Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients.

BACKGROUND: Diagnosing obstructive coronary artery disease (CAD) in at-risk patients can be challenging and typically requires both noninvasive imaging methods and coronary angiography, the gold standard. Previous studies have suggested that peripheral blood gene expression can indicate the presence of CAD. OBJECTIVE: To validate a previously developed 23-gene, expression-based classification test for diagnosis of obstructive CAD in nondiabetic patients. DESIGN: Multicenter prospective trial with blood samples obtained before coronary angiography. (ClinicalTrials.gov registration number: NCT00500617) SETTING: 39 centers in the United States. PATIENTS: An independent validation cohort of 526 nondiabetic patients with a clinical indication for coronary angiography. MEASUREMENTS: Receiver-operating characteristic (ROC) analysis of classifier score measured by real-time polymerase chain reaction, additivity to clinical factors, and reclassification of patient disease likelihood versus disease status defined by quantitative coronary angiography. Obstructive CAD was defined as 50% or greater stenosis in 1 or more major coronary arteries by quantitative coronary angiography. RESULTS: The area under the ROC curve (AUC) was 0.70 ± 0.02 (P < 0.001); the test added to clinical variables (Diamond-Forrester method) (AUC, 0.72 with the test vs. 0.66 without; P = 0.003) and added somewhat to an expanded clinical model (AUC, 0.745 with the test vs. 0.732 without; P = 0.089). The test improved net reclassification over both the Diamond-Forrester method and the expanded clinical model (P < 0.001). At a score threshold that corresponded to a 20% likelihood of obstructive CAD (14.75), the sensitivity and specificity were 85% and 43% (yielding a negative predictive value of 83% and a positive predictive value of 46%), with 33% of patient scores below this threshold. LIMITATION: Patients with chronic inflammatory disorders, elevated levels of leukocytes or cardiac protein markers, or diabetes were excluded. CONCLUSION: A noninvasive whole-blood test based on gene expression and demographic characteristics may be useful for assessing obstructive CAD in nondiabetic patients without known CAD. PRIMARY FUNDING SOURCE: CardioDx.

A phase 1 study to evaluate the safety and LDL cholesterol-lowering effects of RG7652, a fully human monoclonal antibody against proprotein convertase subtilisin/kexin type 9.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) downregulates low-density lipoprotein (LDL) receptors, thereby leading to a rise in circulating LDL cholesterol (LDL-C). RG7652 is a fully human monoclonal antibody against PCSK9. This placebo-controlled, phase 1 ascending-dose study in healthy subjects evaluated the safety of RG7652 and its efficacy as a potential LDL-C-lowering drug. HYPOTHESIS: Anti-PCSK9 antibody therapy safely and effectively reduces LDL-C. METHODS: Subjects (N = 80) were randomized into 10 cohorts. Six sequential single-dose cohorts received 10, 40, 150, 300, 600, or 800 mg of RG7652 via subcutaneous injection. Four multiple-dose cohorts received 40 or 150 mg of RG7652 once weekly for 4 weeks, either with or without statin therapy (atorvastatin). RESULTS: Adverse events (AEs) were generally mild; the most common AEs were temporary injection-site reactions. No serious AEs, severe AEs, AEs leading to study-drug discontinuation, or dose-limiting toxicities were reported. RG7652 monotherapy reduced mean LDL-C levels by up to 64% and as much as 100 mg/dL at week 2; the effect magnitude and duration increased with dose (≥57 days following a single RG7652 dose ≥300 mg). Exploratory analyses showed reduced oxidized LDL, lipoprotein(a), and lipoprotein-associated phospholipase A2 with RG7652. Antidrug antibody against RG7652 tested positive in 2 of 60 (3.3%) RG7652-treated and in 4 of 20 (20.0%) placebo-treated subjects. Simultaneous atorvastatin administration did not appear to impact the pharmacokinetic profile or lipid-lowering effects of RG7652. CONCLUSIONS: Overall, RG7652 elicited substantial and sustained dose-related LDL-C reductions with an acceptable safety profile and minimal immunogenicity.

Effects of RG7652, a Monoclonal Antibody Against PCSK9, on LDL-C, LDL-C Subfractions, and Inflammatory Biomarkers in Patients at High Risk of or With Established Coronary Heart Disease (from the Phase 2 EQUATOR Study).

