Multiomics Analysis Provides Novel Pathways Related to Progression of Heart Failure.

BACKGROUND: Despite major advances in pharmacological treatment for patients with heart failure, residual mortality remains high. This suggests that important pathways are not yet targeted by current heart failure therapies. OBJECTIVES: We sought integration of genetic, transcriptomic, and proteomic data in a large cohort of patients with heart failure to detect major pathways related to progression of heart failure leading to death. METHODS: We used machine learning methodology based on stacked generalization framework and gradient boosting algorithms, using 54 clinical phenotypes, 403 circulating plasma proteins, 36,046 transcript expression levels in whole blood, and 6 million genomic markers to model all-cause mortality in 2,516 patients with heart failure from the BIOSTAT-CHF (Systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure) study. Results were validated in an independent cohort of 1,738 patients. RESULTS: The mean age of the patients was 70 years (Q1-Q3: 61-78 years), 27% were female, median N-terminal pro-B-type natriuretic peptide was 4,275 ng/L (Q1-Q3: 2,360-8,486 ng/L), and 7% had heart failure with preserved ejection fraction. During a median follow-up of 21 months, 657 (26%) of patients died. The 4 major pathways with a significant association to all-cause mortality were: 1) the PI3K/Akt pathway; 2) the MAPK pathway; 3) the Ras signaling pathway; and 4) epidermal growth factor receptor tyrosine kinase inhibitor resistance. Results were validated in an independent cohort of 1,738 patients. CONCLUSIONS: A systems biology approach integrating genomic, transcriptomic, and proteomic data identified 4 major pathways related to mortality. These pathways are related to decreased activation of the cardioprotective ERBB2 receptor, which can be modified by neuregulin.

Whole blood transcriptomic profiling identifies molecular pathways related to cardiovascular mortality in heart failure.

AIMS: Chronic heart failure (CHF) is a systemic syndrome with a poor prognosis and a need for novel therapies. We investigated whether whole blood transcriptomic profiling can provide new mechanistic insights into cardiovascular (CV) mortality in CHF. METHODS AND RESULTS: Transcriptome profiles were generated at baseline from 944 CHF patients from the BIOSTAT-CHF study, of whom 626 survived and 318 died from a CV cause during a follow-up of 21 months. Multivariable analysis, including adjustment for cell count, identified 1153 genes (6.5%) that were differentially expressed between those that survived or died and strongly related to a validated clinical risk score for adverse prognosis. The differentially expressed genes mainly belonged to five non-redundant pathways: adaptive immune response, proteasome-mediated ubiquitin-dependent protein catabolic process, T-cell co-stimulation, positive regulation of T-cell proliferation, and erythrocyte development. These five pathways were selectively related (RV coefficients >0.20) with seven circulating protein biomarkers of CV mortality (fibroblast growth factor 23, soluble ST2, adrenomedullin, hepcidin, pentraxin-3, WAP 4-disulfide core domain 2, and interleukin-6) revealing an intricate relationship between immune and iron homeostasis. The pattern of survival-associated gene expression matched with 29 perturbagen-induced transcriptome signatures in the iLINCS drug-repurposing database, identifying drugs, approved for other clinical indications, that were able to reverse in vitro the molecular changes associated with adverse prognosis in CHF. CONCLUSION: Systematic modelling of the whole blood protein-coding transcriptome defined molecular pathways that provide a link between clinical risk factors and adverse CV prognosis in CHF, identifying both established and new potential therapeutic targets.

Telomere length is independently associated with all-cause mortality in chronic heart failure.

OBJECTIVE: Patients with heart failure have shorter mean leucocyte telomere length (LTL), a marker of biological age, compared with healthy subjects, but it is unclear whether this is of prognostic significance. We therefore sought to determine whether LTL is associated with outcomes in patients with heart failure. METHODS: We measured LTL in patients with heart failure from the BIOSTAT-CHF Index (n=2260) and BIOSTAT-CHF Tayside (n=1413) cohorts. Cox proportional hazards analyses were performed individually in each cohort and the estimates combined using meta-analysis. Our co-primary endpoints were all-cause mortality and heart failure hospitalisation. RESULTS: In age-adjusted and sex-adjusted analyses, shorter LTL was associated with higher all-cause mortality in both cohorts individually and when combined (meta-analysis HR (per SD decrease in LTL)=1.16 (95% CI 1.08 to 1.24); p=2.66×10-5), an effect equivalent to that of being four years older. The association remained significant after adjustment for the BIOSTAT-CHF clinical risk score to account for known prognostic factors (HR=1.12 (95% CI 1.05 to 1.20); p=1.04×10-3). Shorter LTL was associated with both cardiovascular (HR=1.09 (95% CI 1.00 to 1.19); p=0.047) and non-cardiovascular deaths (HR=1.18 (95% CI 1.05 to 1.32); p=4.80×10-3). There was no association between LTL and heart failure hospitalisation (HR=0.99 (95% CI 0.92 to 1.07); p=0.855). CONCLUSION: In patients with heart failure, shorter mean LTL is independently associated with all-cause mortality.

Genetic risk and atrial fibrillation in patients with heart failure.

