And finally, a big round of applause for our first place travel grant winner, Dr. Catarina Correia! She researches protein interaction networks in autism spectrum disorders and presented her recent results at the International Meeting for Autism Research in Toronto, ON last month. We’re glad the travel grant helped her attend!
I am currently pursuing a post-doctoral project at Instituto Gulbenkian de Ciência and Instituto Nacional de Saúde Dr. Ricardo Jorge (Portugal) working on the analysis of GWAS carried out by the Autism Genome Project (AGP), a large international consortium for autism genetics. My research aims to develop a network-based approach for GWAS data analysis by combining association results with protein-protein interaction data, and characterize potentially pathogenic CNVs identified in the AGP whole genome CNV analysis.
Key advancements in genotyping, sequencing technologies and analysis methods, and the formation of consortia made large genomic screenings feasible. So far, more than 1000 GWAS studies have been conducted, spanning over 200 phenotypes. However, despite many promising achievements, most of the genome-wide association studies for complex disorders identified common risk variants that only affected disease risks to small extents. These disappointing results highlight the need for alternative approaches that shift the focus from individual markers towards a broader view of affected pathways and biological processes. Additionally, the unprecedented pace at which huge amounts of genome wide data (GWAS, CNV or expression studies) are produced creates the need for tools to integrate these multiple types and sources of data.
237 traits linked to genomic loci by 1449 GWAS studies
(Source: www.genome.gov/GWAStudies)
The main objective of my network-based approach to autism GWAS is to identify sub-networks implicated in autism and to prioritize candidate genes for follow-up analysis. NextBio Genetic Markers is a very simple and quick way to collect a list of known genes previously associated with autism that can be used as a gold standard to validate candidate genes identified in my approach. The integration of multiple types of curated content provides a source of high confidence data. After the validation of my approach and the identification of protein sub-networks possibly associated with autism, I used several NextBio apps to prioritize genes for further study. Individual gene queries helped me glance at a wide variety of information on the gene, such as the most correlated compounds, tissues and diseases. I used these to identify genes expressed in the nervous system and previously implicated in autism or other neuropsychiatric disorders. The Meta-analysis app also proved very useful to prioritize candidates by providing me data on genes with significant combined evidence from multiple studies implicating them in autism.
In my research project I have also been characterizing potentially pathogenic CNVs identified in a whole genome CNV analysis for autism susceptibility. Searches on the genes intersected by rare CNVs have helped us to select relevant CNVs to follow up, giving complete information about relevant correlations with those genes. One of the most interesting CNVs I have been working on is a small in tandem duplication encompassing the ANXA1 gene that is present in 12/3063 patients and absent in 8000 control individuals. In this case, the information retrieved from Body Atlas is highly relevant to the expression studies performed for this gene. Information from several apps, especially Knockdown Atlas have elucidated possible mechanisms by which this gene can be implicated in autism, most of them required analysis of public datasets and are not fully described in the papers, helping us in the design of follow up studies.
SHARE
