Wen Wang, United States of America
University of Minnesota Computer Science and EngineeringAuthor Of 1 Presentation
SYSTEMATIC ANALYSIS OF GENETIC INTERACTIONS IN PARKINSON’S DISEASE REVEALS INTERACTIONS WITH KNOWN RISK GENES
Abstract
Aims
Traditional approaches to genome-wide association studies (GWAS) on Parkinson’s disease (PD) are based largely on single-locus tests, despite the genetic complexity of the disease. Genetic interactions refer to combinations of two or more genes whose contribution to a phenotype cannot be fully explained by their independent effects. Detecting genetic interactions systematically with statistical significance remains a major challenge due to the daunting number of variant combinations possible in the human genome.
Methods
We developed a method called BridGE for identifying genetic interactions between pathways from human population genetic data (Wang et al. 2017, Fang, Wang et al. 2019), which leverages the expected structure of genetic interactions revealed by large-scale interaction screens in model organisms. Here, we describe improvements to the BridGE method along with its application to two PD cohorts.
Results
We identified 20 between-pathway interactions (FDR<0.05) and 12 within-pathway interactions (FDR<0.1) associated with PD risk, with a large fraction (10 of 32) of the interactions replicating on an independent cohort (Fig.1). All replicating interactions are connected to the Parkinson’s Disease Gene Set and the Parkin Pathway.
Conclusions
Many of the discovered pathways show clear relevance to PD (Fig.1). The majority of replicated interactions involved the known Parkinson’s disease risk genes, suggesting that many of the established risk variants are modified by variants in multiple, previously unappreciated distinct pathways. We expect further exploration of discovered interactions is likely to be fruitful for understanding the underlying genetic basis of PD.
Presenter of 2 Presentations
LIVE DISCUSSION
- Gloriia Novikova, United States of America
- Julien Chapuis, France
- Marcos R. Costa, France
- Yuk Yee Leung, United States of America
- Konstantin Senkevich, Canada
- Wen Wang, United States of America
- Carolina Soriano-Tarraga, United States of America
- Conceição Bettencourt, United Kingdom
- John Hardy, United Kingdom
SYSTEMATIC ANALYSIS OF GENETIC INTERACTIONS IN PARKINSON’S DISEASE REVEALS INTERACTIONS WITH KNOWN RISK GENES
Abstract
Aims
Traditional approaches to genome-wide association studies (GWAS) on Parkinson’s disease (PD) are based largely on single-locus tests, despite the genetic complexity of the disease. Genetic interactions refer to combinations of two or more genes whose contribution to a phenotype cannot be fully explained by their independent effects. Detecting genetic interactions systematically with statistical significance remains a major challenge due to the daunting number of variant combinations possible in the human genome.
Methods
We developed a method called BridGE for identifying genetic interactions between pathways from human population genetic data (Wang et al. 2017, Fang, Wang et al. 2019), which leverages the expected structure of genetic interactions revealed by large-scale interaction screens in model organisms. Here, we describe improvements to the BridGE method along with its application to two PD cohorts.
Results
We identified 20 between-pathway interactions (FDR<0.05) and 12 within-pathway interactions (FDR<0.1) associated with PD risk, with a large fraction (10 of 32) of the interactions replicating on an independent cohort (Fig.1). All replicating interactions are connected to the Parkinson’s Disease Gene Set and the Parkin Pathway.
Conclusions
Many of the discovered pathways show clear relevance to PD (Fig.1). The majority of replicated interactions involved the known Parkinson’s disease risk genes, suggesting that many of the established risk variants are modified by variants in multiple, previously unappreciated distinct pathways. We expect further exploration of discovered interactions is likely to be fruitful for understanding the underlying genetic basis of PD.