Manuel Rivas, PhD
Assistant Professor
DBDS, Stanford University

ABSTRACT:

Genome sequencing studies applied to large case-control series, populations or biobanks with extensive phenotyping raise novel analytical challenges and present new opportunities to interrogate the human genome to better understand disease. In this talk I will focus on a special class of genetic variants that are increasingly found in sequencing studies, protein truncating variants (PTVs), which are typically expected to have large effect on gene function, are enriched for disease-causing mutations, and in the past few years some have been found to be protective against disease. PTVs, while not the only ones relevant to disease, offer unique insights into likely benefits and risks from therapeutic inhibition of the gene. I will consider recent sequencing efforts in autoimmune diseases and cardiometabolic traits to identify protective PTVs, and discuss the importance of improving our understanding of their functional consequences. I will introduce a statistical framework, named MRP, for rare variant association studies, that considers correlation, scale, and directionality of genetic effects across a group of 1) genetic variants, 2) phenotypes, and 3) studies. In so doing I am able to present formulations of the framework that considers the use of summary statistic data, the standard univariate and multivariate gene-based models, models for identifying protective protein-truncating variants, or computational algorithms to estimate the underlying mixture of neutral and functional variants from the distribution of rare variants and phenotype, which may provide opportunities for discovery and inference that are not addressed by the traditional one variant-one phenotype association study. These extensions are critical and poised to take advantage of major biobanking and precision medicine initiatives (e.g. UK Biobank, Finland Biobank, US PMI) since we need to understand the full range of medical consequences – good and bad – of variation in a gene in order to confidently generate effective therapeutic hypotheses while recognizing unintended consequences up front rather than after tremendous investment is made.  Finally, I will present opportunities to contribute to methods/tool development for precision health and DNA sequencing studies.