Nat Commun.: auth.: group Reymond

Nat Commun. 2021 Sep 24;12(1):5647. doi: 10.1038/s41467-021-25805-y.

Differentially expressed genes reflect disease-induced rather than disease-causing changes in the transcriptome

Eleonora Porcu 1 2 3Marie C Sadler 4 5Kaido Lepik 6 7Chiara Auwerx 8 4 5Andrew R Wood 9Antoine Weihs 10Maroun S Bou Sleiman 11Diogo M Ribeiro 4 12Stefania Bandinelli 13Toshiko Tanaka 14Matthias Nauck 15 16Uwe Völker 16 17Olivier Delaneau 4 12Andres Metspalu 18Alexander Teumer 16 19Timothy Frayling 20Federico A Santoni 21Alexandre Reymond 8Zoltán Kutalik 4 5 9 12


Comparing transcript levels between healthy and diseased individuals allows the identification of differentially expressed genes, which may be causes, consequences or mere correlates of the disease under scrutiny. We propose a method to decompose the observational correlation between gene expression and phenotypes driven by confounders, forward- and reverse causal effects. The bi-directional causal effects between gene expression and complex traits are obtained by Mendelian Randomization integrating summary-level data from GWAS and whole-blood eQTLs. Applying this approach to complex traits reveals that forward effects have negligible contribution. For example, BMI- and triglycerides-gene expression correlation coefficients robustly correlate with trait-to-expression causal effects (rBMI = 0.11, PBMI = 2.0 × 10-51 and rTG = 0.13, PTG = 1.1 × 10-68), but not detectably with expression-to-trait effects. Our results demonstrate that studies comparing the transcriptome of diseased and healthy subjects are more prone to reveal disease-induced gene expression changes rather than disease causing ones.