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Other titre : A novel measurement approach and evidence for multi-system physiological dysregulation during aging

dc.contributor.authorCohen, Alanfr
dc.contributor.authorMilot, Emmanuelfr
dc.contributor.authorFülöp, Tamasfr
dc.contributor.authorYong, Jianfr
dc.contributor.authorCohen, Alanfr
dc.contributor.otherSeplaki, Christopher L.fr
dc.contributor.otherBandeen-Roche, Karenfr
dc.contributor.otherFried, Linda P.fr
dc.date.accessioned2018-01-24T17:53:25Z
dc.date.available2018-01-24T17:53:25Z
dc.date.created2013fr
dc.date.issued2018-01-24
dc.identifier.urihttp://hdl.handle.net/11143/11821
dc.description.abstractAbstract: Previous studies have identified many biomarkers that are associated with aging and related outcomes, but the relevance of these markers for underlying processes and their relationship to hypothesized systemic dysregulation is not clear. We address this gap by presenting a novel method for measuring dysregulation via the joint distribution of multiple biomarkers and assessing associations of dysregulation with age and mortality. Using longitudinal data from the Women’s Health and Aging Study, we selected a 14-marker subset from 63 blood measures: those that diverged from the baseline population mean with age. For the 14 markers and all combinatorial sub-subsets we calculated a multivariate distance called the Mahalanobis distance (MHBD)2 for all observations, indicating how “strange” each individual’s biomarker profile was relative to the baseline population mean. In most models, MHBD correlated positively with age, MHBD increased within individuals over time, and higher MHBD predicted higher risk of subsequent mortality. Predictive power increased as more variables were incorporated into the calculation of MHBD. Biomarkers from multiple systems were implicated. These results support hypotheses of simultaneous dysregulation in multiple systems and confirm the need for longitudinal, multivariate approaches to understanding biomarkers in aging.fr
dc.language.isoengfr
dc.relation.isversionofhttps://doi.org/10.1016/j.mad.2013.01.004fr
dc.rightsAttribution - Pas d’Utilisation Commerciale - Pas de Modification 2.5 Canada*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/ca/*
dc.subjectDysregulationfr
dc.subjectBiomarkerfr
dc.subjectMultivariatefr
dc.subjectAgingfr
dc.subjectPhysiologyfr
dc.titleA novel statistical approach shows evidence for multi-system physiological dysregulation during agingfr
dc.title.alternativeA novel measurement approach and evidence for multi-system physiological dysregulation during agingfr
dc.typeArticlefr
udes.description.typestatusPrépublicationfr
udes.description.typepubScientifiquefr
udes.description.diffusionDiffusé par Savoirs UdeS, le dépôt institutionnel de l'Université de Sherbrookefr
dc.identifier.bibliographicCitationCohen, A., Milot, E., Yong, J., Seplaki, C. L., Fülöp, T., Bandeen-Roche, K., et Fried, L. P. (2013). A novel statistical approach shows evidence for multi-system physiological dysregulation during aging. Manuscrit soumis pour publication. https://doi.org/10.1016/j.mad.2013.01.004fr
udes.autorisation.depottruefr
udes.description.ordreauteursCohen, Alan; Milot, Emmanuel; Yong, Jian; Seplaki, Christopher L.; Fülöp, Tamas; Bandeen-Roche, Karen; Fried, Linda P.fr


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Attribution - Pas d’Utilisation Commerciale - Pas de Modification 2.5 Canada
Except where otherwise noted, this document's license is described as Attribution - Pas d’Utilisation Commerciale - Pas de Modification 2.5 Canada