Jason L Sanders1, Alice M Arnold2, Robert M Boudreau3, Calvin H Hirsch4, Jorge R Kizer5, Robert C Kaplan6, Anne R Cappola7, Mary Cushman8, Mini E Jacob9,10, Stephen B Kritchevsky11, Anne B Newman3. 1. Department of Medicine, Massachusetts General Hospital, Boston. 2. Department of Biostatistics, University of Washington, Seattle. 3. Department of Epidemiology, University of Pittsburgh, Pennsylvania. 4. Department of Medicine, University of California-Davis, Sacramento. 5. Department of Medicine, Albert Einstein College of Medicine, Bronx, New York. 6. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York. 7. Department of Medicine, University of Pennsylvania, Philadelphia. 8. Departments of Medicine and Pathology, University of Vermont, Burlington. 9. New England GRECC, VA Boston Healthcare System, Boston, Massachusetts. 10. Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts. 11. Department of Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina.
Abstract
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.
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.
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