Association of Biomarker and Physiologic Indices With Mortality in Older Adults: Cardiovascular Health Study.
Aged
Aging
/ blood
Biomarkers
/ blood
Cardiovascular Diseases
/ blood
Cystatin C
/ blood
Female
Follow-Up Studies
Forecasting
Humans
Insulin-Like Growth Factor I
/ metabolism
Male
Natriuretic Peptide, Brain
/ blood
Peptide Fragments
/ blood
Protein Precursors
Retrospective Studies
Risk Assessment
/ methods
Risk Factors
Survival Rate
/ trends
United States
/ epidemiology
Journal
The journals of gerontology. Series A, Biological sciences and medical sciences
ISSN: 1758-535X
Titre abrégé: J Gerontol A Biol Sci Med Sci
Pays: United States
ID NLM: 9502837
Informations de publication
Date de publication:
01 01 2019
01 01 2019
Historique:
received:
20
11
2017
accepted:
09
04
2018
pubmed:
17
4
2018
medline:
2
11
2019
entrez:
17
4
2018
Statut:
ppublish
Résumé
A goal of gerontology is discovering aging phenotypes that reflect biological aging distinct from disease pathogenesis. Biomarkers that strongly and independently associated with mortality and that statistically attenuated chronologic age could be used to define such a phenotype. We determined the association of a Biomarker Index (BI) with mortality and compared it with a validated Physiologic Index (PI) in older adults. The indices were constructed in the Cardiovascular Health Study, mean (SD) age 74.5 (5.1) years. The BI incorporated circulating levels of new biomarkers, including insulin-like growth factor-1, insulin-like growth factor-binding protein 3, amino-terminal pro-B-type natriuretic peptide, dehydroepiandrosterone sulfate, and interleukin-6, and was built in test (N = 2,197) and validation (N = 1,124) samples. The PI included carotid intima-media thickness, pulmonary capacity, brain white matter grade, cystatin-C, and fasting glucose. Multivariable Cox proportional hazards models predicting death were calculated with 10 years of follow-up. In separate age-adjusted models, the hazard ratio for mortality per point of the BI was 1.30 (95% confidence interval 1.25, 1.34) and the BI attenuated age by 25%. The hazard ratio for the PI was 1.28 (1.24, 1.33; 29% age attenuation). In the same model, the hazard ratio for the BI was 1.23 (1.18, 1.28) and for the PI was 1.22 (1.17, 1.26), and age was attenuated 42.5%. Associations persisted after further adjustment. The BI and PI were significantly and independently associated with mortality. Both attenuated the age effect on mortality substantially. The indices may be feasible phenotypes for developing interventions hoping to alter the trajectory of aging.
Sections du résumé
Background
A goal of gerontology is discovering aging phenotypes that reflect biological aging distinct from disease pathogenesis. Biomarkers that strongly and independently associated with mortality and that statistically attenuated chronologic age could be used to define such a phenotype. We determined the association of a Biomarker Index (BI) with mortality and compared it with a validated Physiologic Index (PI) in older adults.
Methods
The indices were constructed in the Cardiovascular Health Study, mean (SD) age 74.5 (5.1) years. The BI incorporated circulating levels of new biomarkers, including insulin-like growth factor-1, insulin-like growth factor-binding protein 3, amino-terminal pro-B-type natriuretic peptide, dehydroepiandrosterone sulfate, and interleukin-6, and was built in test (N = 2,197) and validation (N = 1,124) samples. The PI included carotid intima-media thickness, pulmonary capacity, brain white matter grade, cystatin-C, and fasting glucose. Multivariable Cox proportional hazards models predicting death were calculated with 10 years of follow-up.
Results
In separate age-adjusted models, the hazard ratio for mortality per point of the BI was 1.30 (95% confidence interval 1.25, 1.34) and the BI attenuated age by 25%. The hazard ratio for the PI was 1.28 (1.24, 1.33; 29% age attenuation). In the same model, the hazard ratio for the BI was 1.23 (1.18, 1.28) and for the PI was 1.22 (1.17, 1.26), and age was attenuated 42.5%. Associations persisted after further adjustment.
Conclusions
The BI and PI were significantly and independently associated with mortality. Both attenuated the age effect on mortality substantially. The indices may be feasible phenotypes for developing interventions hoping to alter the trajectory of aging.
