Marked elevation of B-type natriuretic peptide in patients with heart failure and preserved ejection fraction.

UNLABELLED: Marked elevations of B-type natriuretic peptide (BNP) are not generally seen in patients with heart failure and preserved ejection fraction (HFpEF). The objective of this study was to examine the clinical and laboratory characteristics of a large cohort of patients with HFpEF and markedly elevated BNP. A retrospective examination of 421 inpatients at a university hospital admitted with a diagnosis of HFpEF was performed. Clinical and echocardiographic data in 4 groups of patients with levels of BNP ≤ 100 pg/mL, 100-400 pg/mL, 400-1,000 pg/mL and > 1,000 pg/mL were compared. Patients with HFpEF and BNP > 1,000 pg/mL (28% of the population) were characterized by impaired renal function and greater use of anti-hypertensive medications. A subset of these patients with BNP > 1,000 pg/mL had normal renal function (21%) and were significantly older, more frequently female, and tended to have lower ejection fractions. Conversely, patients with HFpEF and BNP ≤ 100 pg/mL were younger and had preserved renal function. BNP was inversely related to the likelihood of subsequent admission for heart failure, but not to myocardial infarction or death. IN CONCLUSION: BNP > 1,000 pg/mL is seen in almost 1/3 of patients hospitalized with HFpEF. This elevation of BNP often reflects impaired renal function, but can also be seen in patients with preserved renal function but relatively impaired systolic function.

Gene coexpression network topology of cardiac development, hypertrophy, and failure.

BACKGROUND: Network analysis techniques allow a more accurate reflection of underlying systems biology to be realized than traditional unidimensional molecular biology approaches. Using gene coexpression network analysis, we define the gene expression network topology of cardiac hypertrophy and failure and the extent of recapitulation of fetal gene expression programs in failing and hypertrophied adult myocardium. METHODS AND RESULTS: We assembled all myocardial transcript data in the Gene Expression Omnibus (n=1617). Because hierarchical analysis revealed species had primacy over disease clustering, we focused this analysis on the most complete (murine) dataset (n=478). Using gene coexpression network analysis, we derived functional modules, regulatory mediators, and higher-order topological relationships between genes and identified 50 gene coexpression modules in developing myocardium that were not present in normal adult tissue. We found that known gene expression markers of myocardial adaptation were members of upregulated modules but not hub genes. We identified ZIC2 as a novel transcription factor associated with coexpression modules common to developing and failing myocardium. Of 50 fetal gene coexpression modules, 3 (6%) were reproduced in hypertrophied myocardium and 7 (14%) were reproduced in failing myocardium. One fetal module was common to both failing and hypertrophied myocardium. CONCLUSIONS: Network modeling allows systems analysis of cardiovascular development and disease. Although we did not find evidence for a global coordinated program of fetal gene expression in adult myocardial adaptation, our analysis revealed specific gene expression modules active during both development and disease and specific candidates for their regulation.

Pathway analysis of coronary atherosclerosis.

Large-scale gene expression studies provide significant insight into genes differentially regulated in disease processes such as cancer. However, these investigations offer limited understanding of multisystem, multicellular diseases such as atherosclerosis. A systems biology approach that accounts for gene interactions, incorporates nontranscriptionally regulated genes, and integrates prior knowledge offers many advantages. We performed a comprehensive gene level assessment of coronary atherosclerosis using 51 coronary artery segments isolated from the explanted hearts of 22 cardiac transplant patients. After histological grading of vascular segments according to American Heart Association guidelines, isolated RNA was hybridized onto a customized 22-K oligonucleotide microarray, and significance analysis of microarrays and gene ontology analyses were performed to identify significant gene expression profiles. Our studies revealed that loss of differentiated smooth muscle cell gene expression is the primary expression signature of disease progression in atherosclerosis. Furthermore, we provide insight into the severe form of coronary artery disease associated with diabetes, reporting an overabundance of immune and inflammatory signals in diabetics. We present a novel approach to pathway development based on connectivity, determined by language parsing of the published literature, and ranking, determined by the significance of differentially regulated genes in the network. In doing this, we identify highly connected "nexus" genes that are attractive candidates for therapeutic targeting and followup studies. Our use of pathway techniques to study atherosclerosis as an integrated network of gene interactions expands on traditional microarray analysis methods and emphasizes the significant advantages of a systems-based approach to analyzing complex disease.