AIMS: To study the association between an atrial fibrillation (AF) genetic risk score with prevalent AF and all-cause mortality in patients with heart failure. METHODS AND RESULTS: An AF genetic risk score was calculated in 3759 European ancestry individuals (1783 with sinus rhythm, 1976 with AF) from the BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF) by summing 97 single nucleotide polymorphism (SNP) alleles (ranging from 0-2) weighted by the natural logarithm of the relative SNP risk from the latest AF genome-wide association study. Further, we assessed AF risk variance explained by additive SNP variation, and performance of clinical or genetic risk factors, and the combination in classifying AF prevalence. AF was classified as AF or atrial flutter (AFL) at baseline electrocardiogram and/or a history of AF or AFL. The genetic risk score was associated with AF after multivariable adjustment. Odds ratio for AF prevalence per 1-unit increase genetic risk score was 2.12 (95% confidence interval 1.84-2.45, P = 2.15 × 10-24 ) in the total cohort, 2.08 (1.72-2.50, P = 1.30 × 10-14 ) in heart failure with reduced ejection fraction (HFrEF) and 2.02 (1.37-2.99, P = 4.37 × 10-4 ) in heart failure with preserved ejection fraction (HFpEF). AF-associated loci explained 22.9% of overall AF SNP heritability. Addition of the genetic risk score to clinical risk factors increased the C-index by 2.2% to 0.721. CONCLUSIONS: The AF genetic risk score was associated with increased AF prevalence in HFrEF and HFpEF. Genetic variation accounted for 22.9% of overall AF SNP heritability. Addition of genetic risk to clinical risk improved model performance in classifying AF prevalence.

Large-Scale Analysis of Determinants, Stability, and Heritability of High-Density Lipoprotein Cholesterol Efflux Capacity.

OBJECTIVE: Cholesterol efflux capacity (CEC) has emerged as a biomarker of coronary artery disease risk beyond plasma high-density lipoprotein (HDL) cholesterol (HDL-C) level. However, the determinants of CEC are incompletely characterized. We undertook a large-scale family-based population study to identify clinical, biochemical, and HDL particle parameter determinants of CEC, characterize reasons for the discordancy with HDL-C, quantify its heritability, and assess its stability over 10 to 12 years. APPROACHES AND RESULTS: CEC was quantified in 1988 individuals from the GRAPHIC (Genetic Regulation of Arterial Pressure of Humans in the Community) cohort, comprising individuals from 2 generations from 520 white nuclear families. Serum lipid and lipoprotein levels were determined by ultracentrifugation or nuclear magnetic resonance and HDL particle size and number quantified by nuclear magnetic resonance. Ninety unrelated individuals had repeat CEC measurements in samples collected after 10 to 12 years. CEC was positively correlated with HDL-C (R=0.62; P<0.0001). Among clinical and biochemical parameters, age, systolic blood pressure, alcohol consumption, serum albumin, triglycerides, phospholipids, and lipoprotein(a) were independently associated with CEC. Among HDL particle parameters, HDL particle number, particle size, and apolipoprotein A-II level were independently associated with CEC. Serum triglyceride level partially explained discordancy between CEC and HDL-C. CEC measurements in samples collected 10 to 12 years apart were strongly correlated (r=0.73; P<0.0001). Heritability of CEC was 0.31 (P=3.89×10-14) without adjustment for HDL-C and 0.13 (P=1.44×10-3) with adjustment. CONCLUSIONS: CEC is a stable trait over time, is influenced by specific clinical, serum, and HDL particle parameters factors beyond HDL-C, can be maintained in persons with a low plasma HDL-C by elevated serum triglyceride level, and is modestly independently heritable.

STARS is essential to maintain cardiac development and function in vivo via a SRF pathway.

BACKGROUND: STARS (STriated muscle Activator of Rho Signaling) is a sarcomeric protein expressed early in cardiac development that acts as an acute stress sensor for pathological remodeling. However the role of STARS in cardiac development and function is incompletely understood. Here, we investigated the role of STARS in heart development and function in the zebrafish model and in vitro. METHODOLOGY AND PRINCIPAL FINDINGS: Expression of zebrafish STARS (zSTARS) first occurs in the somites by the 16 somite stage [17 hours post fertilization (hpf)]. zSTARS is expressed in both chambers of the heart by 48 hpf, and also in the developing brain, jaw structures and pectoral fins. Morpholino-induced knockdown of zSTARS alters atrial and ventricular dimensions and decreases ventricular fractional shortening (measured by high-speed video microscopy), with pericardial edema and decreased or absent circulation [abnormal cardiac phenotypes in 126/164 (77%) of morpholino-injected embryos vs. 0/152 (0%) of control morpholino embryos]. Co-injection of zsrf (serum response factor) mRNA rescues the cardiac phenotype of zSTARS knockdown, resulting in improved fractional shortening and ventricular end-diastolic dimensions. Ectopic over-expression of STARS in vitro activates the STARS proximal promoter, which contains a conserved SRF site. Chromatin immunoprecipitation demonstrates that SRF binds to this site in vivo and the SRF inhibitor CCG-1423 completely blocks STARS proximal reporter activity in H9c2 cells. CONCLUSIONS/SIGNIFICANCE: This study demonstrates for the first time that STARS deficiency severely disrupts cardiac development and function in vivo and revealed a novel STARS-SRF feed-forward autoregulatory loop that could play an essential role in STARS regulation and cardiac function.

Myocyte stress 1 plays an important role in cellular hypertrophy and protection against apoptosis.

Myocyte stress 1 (MS1) is a recently described striated muscle actin-binding protein that is up-regulated in the early stages of pressure overload left ventricular hypertrophy. The aim of this study was to determine whether MS1 induces cellular hypertrophy and protects against apoptosis. Over-expressed MS1 co-localized with actin in H9c2 cells and altered expression of genes of the myocardin-related transcription factor (MRTF)/serum response factor (SRF) transcriptional pathways and in addition the apoptosis repressor with caspase recruitment domain (Nol3) gene. The size of cells over-expressing MS1 was significantly increased by 55% and over-expression of MS1 dramatically inhibited staurosporine-induced apoptosis by 89%. These findings suggest the involvement of MS1 in cellular hypertrophy and protection against apoptosis.