| Reference : Excess of singleton loss-of-function variants in Parkinson's disease contributes to g... |
| Scientific journals : Article | |||
| Life sciences : Genetics & genetic processes | |||
| Systems Biomedicine | |||
| http://hdl.handle.net/10993/42515 | |||
| Excess of singleton loss-of-function variants in Parkinson's disease contributes to genetic risk. | |
| English | |
Bobbili, Dheeraj Reddy  [] | |
| Banda, Peter [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >] | |
| Krüger, Rejko [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit >] | |
| May, Patrick [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >] | |
| 13-Feb-2020 | |
| Journal of Medical Genetics | |
| BMJ Publishing Group | |
| Yes (verified by ORBilu) | |
| International | |
| 0022-2593 | |
| 1468-6244 | |
| London | |
| United Kingdom | |
| [en] Parkinson's disease ; genetic risk ; singelton variants | |
| [en] Background Parkinson’s disease (PD) is a neurodegenerative disorder with complex genetic architecture. Besides rare mutations in high-risk genes related to monogenic familial forms of PD, multiple variants associated with sporadic PD were discovered via association studies.
Methods We studied the whole-exome sequencing data of 340 PD cases and 146 ethnically matched controls from the Parkinson’s Progression Markers Initiative (PPMI) and performed burden analysis for different rare variant classes. Disease prediction models were built based on clinical, non-clinical and genetic features, including both common and rare variants, and two machine learning methods. Results We observed a significant exome-wide burden of singleton loss-of-function variants (corrected p=0.037). Overall, no exome-wide burden of rare amino acid changing variants was detected. Finally, we built a disease prediction model combining singleton loss-of-function variants, a polygenic risk score based on common variants, and family history of PD as features and reached an area under the curve of 0.703 (95% CI 0.698 to 0.708). By incorporating a rare variant feature, our model increased the performance of the state-of-the-art classification model for the PPMI dataset, which reached an area under the curve of 0.639 based on common variants alone. Conclusion The main finding of this study is to highlight the contribution of singleton loss-of-function variants to the complex genetics of PD and that disease risk prediction models combining singleton and common variants can improve models built solely on common variants. | |
| Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) ; Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) ; University of Luxembourg: High Performance Computing - ULHPC | |
| DFG, JPND, FNR | |
| Researchers | |
| http://hdl.handle.net/10993/42515 | |
| 10.1136/jmedgenet-2019-106316 | |
| https://jmg.bmj.com/content/early/2020/02/13/jmedgenet-2019-106316 | |
| H2020 ; 639034 - NCP_WIDE.NET - Transnational Network of cooperation for WIDESPREAD NCPs | |
| FnR ; FNR11264123 > Rejko Krüger > NCER-PD > > 01/01/2015 > 30/11/2020 > 2013 |
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