Written by Aaron Khemchandani, Science Writer.
For the first time, a team of Texas scientists have used a new functional genomics approach to identify and validate a set of genes that could significantly affect the progression of Parkinson’s Disease (PD). The research, published last week in the journal Human Molecular Genetics, may help us uncover several long-standing mysteries surrounding the disease and, ultimately, radically change the ways in which we study neurodegenerative conditions.
The mysteries of our genome
Many neurodegenerative disorders, including PD, are caused by environmental factors as well as combinations of polygenic mutations – mutations across multiple genes. Identifying the genetic components involved in PD progression is crucial to understanding the intricacies of this disease, but we remain a long way off uncovering the entire spectrum of genes that contribute to the condition. However, this research could change that.
Scientists at the Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital and the Baylor College of Medicine developed a multidisciplinary method of gene identification that combines computational and in vivo biological strategies. Through applying this methodology within an animal model, the team were able to screen and functionally validate many PD-associated genes within a short timeframe, newly identifying 50 genes that could modulate disease pathology.
Better, faster, stronger
For the better part of two decades, genome-wide association studies (GWAS) have been the primary method used to analyse large numbers of genomes and pick out the common genetic variabilities correlated with increased risk for complex neurodegenerative disorders. However, while this method is effective in identifying specific associations, further studies in cultured cells or animal models are necessary to determine the functional role of those variants in disease pathogenesis. In addition, both processes are relatively inefficient and cumbersome, particularly for a polygenic disease like PD.
In recent years, a new technique known as transcriptome-wide association studies (TWAS) has been introduced, which – in contrast to GWAS – identifies associations between gene expression levels and disease pathogenesis, rather than merely revealing the specific variations involved. By combining GWAS and TWAS in a multi-step analysis, the researchers were able to identify 160 candidate genes that appeared to correspond to PD pathology.
The team then conducted complementary computational analyses to whittle this number down to 81, before finally applying the data to computational algorithms and carrying out further experiments within fruit fly animal models. They identified the functional involvement of 50 PD risk genes as well as 14 potentially protective genes, opening up more avenues for the study of new therapeutics.
The combined utilisation of GWAS, TWAS and computational algorithms within a single screening is far more efficient in comparison to the sole implementation of GWAS or TWAS. Therefore, this new method of integrated genetic analysis may make a pronounced contribution to how scientists conduct future research.
A source of hope for millions
Over 10 million people currently live with PD worldwide, and the prevalence of this condition has doubled over the past 25 years. Disability and mortality due to the disease is also on the rise, and that is why research like this is vital. These emerging techniques may significantly deepen our genetic understanding of PD, providing the key we need to unlock a wide range of effective therapies – not just for this condition, but for a host of genetic disorders.
