Identifying amyloid pathology-related cerebrospinal fluid biomarkers for Alzheimer's disease in a multicohort study

• Type of Material: Article
• Authors: Yuk Yee Leung, University of Pennsylvania; Jon B. Toledo, University of Pennsylvania; Alexey Nefedov, University of Pennsylvania; Robi Polikar, Rowan University; Nandini Raghavan, Janssen Research & Development, LLC; Sharon X. Xie, University of Pennsylvania; Michael Farnum, Janssen Research & Development, LLC; Tim Schultz, Janssen Research & Development, LLC; Young Baek, University of Pennsylvania; Vivianna M. Van Deerlin, University of Pennsylvania; William Hu, Emory University; David M. Holtzman, Washington University in St. Louis; Anne M. Fagan, Washington University in St. Louis; Richard J. Perrin, Washington University in St. Louis; Murray Grossman, University of Pennsylvania; Holly D. Soares, Bristol-Meyer Squibb; Mitchel A. Kling, University of Pennsylvania; Matthew Mailman, Janssen Research & Development, LLC; Steven E. Arnold, University of Pennsylvania; Vaibhav Narayan, Janssen Research & Development, LLC; Virginia M-Y. Lee, University of Pennsylvania; Leslie M. Shaw, University of Pennsylvania; David Baker, Janssen Research & Development, LLC; Gayle M. Wittenberg, Janssen Research & Development, LLC; John Q. Trojanowski, University of Pennsylvania; Li-San Wang, University of Pennsylvania
• Language: English
• Date: 2015-09-01
• Publisher: Elsevier
• Publication Version: Final Published Version
• Copyright Statement: © 2015 The Authors.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.dadm.2015.06.008
• Title of Journal or Parent Work: Alzheimer's and Dementia
• ISSN: 1552-5260
• Volume: 1
• Issue: 3
• Start Page: 339
• End Page: 348
• Grant/Funding Information: This publication was made possible by grant number UL1 RR024992 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH) and NIH Roadmap for Medical Research.; This work was supported by a grant to Washington University from Pfizer.; This work was sponsored by a collaborative research project between the University of Pennsylvania, the Center for Neurodegenerative Disease Research, and Janssen entity.; J.B.T. was supported by a grant of the Alfonso Martin Escudero Foundation.; This work was also supported by the National Institutes of Health grants P50 AG05681, P01AG03991, P01 AG026276, P30 NS057105, and the Charles and Joanne Knight Alzheimer Research Initiative.; For additional funding information, see the full article.; This work was also supported by the UPennAG-10124.
• Keywords: Cerebrospinal fluid; Biomarkers; Dementia; Amyloid beta; Cognitive impairment; Alzheimer’s disease
• Research Categories: Biology, Neuroscience; Health Sciences, Pathology

Abstract

Introduction: The dynamic range of cerebrospinal fluid (CSF) amyloid β (Aβ1–42) measurement does not parallel to cognitive changes in Alzheimer's disease (AD) and cognitively normal (CN) subjects across different studies. Therefore, identifying novel proteins to characterize symptomatic AD samples is important. Methods: Proteins were profiled using a multianalyte platform by Rules Based Medicine (MAP-RBM). Due to underlying heterogeneity and unbalanced sample size, we combined subjects (344 AD and 325 CN) from three cohorts: Alzheimer's Disease Neuroimaging Initiative, Penn Center for Neurodegenerative Disease Research of the University of Pennsylvania, and Knight Alzheimer's Disease Research Center at Washington University in St. Louis. We focused on samples whose cognitive and amyloid status was consistent. We performed linear regression (accounted for age, gender, number of apolipoprotein E (APOE) e4 alleles, and cohort variable) to identify amyloid-related proteins for symptomatic AD subjects in this largest ever CSF–based MAP-RBM study. ANOVA and Tukey's test were used to evaluate if these proteins were related to cognitive impairment changes as measured by mini-mental state examination (MMSE). Results: Seven proteins were significantly associated with Aβ1–42 levels in the combined cohort (false discovery rate adjusted P < .05), of which lipoprotein a (Lp(a)), prolactin (PRL), resistin, and vascular endothelial growth factor (VEGF) have consistent direction of associations across every individual cohort. VEGF was strongly associated with MMSE scores, followed by pancreatic polypeptide and immunoglobulin A (IgA), suggesting they may be related to staging of AD. Discussion: Lp(a), PRL, IgA, and tissue factor/thromboplastin have never been reported for AD diagnosis in previous individual CSF–based MAP-RBM studies. Although some of our reported analytes are related to AD pathophysiology, other's roles in symptomatic AD samples worth further explorations.