Cardiovascular disease (CVD) remains the leading cause of mortality in westernized countries, despite optimum medical therapy to lower LDL cholesterol. The pursuit of novel therapies to target this residual risk has focused on raising levels of HDL cholesterol in order to exploit its atheroprotective effects1. MicroRNAs have emerged as important post-transcriptional regulators of lipid metabolism, and are thus a new class of targets for therapeutic intervention2. MicroRNA-33a and b (miR-33a/b) are intronic microRNAs embedded in the sterol response element binding protein genes SREBF2 and SREBF13–5, respectively, that repress expression of the cholesterol transporter ABCA1, a key regulator of HDL biogenesis. Recent studies in mice suggest that antagonizing miR-33a may be an effective strategy for raising plasma HDL3–5 and protecting from atherosclerosis6, however extrapolation of these findings to humans is complicated by the fact that mice lack miR-33b which is present only in the SREBF1 gene of higher mammals. Here we show in African green monkeys that systemic delivery of an anti-miR oligonucleotide that targets both miR-33a and miR-33b increases hepatic expression of ABCA1 and induces a sustained increase in plasma HDL over 12 weeks. Notably, miR-33 antagonism in this non-human primate model also increased the expression of miR-33 target genes involved in the oxidation of fatty acids (CROT, CPT1A, HADHB, PRKAA1) and reduced genes involved in fatty acid synthesis (SREBF1, FASN, ACLY, ACACA), resulting in a marked suppression of plasma VLDL triglyceride levels, a finding not previously observed in mice. These data establish, in a model highly relevant to humans, that pharmacological inhibition of miR-33a and b is a promising therapeutic strategy to raise plasma HDL and lower VLDL triglycerides for the treatment of dyslipidemias that increase cardiovascular disease risk.

Scarring of the kidney is a major public health concern, directly promoting loss of kidney function. In order to understand the role of microRNA (miRNA) in the progression of kidney scarring in response to injury, we investigated changes in miRNA expression in two kidney fibrosis models, and identified 24 commonly upregulated miRNAs. Among them, miR-21 was highly elevated in both animal models and human transplant kidney nephropathy. Deletion of miR-21 in mice resulted in no overt abnormality. However, miR-21-/- mice suffered far less interstitial fibrosis in response to kidney injury, which was pheno-copied in wild-type mice treated with anti-miR-21 oligonucleotides. Surprisingly, global de-repression of miR-21 target messenger RNAs was only readily detectable in miR-21-/- kidneys after injury. Analysis of gene expression profiles identified groups of genes involved in metabolic pathways that were up-regulated in the absence of miR-21, including the lipid metabolism pathway regulated by Peroxisome proliferator activated receptor-α (Pparα), a direct miR-21 target. Over-expression of Pparα prevented UUO-induced injury and fibrosis. Pparα deficiency abrogated the anti-fibrotic effect of anti-miR21 oligonucleotides. miR-21 also regulates the redox metabolic pathway. The mitochondrial inhibitor of reactive oxygen species generation, Mpv17l, was repressed by miR-21, correlating closely with enhanced oxidative kidney damage. These studies demonstrate that miR-21 contributes to fibrogenesis and epithelial injury in the kidney in two mouse models and is a candidate target for anti-fibrotic therapies.

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ToppCluster is a web server application that leverages a powerful enrichment analysis and underlying data environment for comparative analyses of multiple gene lists. It generates heatmaps or connectivity networks that reveal functional features shared or specific to multiple gene lists. ToppCluster uses hypergeometric tests to obtain list-specific feature enrichment P-values for currently 17 categories of annotations of human-ortholog genes, and provides user-selectable cutoffs and multiple testing correction methods to control false discovery. Each nameable gene list represents a column input to a resulting matrix whose rows are overrepresented features, and individual cells per-list P-values and corresponding genes per feature. ToppCluster provides users with choices of tabular outputs, hierarchical clustering and heatmap generation, or the ability to interactively select features from the functional enrichment matrix to be transformed into XGMML or GEXF network format documents for use in Cytoscape or Gephi applications, respectively. Here, as example, we demonstrate the ability of ToppCluster to enable identification of list-specific phenotypic and regulatory element features (both cis-elements and 3′UTR microRNA binding sites) among tissue-specific gene lists. ToppCluster’s functionalities enable the identification of specialized biological functions and regulatory networks and systems biology-based dissection of biological states. ToppCluster can be accessed freely at http://toppcluster.cchmc.org.