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- W4386827555 abstract "It has become widely accepted that sample cellular composition is a significant determinant of the gene expression patterns observed in any transcriptomic experiment performed with bulk tissue. Despite this, many investigations currently performed with whole blood do not experimentally account for possible inter-specimen differences in cellularity, and often assume that any observed gene expression differences are a result of true differences in nuclear transcription. In order to determine how confounding of an assumption this may be, in this study, we recruited a large cohort of human donors (n = 138) and used a combination of next generation sequencing and flow cytometry to quantify and compare the underlying contributions of variance in leukocyte counts versus variance in other biological factors to overall variance in whole blood transcript levels. Our results suggest that the combination of donor neutrophil and lymphocyte counts alone are the primary determinants of whole blood transcript levels for up to 75% of the protein-coding genes expressed in peripheral circulation, whereas the other factors such as age, sex, race, ethnicity, and common disease states have comparatively minimal influence. Broadly, this infers that a majority of gene expression differences observed in experiments performed with whole blood are driven by latent differences in leukocyte counts, and that cell count heterogeneity must be accounted for to meaningfully biologically interpret the results." @default.
- W4386827555 created "2023-09-19" @default.
- W4386827555 creator A5058061687 @default.
- W4386827555 creator A5073145325 @default.
- W4386827555 creator A5074089864 @default.
- W4386827555 date "2023-11-01" @default.
- W4386827555 modified "2023-10-17" @default.
- W4386827555 title "Donor white blood cell differential is by a wide margin the single largest determinant of whole blood gene expression patterns" @default.
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- W4386827555 doi "https://doi.org/10.1016/j.ygeno.2023.110708" @default.
- W4386827555 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37730167" @default.
- W4386827555 hasPublicationYear "2023" @default.
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