Proteomic profiles of incident mild cognitive impairment and Alzheimer's disease among adults with Down syndrome

Sid E. O'Bryant, Fan Zhang, Wayne Silverman, Joseph H. Lee, Sharon J. Krinsky-McHale, Deborah Pang, James Hall, Nicole Schupf

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Introduction: We sought to determine if proteomic profiles could predict risk for incident mild cognitive impairment (MCI) and Alzheimer's disease (AD) among adults with Down syndrome (DS). Methods: In a cohort of 398 adults with DS, a total of n = 186 participants were determined to be non-demented and without MCI or AD at baseline and throughout follow-up; n = 103 had incident MCI and n = 81 had incident AD. Proteomics were conducted on banked plasma samples from a previously generated algorithm. Results: The proteomic profile was highly accurate in predicting incident MCI (area under the curve [AUC] = 0.92) and incident AD (AUC = 0.88). For MCI risk, the support vector machine (SVM)-based high/low cut-point yielded an adjusted hazard ratio (HR) = 6.46 (P <.001). For AD risk, the SVM-based high/low cut-point score yielded an adjusted HR = 8.4 (P <.001). Discussion: The current results provide support for our blood-based proteomic profile for predicting risk for MCI and AD among adults with DS.

Original languageEnglish
Article numbere12033
JournalAlzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
Volume12
Issue number1
DOIs
StatePublished - 2020

Keywords

  • Down syndrome
  • dementia
  • mild cognitive impairment
  • plasma
  • proteomic

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