Human Genetic risk factors for Disseminated Coccidioidomycosis (DCM)

Scientific Project 3: Human Genetic Risk Factors for Disseminated Coccidioidomycosis (DCM) ABSTRACT This project will focus on elucidating human host genetic risk variants that predispose individuals to DCM. For the past 80 years, epidemiological studies have demonstrated that certain specific racial and ethnic groups were more likely to progress towards severe disseminated Coccidioidomycosis, While many of these observations have held up over, the underlying mechanistic and genetic pathogenesis underlying these epidemiological observation have not been fully evaluated. There have been several major barriers to these types of genomic studies where the relationship between host-genetic background and environment (here infection): 1) small- sample sizes for most studies; 2) challenge of handling terabytes of genomic data; 3) limited sequencing data for non-european populations;and 4) identifying relevant functional readouts to confirm the effect of variants in relevant model systems. In this U19 proposal, project 3 brings together over 600 existing exome and genome sequencing datasets and proposes to collect and sequence over 500 additional cases and controls. This will be the largest genetic study of coccidioidomycosis to date. Key to this data analysis is the experts in this proposal whose expertise enables us to handle Terabytes of data and to analyze it using ancestry-specific approaches. We will explore two major hypotheses: that common variants that make up ancestry-specific approaches underly race and ethnicity specific differences in DCM or that rare genetic variants in key immune signaling pathways increase risk of DCM. Both hypotheses are not necessarily mutually exclusive and may explain some of the disease associations that have been observed. In addition to identifying the DNA variants, we will perform ATAC-seq, RNA-sequencing studies to functionally validate non-coding and splicing changes caused by non- coding genetic variants. A key aspect of this project is its ability to rapidly integrate with projects 1 and 2 and Core C in order to validate novel genetic variants and their effects on immune pathways. It will allow us to directly bridge the gap between identified genetic variants and clinical function.