Predicting tissue-specific gene expression from whole blood transcriptome

Mahashweta Basu, Kun Wang, Eytan Ruppin*, Sridhar Hannenhalli*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

56 Scopus citations

Abstract

Complex diseases are mediated via transcriptional dysregulation in multiple tissues. Thus, knowing an individual’s tissue-specific gene expression can provide critical information about her health. Unfortunately, for most tissues, the transcriptome cannot be obtained without invasive procedures. Could we, however, infer an individual’s tissue-specific expression from her whole blood transcriptome? Here, we rigorously address this question. We find that an individual’s whole blood transcriptome can significantly predict tissue-specific expression levels for ~60% of the genes on average across 32 tissues, with up to 81% of the genes in skeletal muscle. The tissue-specific expression inferred from the blood transcriptome is almost as good as the actual measured tissue expression in predicting disease state for six different complex disorders, including hypertension and type 2 diabetes, substantially surpassing the blood transcriptome. The code for tissue-specific gene expression prediction, TEEBoT, is provided, enabling others to study its potential translational value in other indications.

Original languageEnglish
Article numbereabd6991
JournalScience advances
Volume7
Issue number14
DOIs
StatePublished - Mar 2021
Externally publishedYes

Funding

FundersFunder number
National Cancer InstituteZIABC011802

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