title: Integration and relative value of biomarkers for prediction of MCI to AD progression: spatial patterns of brain atrophy, cognitive scores, APOE genotype and CSF biomarkers.
abstract: This study evaluates the individual, as well as relative and joint value of indices obtained from magnetic resonance imaging (MRI) patterns of brain atrophy (quantified by the SPARE-AD index), cerebrospinal fluid (CSF) biomarkers, APOE genotype, and cognitive performance (ADAS-Cog) in progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) within a variable follow-up period up to 6 years, using data from the Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1). SPARE-AD was first established as a highly sensitive and specific MRI-marker of AD vs. cognitively normal (CN) subjects (AUC = 0.98). Baseline predictive values of all aforementioned indices were then compared using survival analysis on 381 MCI subjects. SPARE-AD and ADAS-Cog were found to have similar predictive value, and their combination was significantly better than their individual performance. APOE genotype did not significantly improve prediction, although the combination of SPARE-AD, ADAS-Cog and APOE ε4 provided the highest hazard ratio estimates of 17.8 (last vs. first quartile). In a subset of 192 MCI patients who also had CSF biomarkers, the addition of Aβ1-42, t-tau, and p-tau181p to the previous model did not improve predictive value significantly over SPARE-AD and ADAS-Cog combined. Importantly, in amyloid-negative patients with MCI, SPARE-AD had high predictive power of clinical progression. Our findings suggest that SPARE-AD and ADAS-Cog in combination offer the highest predictive power of conversion from MCI to AD, which is improved, albeit not significantly, by APOE genotype. The finding that SPARE-AD in amyloid-negative MCI patients was predictive of clinical progression is not expected under the amyloid hypothesis and merits further investigation.
authors.affiliation: Section of Biomedical Image Analysis, Department of Radiology, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Xiao
authors.initials: X
authors.lastname: Da
authors.affiliation: Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
authors.forename: Jon B
authors.initials: JB
authors.lastname: Toledo
authors.affiliation: Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
authors.forename: Jarcy
authors.initials: J
authors.lastname: Zee
authors.affiliation: Memory Center, University of Pennsylvania, Philadelphia, PA, USA ; Section of Biomedical Image Analysis, Department of Radiology, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: David A
authors.initials: DA
authors.lastname: Wolk
authors.affiliation: Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
authors.forename: Sharon X
authors.initials: SX
authors.lastname: Xie
authors.affiliation: Section of Biomedical Image Analysis, Department of Radiology, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Yangming
authors.initials: Y
authors.lastname: Ou
authors.affiliation: Section of Biomedical Image Analysis, Department of Radiology, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Amanda
authors.initials: A
authors.lastname: Shacklett
authors.affiliation: Section of Biomedical Image Analysis, Department of Radiology, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Paraskevi
authors.initials: P
authors.lastname: Parmpi
authors.affiliation: Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
authors.forename: Leslie
authors.initials: L
authors.lastname: Shaw
authors.affiliation: Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
authors.forename: John Q
authors.initials: JQ
authors.lastname: Trojanowski
authors.affiliation: Section of Biomedical Image Analysis, Department of Radiology, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Christos
authors.initials: C
authors.lastname: Davatzikos
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis*; D016229:Amyloid beta-Peptides / Q000134:cerebrospinal fluid; D001057:Apolipoproteins E / Q000235:genetics*; D001284:Atrophy / Q000473:pathology; D015415:Biomarkers / Q000134:cerebrospinal fluid*; D001921:Brain / Q000473:pathology*; D060825:Cognitive Dysfunction / Q000134:cerebrospinal fluid / Q000235:genetics* / Q000473:pathology; D018450:Disease Progression; D005260:Female; D005838:Genotype; D006801:Humans; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging; D008297:Male; D009483:Neuropsychological Tests; D010446:Peptide Fragments / Q000134:cerebrospinal fluid; D011569:Psychiatric Status Rating Scales; D012372:ROC Curve; D016875:tau Proteins / Q000134:cerebrospinal fluid
chemical_list: D016229:Amyloid beta-Peptides; D001057:Apolipoproteins E; D015415:Biomarkers; D010446:Peptide Fragments; C075222:amyloid beta-protein (1-42); D016875:tau Proteins
keywords: Amyloid; Biomarkers of AD; Cerebrospinal fluid; Dementia; Early Alzheimer's disease; Magnetic resonance imaging; Mild cognitive impairment