About

Neurological diseases such as Alzheimer’s disease (AD), Parkinson's disease (PD), Frontotemporal dementia (FTD), and other neurodegenerative diseases are complex traits that require multidisciplinary and translational approaches to understand the biology of the disease, characterize the genes that lead to disease, to identify and validate novel targets and therapeutic approaches. High-throughput technologies are instrumental in generating a detailed molecular landscape of neurological diseases.

We plan to utilize large phenotypic, genomic, transcriptomic, proteomic and other -omics datasets of neurological diseases to identify molecular profiles that provide novel insight into altered pathways associated with disease etiology and progression.

We plan to create a robust resource to support researchers who will contribute to the future of personalized medicine within the field of neurology. Personalized medicine is an emerging approach to understanding, preventing, and treating a disease that considers individual variability in disease biology & genes, environment, and lifestyle for each person. We plan to develop a core of standardized de-identified HIPAA-compliant longitudinal clinical data based on clinical data elements available for each unique individual.

Many neurologic diseases lack adequate means of objective diagnosis or the ability to monitor pathologic changes over time. In addition, most are progressive with limited, if any, available disease-modifying interventions. There is an increasing need to develop validated measures (biomarkers) whose presence indicates the disease under study. These biomarkers may be used to monitor diseases clinically, for observational studies, or to measure the influence of an intervention. 

Our lab is focused on the deep-molecular characterization of a clinically well-defined cohort of patients with neurodegenerative diseases anchored in genomic data. We use a multi-disciplinary approach applying high-throughput technologies to generate a detailed molecular landscape of biospecimens of patients with neurodegenerative diseases. We generate and integrate large phenotypic (clinical and neuropathological) with genomic, transcriptomic, proteomic, and metabolomics datasets to identify novel molecular profiles associated with disease biology and clinical progression. We are also interested in the functional characterization of the autophagy-lysosomal dysfunction in neurodegenerative diseases in cells and mouse models. We combine state-of-the-art approaches in human genetic discoveries (e.g. whole exome sequencing and GWAS data), functional genomic analyses in samples neurodegenerative disease patients (e.g. single-nucleus RNA-sequencing, proteomic data, Bulk-RNA sequencing data) with in vitro (e.g. CRISPR/Cas9-corrected patient-derived cells) and in vivo (e.g. stereotaxic delivery of Adeno-associated virus) experiments. We aim to increase our understanding of the etiology of neurodegeneration to enable molecular subtyping of patients with neurodegenerative diseases, reveal novel intermediate traits involved in neurodegeneration, provide strategies for cohort selection for testing therapeutic targets, and pave the road to identify disease-modifying targets for neurodegenerative diseases.