RG7652 (MPSK3169A), a fully human immunoglobulin G1 (IgG1) monoclonal antibody directed against proprotein convertase subtilisin/kexin type 9 (PCSK9), blocks the interaction between PCSK9 and low-density lipoprotein (LDL) receptor. EQUATOR (ClinicalTrials.govNCT01609140), a randomized, double-blind, and dose-ranging phase 2 study, evaluated RG7652 in patients (1) at high risk for or (2) with coronary heart disease (CHD). The primary end point was change in LDL cholesterol (LDL-C) from baseline to day 169. Patients (n = 248; median age, 64 years; 57% men; 52% with established CHD; 82% on statins) with baseline LDL-C levels of 90 to 250 mg/dl (mean, 126 mg/dl) continuing on standard-of-care therapy were randomized to receive 1 of 5 RG7652 doses or placebo, subcutaneously every 4, 8, or 12 weeks for 24 weeks. Significant dose-dependent reductions in LDL-C levels from baseline to nadir (56 to 74 mg/dl [48% to 60%]) were observed in all RG7652-dosed patients; effects persisted to day 169 with the highest doses (reduction vs placebo up to 62 mg/dl [51%]) with no unexpected safety signals. RG7652 reduced apolipoprotein B and lipoprotein(a) levels. LDL-C subfraction analysis by nuclear magnetic resonance spectroscopy revealed a prominent decrease in large LDL-C and some decrease in small LDL particles. There was significant reduction in mean particle size of LDL-C on day 169 but no significant reductions in systemic markers of inflammation (high-sensitivity C-reactive protein, interleukin-6, and tumor necrosis factor-alpha). RG7652 reduced LDL-C levels and was well tolerated in patients at high risk for or with CHD on standard-of-care therapy. In conclusion, RG7562 treatment affected large LDL-C and, to a lesser extent, small LDL-C particles; RG7562 did not affect systemic circulating pro-inflammatory cytokines or high-sensitivity C-reactive protein.

Modeling and Simulation to Support Phase 2 Dose Selection for RG7652, a Fully Human Monoclonal Antibody Against Proprotein Convertase Subtilisin/Kexin Type 9.

RG7652 is a fully humanized monoclonal antibody targeting human PCSK9, a regulator of serum low density lipoprotein cholesterol (LDLc) levels. RG7652 prevents degradation of the hepatic LDLc receptors by blocking PCSK9 binding and thereby resulting in efficient LDLc uptake by hepatocytes. The pharmacokinetics of RG7652 have been evaluated in healthy subjects after single and multiple subcutaneous doses. Pharmacokinetic (PK) and pharmacodynamic (PD) models were developed to explain the antibody PK and LDLc time course data. The PK and PD models based on data from healthy subjects were used to simulate the effects of RG7652 on LDLc levels for a range of potential dose regimens in patients with coronary heart disease. A one-compartment PK model combined with an indirect PD response model was able to adequately describe the PK and LDLc data. Simulations of 400 mg every 4 weeks or 800 mg every 8 weeks regimens show significant LDLc reduction and suggest that dosing RG7652 once every month or once every 2 months is predicted to be optimal for the treatment of hypercholesterolemia. The PK and PD model successfully described the PK and LDLc data from healthy subjects in a Phase 1 study, and the model-based simulations provided useful insights and quantitative understanding for the selection of Phase 2 study doses in patients with coronary heart disease. The approach used in the case study demonstrates the utility of modeling and simulation in designing dose-ranging studies.

Development of a blood-based gene expression algorithm for assessment of obstructive coronary artery disease in non-diabetic patients.

BACKGROUND: Alterations in gene expression in peripheral blood cells have been shown to be sensitive to the presence and extent of coronary artery disease (CAD). A non-invasive blood test that could reliably assess obstructive CAD likelihood would have diagnostic utility. RESULTS: Microarray analysis of RNA samples from a 195 patient Duke CATHGEN registry case:control cohort yielded 2,438 genes with significant CAD association (p < 0.05), and identified the clinical/demographic factors with the largest effects on gene expression as age, sex, and diabetic status. RT-PCR analysis of 88 CAD classifier genes confirmed that diabetic status was the largest clinical factor affecting CAD associated gene expression changes. A second microarray cohort analysis limited to non-diabetics from the multi-center PREDICT study (198 patients; 99 case: control pairs matched for age and sex) evaluated gene expression, clinical, and cell population predictors of CAD and yielded 5,935 CAD genes (p < 0.05) with an intersection of 655 genes with the CATHGEN results. Biological pathway (gene ontology and literature) and statistical analyses (hierarchical clustering and logistic regression) were used in combination to select 113 genes for RT-PCR analysis including CAD classifiers, cell-type specific markers, and normalization genes.RT-PCR analysis of these 113 genes in a PREDICT cohort of 640 non-diabetic subject samples was used for algorithm development. Gene expression correlations identified clusters of CAD classifier genes which were reduced to meta-genes using LASSO. The final classifier for assessment of obstructive CAD was derived by Ridge Regression and contained sex-specific age functions and 6 meta-gene terms, comprising 23 genes. This algorithm showed a cross-validated estimated AUC = 0.77 (95% CI 0.73-0.81) in ROC analysis. CONCLUSIONS: We have developed a whole blood classifier based on gene expression, age and sex for the assessment of obstructive CAD in non-diabetic patients from a combination of microarray and RT-PCR data derived from studies of patients clinically indicated for invasive angiography. CLINICAL TRIAL REGISTRATION INFORMATION: PREDICT, Personalized Risk Evaluation and Diagnosis in the Coronary Tree, http://www.clinicaltrials.gov, NCT00500617.

AKAP10 (I646V) functional polymorphism predicts heart rate and heart rate variability in apparently healthy, middle-aged European-Americans.

