PROJECT SUMMARYDisseminated coccidioidomycosis (DCM) is a rare and potentially life-threatening consequence of infectionwith a desert soil dwelling fungal pathogen native to the Southwestern USA (Coccidioides spp.). The reasonwhy a subset (<5%) of otherwise healthy people develop this adverse outcome after infection while most othersdo not is largely unknown. However evidence points to genetics primarily involving variation in the immunesystem. To discover the systems genetic patterns and pathways associated with DCM we will examine thedifferential distribution of variants in biologically meaningful gene sets at genome-wide scale to find patternsthat underlie disease susceptibility. Focusing on aggregated systems-level sets allows us to find patterns in thepresence of cross-patient differences and substantially increases our statistical discovery power by reducingthe number of features being directly tested. This study will be the first of its scope and kind using the largestcohort ever assembled for this disease (DNA collected from 147 susceptible DCM cases and 388 resistantcontrols presenting as self-limited pulmonary coccidioidomycosis). The data and results gathered under thisproposal thus present a unique resource to lay important foundations for the study of DCM pathogenesis. TheDNA has been both (i) genome-wide genotyped for common variation and (ii) exome sequenced to look forrare protein-altering variation. In our first Aim we will study the genotype data in three different ways. Firstwe will look for association between DCM and variation in the human leukocyte antigen region (HLA) whichplays an important role in many infectious diseases. Second we will look at the distribution of patientgenotypes at infection-relevant reQTL variant sets to model if DCM versus PUL have differences correlatedwith their phenotype. These reQTL variant sets are groups of DNA positions where different alleles can causestronger or weaker gene expression responses after infection or stimulation and differences between DCM andPUL at those positions could imply that their Coccidioides-response capacity may differ. Third we will conducta pathway-association study using both hypothesis-driven and unbiasedly selected pathways (sets of genes) tosee if these genesets are enriched for variants associated with DCM. For our second Aim we will analyze therare variants found in patient exomes to compare whether DCM participants have an excess of rare andprotein-damaging mutations in immune or other candidate pathways. We will use a two-step version of thesmall sample size optimized Sequence Kernel Association test comparing the distribution of these mutationsbetween DCM and PUL participants. Using a pathway or gene set approach allows us to look at differentiallyimpacted systems rather than requiring each participant to carry the same single-gene mutation. Results of thestudies under these two aims will lead to a better understanding the human genetic variation associated withDCM will help us understand this emerging infectious disease (NIAID Category C) identify people at lower orhigher risk and ultimately build towards improvements in clinical care and patient experience.