Circulating apoE4 protein levels from dried blood spots predict cognitive function in a large population-based survey setting.

INTRODUCTION: The apolipoprotein E (APOE) ε4 allele carries risk for cognitive impairment, but whether the level of circulating apoE4 protein in carriers affects cognition is unclear, as is how health and lifestyle impact circulating apoE4 levels. METHODS: We assayed apoE4 protein levels in dried blood spots of 12,532 adults aged 50+. Regression analyses tested the likelihood of cognitive impairment between groups and within those with detected apoE4 protein. Predictors of circulating apoE4 were assessed. RESULTS: We detected protein binding that indicates the presence of an APOE ε4 allele in 28.4% of this group. This group was more likely to have cognitive impairment, and this risk increases with age. However, higher apoE4 levels were associated with less likelihood of cognitive impairment within this group. Antihypertensive medication predicted apoE4 protein levels. DISCUSSION: The apoE4 isoform is associated with a deficient protein and worse cognition. This association is modulated by the level of circulating apoE4 protein in ε4 carriers. HIGHLIGHTS: An assay to quantify apoE4 levels from dried blood spot samples was applied. The apoE4 protein was detected as specific binding at ≥30,000 pg/mL in 28.4% of samples. Having the apoE4 protein was associated with worse cognitive performance. Higher apoE4 protein levels in those who have it were associated with better cognition. Cardiovascular factors influenced levels of apoE4 protein.

Effects of spot size on biomarker levels of field-collected dried blood spots: A new algorithm for exact dried blood spot size measurement.

OBJECTIVES: The quality of blood values analyzed from survey-collected dried blood spot (DBS) samples is affected by fieldwork conditions, particularly spot size. We offer an image-based algorithm that accurately measures the area of field-collected DBS and we investigate the impact of spot size on the analyzed blood marker values. METHODS: SHARE, a pan-European study, collected 24 000 DBS samples in 12 countries in its sixth wave. Our new algorithm uses photographs of the DBS samples to calculate the number of pixels of the blood-covered area to measure the spot sizes accurately. We ran regression models to examine the association of spot size and seven DBS analytes. We then compared the application of our new spot-size measures to common spot-size estimation. RESULTS: Using automated spot-size measurement, we found that spot size has a significant effect on all markers. Smaller spots are associated with lower measured levels, except for HbA1c, for which we observe a negative effect. Our precisely measured spot sizes explain substantially more variance of DBS analytes compared to commonly used spot-size estimation. CONCLUSION: The new algorithm accurately measures the size of field-collected DBS in an automated way. This methodology can be applied to surveys even with very large numbers of observations. The measured spot sizes improve the accuracy of conversion formulae that translate blood marker values derived from DBS into venous blood values. The significance of the spot-size effects on biomarkers in DBS should also incentivize the improvement of fieldwork training and monitoring.

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.

Assessment of circulating apoE4 levels from dried blood spot samples in a large survey setting.

INTRODUCTION: The apolipoprotein E (APOE) ε4 allele is associated with high risk for Alzheimer's disease. It is unclear whether individual levels of the circulating apoE4 protein in ε4 carriers confer additional risk. Measuring apoE4 protein levels from dried blood spots (DBS) has the potential to provide information on genetic status as well as circulating levels and to include these measures in large survey settings. METHODS: We developed a multiplex immunoassay to detect apoE4 protein levels in DBS from 15,974 participants, aged 50+ from Wave 6 of the Survey of Health, Ageing and Retirement in Europe (SHARE). RESULTS: The apoE4 protein signal was presented in two separable distributions. One distribution corresponded to carriers of at least one copy of the ε4 allele. Fieldwork cofounders affected protein levels but did not explain individual differences. DISCUSSION: Future research should investigate how genotype and apoE4 level interact with lifestyle and other variables to impact cognitive aging.

Bodyweight change and cognitive performance in the older population.

Preservation of cognitive function is one of the major concerns in contemporary ageing societies. At the same time, overweight and obesity, which have been identified as risk factors for poor health development, have been increasing in many countries all over the world. This study examines the relationship between bodyweight change and cognitive decline in old age and it aims to determine whether and how changes in body mass index (BMI) affect the development of cognitive functioning in old age. Using longitudinal data from the Survey of Health, Ageing and Retirement in Europe (SHARE), covering four waves between 2006 and 2016 with 58,389 participants from 15 countries aged 50+, we estimated asymmetric fixed effects models by gender, adding possible confounding variables such as age, grip strength, health conditions, and physical activity. Additionally, we investigated possible heterogeneity in the BMI-cognition relation. We found a positive association between BMI change and change in cognitive performance, which was dominantly driven by BMI decrease. Weight loss was typically negatively related to cognition, particularly at low levels of BMI and mainly due to health conditions affecting both bodyweight and cognitive performance. Weight gain was, on average, not significantly related to cognitive performance; only respondents with preceding weight loss profited from small increases in BMI. Our analyses provide no support for an "obesity paradox" in cognition, according to which higher weight preserves cognition in old age. The association between weight change and cognitive performance in older age is based on weight changes being related to illness and recovery.