Exaggerated inflammation and monocytosis associate with diastolic dysfunction in heart failure with preserved ejection fraction: evidence of M2 macrophage activation in disease pathogenesis

BACKGROUND: Heart failure with preserved ejection fraction (HFPEF) is a major health problem associated with myocardial leukocyte infiltration, inflammation, and fibrosis. Monocyte and macrophage subsets play a role in HFPEF but have not been studied. We analyzed peripheral blood monocyte phenotype and plasma markers of monocyte activation in patients with HFPEF, asymptomatic LV diastolic dysfunction (aLVDD), and asymptomatic hypertension (aHTN).

METHODS AND RESULTS: Peripheral blood was collected from 23 aHTN, 30 aLVDD, and 30 HFPEF patients. Peripheral cytokines of classic/pro-inflammatory (tumor necrosis factor alpha, interleukin (IL) 12, IL-6, monocyte chemoattractant protein 1, C-X-C motif chemokine 10) and alternative/anti-inflammatory monocytes (chemokine-C-C motif ligand (CCL) 17, CCL-18, soluble CD163) were increased in aLVDD and HFPEF. Peripheral blood mononuclear cells and monocytes were purified and surface-stained for CD14, CD16, CD163, and CD206. Peripheral monocyte percentage was increased in aLVDD and HFPEF and correlated with echocardiographic LVDD indices. Classic/pro-inflammatory monocyte numbers were increased in aLVDD and HFPEF, and alternative/anti-inflammatory monocyte numbers were increased in HFPEF. CD163 M2-macrophage receptor was reduced in HFPEF. Culture of healthy donor monocytes (n = 3) with HFPEF patient-derived sera (n = 6) promoted M2 macrophage features as evidenced by altered morphology and genes (CD206, IL-10).

CONCLUSIONS: Increased peripheral inflammation, monocytosis, and monocyte differentiation to anti-inflammatory/profibrotic M2 macrophages likely associate with HFPEF and its precedent asymptomatic LVDD phase.

Homozygous deletion mapping in myeloma samples identifies genes and an expression signature relevant to pathogenesis and outcome.

PURPOSE: Myeloma is a clonal malignancy of plasma cells. Poor-prognosis risk is currently identified by clinical and cytogenetic features. However, these indicators do not capture all prognostic information. Gene expression analysis can be used to identify poor-prognosis patients and this can be improved by combination with information about DNA-level changes. EXPERIMENTAL DESIGN: Using single nucleotide polymorphism-based gene mapping in combination with global gene expression analysis, we have identified homozygous deletions in genes and networks that are relevant to myeloma pathogenesis and outcome. RESULTS: We identified 170 genes with homozygous deletions and corresponding loss of expression. Deletion within the "cell death" network was overrepresented and cases with these deletions had impaired overall survival. From further analysis of these events, we have generated an expression-based signature associated with shorter survival in 258 patients and confirmed this signature in data from two independent groups totaling 800 patients. We defined a gene expression signature of 97 cell death genes that reflects prognosis and confirmed this in two independent data sets. CONCLUSIONS: We developed a simple 6-gene expression signature from the 97-gene signature that can be used to identify poor-prognosis myeloma in the clinical environment. This signature could form the basis of future trials aimed at improving the outcome of poor-prognosis myeloma.

Immunoglobulin gene rearrangements and the pathogenesis of multiple myeloma.

The ability to rearrange the germ-line DNA to generate antibody diversity is an essential prerequisite for the production of a functional repertoire. While this is essential to prevent infections, it also represents the "Achilles heel" of the B-cell lineage, occasionally leading to malignant transformation of these cells by translocation of protooncogenes into the immunoglobulin (Ig) loci. However, in evolutionary terms this is a small price to pay for a functional immune system. The study of the configuration and rearrangements of the Ig gene loci has contributed extensively to our understanding of the natural history of development of myeloma. In addition to this, the analysis of Ig gene rearrangements in B-cell neoplasms provides information about the clonal origin of the disease, prognosis, as well as providing a clinical useful tool for clonality detection and minimal residual disease monitoring. Herein, we review the data currently available on both Ig gene rearrangements and protein patterns seen in myeloma with the aim of illustrating how this knowledge has contributed to our understanding of the pathobiology of myeloma.

Integration of global SNP-based mapping and expression arrays reveals key regions, mechanisms, and genes important in the pathogenesis of multiple myeloma.

Multiple myeloma is characterized by genomic alterations frequently involving gains and losses of chromosomes. Single nucleotide polymorphism (SNP)-based mapping arrays allow the identification of copy number changes at the sub-megabase level and the identification of loss of heterozygosity (LOH) due to monosomy and uniparental disomy (UPD). We have found that SNP-based mapping array data and fluorescence in situ hybridization (FISH) copy number data correlated well, making the technique robust as a tool to investigate myeloma genomics. The most frequently identified alterations are located at 1p, 1q, 6q, 8p, 13, and 16q. LOH is found in these large regions and also in smaller regions throughout the genome with a median size of 1 Mb. We have identified that UPD is prevalent in myeloma and occurs through a number of mechanisms including mitotic nondisjunction and mitotic recombination. For the first time in myeloma, integration of mapping and expression data has allowed us to reduce the complexity of standard gene expression data and identify candidate genes important in both the transition from normal to monoclonal gammopathy of unknown significance (MGUS) to myeloma and in different subgroups within myeloma. We have documented these genes, providing a focus for further studies to identify and characterize those that are key in the pathogenesis of myeloma.