title: Optimal Versus Realized Trajectories of Physiological Dysregulation in Aging and Their Relation to Sex-Specific Mortality Risk.
abstract: While longitudinal changes in biomarker levels and their impact on health have been characterized for individual markers, little is known about how overall marker profiles may change during aging and affect mortality risk. We implemented the recently developed measure of physiological dysregulation based on the statistical distance of biomarker profiles in the framework of the stochastic process model of aging, using data on blood pressure, heart rate, cholesterol, glucose, hematocrit, body mass index, and mortality in the Framingham original cohort. This allowed us to evaluate how physiological dysregulation is related to different aging-related characteristics such as decline in stress resistance and adaptive capacity (which typically are not observed in the data and thus can be analyzed only indirectly), and, ultimately, to estimate how such dynamic relationships increase mortality risk with age. We found that physiological dysregulation increases with age; that increased dysregulation is associated with increased mortality, and increasingly so with age; and that, in most but not all cases, there is a decreasing ability to return quickly to baseline physiological state with age. We also revealed substantial sex differences in these processes, with women becoming dysregulated more quickly but with men showing a much greater sensitivity to dysregulation in terms of mortality risk.
authors.affiliation: Biodemography of Aging Research Unit (BARU), Social Science Research Institute, Duke University , Durham, NC , USA.
authors.forename: Konstantin G
authors.initials: KG
authors.lastname: Arbeev
authors.affiliation: Groupe de Recherche PRIMUS, Department of Family Medicine, CHUS-Fleurimont, University of Sherbrooke , Sherbrooke, QC , Canada.
authors.forename: Alan A
authors.initials: AA
authors.lastname: Cohen
authors.affiliation: Biodemography of Aging Research Unit (BARU), Social Science Research Institute, Duke University , Durham, NC , USA.
authors.forename: Liubov S
authors.initials: LS
authors.lastname: Arbeeva
authors.affiliation: Groupe de Recherche PRIMUS, Department of Family Medicine, CHUS-Fleurimont, University of Sherbrooke , Sherbrooke, QC , Canada.
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Milot
authors.affiliation: Biodemography of Aging Research Unit (BARU), Social Science Research Institute, Duke University , Durham, NC , USA.
authors.forename: Eric
authors.initials: E
authors.lastname: Stallard
authors.affiliation: Biodemography of Aging Research Unit (BARU), Social Science Research Institute, Duke University , Durham, NC , USA.
authors.forename: Alexander M
authors.initials: AM
authors.lastname: Kulminski
authors.affiliation: Biodemography of Aging Research Unit (BARU), Social Science Research Institute, Duke University , Durham, NC , USA.
authors.forename: Igor
authors.initials: I
authors.lastname: Akushevich
authors.affiliation: Biodemography of Aging Research Unit (BARU), Social Science Research Institute, Duke University , Durham, NC , USA.
authors.forename: Svetlana V
authors.initials: SV
authors.lastname: Ukraintseva
authors.affiliation: The Danish Aging Research Center, University of Southern Denmark, Odense, Denmark; Department of Clinical Genetics, Odense University Hospital, Odense, Denmark; Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark.
authors.forename: Kaare
authors.initials: K
authors.lastname: Christensen
authors.affiliation: Biodemography of Aging Research Unit (BARU), Social Science Research Institute, Duke University , Durham, NC , USA.
