Download 2016 department of medicine research day

2016 DEPARTMENT OF MEDICINE RESEARCH DAY
Title of Poster: Leukocyte Time-Dependent Biology & Outcomes in Advanced Heart
Failure
Presenter: Galyna Bondar, PhD
Division: Cardiology
☒ Faculty ☐ Fellow ☐ Resident ☐ Post-doc Research Fellow ☐ Graduate Student ☐ Medical Student ☐Other
Principal Investigator/Mentor: Mario Deng M.D. Co-Investigators: Martin Cadeiras M.D., Nicholas Wisniewski
Ph.D., Azadeh Esmaeili M.D., Giovanny Godoy, Eleanor Chang, Maral Bakir, Sophie Kupiec-Weglinski, Desai Chu, Tra-Mi
Bao, Josephine Hai, Robin Yee, Amy Li, Miki Rai, Dan Tran, Liliana Madrigal, Ryan Togashi, Peipei Ping Ph.D, Elaine Reed
Ph.D..
Thematic Poster Category:
Atherosclerosis
Infections, Injury and Repair, Inflammation, Host Defense, Immunology, Hemostasis and
Abstract
Introduction: Mechanical Circulatory Support (MCS) Devices serve as a bridge to heart
transplantation, recovery, or lifelong support for patients with Advanced Heart Failure (AdHF). The
inflammatory response after MCS implantation is of major interest as it links to either successful
resolution of surgical injury or prolonged activation of the inflammatory response and progression to
the multiorgan dysfunction syndrome (MOD). Deaths that arise from the implantation are often caused
by MOD, hypothesized to develop from an exaggerated systemic inflammatory response. Therefore,
the primary focus of this study is to develop a set of biomarkers to characterize inflammatory
response, to predict outcomes after MCS implantation in a time-dependent manner. These biomarkers,
exhibiting a strong relationship with clinical markers (e.g. SOFA score), will play a pivotal role in the
decision-making processes for cardiologists and patients.
Methods: This study was approved by the UCLA Office of Human Research Protection Program IRB #
12-000351 as well as all patients signed an informed consent. Samples have been collected between
November 2011 and May 2015.
We collected blood samples from 19 consecutive patients (57±15 years old, 95 samples) undergoing
MCS implantation on the day before surgery, followed by days 1, 3, 5, and 8 postoperatively. We also
collected samples from 4 healthy age matched controls (20 samples). Total RNA was purified,
amplified and hybridized on Illumina Whole Genome Expression Chips. In order to establish a
Peripheral Blood Mononuclear Cell (PBMC)-module eigengene framework for this phenotype-specific
analysis, we analyzed our dataset using Weighted Gene Coexpression Network Analysis (WGCNA). We
isolated 20 modules in this sample collection representing 4 clinical phenotypes (Healthy
Volunteers=HV, Heart Failure Controls=HFC, Mechanical Circulatory Support=MCS and Heart
Transplantation=HTx). Out of the 20 modules, those 9 modules that showed the highest correlation
with the clinical traits and p-value < 0.05 were selected for further characterization of
transcriptome/phenome relationships, utilizing the Strand NGS 2.6 (Agilent) software.
Results: Time independent analysis: To identify molecular biomarkers for the MCS group, we
compared the HFC, MCS and HTx groups to the HV group using a Moderated T test. 5373 genes were
identified across the three groups vs HV. Gene Ontology (GO) and Pathway analysis revealed
enrichment of multiple gene ontology categories related to altered expression of the inflammatory
response. Time series analysis: To examine differences in the gene expression on the patients’
outcome after the MCS surgery we created a time series analysis for the HV and MCS groups. We
compared every time-point against baseline (timepoint 1) and across time-points using rank-based
Friedman repeated-measures testing. Based on the analysis, the HV group showed no differences in
gene expression across all timepoints in contrast to the MCS group, which demonstrated a pronounced
inflammatory response after surgery. 341 differentially expressed transcripts were identified (Fig 1).
These genes represented 136 significantly overrepresented Gene Ontology (GO) “Biological Process”
categories: immune system, metabolic and cellular processes, signaling, localization, biological
regulation and biogenesis.
Conclusions: The inflammatory response during course after MCS can be assessed with GEP of PBMC.
This dataset may serve to create biomarkers to predict outcomes in AdHF.
References
1) Sinha A, Shahzad K, Latif F, Cadeiras M, von Bayern M, Oz S, Naka Y, Deng MC. Peripheral
Blood Mononuclear Cell Transcriptome Profiles Suggest T-cell Immunosuppression after
Uncomplicated Mechanical Circulatory Support Device Surgery. Hum Immunol 2010:71:164-9
2) Bondar G, Cadeiras M, Wisniewski N, Maque J, Chittoor J, Chang E, Bakir M, Starling C,
Shahzad K, Ping P, Reed E, Deng M. Comparison of whole blood and peripheral blood
mononuclear cell gene expression for evaluation of the perioperative inflammatory response in
patients with advanced heart failure. PloS one. 2014;9(12):e115097. PMID: 25517110.
Pmc4269402
3) Wisniewski Nicholas, Galyna Bondar, Christoph Rau, Jay Chittoor, Eleanor Chang, Azadeh
Esmaeili, Martin Cadeiras, and Mario Deng. An integrative model of leukocyte genomics and
organ dysfunction in heart failure patients requiring mechanical circulatory support. bioRxiv
preprint first posted online August 14, 2015; doi: http://dx.doi.org/10.1101/024646 Genome
Medicine Submission
Funding for the MyLeukoMAPTM pilot study phase was obtained by Columbia University NIH SCCOR Grant (PI Rose, Co-PI
Deng), UCLA NIH R21 (PI Deng), UCLA R01 (PI Weiss, Joint PI Deng), UCLA R01 (PI Ping, Co-I Deng), UCLA DOM and
Columbia University (Geier, Milo, Tocco) and UCLA patient philanthropy (Mulder)
Figure: PBMC GEP Hierarchical Clustering on MCS Time Series.