Search

Background Dried blood spot (DBS) sample collection has been suggested as a less invasive, cheaper and more convenient alternative to venepuncture, which requires trained personnel, making it a potentially viable approach for self-collection of blood on a large scale. We examine whether participants in a longitudinal survey were willing to provide a DBS sample in different interview settings, and how resulting cardiovascular risk biomarkers compared with those from venous blood to calculate clinical risk. Methods Participants of the Understanding Society Innovation Panel, a representative sample of UK households, were randomly assigned to three modes of interview. Most participants (84%) were interviewed in their allocated mode. Participants (n = 2162) were interviewed by a nurse who collected both a blood sample by venepuncture and a DBS card (‘nurse collection’) or participants were seen by an interviewer or took part in the survey online to self-collect a DBS card (‘self-collection’). All DBS cards were returned in the post after the sample had dried. Lipids (total cholesterol, HDL-cholesterol, triglycerides), HbA1c and C-reactive protein were measured in venous and DBS samples and equivalence calculated. The resultant values were used to confirm equivalent prevalence of risk of cardiovascular disease in each type of blood sample by mode of participation. Results Of participants interviewed by a nurse 69% consented to venous blood sample and 74% to a DBS sample, while in the self-collection modes, 35% consented to DBS collection. Demographic characteristics of participants in self-collection mode was not different to those in nurse collection mode. The percentage of participants with clinically raised biomarkers did not significantly differ between type of blood collection (for example, 62% had high cholesterol (> 5 mmol/l) measured by venepuncture and 67% had high cholesterol within the self-collected DBS sample (p = 0.13)). Conclusion While self-collected DBS sampling had a lower response rate to DBS collected by a nurse, participation did not vary by key demographic characteristics. This study demonstrates that DBS collection is a feasible method of sample collection that can provide acceptable measures of clinically relevant biomarkers, enabling the calculation of population levels of cardiovascular disease risk.

Background: While medical studies generally provide health feedback to participants, in observational studies this is not always the case due to logistical and financial difficulties, or concerns about changing observed behaviours. However, evidence suggests that lack of feedback may deter participants from providing biological samples. This paper investigates the effect of offering feedback of blood results on participation in biomeasure sample collection.Methods: Participants aged 16 and over from a longitudinal study – the Understanding Society Innovation Panel - were randomised to three arms – nurse interviewer, interviewer, web survey – and invited to participate in biomeasures data collection. Within each arm they were randomised to receive feedback of their blood results or not. For those interviewed by a nurse both venous and dried blood samples (DBS) were taken in the interview. For the other two arms, they were asked if they would be willing to take a sample, and if they agreed a DBS kit was left or sent to them so the participant could take their own sample and return it. Blood samples were analysed and, if in the feedback arms, participants were sent their total cholesterol and HbA1c results.Response rates for feedback and non-feedback groups were compared: overall; in each arm of the study; by socio-demographic and health characteristics; and by previous study participation. Logistic regression models of providing a blood sample by feedback group and data collection approach controlling for confounders were calculated.Results: Overall 2162 (80.3% of individuals in responding households) took part in the survey; of those 1053 (48.7%) consented to provide a blood sample. Being offered feedback had little effect on overall participation but did increase consent to provide a blood sample (unadjusted OR 1.38; CI: 1.16–1.64). Controlling for participant characteristics, the effect of feedback was highest among web participants (1.55; 1.11–2.17), followed by interview participants (1.35; 0.99 –1.84) and then nurse interview participants (1.30; 0.89–1.92).Conclusions: Offering feedback of blood results increased willingness to give samples, especially for those taking part in a web survey.

Most epigenetic epidemiology to date has utilized microarrays to identify positions in the genome where variation in DNA methylation is associated with environmental exposures or disease. However, these profile less than 3% of DNA methylation sites in the human genome, potentially missing affected loci and preventing the discovery of disrupted biological pathways. Third generation sequencing technologies, including Nanopore sequencing, have the potential to revolutionize the generation of epigenetic data, not only by providing genuine genome-wide coverage but profiling epigenetic modifications direct from native DNA. Here we assess the viability of using Nanopore sequencing for epidemiology by performing a comparison with DNA methylation quantified using the most comprehensive microarray available, the Illumina EPIC array. We implemented a CRISPR-Cas9 targeted sequencing approach in concert with Nanopore sequencing to profile DNA methylation in three genomic regions to attempt to rediscover genomic positions that existing technologies have shown are differentially methylated in tobacco smokers. Using Nanopore sequencing reads, DNA methylation was quantified at 1779 CpGs across three regions, providing a finer resolution of DNA methylation patterns compared to the EPIC array. The correlation of estimated levels of DNA methylation between platforms was high. Furthermore, we identified 12 CpGs where hypomethylation was significantly associated with smoking status, including 10 within the AHRR gene. In summary, Nanopore sequencing is a valid option for identifying genomic loci where large differences in DNAm are associated with a phenotype and has the potential to advance our understanding of the role differential methylation plays in the etiology of complex disease.