At the intersection of neuroscience, genetics, and genomics, researchers in the Department of Genetics and Genomic Sciences (GGS) are uncovering the molecular mechanisms that drive neurological and psychiatric conditions. Using cutting-edge multi-omic technologies and innovative computational tools, our Neurogenomics team is advancing therapeutic discovery across a wide range of neurodevelopmental, neuropsychiatric, and neurodegenerative disorders.
We develop novel statistical models, biological network methods, and experimental systems for disease modeling. Our efforts are strengthened by close collaboration with leading institutional partners, including the Ronald M. Loeb Center for Alzheimer’s Disease, Friedman Brain Institute, Seaver Autism Center for Research and Treatment, Mindich Child Health and Development Institute, Black Family Stem Cell Institute, and the Center for Disease Neurogenomics.
Our Alzheimer’s disease research builds on genome-wide association studies (GWAS) that have identified germline variants enriched in myeloid-specific enhancers - highlighting the role of microglia, the brain’s resident immune cells, in disease etiology. These variants influence risk through epigenetic regulation of genes involved in microglial phagocytosis. By investigating efferocytosis (the clearance of dead cells), we aim to identify and prioritize therapeutic targets for modifying disease progression.
In parallel, our team investigates the role of somatic mutations - both sequence and copy number changes that arise after fertilization and accumulate with age - in healthy and diseased brain tissue. In autism spectrum disorder, for instance, we have identified somatic mutations that may alter enhancer-like regions and transcription factor binding motifs. This work sheds light on how genetic mosaicism contributes to neurodevelopmental and neurodegenerative disease.
We also lead in the integration of machine learning and artificial intelligence approaches to map disease-relevant biological networks. Our team specializes in combining single-cell and cell-type-specific multi-omic data with functional studies in in vitro and in vivo models. This systems-level approach enables the identification of critical network drivers and accelerates the discovery of therapeutic targets for complex brain disorders.