Despite advances in management, heart failure (HF) is still associated with poor outcomes. Insulin resistance is a common comorbidity in HF and independently portends worse outcomes. The mechanism by which insulin resistance develops in HF has not been fully elucidated. Studies in subjects without HF have demonstrated causal role of the gut microbiome in development of insulin resistance. Heart failure is associated with altered gut microbiome, but it is not known how these changes in the microbiome affect the HF host metabolism and if they increase the risk of developing insulin resistance. Because HF and insulin resistance share some gut microbiome patterns, I hypothesize that the HF-related changes in the gut microbiome may contribute to systemic metabolic changes that mediate insulin resistance in HF. I will test this hypothesis by defining gut microbiome composition and concomitant metabolic profile in HF patients with and without insulin resistance.
In Specific Aim 1, I will describe the gut microbiome patterns in HF patients in relation to their insulin resistance. My hypothesis is that, compared to insulin-sensitive HF patients, insulin-resistant HF patients, will have decreased gut microbial diversity, relative depletion of anti-inflammatory Lachnospiraceae, and enrichment of the Prevotellaceae and Bacteroidaceae. By employing both 16S rRNA sequencing and shotgun metagenomic sequencing, I will describe relative species abundance and relative gene abundance in the microbial community, the latter of which will provide information about functional capacity of the microbiome. I will then examine correlation between specific microbes/microbial gene clusters with clinical insulin resistance, in effort to identify microbiomes and microbial gene clusters that may be contributing to insulin resistance.
In Specific Aim 2, I will correlate the gut microbiome patterns to the serum metabolome in HF patients stratified by insulin resistance. Insulin resistance is associated with elevated levels of serum branched chain amino acids (BCAAs). Gut microbiota interact with the host through circulating metabolites, and, indeed, gut commensals Prevotella copri and Bacteroides vulgatus have been shown to drive high levels of BCAAs in insulin resistant states. I hypothesize that, compared to the insulin-sensitive HF patients, insulin-resistant HF patients will have a distinct metabolic profile (e.g., higher levels of BCAAs) which will correlate with their gut microbial signature (e.g., greater abundance of Prevotelaceae and Bacteroides). To test this hypothesis, I will characterize the serum metabolome of the HF population described in Specific Aim 1 using a comprehensive clinical blood panel and liquid chromatography-tandem mass spectrometry, then examine correlation between the microbes/microbial gene clusters associated with insulin resistance in Aim 1, and specific metabolites. At the culmination of this project I will define important patterns of gut microbiome-host interactions in HF, which can serve as basis for improved understanding of the mechanism of insulin resistance in this disease, and enable identification of novel preventative and therapeutic pathways in HF.

Public Health Relevance

I propose to concomitantly characterize the gut microbiome and the host serum metabolome in heart failure patients with and without insulin resistance, in order to identify gut microbial species or gene clusters, and serum metabolites that correlate with insulin resistance in heart failure. The findings of this unique dual omics study will extend out insights into the role of the gut microbiome in the pathogenesis of insulin resistance in heart failure, and allow identification of novel therapeutic targets in this population.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32HL143916-02
Application #
9827492
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Wang, Wayne C
Project Start
2018-12-01
Project End
2021-11-30
Budget Start
2019-12-01
Budget End
2020-11-30
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Stanford University
Department
Genetics
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305