Theses Doctoral

Investigating the utility of exome sequencing for kidney disease

Groopman, Emily

Exome sequencing (ES) has empowered genetic diagnosis and novel gene discovery, and is increasingly applied as a first-line test for a variety of disorders. Chronic kidney disease (CKD) affects more than in 1 in 10 persons worldwide, resulting in high morbidity, mortality, and healthcare costs. As CKD displays substantial genetic and phenotypic heterogeneity, the unbiased approach of ES can help to pinpoint a specific etiology and thereby support personalized care. However, the broader utility of ES for nephropathy and challenges associated with such expanded implementation have yet to be systematically assessed. Here, we investigate these questions through integrating ES and phenotype data from large CKD case and control cohorts. First, we survey the genetic and clinical disease spectrum of Mendelian forms of kidney and genitourinary disease, and generate a comprehensive curated list of gene-disease pairs. We then use ES data from 7,974 self-declared healthy adults to evaluate the population prevalence of candidate pathogenic variants for Mendelian nephropathy under different analytic filtering pipelines. We observe an appreciable frequency of putatively diagnostic variants for these conditions using stringent as well as standard filters, resulting in a considerable burden for both variant interpretation and clinical follow-up. Next, we perform ES and diagnostic analysis in a combined cohort of 3,315 all-cause CKD cases. We find diagnostic variants among patients spanning clinical disease categories, and that both the primary and secondary genetic findings resulting from ES have meaningful implications for medical management. We conclude by discussing the greater insights regarding the value of ES for kidney disease emerging from our investigations, and promising avenues for subsequent studies.


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More About This Work

Academic Units
Cellular, Molecular and Biomedical Studies
Thesis Advisors
Gharavi, Ali G.
Ph.D., Columbia University
Published Here
December 10, 2018