Previous evidence suggests that the dual-specific A kinase-anchoring protein 2 functional polymorphism (AKAP10 (A/G) I646V) influences heart rate (HR) and heart rate variability (HRV) in mice and humans (N=122) with cardiovascular disease. Here, we asked whether this AKAP10 variant predicts HR and HRV in a large sample of healthy humans. Resting HR and short-term time and frequency domain measures of HRV (5 min during paced and unpaced respiration conditions) were assessed in a U.S. community sample (N=1,033) of generally healthy men and women (age 30-54) of European ancestry. Each person was genotyped for the AKAP10 variant. As with previous work, the AKAP10 Val allele predicted greater resting HR (Paced p<.01; Unpaced p<.03) and diminished HRV (Paced ps <.05) suggesting that this variant may modulate the sensitivity of cardiac pacemaker cells to autonomic inputs, possibly conferring risk for arrhythmias and sudden cardiac death.

Correlation of peripheral-blood gene expression with the extent of coronary artery stenosis.

BACKGROUND: The molecular pathophysiology of coronary artery disease (CAD) includes cytokine release and a localized inflammatory response within the vessel wall. The extent to which CAD and its severity is reflected by gene expression in circulating cells is unknown. METHODS AND RESULTS: From an initial coronary catheterization cohort we identified 41 patients, comprising 27 cases with angiographically significant CAD and 14 controls without coronary stenosis. Whole-genome microarray analysis performed on peripheral-blood mononuclear cells yielded 526 genes with >1.3-fold differential expression (P<0.05) between cases and controls. Real-time polymerase chain reaction on 106 genes (the 50 most significant microarray genes and 56 additional literature genes) in an independent subset of 95 patients (63 cases, 32 controls) from the same cohort yielded 14 genes (P<0.05) that independently discriminated CAD state in a multivariable analysis that included clinical and demographic factors. From an independent second catheterization cohort, 215 patients were selected for real-time polymerase chain reaction-based replication. A case:control subset of 107 patients (86 cases, 21 controls) replicated 11 of the 14 multivariably significant genes from the first cohort. An analysis of the 14 genes in the entire set of 215 patients demonstrated that gene expression was proportional to maximal coronary artery stenosis (P<0.001 by ANOVA). CONCLUSIONS: Gene expression in peripheral-blood cells reflects the presence and extent of CAD in patients undergoing angiography.

Gene-trapped mouse embryonic stem cell-derived cardiac myocytes and human genetics implicate AKAP10 in heart rhythm regulation.

Sudden cardiac death due to abnormal heart rhythm kills 400,000-460,000 Americans each year. To identify genes that regulate heart rhythm, we are developing a screen that uses mouse embryonic stem cells (mESCs) with gene disruptions that can be differentiated into cardiac cells for phenotyping. Here, we show that the heterozygous disruption of the Akap10 (D-AKAP2) gene that disrupts the final 51 aa increases the contractile response of cultured cardiac cells to cholinergic signals. In both heterozygous and homozygous mutant mice derived from these mESCs, the same Akap10 disruption increases the cardiac response to cholinergic signals, suggesting a dominant interfering effect of the Akap10 mutant allele. The mutant mice have cardiac arrhythmias and die prematurely. We also found that a common variant of AKAP10 in humans (646V, 40% of alleles) was associated with increased basal heart rate and decreased heart rate variability (markers of low cholinergic/vagus nerve sensitivity). These markers predict an increased risk of sudden cardiac death. Although the molecular mechanism remains unknown, our findings in mutant mESCs, mice, and a common human AKAP10 SNP all suggest a role for AKAP10 in heart rhythm control. Our stem cell-based screen may provide a means of identifying other genes that control heart rhythm.

Modeling insertional mutagenesis using gene length and expression in murine embryonic stem cells.

BACKGROUND: High-throughput mutagenesis of the mammalian genome is a powerful means to facilitate analysis of gene function. Gene trapping in embryonic stem cells (ESCs) is the most widely used form of insertional mutagenesis in mammals. However, the rules governing its efficiency are not fully understood, and the effects of vector design on the likelihood of gene-trapping events have not been tested on a genome-wide scale. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we used public gene-trap data to model gene-trap likelihood. Using the association of gene length and gene expression with gene-trap likelihood, we constructed spline-based regression models that characterize which genes are susceptible and which genes are resistant to gene-trapping techniques. We report results for three classes of gene-trap vectors, showing that both length and expression are significant determinants of trap likelihood for all vectors. Using our models, we also quantitatively identified hotspots of gene-trap activity, which represent loci where the high likelihood of vector insertion is controlled by factors other than length and expression. These formalized statistical models describe a high proportion of the variance in the likelihood of a gene being trapped by expression-dependent vectors and a lower, but still significant, proportion of the variance for vectors that are predicted to be independent of endogenous gene expression. CONCLUSIONS/SIGNIFICANCE: The findings of significant expression and length effects reported here further the understanding of the determinants of vector insertion. Results from this analysis can be applied to help identify other important determinants of this important biological phenomenon and could assist planning of large-scale mutagenesis efforts.