Neurogenomics

With extensive knowledge and experience at the interface of neuroscience, human genetics and genomics, our Neurogenomics researchers leverage cutting-edge multi-omic technologies to uncover disease mechanisms and lead discoveries of therapeutic interventions. Our research interests cover a range of neurodevelopmental, neuropsychiatric, and neurodegenerative disorders and diseases. We development innovative statistical and biological network methods and pioneer state of the art systems for disease modelling. Our institutional partners include the Ronald M. Loeb Center for Alzheimer’s Disease, the Friedman Brain Institute, the Seaver Autism Center for Research and Treatment, the MINDICH Child Health and Development Institute, the Black Family Stem Cell Institute, and the Center for Disease Neurogenomics.

  • Genome-wide association studies (GWAS) identified germline mutations associated with Alzheimer's Disease (AD), many of which are enriched in myeloid-specific enhancers, implicating microglia, the resident macrophages of the central nervous system, in AD etiology. This set of variants influence the AD risk through epigenetic regulation of genes functioning in microglial phagocytosis. Our work prioritizes novel therapeutic targets of AD by studying efferocytosis in the brain's immune system in modulating the disease risk.
  • Somatic mutations, DNA sequence and copy number alterations in proliferative and postmitotic cells throughout the human life span since fertilization, are prevalent in healthy and diseased tissues. Somatic mutations accumulate with age, and in autistic brains, are associated with creating putative transcription factor binding motifs in enhancer-like regions. Our researchers use a multidisciplinary approach to discover the implications of somatic mutations in neurodegeneration.
  • Through a blend of deep expertise in developing innovative machine-learning and artificial intelligence algorithms, methodologies, and strategies, we specialized in the integration of critical disease-related biological networks and network drivers from single cell and cell-type-specific multi-omics data with in vitro and in vivo experimental models for therapeutic discoveries.