Nutrition and Metabolic Profiles in the Natural History of Dementia: Recent Insights from Systems Biology and Life Course Epidemiology

Curr Nutr Rep. 2019 Sep;8(3):256-269. doi: 10.1007/s13668-019-00285-1.

Abstract

Purpose of review: Worldwide, approximately 50 million people have dementia (mostly Alzheimer's disease). Dementia results from a multicomponent pathophysiology that follows complex dynamics over many years before symptoms become apparent. Nutrition may represent a target of choice for the primary prevention of dementia; however, there is still no firm answer on how to prevent dementia efficiently. We provide a broad overview of recent studies leveraging system biology and life-long epidemiology to address the multidimensionality and dynamical patterns underlying dementia and improve knowledge on the link between nutrition, cardiometabolic health and dementia risk.

Recent findings: The aging of reference population-based cohort studies, the increasing availability of cutting-edge biomarkers (e.g., brain imaging, metabolomics) and the refinement of statistical tools to model complex exposures and dynamical health outcomes have yielded substantial progress in the understanding of dementia. Systems biology coupled with life-course epidemiology will pave the way toward novel precision nutrition approaches for prevention and management of dementia.

Keywords: Alzheimer’s disease; Amino acids; Biomarkers; Cardiometabolic factors; Cognitive aging; Cognitive function; Dementia; Healthy lifestyle; Life course epidemiology; Lifelong exposures; Lipidomics; Lipids; Metabolomics.

Publication types

  • Review

MeSH terms

  • Aging
  • Alzheimer Disease / prevention & control
  • Amino Acids / metabolism
  • Biomarkers
  • Cognition
  • Cognitive Aging
  • Dementia / epidemiology
  • Dementia / physiopathology
  • Dementia / prevention & control*
  • Healthy Lifestyle
  • Homeostasis
  • Humans
  • Lipidomics
  • Metabolome*
  • Metabolomics / methods
  • Neuroimaging / methods
  • Nutritional Status*
  • Risk Factors
  • Systems Biology*

Substances

  • Amino Acids
  • Biomarkers