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.

Case-control single-marker and haplotypic association analysis of pedigree data.

Related individuals collected for use in linkage studies may be used in case-control linkage disequilibrium analysis, provided one takes into account correlations between individuals due to identity-by-descent (IBD) sharing. We account for these correlations by calculating a weight for each individual. The weights are used in constructing a composite likelihood, which is maximized iteratively to form likelihood ratio tests for single-marker and haplotypic associations. The method scales well with increasing pedigree size and complexity, and is applicable to both autosomal and X chromosomes. We apply the approach to an analysis of association between type 2 diabetes and single-nucleotide polymorphism markers in the PPAR-gamma gene. Simulated data are used to check validity of the test and examine power. Analysis of related cases has better power than analysis of population-based cases because of the increased frequencies of disease-susceptibility alleles in pedigrees with multiple cases compared to the frequencies of these alleles in population-based cases. Also, utilizing all cases in a pedigree rather than just one per pedigree improves power by increasing the effective sample size. We demonstrate that our method has power at least as great as that of several competing methods, while offering advantages in the ability to handle missing data and perform haplotypic analysis.