Paola Sebastiani1, Bharat Thyagarajan2, Fangui Sun1, Lawrence S Honig3, Nicole Schupf4, Stephanie Cosentino3, Mary F Feitosa5, Mary Wojczynski5, Anne B Newman6, Monty Montano7, Thomas T Perls8. 1. Department of Biostatistics, School of Public Health, Boston University, Boston, Massachusetts. 2. Department of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, Minnesota. 3. Department of Neurology, College of Science and Physicians, Sergievsky Center, Columbia University, New York, New York. 4. Department of Epidemiology, Mailman School of Public Health, Sergievsky Center, Columbia University, New York, New York. 5. Department of Genetics, School of Medicine, Washington University, St. Louis, Missouri. 6. Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania. 7. Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts. 8. Department of Medicine, School of Medicine and Geriatric Section, Boston University, Boston Medical Center, Boston, Massachusetts.
Abstract
OBJECTIVES: To determine reference values for laboratory tests in individuals aged 85 and older. DESIGN: Cross-sectional cohort study. SETTING: International. PARTICIPANTS: Long Life Family Study (LLFS) participants (N~5,000, age: range 25-110, median 67, 45% male). MEASUREMENTS: Serum biomarkers were selected based on association with aging-related diseases and included complete blood count, lipids (triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol), 25-hydroxyvitamin D2 and D3, vitamin D epi-isomer, diabetes mellitus-related biomarkers (adiponectin, insulin, insulin-like growth factor 1, glucose, glycosylated hemoglobin, soluble receptor for advanced glycation endproduct), kidney disease-related biomarkers (albumin, creatinine, cystatin), endocrine biomarkers (dehydroepiandrosterone, sex-hormone binding globulin, testosterone), markers of inflammation (interleukin 6, high-sensitivity C-reactive protein, N-terminal pro b-type natriuretic peptide), ferritin, and transferrin. RESULTS: Of 38 measured biomarkers, 34 were significantly correlated with age. Summary statistics were generated for all biomarkers according to sex and 5-year age increments from 50 and up after excluding participants with diseases and treatments that were associated with biomarkers. A biomarker data set was also generated that will be useful for other investigators seeking to compare biomarker levels between studies. CONCLUSION: Levels of several biomarkers change with older age in healthy individuals. The descriptive statistics identified herein will be useful in future studies and, if replicated in additional studies, might also become useful in clinical practice. The availability of the reference data set will facilitate appropriate calibration of biomarkers measured in different laboratories.
OBJECTIVES: To determine reference values for laboratory tests in individuals aged 85 and older. DESIGN: Cross-sectional cohort study. SETTING: International. PARTICIPANTS: Long Life Family Study (LLFS) participants (N~5,000, age: range 25-110, median 67, 45% male). MEASUREMENTS: Serum biomarkers were selected based on association with aging-related diseases and included complete blood count, lipids (triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol), 25-hydroxyvitamin D2 and D3, vitamin D epi-isomer, diabetes mellitus-related biomarkers (adiponectin, insulin, insulin-like growth factor 1, glucose, glycosylated hemoglobin, soluble receptor for advanced glycation endproduct), kidney disease-related biomarkers (albumin, creatinine, cystatin), endocrine biomarkers (dehydroepiandrosterone, sex-hormone binding globulin, testosterone), markers of inflammation (interleukin 6, high-sensitivity C-reactive protein, N-terminal pro b-type natriuretic peptide), ferritin, and transferrin. RESULTS: Of 38 measured biomarkers, 34 were significantly correlated with age. Summary statistics were generated for all biomarkers according to sex and 5-year age increments from 50 and up after excluding participants with diseases and treatments that were associated with biomarkers. A biomarker data set was also generated that will be useful for other investigators seeking to compare biomarker levels between studies. CONCLUSION: Levels of several biomarkers change with older age in healthy individuals. The descriptive statistics identified herein will be useful in future studies and, if replicated in additional studies, might also become useful in clinical practice. The availability of the reference data set will facilitate appropriate calibration of biomarkers measured in different laboratories.
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