Literature DB >> 12590174

Assessment of normal variability in peripheral blood gene expression.

Catherine Campbell1, Suzanne D Vernon, Kevin L Karem, Rosane Nisenbaum, Elizabeth R Unger.   

Abstract

Peripheral blood is representative of many systemic processes and is an ideal sample for expression profiling of diseases that have no known or accessible lesion. Peripheral blood is a complex mixture of cell types and some differences in peripheral blood gene expression may reflect the timing of sample collection rather than an underlying disease process. For this reason, it is important to assess study design factors that may cause variability in gene expression not related to what is being analyzed. Variation in the gene expression of circulating peripheral blood mononuclear cells (PBMCs) from three healthy volunteers sampled three times one day each week for one month was examined for 1,176 genes printed on filter arrays. Less than 1% of the genes showed any variation in expression that was related to the time of collection, and none of the changes were noted in more than one individual. These results suggest that observed variation was due to experimental variability.

Mesh:

Year:  2002        PMID: 12590174      PMCID: PMC3851112          DOI: 10.1155/2002/462465

Source DB:  PubMed          Journal:  Dis Markers        ISSN: 0278-0240            Impact factor:   3.434


  7 in total

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Authors:  Martin Steinau; Elizabeth R Unger; Suzanne D Vernon; James F Jones; Mangalathu S Rajeevan
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2.  Limited dynamic range of immune response gene expression observed in healthy blood donors using RT-PCR.

Authors:  Kevin McLoughlin; Ken Turteltaub; Danute Bankaitis-Davis; Richard Gerren; Lisa Siconolfi; Kathleen Storm; John Cheronis; David Trollinger; Dennis Macejak; Victor Tryon; Michael Bevilacqua
Journal:  Mol Med       Date:  2006 Jul-Aug       Impact factor: 6.354

3.  Evidence for microRNA involvement in exercise-associated neutrophil gene expression changes.

Authors:  Shlomit Radom-Aizik; Frank Zaldivar; Stacy Oliver; Pietro Galassetti; Dan M Cooper
Journal:  J Appl Physiol (1985)       Date:  2010-01-28

4.  Blood-based gene expression signatures of infants and toddlers with autism.

Authors:  Karen Pierce; Eric Courchesne; Stephen J Glatt; Ming T Tsuang; Mary Winn; Sharon D Chandler; Melanie Collins; Linda Lopez; Melanie Weinfeld; Cindy Carter; Nicholas Schork
Journal:  J Am Acad Child Adolesc Psychiatry       Date:  2012-08-02       Impact factor: 8.829

5.  Predicting Autism Spectrum Disorder Using Blood-based Gene Expression Signatures and Machine Learning.

Authors:  Dong Hoon Oh; Il Bin Kim; Seok Hyeon Kim; Dong Hyun Ahn
Journal:  Clin Psychopharmacol Neurosci       Date:  2017-02-28       Impact factor: 2.582

6.  A longitudinal study of gene expression in healthy individuals.

Authors:  Chris Karlovich; Guillemette Duchateau-Nguyen; Andrea Johnson; Patricia McLoughlin; Mercidita Navarro; Carole Fleurbaey; Lori Steiner; Michel Tessier; Tracy Nguyen; Monika Wilhelm-Seiler; John P Caulfield
Journal:  BMC Med Genomics       Date:  2009-06-07       Impact factor: 3.063

7.  Integration of gene expression, clinical, and epidemiologic data to characterize Chronic Fatigue Syndrome.

Authors:  Toni Whistler; Elizabeth R Unger; Rosane Nisenbaum; Suzanne D Vernon
Journal:  J Transl Med       Date:  2003-12-01       Impact factor: 5.531

  7 in total

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