Saliva sampling in global clinical studies: the impact of low sampling volume on performance of DNA in downstream genotyping experiments.

BACKGROUND: The collection of viable DNA samples is an essential element of any genetics research programme. Biological samples for DNA purification are now routinely collected in many studies with a variety of sampling methods available. Initial observation in this study suggested a reduced genotyping success rate of some saliva derived DNA samples when compared to blood derived DNA samples prompting further investigation. METHODS: Genotyping success rate was investigated to assess the suitability of using saliva samples in future safety and efficacy pharmacogenetics experiments. The Oragene® OG-300 DNA Self-Collection kit was used to collect and extract DNA from saliva from 1468 subjects enrolled in global clinical studies. Statistical analysis evaluated the impact of saliva sample volume of collection on the quality, yield, concentration and performance of saliva DNA in genotyping assays. RESULTS: Across 13 global clinical studies that utilized the Oragene® OG-300 DNA Self-Collection kit there was variability in the volume of saliva sample collection with ~31% of participants providing 0.5 mL of saliva, rather than the recommended 2 mL. While the majority of saliva DNA samples provided high quality genotype data, collection of 0.5 mL volumes of saliva contributed to DNA samples being significantly less likely to pass genotyping quality control standards. Assessment of DNA sample characteristics that may influence genotyping outcomes indicated that saliva sample volume, DNA purity and turbidity were independently associated with sample genotype pass rate, but that saliva collection volume had the greatest effect. CONCLUSION: When employing saliva sampling to obtain DNA, it is important to encourage all study participants to provide sufficient sample to minimize potential loss of data in downstream genotyping experiments.

Improving clinical trial sampling for future research - an international approach: outcomes and next steps from the DIA future use sampling workshop 2011.

Clinical trial samples collected for pharmacogenomic and future research are vital resources for the development of safe and effective drugs, yet collecting adequate, representative sample sets in global trials is challenging. The Drug Information Association (DIA) sponsored a workshop on future use sampling in September 2011, bringing together experts from regulatory agencies, academia and industry to discuss challenges to future use sample collection and identify actions to improve collection. Several common themes and associated action items emerged, including the need for international guidance on the collection of samples for future research; additional discussion related to coding, scope of research, and return of research results; and additional education about pharmacogenomic/future research and the importance of long-term storage of specimens.

Enabling pharmacogenomic clinical trials through sampling.

Discussion and output from the US FDA and the pharmaceutical industry from the Drug Information Association/FDA 5th Workshop in a series on pharmacogenomics entitled: 'Generating and Weighing Evidence in Drug Development and Regulatory Decision Making'. A major topic area at the 5th FDA/Industry Workshop on Pharmacogenomics, February 2-4, 2010 in Bethesda (MD, USA), was enabling pharmacogenomic clinical trials through collection of future use samples. The importance of the collection of samples with permission for future analyses was affirmed by both industry and the FDA. In addition, current barriers for the collection of such samples were detailed and possible solutions for overcoming barriers at sites, as well as globally within countries, were discussed. The importance of international concordance on collection of these samples was emphasized, and potential areas for industry to harmonize sample collection practices. A standalone workshop on issues related to sampling was determined to be a key step for solving issues related to future use sample collection during drug development.

Linkage analysis using single nucleotide polymorphisms.

We performed multipoint linkage analysis using 83 markers from the SNP Consortium (TSC) SNP linkage map in 3 regions covering 190 cM previously scanned with microsatellite markers and found to be linked to type 2 diabetes. Since the average linkage disequilibrium present in the TSC SNP marker clusters is relatively low, we assumed the intracluster genetic distances were a reasonable small nonzero distance (0.03 cM) and performed linkage analysis using GENEHUNTER PLUS and ASM linkage analysis software. We found that for the pedigree structures and missing data patterns in our samples the average information content in all three regions and the LOD score curves in two regions obtained from the TSC SNP markers were similar to results obtained from microsatellite marker maps with 10 cM average spacing. We also give an algorithm which extends the Lander-Green algorithm to permit multipoint linkage analysis of clusters of tightly linked markers with arbitrarily high levels of intracluster linkage disequilibrium.