Nature Communications (Sep 2021)
Differentially expressed genes reflect disease-induced rather than disease-causing changes in the transcriptome
- Eleonora Porcu,
- Marie C. Sadler,
- Kaido Lepik,
- Chiara Auwerx,
- Andrew R. Wood,
- Antoine Weihs,
- Maroun S. Bou Sleiman,
- Diogo M. Ribeiro,
- Stefania Bandinelli,
- Toshiko Tanaka,
- Matthias Nauck,
- Uwe Völker,
- Olivier Delaneau,
- Andres Metspalu,
- Alexander Teumer,
- Timothy Frayling,
- Federico A. Santoni,
- Alexandre Reymond,
- Zoltán Kutalik
Affiliations
- Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne
- Marie C. Sadler
- Swiss Institute of Bioinformatics
- Kaido Lepik
- Institute of Computer Science, University of Tartu
- Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne
- Andrew R. Wood
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter
- Antoine Weihs
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald
- Maroun S. Bou Sleiman
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne
- Diogo M. Ribeiro
- Swiss Institute of Bioinformatics
- Stefania Bandinelli
- Local Health Unit Toscana Centro
- Toshiko Tanaka
- Clinical Res Branch, National Institute of Aging
- Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald
- Uwe Völker
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald
- Olivier Delaneau
- Swiss Institute of Bioinformatics
- Andres Metspalu
- Estonian Biobank, University of Tartu
- Alexander Teumer
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald
- Timothy Frayling
- University of Exeter Medical School, University of Exeter
- Federico A. Santoni
- Endocrine, Diabetes, and Metabolism Service, Lausanne University Hospital
- Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne
- Zoltán Kutalik
- Swiss Institute of Bioinformatics
- DOI
- https://doi.org/10.1038/s41467-021-25805-y
- Journal volume & issue
-
Vol. 12,
no. 1
pp. 1 – 9
Abstract
Identification of gene expression changes between healthy and diseased individuals can reveal mechanistic insights and biomarkers. Here, the authors propose a bi-directional transcriptome-wide Mendelian Randomization approach to assess causal effects between gene expression and complex traits.
