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Quality-Controlled Measurement Methods for Quantification of Variations in Transcript Abundance in Whole Blood Samples from Healthy Volunteers

¹ Gene Express, Inc., Toledo, OH.
² Pfizer Global Research and Development, Ann Arbor, MI.
³ Innovative Analytics, Inc., Kalamazoo, MI.
⁴ Division of Pulmonary and Critical Care Medicine, Departments of Medicine and Pathology, University of Toledo Health Sciences Campus, Toledo, OH.
⁵ Asuragen, Austin, TX.
⁶ Radiant Research, Lincoln, NE.

^aAddress correspondence to this author at: Division of Pulmonary and Critical Care Medicine, Department of Medicine, Rm. 0012, Ruppert Health Bldg., University of Toledo Health Sciences Campus, 3000 Arlington Ave., Toledo, OH 43614. Fax 419-383-6244; e-mail: James.Willey2{at}utoledo.edu.

Background: Transcript abundance (TA) measurement in whole blood frequently is conducted to identify potential biomarkers for disease risk and to predict or monitor drug response. Potential biomarkers discovered in this way must be validated by quantitative technology. In this study we assessed the use of standardized reverse transcription PCR (StaRT-PCR^TM) to validate potential biomarkers discovered through whole blood TA profiling.

Methods: For each of 15 healthy volunteers, 6 blood samples were obtained, including 3 samples at each of 2 separate visits. Total variation in TA for each gene was partitioned into replicate, sample, visit, study participant, and residual components.

Results: Variation originating from technical processing was <5% of total combined variation and was primarily preanalytical. Interindividual biological sample variation was larger than technical variation. For 12 of 19 tests, the distribution of measured values was gaussian (Shapiro–Wilks test).

Conclusion: For control or diseased population groups with variation rates as low as those observed in this control group, 17 individuals per group would be required to detect 1 SD change with 80% power with a 2-sided = 0.05 statistical test for mean differences.

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