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

Yuk Yee Leung,Anne M Fagan,Nandini Raghavan,Leslie M Shaw,John Q Trojanowski,Sharon X Xie,Robi Polikar,Richard J Perrin,Vaibhav A Narayan,Mitchel A Kling,Vivianna M Van Deerlin,Steven E Arnold,Murray Grossman,Jon B Toledo,Alexey Nefedov,Gayle M Wittenberg,David Baker,Michael Farnum,David M Holtzman,William T Hu,Tim Schultz,Virginia M.‐Y Lee ,Matthew D Mailman ,Young Min Baek ,Holly Soares ,Li-San Wang

doi:10.1016/j.dadm.2015.06.008

Abstract

IntroductionThe 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. MethodsProteins 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). ResultsSeven 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. DiscussionLp(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.

Highlights

The dynamic range of cerebrospinal fluid (CSF) amyloid b (Ab1–42) measurement does not parallel to cognitive changes in Alzheimer’s disease (AD) and cognitively normal (CN) subjects across different studies
The purpose of our study was twofold: (1) to identify multianalyte platform by Rules Based Medicine (MAP-RBM) analytes suggestive of the presence or absence of amyloid pathology quantified by CSF Ab1–42 levels (Ab1–42 cutoff defined by Shaw et al [17] regardless of clinical diagnoses) and (2) study how these biomarkers correlate with cognitive performance
We analyzed MAP-RBM data from the three cohorts to find analytes that were associated with CSF Ab1–42 levels in individuals whose cognitive status was consistent with their amyloid status as defined by CSF Ab1–42 levels

Summary

Introduction

The dynamic range of cerebrospinal fluid (CSF) amyloid b (Ab1–42) measurement does not parallel to cognitive changes in Alzheimer’s disease (AD) and cognitively normal (CN) subjects across different studies. Alzheimer’s disease (AD) is pathologically characterized by the presence of extracellular amyloid plaques (APs) and intracellular hyperphosphorylated tau neurofibrillary tangles, which are known to be correlated with cerebrospinal fluid (CSF) levels of amyloid b (Ab1–42), total tau (t-tau), and phosphorylated tau (p-tau181) [1,2] The measurements of these proteins in the CSF using enzyme-linked immunosorbent assay (ELISA) and xMAP technology were able to distinguish most AD and cognitively normal (CN) subjects [3,4]. These CSF biomarkers are included in the revised version of the commonly used diagnosis criteria Institute of Neurological and Communicative Disorders and Stroke (NINCDS) and the Alzheimer’s Disease and Related Disorders Association (ADRDA) in 2011 for supporting clinical diagnoses [5]. Due to the heterogeneity of the disease populations, it is critical to validate identified biomarker candidates across different cohorts

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