Blood metabolite markers of preclinical Alzheimer's disease in two longitudinally followed cohorts of older individuals

详细信息    查看全文

• 作者：Ramon Casanova^a ; Sudhir Varma^b ; Brittany Simpson^c ; ^d ; Min Kim^e ; Yang An^f ; Santiago Saldana^a ; Carlos Riveros^g ; Pablo Moscato^g ; Michael Griswold^h ; Denise Sonntagⁱ ; Judith Wahrheitⁱ ; Kristaps Klavinsⁱ ; Palmi V. Jonsson^j ; Gudny Eiriksdottir^k ; Thor Aspelund^j ; ^k ; Lenore J. Launer^l ; Vilmundur Gudnason^j ; ^k ; Cristina Legido Quigley^e ; Madhav Thambisetty^c ; ^{thambisettym@mail.nih.gov" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Preclinical Alzheimer's disease ; Biomarker ; Metabolomics ; Phospholipids ; Machine learning
• 刊名：Alzheimer's & Dementia
• 出版年：2016
• 出版时间：July 2016
• 年：2016
• 卷：12
• 期：7
• 页码：815-822
• 全文大小：564 K

文摘

Recently, quantitative metabolomics identified a panel of 10 plasma lipids that were highly predictive of conversion to Alzheimer's disease (AD) in cognitively normal older individuals (n = 28, area under the curve [AUC] = 0.92, sensitivity/specificity of 90%/90%).

Methods

Quantitative targeted metabolomics in serum using an identical method as in the index study.

Results

We failed to replicate these findings in a substantially larger study from two independent cohorts—the Baltimore Longitudinal Study of Aging ([BLSA], n = 93, AUC = 0.642, sensitivity/specificity of 51.6%/65.7%) and the Age, Gene/Environment Susceptibility-Reykjavik Study ([AGES-RS], n = 100, AUC = 0.395, sensitivity/specificity of 47.0%/36.0%). In analyses applying machine learning methods to all 187 metabolite concentrations assayed, we find a modest signal in the BLSA with distinct metabolites associated with the preclinical and symptomatic stages of AD, whereas the same methods gave poor classification accuracies in the AGES-RS samples.

Discussion

We believe that ours is the largest blood biomarker study of preclinical AD to date. These findings underscore the importance of large-scale independent validation of index findings from biomarker studies with relatively small sample sizes.