Abstract: With ageing populations worldwide, neurodegenerative diseases are placing an ever-increasing burden on long-term well-being, healthcare costs and family life. Despite decades of research and enormous investment, no disease-modifying treatment is available for the most common of these diseases: Alzheimer’s (AD). The majority of these, to-date unsuccessful, efforts have focused on one potential cause of AD: amyloid-β aggregation. Combining population-scale data collection, human genetics and machine learning provides a way forward to uncover and characterize new causal cellular processes involved in AD. This would provide an array of potential therapeutic targets, increasing the chance that one will be more easily modulated than the amyloid-β pathway. AD-specific multi-omics datasets of unprecedented scale are being actively collected: whole genome sequencing (WGS), gene expression (RNA-seq) and epigenomics (ATAC-seq, histone ChIP-seq) from >1000 post-mortem AD brains, single-cell transcriptomes and similar modalities in peripheral and brain-resident innate immune cells. Here, I will describe our efforts to effectively integrating these diverse data to better understand molecular underpinnings of neurodegeneration. We leverage state-of-the-art machine learning (ML), combined with human genetic analyses, to address this challenge. We built the most comprehensive catalog to date of genetic effects on the human microglia transcriptome (n=555 donors) and propose molecular mechanisms of action of candidate functional genetic variants in AD. We also generate a large-scale isoform centric map of human microglia transcriptome to identify disease-associated isoforms. Finally, we will discuss the experimental, computational, and conceptual advances that will be necessary to fully elucidate the effects of functional variants and genes on cellular dysregulation and disease risk.
Bio: Towfique Raj, Ph.D. is a core faculty member in the Ronald M. Loeb Center for Alzheimer’s Disease and an associate professor in the Department of Neuroscience and the Department of Genetics and Genomics at Icahn School of Medicine at Mount Sinai, New York. Dr. Raj received Ph.D. in Genetics from Cambridge University and completed a postdoctoral fellowship at the Broad Institute. Before joining the faculty at Mount Sinai, Dr Raj was an Instructor of Neurology at Harvard Medical School and was subsequently a Visiting Scholar at Stanford University. Dr. Raj’s research is primarily focused on deciphering the genetic basis of complex human traits, particularly in the context of neurodegenerative diseases. He employs high-throughput functional genomics and genetic association studies to identify genomic regions affecting cellular traits. Although his work centers on computational methods, involving extensive big data analysis, machine learning, and statistical development, he collaborates closely with experimental biologists. Dr. Raj has also contributed to understanding the importance of RNA processing, which plays a key role in neurodegenerative diseases. He has taken the lead in large-scale omic profiling of peripheral blood and CNS cells, such as microglia, and in the integration of high-dimensional multi-omics data in Alzheimer’s Disease, Parkinson’s Disease, and FTD/ALS. He also holds leadership positions in various consortia, including the Alzheimer’s Disease Sequencing Project (ADSP), where he serves as the Co-Chair of the AI/ML Consortium, member of the Accelerating Medicines Partnership Program Parkinson’s disease (AMP PD), and leads the Genomics Core of the Center Without Walls FTLD-TDP.