PMID- 21266504
OWN - NLM
STAT- MEDLINE
DCOM- 20110812
LR  - 20211020
IS  - 1531-2267 (Electronic)
IS  - 1094-8341 (Print)
IS  - 1094-8341 (Linking)
VI  - 43
IP  - 8
DP  - 2011 Apr 27
TI  - Blood gene expression signatures associate with heart failure outcomes.
PG  - 392-7
LID - 10.1152/physiolgenomics.00175.2010 [doi]
AB  - Gene expression signatures in blood correlate with specific diseases. Such 
      signatures may serve as valuable diagnostic and prognostic tools in disease 
      management. Blood gene expression signatures associated with heart failure may be 
      applied to predict prognosis, monitor disease progression, and optimize 
      treatment. Blood gene expression profiles were generated for 71 subjects with 
      heart failure and 15 controls without heart failure, using the Affymetrix 
      GeneChip U133Plus2.0. Survival analysis identified 197 "mortality genes" that 
      were significantly associated with patient outcome. Functional categorization 
      showed that genes associated with T cell receptor signaling were most 
      significantly overpresented. Cluster analysis of these T cell receptor signaling 
      genes significantly categorized heart failure patients into three risk groups (P 
      = 0.031) that were distinct from the three risk groups categorized by New York 
      Heart Association (NYHA) Classification (P = 0.0002). By combining the analysis 
      of clinical assessment (NYHA class) with T cell receptor signaling gene 
      expression, we proposed a model that demonstrated an even greater differentiation 
      of patients at risk (P = 0.0001). In this discovery study, we identified blood 
      expression signatures associated with heart failure patient outcomes. 
      Characterization of these mortality genes helped identify a set of T cell 
      receptor signaling genes that may be of utility in predicting survival of heart 
      failure patients. These data raise the possibility of prospectively risk 
      stratifying patients with heart failure by integrating blood gene expression 
      signatures with current clinical assessment.
FAU - Vanburen, Peter
AU  - Vanburen P
AD  - Department of Medicine, Cardiology Unit, University of Vermont, Burlington, 
      Vermont, USA. peter.vanburen@uvm.edu
FAU - Ma, Jun
AU  - Ma J
FAU - Chao, Samuel
AU  - Chao S
FAU - Mueller, Enkhtuyaa
AU  - Mueller E
FAU - Schneider, David J
AU  - Schneider DJ
FAU - Liew, Choong-Chin
AU  - Liew CC
LA  - eng
GR  - 5R01HL-077637/HL/NHLBI NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
DEP - 20110125
PL  - United States
TA  - Physiol Genomics
JT  - Physiological genomics
JID - 9815683
RN  - 0 (Receptors, Antigen, T-Cell)
SB  - IM
MH  - Adult
MH  - Aged
MH  - Aged, 80 and over
MH  - Cluster Analysis
MH  - Disease Progression
MH  - Gene Expression Profiling/*methods
MH  - Heart Failure/blood/*genetics/*mortality
MH  - Humans
MH  - Microarray Analysis/*methods
MH  - Middle Aged
MH  - Prognosis
MH  - Receptors, Antigen, T-Cell/*analysis/blood
MH  - Risk Assessment
MH  - Survival Analysis
MH  - Treatment Outcome
PMC - PMC3092336
EDAT- 2011/01/27 06:00
MHDA- 2011/08/13 06:00
PMCR- 2012/04/01
CRDT- 2011/01/27 06:00
PHST- 2011/01/27 06:00 [entrez]
PHST- 2011/01/27 06:00 [pubmed]
PHST- 2011/08/13 06:00 [medline]
PHST- 2012/04/01 00:00 [pmc-release]
AID - physiolgenomics.00175.2010 [pii]
AID - PG-00175-2010 [pii]
AID - 10.1152/physiolgenomics.00175.2010 [doi]
PST - ppublish
SO  - Physiol Genomics. 2011 Apr 27;43(8):392-7. doi: 
      10.1152/physiolgenomics.00175.2010. Epub 2011 Jan 25.