Harmonization of four biomarkers across nine nationally representative studies of older persons.

INTRODUCTION: A growing number of international population surveys have included measurement of biomarkers, but differ in the type of specimens collected, sample processing procedures, shipment protocols, and laboratory assay platforms. The purpose of this study is to harmonize biomarker data from nine nationally representative studies of people 50 years of age and over by adjusting for assay platforms and type of specimens for total cholesterol (total-C), high-density lipoprotein cholesterol (HDL-C), glycosylated hemoglobin (HbA1c), and C-reactive protein (CRP). METHODS: Sets of 24 identical serum, plasma, whole blood, and dried blood spot harmonization samples with known analyte levels were generated at a reference laboratory, shipped at -80°C to the respective study laboratories, and subsequently assayed following the study laboratory's protocol. Both original and harmonized study data were used to calculate mean values and at-risk prevalence. RESULTS: The correlation coefficients between the biomarker values of the harmonization samples obtained by the study laboratories and the reference laboratory were 0.99 or above for all analytes and laboratories, indicating the high quality of assays at all laboratories. However, using the harmonized data from each study, there were significant differences in the mean values and country ranking of the prevalence of at-risk levels of these four biomarkers. CONCLUSIONS: While the biomarker data from the different study laboratories were highly correlated, indicating very high correlation of rank order of specimens, absolute values did vary significantly. This can have a major impact on assessment of international differences in estimates of risks for chronic morbidity and mortality.

Dried blood spot collection, sample quality, and fieldwork conditions: Structural validations for conversion into standard values.

OBJECTIVES: SHARE, a pan-European panel study in 27 European countries and Israel, has collected dried blood spot (DBS) samples from approximately 27 000 respondents in 13 countries. We aim to obtain factors to convert analyte values between DBS and venous blood samples (VBS) taking account of adverse fieldwork conditions such as small spot size, high temperature and humidity, short drying time and long shipment times. METHODS: We obtained VBS and DBS from a set of 20 donors in a laboratory setting, and treated the DBS in a systematic and controlled fashion simulating SHARE fieldwork conditions. We used the 3420 outcomes to estimate from DBS analyte values the values that we would have obtained had it been feasible to collect and analyze the donors' venous blood samples. RESULTS: The influence of field conditions and sample quality on DBS analyte values is significant and differs among assays. Varying spot size is the main challenge and affects all markers except HbA1c. Smaller spots lead to overly high measured levels. A missing desiccant is detrimental for all markers except CRP and tHb. The temperature to which the samples are exposed plays a significant role for HDL and CysC, while too brief a drying time affects CRP and CysC. Lab-based adjustment formulae only accounting for the differences between re-liquefied DBS and venous blood do not address these fieldwork conditions. CONCLUSIONS: By simulating adverse fieldwork conditions in the lab, we were able to validate DBS collected under such conditions and established conversion formulae with high prediction accuracy.

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

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.