Age and Sex Distributions of Age-Related Biomarker Values in Healthy Older Adults from the Long Life Family Study

• Autores: Paola Sebastiani, Bharat Thyagarajan, Fangui Sun-, Lawrence S. Honig, Nicole Schupf, Stephanie Cosentino, Mary F. Feitosa, Mary Wojczynski, Anne B. Newman, Monty Montano, Thomas T. Perls
• Localización: Journal of the American Geriatrics Society, ISSN 0002-8614, Vol. 64, Nº. 11, 2, 2016, págs. 189-194
• Idioma: inglés
• Enlaces
  • Texto completo
• Dialnet Métricas: 1 Cita
• Resumen

  • 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.