Seasonal variation of peripheral blood leukocyte telomere length in Costa Rica : a population-based observational study
No hay miniatura disponible
Fecha
2014
Director
Título de la revista
ISSN de la revista
Título del volumen
Publicador
American Journal of Human Biology; Volumen 26, Número 3
Páginas
Resumen
Objectives: Peripheral blood leukocyte telomere length (LTL) is increasingly being used as a biomarker of aging, but its natural variation in human populations is not well understood. Several other biomarkers show seasonal variation, as do several determinants of LTL. We examined whether there was monthly variation in LTL in Costa Rica, a country with strong seasonal differences in precipitation and infection. Methods: We examined a longitudinal population-based cohort of 581 Costa Rican adults age 60 and above, from which blood samples were drawn between October 2006 and July 2008. LTL was assayed from these samples using the quantitative PCR method. Multivariate regression models were used to examine correlations between month of blood draw and LTL. Results: Telomere length from peripheral blood leukocytes varied by as much as 200 base pairs depending on month of blood draw, and this difference is not likely to be due to random variation. A moderate proportion of this association is statistically accounted for by month and region specific average rainfall. We found shorter telomere length associated with greater rainfall. Conclusions: There are two possible explanations of our findings. First, there could be relatively rapid month-to-month changes in LTL. This conclusion would have implications for understanding the natural population dynamics of telomere length. Second, there could be seasonal differences in constituent cell populations. This conclusion would suggest that future studies of LTL use methods to account for the potential impact of constituent cell type.
Descripción
Palabras clave
POBLACION, ESTUDIOS DE CASOS, ENVEJECIMIENTO, BIOMARCADORES, VARIACION GENETICA, LEUCOCITOS, ESTUDIOS LONGITUDINALES, ANALISIS MULTIVARIABLE, ANALISIS DE REGRESION