The “development of metabolic and functional markers of dementia in older people” (ODINO) study: Rationale, design and methods

Roberto Bernabei, Emanuele Marzetti, Rosa Liperoti, Riccardo Calvani, Jacopo Gervasoni, Aniello Primiano, Domenico Fusco, Maria Rita Lo Monaco, Federico Marini, Alessandra Biancolillo

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Mild cognitive impairment (MCI), also termed mild neurocognitive disorder, includes a heterogeneous group of conditions characterized by declines in one or more cognitive domains greater than that expected during “normal” aging but not severe enough to impair functional abilities. MCI has been associated with an increased risk of developing dementia and even considered an early stage of it. Therefore, noninvasively accessible biomarkers of MCI are highly sought after for early identification of the condition. Systemic inflammation, metabolic perturbations, and declining physical performance have been described in people with MCI. However, whether biological and functional parameters differ across MCI neuropsychological subtypes is presently debated. Likewise, the predictive value of existing biomarkers toward MCI conversion into dementia is unclear. The “develOpment of metabolic and functional markers of Dementia IN Older people” (ODINO) study was conceived as a multi-dimensional investigation in which multi-marker discovery will be coupled with innovative statistical approaches to characterize patterns of systemic inflammation, metabolic perturbations, and physical performance in older adults with MCI. The ultimate aim of ODINO is to identify potential biomarkers specific for MCI subtypes and predictive of MCI conversion into Alzheimer’s disease or other forms of dementia over a three-year follow-up. Here, we describe the rationale, design, and methods of ODINO.
Original languageEnglish
Pages (from-to)22-N/A
Number of pages14
JournalJournal of Personalized Medicine
Volume10
DOIs
Publication statusPublished - 2020

Keywords

  • Aging
  • Alzheimer’s disease
  • Biomarkers
  • Cognitive decline
  • Cytokines
  • Metabolomics
  • Multivariate analysis
  • Neuroinflammation
  • Person-tailored
  • Physical performance

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