The major goal of this proposal is to conduct the first multi-omics translational study of Primary Biliary Cholangitis (PBC), thereby identifying the systems-level networks driving pathological processes in this rare, autoimmune liver disease. Improved understanding of PBC pathogenesis is urgently needed to inform tailored care and the development of new effective therapies. Comprehensive assessments of immunity and the role of environmental influence in PBC are currently lacking. Such evaluations would provide critical knowledge to leverage recent advances in the field?s ability to pharmacologically alter the immune system, thereby providing new hope to PBC patients. Having made significant contributions to the understanding of the genomic architecture underlying development of autoimmunity in PBC, we propose a novel, patient-oriented, multi- omics approach. In this new application, we will decipher how peripheral cellular immunity and non-cellular circulating factors contribute to PBC pathogenesis. We hypothesize that multi-omic analyses integrating cellular and non-cellular factors will identify systems-level pathways driving PBC pathogenesis. To test this hypothesis, we develop an innovative platform that combines aspects of machine learning and quantum statistical mechanics to identify omics-based signatures of PBC that when integrated with clinical features will unveil biological pathways driving disease pathogenesis. To perform this multi-omic study of PBC, we have assembled a world-class, multi-disciplinary team synergizing expertise in PBC biology and omics-scale analytics as well as resources across Mayo Clinic and Columbia University. With a new, in-hand collection of diverse biological specimens from 300 deeply- phenotyped PBC patients and 300 well-matched controls, our studies are already underway with preliminary data demonstrating measureable immunome, methylome, inflammatory protein, exposome, and metabolome differences between PBC patients and controls.
In Aim 1, we thoroughly evaluate peripheral immune composition (the immunome) and activation state (methylome, transcriptome, inflammatory proteins) using mass-cytometry (CyTOF), sequencing- and proximity extension-based methods.
In Aim 2, we perform a cutting-edge study of exogenous chemicals ?the exposome? and endogenous metabolites ?the metabolome? using ultrahigh resolution mass spectroscopy to discover pathogenic alterations in metabolism in PBC. We also develop an assay to quantify liver-specific cell-free DNA in blood as a measure of disease severity.
In Aim 3, we integrate omic-specific signatures (Aims 1 and 2) using a novel approach to identify and prioritize PBC- associated features for further biological investigation. We then infer clinically-relevant subgroups of PBC patients by performing similarity network fusion analysis. In summary, using state-of-the-art, multi-omic analyses, we will discover systems-level networks driving PBC pathogenesis, spurring development of new hypotheses and studies designed to elucidate PBC pathobiology and identify novel therapies.

Public Health Relevance

We will conduct the first multi-omics translational study of primary biliary cholangitis (PBC), to improve understanding of the culprits driving this rare, autoimmune liver disease. By integrating multiple layers of omics data, we will better define the architecture of cellular networks driving PBC. In so doing, we will identify molecular signatures including immune alterations, environmental toxins, and metabolism-related chemicals unique to PBC patients, thereby spurring improved understanding of PBC pathobiology and identification of novel druggable targets.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
1R01DK126691-01
Application #
10095117
Study Section
Hepatobiliary Pathophysiology Study Section (HBPP)
Program Officer
Sherker, Averell H
Project Start
2020-12-21
Project End
2024-11-30
Budget Start
2020-12-21
Budget End
2021-11-30
Support Year
1
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Mayo Clinic, Rochester
Department
Type
DUNS #
006471700
City
Rochester
State
MN
Country
United States
Zip Code
55905