Dried blood spots: Effects of less than optimal collection, shipping time, heat, and humidity

Publication Abstract

Crimmins, Eileen, Jessica Faul, Jennifer Ailshire, Yuan S. Zhang, Jung Ki Kim, Stephen Frochen, Hyewon Kang, Hyunju Shim, et al. Forthcoming. "Dried blood spots: Effects of less than optimal collection, shipping time, heat, and humidity." American Journal of Human Biology.

Objectives: This study investigates how factors related to collection, storage, transport time, and environmental conditions affect the quality and accuracy of analyses of dried blood spot (DBS) samples. Methods: Data come from the 2016 Health and Retirement Study (HRS) DBS laboratory reports and the HRS merged with the National Climatic Data Center (NCDC) Global Historical Climate Network Daily (NCDC GHCN-Daily) and the NCDC Local Climatological Data, by zip code. We ran regression models to examine the associations between assay values based on DBS for five analytes (total cholesterol, high-density lipoprotein (HDL) cholesterol, glycosylated hemoglobin (HbA1c), C-reactive protein (CRP), and cystatin C) and the characteristics of DBS cards and drops, shipping time, and temperature, and humidity at the time of collection. Results: We found cholesterol measures to be sensitive to many factors including small spots, shipping time, high temperature and humidity. Small spots in DBS cards are related to lower values across all analytes. Longer DBS transit time before freezing is associated with lower values of total and HDL cholesterol and cystatin C. Results were similar whether or not venous blood sample values were included in equations. Conclusions: Small spots, long shipping time, and exposure to high temperature and humidity need to be avoided if possible. Quality of spots and cards and information on shipping time and conditions should be coded with the data to make adjustments in values when necessary. The different results across analytes indicate that results cannot be generalized to all DBS assays.

10.1002/ajhb.23390

Keywords:
Genomics Methodology

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