High-throughput technologies have been instrumental in generating a detailed molecular landscape of neurodegenerative diseases. However, the interpretation of such large amounts of data remains a challenge. My research interests are focused on the interrogation of large phenotypic, genomic, transcriptomic and proteomic datasets of neurodegenerative diseases to identify molecular profiles that provide novel insight into altered pathways associated with disease etiology and progression. I employ bioinformatic and machine learning approaches to aggregate distinct omics datasets to identify the genetic architecture of complex neurodegenerative diseases. In the lab we generate high-throughput proteomic data for a large collection of brains, cerebrospinal fluid and plasma and brain single-cell sequencing data and coupling this data with genome-wide genotyping (GWAS and Whole Genome Sequencing) to generate complex hypothesis that can be later experimentally validated. The ultimate objective of my research is: i) to increase our understanding of the etiology of neurodegeneration; ii) to enable early diagnosis of neurodegeneration; iii) to reveal novel intermediate traits involved in neurodegeneration and other complex traits; iv) to provide strategies for cohort selection for testing therapeutic targets; and v) to pave the road to identify disease-modifying treatments for neurodegenerative diseases.
Oscar Harari Lab
Identification of “omics” (proteomic, transcriptomic and genetic) factors associated with neurodegeneration Read More