Abstract
Knowledge about the extent of total variation experienced between samples from different individuals is of great importance for the design of not only proteomics but every clinical study. This variation defines the smallest statistically significant detectable signal difference when comparing two groups of individuals. We isolated platelets from 20 healthy human volunteers aged 56-100 years because this age group is most commonly encountered in the clinics. We determined the technical and total variation experienced in a proteome analysis using two-dimensional DIGE with IPGs in the pI ranges 4-7 and 6-9. Only spots that were reproducibly detectable in at least 90% of all gels (n = 908) were included in the study. All spots had a similar technical variation with a median coefficient of variation (cv) of about 7%. In contrast, spots showed a more diverse total variation between individuals with a surprisingly low median cv of only 18%. Because most known biomarkers show an effect size in a 1-2-fold range of their cv, any future clinical proteomics study with platelets will require an analytical method that is able to detect such small quantitative differences. In addition, we calculated the minimal number of samples (sample size) needed to detect given protein expression differences with statistical significance.
Highlights
Knowledge about the extent of total variation experienced between samples from different individuals is of great importance for the design of proteomics but every clinical study
Total Variation between Individuals—To evaluate the extent of variation between individuals, platelet protein extracts of 20 healthy volunteers were covalently labeled by fluorescent tags with either Cy3 or Cy5
We assessed the biological variation of about 900 proteins (484 acidic and 424 alkaline) of human platelets from elderly subjects
Summary
Knowledge about the extent of total variation experienced between samples from different individuals is of great importance for the design of proteomics but every clinical study. This variation defines the smallest statistically significant detectable signal difference when comparing two groups of individuals. Because most known biomarkers show an effect size in a 1–2-fold range of their cv, any future clinical proteomics study with platelets will require an analytical method that is able to detect such small quantitative differences.
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