| Title: | Oxytocin-pathway polygenic scores for severe mental disorders and metabolic phenotypes in the UK Biobank |
| Journal: | Translational Psychiatry |
| Published: | 25 Nov 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/34824196/ |
| DOI: | https://doi.org/10.1038/s41398-021-01725-9 |
| URL: | https://www.nature.com/articles/s41398-021-01725-9.pdf |
Publication 10740
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Oxytocin is a neuromodulator and hormone that is typically associated with social cognition and behavior. In light of its purported effects on social cognition and behavior, research has investigated its potential as a treatment for psychiatric illnesses characterized by social dysfunction, such as schizophrenia and bipolar disorder. While the results of these trials have been mixed, more recent evidence suggests that the oxytocin system is also linked with cardiometabolic conditions for which individuals with severe mental disorders are at a higher risk for developing. To investigate whether the oxytocin system has a pleiotropic effect on the etiology of severe mental illness and cardiometabolic conditions, we explored oxytocin's role in the shared genetic liability of schizophrenia, bipolar disorder, type-2 diabetes, and several phenotypes linked with cardiovascular disease and type 2 diabetes risk using a polygenic pathway-specific approach. Analysis of a large sample with about 480,000 individuals (UK Biobank) revealed statistically significant associations across the range of phenotypes analyzed. By comparing these effects to those of polygenic scores calculated from 100 random gene sets, we also demonstrated the specificity of many of these significant results. Altogether, our results suggest that the shared effect of oxytocin-system dysfunction could help partially explain the co-occurrence of social and cardiometabolic dysfunction in severe mental illnesses.</p>
8 Authors
- Adriano Winterton
- Francesco Bettella
- Ann-Marie G. de Lange
- Marit Haram
- Nils Eiel Steen
- Lars T. Westlye
- Ole A. Andreassen
- Daniel S. Quintana
1 Application
| Application ID | Title |
|---|---|
| 27412 | Boosting the power of GWAS using novel statistical tools |
Enabling scientific discoveries that improve human health