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

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

doi:10.1016/j.dadm.2015.06.008

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

Alzheimers Dement (Amst). 2015 Sep 1;1(3):339-348. doi: 10.1016/j.dadm.2015.06.008.

Authors

Yuk Yee Leung¹, Jon B Toledo², Alexey Nefedov³, Robi Polikar⁴, Nandini Raghavan⁵, Sharon X Xie⁶, Michael Farnum⁷, Tim Schultz⁷, Young Baek², Vivianna V Deerlin², William T Hu⁸, David M Holtzman⁹, Anne M Fagan⁹, Richard J Perrin¹⁰, Murray Grossman¹¹, Holly D Soares¹², Mitchel A Kling¹³, Matthew Mailman⁷, Steven E Arnold¹⁴, Vaibhav A Narayan⁷, Virginia M-Y Lee², Leslie M Shaw², David Baker⁷, Gayle M Wittenberg¹⁴, John Q Trojanowski², Li-San Wang¹

Affiliations

¹ Department of Pathology & Laboratory Medicine, Institute on Aging, Institute for Biomedical Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
² Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, Philadelphia, PA, USA.
³ Department of Pathology & Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
⁴ Department of Electrical and Computer Engineering, Rowan University, Glassboro, NJ, USA.
⁵ Department of Quantitative Science, Janssen Research & Development, LLC, Titusville, NJ, USA.
⁶ Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
⁷ Department of Neuroscience, Janssen Research & Development, LLC, Titusville, NJ, USA.
⁸ Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.
⁹ Department of Neurology, Knight Alzheimer's Disease Research Center, Hope Center for Neurodegenerative Disorders, Washington University, St Louis, MO, USA.
¹⁰ Department of Pathology and Immunology, Division of Neuropathology, Knight Alzheimer Disease Research Center, Hope Center for Neurological Disorders, Washington University, St Louis, MO, USA.
¹¹ Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
¹² Clinical Biomarkers, Bristol-Meyer Squibb, Hopewell, NJ, USA.
¹³ Behavioral Health Service, Philadelphia VA Medical Center, Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
¹⁴ Department of Neurology, Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.

Abstract

Introduction: The dynamic range of cerebrospinal fluid (CSF) amyloid β (Aβ_1-42) 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 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 Aβ_1-42 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, others' roles in symptomatic AD samples worth further explorations.

Keywords: Alzheimer’s disease; Amyloid beta; Biomarkers; Cerebrospinal fluid; Cognitive impairment; Dementia.

Abstract

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