title: Classification for Longevity Potential: The Use of Novel Biomarkers.
abstract: BACKGROUND
  In older people, chronological age may not be the best predictor of residual lifespan and mortality, because with age the heterogeneity in health is increasing. Biomarkers for biological age and residual lifespan are being developed to predict disease and mortality better at an individual level than chronological age. In the current paper, we aim to classify a group of older people into those with longevity potential or controls.
  
  
  METHODS
  In the Leiden Longevity Study participated 1671 offspring of nonagenarian siblings, as the group with longevity potential, and 744 similarly aged controls. Using known risk factors for cardiovascular disease, previously reported markers for human longevity and other physiological measures as predictors, classification models for longevity potential were constructed with multiple logistic regression of the offspring-control status.
  
  
  RESULTS
  The Framingham Risk Score (FRS) is predictive for longevity potential [area under the receiver operating characteristic curve (AUC) = 64.7]. Physiological parameters involved in immune responses and glucose, lipid and energy metabolism further improve the prediction performance for longevity potential (AUCmale = 71.4, AUCfemale = 68.7).
  
  
  CONCLUSIONS
  Using the FRS, the classification of older people in groups with longevity potential and controls is moderate, but can be improved to a reasonably good classification in combination with markers of immune response, glucose, lipid, and energy metabolism. We show that individual classification of older people for longevity potential may be feasible using biomarkers from a wide variety of different biological processes.
authors.affiliation: Molecular Epidemiology, Leiden University Medical Center , Leiden , Netherlands.
authors.forename: Marian
authors.initials: M
authors.lastname: Beekman
authors.affiliation: Medical Statistics and Bioinformatics, Leiden University Medical Center , Leiden , Netherlands.
authors.forename: Hae-Won
authors.initials: HW
authors.lastname: Uh
authors.affiliation: Gerontology and Geriatrics, Leiden University Medical Center , Leiden , Netherlands.
authors.forename: Diana
authors.initials: D
authors.lastname: van Heemst
authors.affiliation: Center for Proteomics and Metabolomics, Leiden University Medical Center , Leiden , Netherlands.
authors.forename: Manfred
authors.initials: M
authors.lastname: Wuhrer
authors.affiliation: Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, Netherlands; Department of Translational Molecular Pathology, MD Anderson Cancer Center, Houston, TX, USA.
authors.forename: L Renee
authors.initials: LR
authors.lastname: Ruhaak
authors.affiliation: Analytical Biosciences, Leiden Academic Centre for Drug Research, Leiden, Netherlands; Instituto Nacional de Medicina Genomica (INMEGEN), Mexico City, Mexico.
authors.forename: Vanessa
authors.initials: V
authors.lastname: Gonzalez-Covarrubias
authors.affiliation: Analytical Biosciences, Leiden Academic Centre for Drug Research, Leiden, Netherlands; Netherlands Metabolomics Centre, Leiden, Netherlands.
authors.forename: Thomas
authors.initials: T
authors.lastname: Hankemeier
authors.affiliation: Medical Statistics and Bioinformatics, Leiden University Medical Center , Leiden , Netherlands.
authors.forename: Jeanine J
authors.initials: JJ
authors.lastname: Houwing-Duistermaat
authors.affiliation: Molecular Epidemiology, Leiden University Medical Center , Leiden , Netherlands.
authors.forename: P Eline
authors.initials: PE
authors.lastname: Slagboom
keywords: Framingham Risk Score; biomarker; classification and prediction; human longevity potential; sex-specific analysis