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Biomarker-guided clustering of Alzheimer's disease clinical syndromes.

Journal article
Authors Nicola Toschi
Simone Lista
Filippo Baldacci
Enrica Cavedo
Henrik Zetterberg
Kaj Blennow
Ingo Kilimann
Stefan J Teipel
Antonio Melo Dos Santos
Stéphane Epelbaum
Foudil Lamari
Remy Genthon
Marie-Odile Habert
Bruno Dubois
Roberto Floris
Francesco Garaci
Andrea Vergallo
Harald Hampel
Published in Neurobiology of aging
Volume 83
Issue November
Pages 42-53
ISSN 1558-1497
Publication year 2019
Published at Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry
Pages 42-53
Language en
Links dx.doi.org/10.1016/j.neurobiolaging...
www.ncbi.nlm.nih.gov/entrez/query.f...
Subject categories Neurochemistry

Abstract

Alzheimer's disease (AD) neuropathology is extremely heterogeneous, and the evolution from preclinical to mild cognitive impairment until dementia is driven by interacting genetic/biological mechanisms not fully captured by current clinical/research criteria. We characterized the heterogeneous "construct" of AD through a cerebrospinal fluid biomarker-guided stratification approach. We analyzed 5 validated pathophysiological cerebrospinal fluid biomarkers (Aβ1-42, t-tau, p-tau181, NFL, YKL-40) in 113 participants (healthy controls [N = 20], subjective memory complainers [N = 36], mild cognitive impairment [N = 20], and AD dementia [N = 37], age: 66.7 ± 10.4, 70.4 ± 7.7, 71.7 ± 8.4, 76.2 ± 3.5 years [mean ± SD], respectively) using Density-Based Spatial Clustering of Applications with Noise, which does not require a priori determination of the number of clusters. We found 5 distinct clusters (sizes: N = 38, 16, 24, 14, and 21) whose composition was independent of phenotypical groups. Two clusters showed biomarker profiles linked to neurodegenerative processes not associated with classical AD-related pathophysiology. One cluster was characterized by the neuroinflammation biomarker YKL-40. Combining nonlinear data aggregation with informative biomarkers can generate novel patient strata which are representative of cellular/molecular pathophysiology and may aid in predicting disease evolution and mechanistic drug response.

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