts MCI, potentially identifying a different set of metabolites than those discovered in individual-metabolite analysis.
We identified 20 metabolites predicting prevalent MCI and/or global cognitive change. Six of them were novel and 14 were previously reported as associated with neurocognitive aging outcomes. The MCI MRS comprised 61 metabolites and improved prediction accuracy from 84% (minimally adjusted model) to 89% in the entire dataset and from 75% to 87% among apolipoprotein E ε4 carriers.
Blood metabolites may serve as biomarkers identifying individuals at risk for MCI among US Hispanics/Latinos.
基于血液代谢组学的生物标志物可能有助于预测神经认知衰老的指标。
我们检测了来自西班牙裔社区健康研究/拉丁裔研究(HCHS/SOL)的1451名参与者所测量的707种血液代谢物与7年后评估的轻度认知障碍(MCI)和整体认知变化之间的关联。我们进一步使用套索惩罚回归构建了一个代谢组学风险评分(MRS)来预测MCI,这可能会识别出与个体代谢物分析中发现的不同的一组代谢物。
我们确定了20种预测普遍存在的MCI和/或整体认知变化的代谢物。其中6种是新发现的,14种先前已报道与神经认知衰老结果相关。MCI的MRS由61种代谢物组成,在整个数据集中,预测准确率从84%(最小调整模型)提高到89%,在载脂蛋白Eε4携带者中从75%提高到87%。
血液代谢物可能作为生物标志物,识别美国西班牙裔/拉丁裔中有MCI风险的个体。