Revealing heterogeneity of brain imaging phenotypes in Alzheimer's disease based on unsupervised clustering of blood marker profiles.

  • Authors
  • Martí-Juan G, Sanroma G, Piella G.
  • UPF authors
  • PIELLA FENOY, GEMA; MARTI JUAN, GERARD;
  • Type
  • Scholarly articles
  • Journal títle
  • PLoS ONE
  • Publication year
  • 2019
  • Volume
  • 14
  • Number
  • 3
  • Pages
  • 0-0
  • ISSN
  • 1932-6203
  • Publication State
  • Published
  • Abstract
  • apos;s disease (AD) affects millions of people and is a major rising problem in health care worldwide. Recent research suggests that AD could have different subtypes, presenting differences in how the disease develops. Characterizing those subtypes could be key to deepen the understanding of this complex disease. In this paper, we used a multivariate, non-supervised clustering method over blood-based markers to find subgroups of patients defined by distinctive blood marker profiles. Our analysis on ADNI database identified 4 possible subgroups, each with a different blood profile. More importantly, we show that subgroups with different profiles have a different relationship between brain phenotypes detected in magnetic resonance imaging and disease condition.
  • Complete citation
  • Martí-Juan G, Sanroma G, Piella G.. Revealing heterogeneity of brain imaging phenotypes in Alzheimer's disease based on unsupervised clustering of blood marker profiles.. PLoS ONE 2019; 14(3).
Bibliometric indicators
  • 3 times cited Scopus
  • 2 times cited WOS
  • Índex Scimago de 1.023(2019)