Date of Award


Document Type

Open Access Thesis

Degree Name

Medical Doctor (MD)



First Advisor

Sílvia Vilarinho


In the past two decades, whole-exome sequencing has been successfully demonstrated as an indispensable instrument in uncovering the genetic etiology underlying numerous types of unexplained liver disease. Characterization of these illnesses into distinct molecular disease entities has revolutionized understanding of pathophysiology and has translated into improved guidance on management, treatment and prognosis for patients. However, hepatologists have been slow to welcome the technology into their mainstream clinical practice, largely due to inadequate training in genomic medicine. There thus remains a pressing need to create various forums through which clinicians can gain better appreciation for the value of genetic analysis in the field of hepatology and amass the knowledge and confidence to incorporate genetic analysis into their own clinical practice.

To address this need, we aimed to facilitate the dissemination of new information on liver disease with an underlying genetic etiology through a two-pronged approach: (1) the generation of an online database housing genotype-phenotype correlation information for diseases affecting the liver, and (2) the promotion of a multidisciplinary Hepatology Genome Rounds series.

In this Thesis, we detail the creation of a comprehensive database focused on genetic liver diseases, reflecting the genotypic and phenotypic profiles of more than 7,500 individuals with genetic variants across 269 genes. This newly developed database will provide clinicians and researchers a centralized source for information on genotype-phenotype correlation to aid in diagnosis and education. In addition, we demonstrate that the Hepatology Genome Rounds series, which is an interdisciplinary forum highlighting hepatology cases of clinical interest and educational value, is an important venue for the distribution of genomic knowledge within the field of hepatology and for providing ongoing education to providers and trainees in genomic medicine. We describe our single-center experience, which has led to the reconsideration of diagnoses in two patients and an improved understanding of genotype-phenotype correlations across all cases. As the value of genetic analysis continues to emerge in understanding human disease and pathophysiology, we foresee similar approaches being adopted at other institutions and in additional specialties in coming years for further propagation of genomics in clinical medicine.


This is an Open Access Thesis.

Open Access

This Article is Open Access