authors.forename: Anatoliy I
authors.initials: AI
authors.lastname: Yashin
keywords: Mahalanobis distance; longitudinal data; mortality; physiological dysregulation; sex differences; stochastic process model
references.citation: Front Genet. 2013 Jan 22;4:3
references.pmid: 23346098
references.citation: Lancet. 2013 Mar 2;381(9868):752-62
references.pmid: 23395245
references.citation: Int J Forecast. 1992 Nov;8(3):433-58
references.pmid: 12157867
references.citation: Rejuvenation Res. 2007 Mar;10(1):75-86
references.pmid: 17378754
references.citation: Math Biosci. 2007 Aug;208(2):538-51
references.pmid: 17300818
references.citation: Exp Gerontol. 2008 Dec;43(12):1052-7
references.pmid: 18835429
references.citation: ScientificWorldJournal. 2001 Aug 08;1:323-36
references.pmid: 12806071
references.citation: Women Health. 1987;12(2):103-45
references.pmid: 3424846
references.citation: J Gerontol A Biol Sci Med Sci. 2009 Oct;64(10):1049-57
references.pmid: 19567825
references.citation: Curr Aging Sci. 2009 Mar;2(1):12-27
references.pmid: 20021396
references.citation: Biogerontology. 2007 Jun;8(3):291-302
references.pmid: 17242962
references.citation: Mech Ageing Dev. 2008 Apr;129(4):191-200
references.pmid: 18242665
references.citation: Biogerontology. 2010 Jun;11(3):257-65
references.pmid: 19644762
references.citation: N Am Actuar J. 2016;20(3):201-232
references.pmid: 27773987
references.citation: Mech Ageing Dev. 2011 Mar;132(3):93-102
references.pmid: 21262255
references.citation: J Am Geriatr Soc. 2005 Jan;53(1):40-7
references.pmid: 15667374
references.citation: J Gerontol. 1994 Jul;49(4):B169-90
references.pmid: 8014388
references.citation: J Clin Epidemiol. 2003 Oct;56(10):968-76
references.pmid: 14568628
references.citation: Mech Ageing Dev. 2014 Nov-Dec;141-142:56-63
references.pmid: 25454986
references.citation: PLoS One. 2015 Mar 11;10(3):e0116489
references.pmid: 25761112
references.citation: Curr Gerontol Geriatr Res. 2010;:
references.pmid: 20953403
references.citation: Horm Behav. 2003 Jan;43(1):2-15
references.pmid: 12614627
references.citation: J Theor Biol. 2009 May 7;258(1):103-11
references.pmid: 19490866
references.citation: Mech Ageing Dev. 2009 Sep;130(9):611-8
references.pmid: 19635493
references.citation: Diabetes. 2009 Jun;58(6):1365-72
references.pmid: 19265026
references.citation: Theor Popul Biol. 1977 Feb;11(1):37-48
references.pmid: 854860
references.citation: Public Health Rep. 1982 Sep-Oct;97(5):417-37
references.pmid: 6750677
references.citation: Scientifica (Cairo). 2012;2012:
references.pmid: 23682334
references.citation: PLoS One. 2015 Apr 13;10(4):e0122541
references.pmid: 25875923
references.citation: Phys Life Rev. 2012 Jun;9(2):177-88; discussion 195-7
references.pmid: 22633776
references.citation: J Appl Physiol (1985). 2000 Aug;89(2):749-59
references.pmid: 10926662
references.citation: Theor Popul Biol. 1989 Apr;35(2):119-41
references.pmid: 2727949
references.citation: Aging Cell. 2015 Dec;14(6):1103-12
references.pmid: 26416593
references.citation: Adv Clin Chem. 2008;46:161-216
references.pmid: 19004190
references.citation: J Am Geriatr Soc. 2005 Dec;53(12):2184-9
references.pmid: 16398907
references.citation: Exp Gerontol. 2014 Sep;57:203-10
references.pmid: 24802990
references.citation: Mech Ageing Dev. 2013 Mar;134(3-4):110-7
references.pmid: 23376244
references.citation: Mech Ageing Dev. 2001 Sep 15;122(13):1447-60
references.pmid: 11470132
references.citation: Postgrad Med. 1996 May;99(5):111-4, 120-2
references.pmid: 8650079
references.citation: Mech Ageing Dev. 2007 Mar;128(3):250-8
references.pmid: 17223183
references.citation: Biogerontology. 2016 Feb;17(1):205-20
references.pmid: 25991473