Genomics is a field of biology that focuses on the structure, function, evolution, mapping and editing of genomes — an organism’s complete set of DNA, including all of its genes. As research into ALS continues to advance, genomics is playing an essential role in the discovery of effective therapeutic treatments.
Hemali Phatnani, Ph.D., director of the Center for Genomics of Neurodegenerative Disease (CGND) at the New York Genome Center (NYGC), is on the forefront of those efforts. Her work involves closely examining the mutated genes that contribute to ALS — a particularly challenging aspect of research because of variations involving both the actual genes and outside influences that contribute to mutations.
Despite those complexities, what Phatnani says researchers really need for a breakthrough is more samples, which can only happen with added collaboration. And that’s where Target ALS can help. In the latest installment of our Under the Microscope series, we spoke with Phatnani about genomics, the importance of insights provided by genomics in ALS research, and how the partnerships facilitated by Target ALS are impacting the industry.
The Center for Genomics of Neurodegenerative Disease (CGND) is dedicated to the study of neurodegenerative diseases such as ALS, dementia, Alzheimer’s disease, frontotemporal dementia, Parkinson’s disease, and Huntington’s disease. CGND’s vision is to establish a center for applying state of the art genetics, genomics and bioinformatics to the study of neurodegenerative disease mechanisms.
CGND’s goals are to use whole genome sequencing to identify mutations that cause neurodegenerative disease. To gain insights into the relationship between mutations, gene expression and disease mechanisms, whole genome sequencing data will ultimately be integrated with other genomic-scale data such as RNA-SEQ, RNA-protein interactions, and DNA methylation patterns.
CGND is helping to create a uniform system of collecting clinical annotation to better enable the integration of genomic data with clinical profiles. This information will be freely available to the research community in a data warehouse for whole genome sequencing and RNA-SEQ analyses.