Meta-analysis of published cerebrospinal fluid proteomics data identifies and validates metabolic enzyme panel as Alzheimer's disease biomarkers

Patrick W. van Zalm, Saima Ahmed, Benoit Fatou, Rudy Schreiber, Omar Barnaby, Adam Boxer, Henrik Zetterberg, Judith A. Steen, Hanno Steen*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

To develop therapies for Alzheimer's disease, we need accurate in vivo diagnostics. Multiple proteomic studies mapping biomarker candidates in cerebrospinal fluid (CSF) resulted in little overlap. To overcome this shortcoming, we apply the rarely used concept of proteomics meta-analysis to identify an effective biomarker panel. We combine ten independent datasets for biomarker identification: seven datasets from 150 patients/controls for discovery, one dataset with 20 patients/controls for down-selection, and two data -sets with 494 patients/controls for validation. The discovery results in 21 biomarker candidates and down -selection in three, to be validated in the two additional large-scale proteomics datasets with 228 diseased and 266 control samples. This resulting 3-protein biomarker panel differentiates Alzheimer's disease (AD) from controls in the two validation cohorts with areas under the receiver operating characteristic curve (AUROCs) of 0.83 and 0.87, respectively. This study highlights the value of systematically re-analyzing pre-viously published proteomics data and the need for more stringent data deposition.
Original languageEnglish
Article number101005
Number of pages15
JournalCell Reports Medicine
Volume4
Issue number4
DOIs
Publication statusPublished - 18 Apr 2023

Keywords

  • MILD COGNITIVE IMPAIRMENT
  • GENE-EXPRESSION
  • PACKAGE
  • CORTEX

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