2016
DOI: 10.3389/fpubh.2016.00233
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Abstract: BackgroundIn 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.MethodsIn the Leiden Longevity Study participated 1671 offspring of nona… Show more

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Cited by 8 publications
(6 citation statements)
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“…Though we find that the IgG glycosylation reflects poor metabolic health, we were unable to find significant differences between middle-aged members of long-lived families and controls, who are known to differ on various metabolic measures 33 , 36 , 38 . Previous work which applied MALDI-MS to the same set of samples reported a significant decrease in the level of bisection of offspring of long-lived people, but only in individuals below 60 years of age 18 , and IgG glycosylation features contributed to the differentiation of controls and members of long-lived families 78 . A recent investigation into the released N -glycan profile of plasma samples within the Leiden Longevity cohort also could not find any association with longevity, while replicating several of the associations we find with N -glycans which likely originate from IgG 65 .Our study design does not allow for estimation of whether IgG glycosylation features offer a predictive value for cardiovascular disease in addition to traditional markers of inflammation.…”
Section: Discussionmentioning
confidence: 79%
“…Though we find that the IgG glycosylation reflects poor metabolic health, we were unable to find significant differences between middle-aged members of long-lived families and controls, who are known to differ on various metabolic measures 33 , 36 , 38 . Previous work which applied MALDI-MS to the same set of samples reported a significant decrease in the level of bisection of offspring of long-lived people, but only in individuals below 60 years of age 18 , and IgG glycosylation features contributed to the differentiation of controls and members of long-lived families 78 . A recent investigation into the released N -glycan profile of plasma samples within the Leiden Longevity cohort also could not find any association with longevity, while replicating several of the associations we find with N -glycans which likely originate from IgG 65 .Our study design does not allow for estimation of whether IgG glycosylation features offer a predictive value for cardiovascular disease in addition to traditional markers of inflammation.…”
Section: Discussionmentioning
confidence: 79%
“…Typically a linear regression is employed to show the differences in slope (see Figure 1 in Hamczyk et al 27 ), or to compare two age groups using Pearson correlation coefficients 29 . Secondly, as in the research of healthy aging and longevity 30,31 , one can consider two groups of young and old. Through a classification task, one can estimate the probability of belonging to either class and determine suitable biomarkers for longevity potential.…”
Section: Discussionmentioning
confidence: 99%
“…27 ), or to compare two age groups using Pearson correlation coefficients 29 . Secondly, as in the research of healthy aging and longevity 30,31 , one can consider two groups of young and old . Through a classification task, one can estimate the probability of belonging to either class and determine suitable biomarkers for longevity potential.…”
Section: Discussionmentioning
confidence: 99%