Date of Award

January 2025

Document Type

Open Access Thesis

Degree Name

Master of Public Health (MPH)

Department

School of Public Health

First Advisor

Andrew DeWan

Second Advisor

Whitney Besse

Abstract

Polycystic liver and kidney diseases are inherited disorders marked by progressive cyst formation in hepatic and renal tissues, leading to significant morbidity through organ enlargement, impaired function, and eventual kidney failure or painful hepatic enlargement. While several genes—including PKD1, PKD2, GANAB, and PRKCSH—are implicated, a substantial proportion of cases remain genetically unexplained, limiting diagnostic precision and therapeutic development. This thesis aims to refine the genetic understanding of polycystic liver diseases through whole exome sequencing of 292 individuals with liver and/or kidney cysts. We first identify pathogenic variants in known disease genes in 133 individuals (46%), confirming the recurrent involvement of PRKCSH, SEC63, PKHD1, GANAB, and others. Subsequently, we analyzed the rest of 159 unsolved cases using rare variant burden testing against Genome Aggregation Database (gnomAD) controls. This approach uncovered MED16 as a novel candidate gene, enriched for deleterious variants and functionally supported by gene intolerance scores, conserved domain localization, and high expression in liver and kidney tissues. Mouse model data further suggest MED16 deficiency may disrupt hepatic physiology and potentially impair pathways.The identification of MED16 expands the genetic landscape of Polycystic liver and kidney diseases and underscores the clinical value of stringent exome analysis in genetically unresolved cohorts. While these initial findings are promising, further validation studies are required to confirm MED16’s pathogenic role before consideration for inclusion in clinical diagnostic panels. Broadly, this research contributes to a deeper understanding of the genetic architecture underlying polycystic liver and kidney diseases, laying groundwork for future investigations that could eventually improve patient diagnosis and clinical management.

Comments

This is an Open Access Thesis.

Open Access

This Article is Open Access

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