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

Author:

Peters Elizabeth Herness1,Rojas-Caro Sandra2,Brigell Mitchell G2,Zahorchak Robert J1,des Etages Shelley Ann2,Ruppel Patricia L3,Knight Charles R4,Austermiller Bradley4,Graham Myrna C1,Wowk Steve5,Banks Sean5,Madabusi Lakshmi V5,Turk Patrick6,Wilder Donna6,Kempfer Carole6,Osborn Terry W1,Willey James C4

Affiliation:

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

Abstract

Abstract 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™) 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 α = 0.05 statistical test for mean differences.

Funder

National Institutes of Health

National Cancer Institute

Publisher

Oxford University Press (OUP)

Subject

Biochemistry, medical,Clinical Biochemistry

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