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Biomarker-guided clustering of Alzheimer's disease clinical syndromes

2019; Elsevier BV; Volume: 83; Linguagem: Inglês

10.1016/j.neurobiolaging.2019.08.032

1558-1497

Nicola Toschi, Simone Lista, Filippo Baldacci, Enrica Cavedo, Henrik Zetterberg, Kaj Blennow, Ingo Kilimann, Stefan Teipel, Antonio Melo dos Santos, Stéphane Epelbaum, Foudil Lamari, Rémy Genthon, Marie‐Odile Habert, Bruno Dubois, Roberto Floris, Francesco Garaci, Andrea Vergallo, Harald Hampel, Hovagim Bakardjian, Habib Benali, Hugo Bertín, Joel Bonheur, Laurie Boukadida, Nadia Boukerrou, Enrica Cavedo, Patrizia A. Chiesa, Olivier Colliot, Bruno Dubois, Marion Dubois, Stéphane Epelbaum, Geoffroy Gagliardi, Rémy Genthon, Marie‐Odile Habert, Harald Hampel, Marion Houot, Aurélie Kas, Foudil Lamari, Marcel Lévy, Simone Lista, Christiane Metzinger, Fanny Mochel, Francis Nyasse, Catherine Poisson, Marie‐Claude Potier, Marie Revillon, Antonio Santos, Katia Santos Andrade, Marine Sole, Mohmed Surtee, Michel Thiebaut de Schotten, Andrea Vergallo, Nadjia Younsi,

Neuroinflammation and Neurodegeneration Mechanisms

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.