Identifiants
pubmed: 29659743
pii: 4969191
doi: 10.1093/gerona/gly075
pmc: PMC6298182
doi:
Substances chimiques
Biomarkers
0
Cystatin C
0
IGF1 protein, human
0
Peptide Fragments
0
Protein Precursors
0
pro-brain natriuretic peptide (1-76)
0
Natriuretic Peptide, Brain
114471-18-0
Insulin-Like Growth Factor I
67763-96-6
Types de publication
Journal Article
Multicenter Study
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
114-120Subventions
Organisme : NIA NIH HHS
ID : P30 AG024827
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201200036C
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG031890
Pays : United States
Organisme : NHLBI NIH HHS
ID : N01HC55222
Pays : United States
Organisme : NHLBI NIH HHS
ID : N01HC85086
Pays : United States
Organisme : NIDDK NIH HHS
ID : P30 DK020541
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268200800007C
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG023629
Pays : United States
Organisme : NHLBI NIH HHS
ID : N01HC85079
Pays : United States
Organisme : NHLBI NIH HHS
ID : N01HC85083
Pays : United States
Références
Circulation. 2012 Dec 18;126(25):2951-61
pubmed: 23159554
J Am Coll Cardiol. 2002 Sep 4;40(5):976-82
pubmed: 12225726
Ann N Y Acad Sci. 1995 Dec 29;774:143-8
pubmed: 8597454
Age Ageing. 1998 Jul;27(4):449-54
pubmed: 9884001
Ann Epidemiol. 1995 Jul;5(4):270-7
pubmed: 8520708
Horm Metab Res. 2002 Mar;34(3):144-9
pubmed: 11972304
J Clin Endocrinol Metab. 1984 Sep;59(3):551-5
pubmed: 6235241
J Am Geriatr Soc. 2009 Mar;57(3):432-40
pubmed: 19187412
JACC Heart Fail. 2015 Jul;3(7):520-528
pubmed: 26160366
Clin Endocrinol (Oxf). 1994 Sep;41(3):351-7
pubmed: 7955442
Arch Intern Med. 2007 Nov 12;167(20):2249-54
pubmed: 17998499
J Gerontol A Biol Sci Med Sci. 2006 Jun;61(6):575-84
pubmed: 16799139
Exp Gerontol. 2010 Jan;45(1):2-4
pubmed: 19651201
J Clin Endocrinol Metab. 2003 May;88(5):2019-25
pubmed: 12727948
Ann Epidemiol. 1991 Feb;1(3):263-76
pubmed: 1669507
Am J Epidemiol. 2007 Sep 1;166(5):518-26
pubmed: 17602136
J Gerontol A Biol Sci Med Sci. 2018 Jun 14;73(7):953-959
pubmed: 28977343
Ageing Res Rev. 2011 Jul;10(3):319-29
pubmed: 21145432
J Clin Endocrinol Metab. 2004 Jan;89(1):114-20
pubmed: 14715837
J Gerontol A Biol Sci Med Sci. 1998 May;53(3):M176-82
pubmed: 9597048
Ageing Res Rev. 2008 Jul;7(3):151-63
pubmed: 18243818
J Gerontol A Biol Sci Med Sci. 2012 Dec;67(12):1439-46
pubmed: 22546961
J Am Geriatr Soc. 2008 Apr;56(4):652-60
pubmed: 18312313
Cell. 2005 Feb 25;120(4):449-60
pubmed: 15734678
J Am Geriatr Soc. 2010 Mar;58(3):421-6
pubmed: 20163485
Ann N Y Acad Sci. 1995 Dec 29;774:121-7
pubmed: 8597452
Am J Epidemiol. 1997 Jun 1;145(11):970-6
pubmed: 9169905
J Am Geriatr Soc. 2008 Jun;56(6):994-8
pubmed: 18422949
Ann N Y Acad Sci. 1995 Dec 29;774:16-28
pubmed: 8597456
Clin Chem. 1995 Feb;41(2):264-70
pubmed: 7874780
J Gerontol A Biol Sci Med Sci. 2009 Dec;64(12):1268-74
pubmed: 19713299
J Gerontol A Biol Sci Med Sci. 2008 Jun;63(6):603-9
pubmed: 18559635
J Am Geriatr Soc. 2011 Sep;59(9):1581-8
pubmed: 21883106
Eur J Endocrinol. 2004 Jul;151(1):1-14
pubmed: 15248817
J Gerontol A Biol Sci Med Sci. 2014 Apr;69(4):479-85
pubmed: 23913930
Ann Epidemiol. 2006 Jul;16(7):510-5
pubmed: 16443373
J Am Geriatr Soc. 1997 Feb;45(2):133-9
pubmed: 9033509
Am J Med. 2003 Oct 15;115(6):429-35
pubmed: 14563498
J Gerontol A Biol Sci Med Sci. 2012 Apr;67(4):409-16
pubmed: 21934123
J Am Geriatr Soc. 2005 Nov;53(11):1991-5
pubmed: 16274384
J Am Geriatr Soc. 1995 Dec;43(12):1350-5
pubmed: 7490385
PLoS One. 2013 Sep 25;8(9):e75809
pubmed: 24244755