The Circulating Microbiome and Premature Mortality in Hemodialysis Patients

Co-Principal Investigator:
Michael A. Langston, Department of Electrical Engineering and Computer Science, University of Tennessee
Abstract:
Deep connections exist between inflammation in end-stage renal disease (ESRD) and the circulating microbiome, which is defined as highly diverse bacterial communities living in the bloodstream. Low-grade chronic inflammation has in fact been implicated as a primary risk factor for ESRD. Patients with this disease tend to have increased intestinal mucosal permeability, leading to translocation from the intestines to the circulation of not only bacterial fragments, but also viable and non-viable intact bacteria. Recent studies have demonstrated the unique immunostimulatory, atherogenic and cardiotoxic properties of circulating bDNA fragments. These observations have led to suggestions that the circulating microbiome can be present in patients with ESRD, and that it can be both quantitatively and qualitatively associated with excess risk of premature morbidity and mortality. A comprehensive taxonomic profile of the circulating microbiome has the potential to help identify previously unrecognized pathogens and provide novel insights into the etiology and mechanisms of inflammation in ESRD. There are critical knowledge gaps, however, in our understanding of this microbiome and its associations with clinical characteristics and outcomes. A central hypothesis of this work is that not only bacteria but also archaea and fungi exist in patients with ESRD, and that these organisms play a major role in the development of premature ESRD mortality, partly mediated by inflammation. To explore this hypothesis, we leverage data from a well-characterized prospective cohort of 978 prevalent ESRD patients receiving regular hemodialysis treatments. Preliminary tasks include measuring microbiome extent and correlating it with ESRD morbidity and mortality. Huge numbers of clinical and other variables will be studied, after which highly scalable graph theoretical tools will be applied in order to extract latent relationships alternately enhanced and repressed in patient subpopulations. The findings of this research are expected to help pave the way for the identification of novel diagnostic and prognostic biomarkers and for the development of target-driven therapeutic strategies that can reduce excess risk of mortality in ESRD.
Research Partners:
The PI for this project is Keiichi Sumida at The University of Tennessee Health Science Center.
Relevant Site of Interest:
DaVita, Inc.