Tragante, V;
Asselbergs, FW;
(2018)
Mendelian randomization: A powerful method to determine causality of biomarkers in diseases.
[Editorial comment].
International Journal of Cardiology
, 268
pp. 227-228.
10.1016/j.ijcard.2018.05.049.
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Abstract
Yeoung and Schooling [ref from this issue] report in this issue of International Journal of Cardiology a bi-directional MR to study the correlation between adiponectin levels and coronary artery disease (CAD). Taking advantage of the fact that many genetic markers have been significantly and independently associated with adiponectin levels and CAD, it is possible to group signals of one trait and test against the other with the possibility of giving a more definitive answer about the causality between adiponectin and CAD in both directions (a graphical demonstration of the method is in Fig. 1). Using only significant and independent SNPs as genetic instrument, the researchers found no causal association of adiponectin on CAD (OR 1.02, 95% CI 0.85–1.24), confirming a previous study using a smaller sample size and set of SNPs. In conclusion, MR studies are helping identify and confirm or reject incidental causation inferences found in clinical trials, animal models and other studies. Given the availability of well-powered genetic studies and the identification of thousands of genetic markers associated with a myriad of traits and diseases, one can expect a fast increase in identification of measurable biomarkers, via MR, that contribute to disease, hopefully leading to better therapies to the most appropriate targets. This approach has attracted the interest of the pharmaceutical industry, with the intention of finding suitable candidates for drug repurposing and development.
| Type: | Article |
|---|---|
| Title: | Mendelian randomization: A powerful method to determine causality of biomarkers in diseases |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.ijcard.2018.05.049 |
| Publisher version: | https://doi.org/10.1016/j.ijcard.2018.05.049 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10067470 |
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