Clinical Chemistry
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Clinical Chemistry 55: 774-785, 2009. First published February 20, 2009; 10.1373/clinchem.2008.119107
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(Clinical Chemistry. 2009;55:774-785.)
© 2009 American Association for Clinical Chemistry, Inc.

Molecular Diagnostics and Genetics

Interindividual and Interethnic Variation in Genomewide Gene Expression: Insights into the Biological Variation of Gene Expression and Clinical Implications

Harris P.Y. Fan1,1, Chen Di Liao1,1, Brenda Yan Fu1,2, Linda C.W. Lam2 and Nelson L.S. Tang1,3,a

Departments of1 Chemical Pathology and 2 Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China; 3 Laboratory for Genetics of Disease Susceptibility, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.

aAddress correspondence to this author at: Department of Chemical Pathology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China. Fax +852 26365090; e-mail nelsontang{at}cuhk.edu.hk.

Background: Analysis of gene expression in peripheral blood samples is increasingly being applied in biomarker studies of disease diagnosis and prognosis. Although knowledge of interindividual and interethnic variation in gene expression is required to set ethnicity-specific reference intervals and to select reference genes and preferred markers from a list of candidate genes, few studies have attempted to characterize such biological variation on a genomewide scale.

Methods: The genomewide expression profiles of 11 355 transcripts expressed among 210 multiethnic individuals of the HapMap project were obtained and analyzed; 4 replicates were included for each sample. The total biological CV in gene expression (CVb) was partitioned into interindividual (CVg), inter-ethnic group (CVe), and residual components by random-effects mixed models.

Results: CVg was the major component of CVb, and the differences among transcripts were large (up to 38%). Distinct groups of genes were characterized by CV values and expression levels. Of the genes with lowest biological variation (CVb < 1.5%), 35 genes were highly expressed, whereas 32 had intermediate or low expression. Although CVg was almost always greater than CVe, we identified 10 genes in which ethnic variation predominated (range, 8%–18%). On the other hand, 17 annotated genes were highly variable with CVg values ranging between 15% and 38%.

Conclusions: Genomewide analysis of gene expression variation demonstrated biological differences among transcripts. Transcripts with the least biological variation are better candidates for reference genes, whereas those with low interindividual variation may be good disease markers. The presence of interethnic variation suggests that ethnicity-specific reference intervals may be necessary.






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