Proteomic cardiovascular risk assessment in chronic kidney disease

AIMS

Chronic kidney disease (CKD) is widely prevalent and independently increases cardiovascular risk. Cardiovascular risk prediction tools derived in the general population perform poorly in CKD. Through large-scale proteomics discovery, this study aimed to create more accurate cardiovascular risk models.

METHODS AND RESULTS

Elastic net regression was used to derive a proteomic risk model for incident cardiovascular risk in 2182 participants from the Chronic Renal Insufficiency Cohort. The model was then validated in 485 participants from the Atherosclerosis Risk in Communities cohort. All participants had CKD and no history of cardiovascular disease at study baseline when ∼5000 proteins were measured. The proteomic risk model, which consisted of 32 proteins, was superior to both the 2013 ACC/AHA Pooled Cohort Equation and a modified Pooled Cohort Equation that included estimated glomerular filtrate rate. The Chronic Renal Insufficiency Cohort internal validation set demonstrated annualized receiver operating characteristic area under the curve values from 1 to 10 years ranging between 0.84 and 0.89 for the protein and 0.70 and 0.73 for the clinical models. Similar findings were observed in the Atherosclerosis Risk in Communities validation cohort. For nearly half of the individual proteins independently associated with cardiovascular risk, Mendelian randomization suggested a causal link to cardiovascular events or risk factors. Pathway analyses revealed enrichment of proteins involved in immunologic function, vascular and neuronal development, and hepatic fibrosis.

CONCLUSION

In two sizeable populations with CKD, a proteomic risk model for incident cardiovascular disease surpassed clinical risk models recommended in clinical practice, even after including estimated glomerular filtration rate. New biological insights may prioritize the development of therapeutic strategies for cardiovascular risk reduction in the CKD population.

Mechanisms of Sodium-Glucose Cotransporter 2 Inhibition: Insights From Large-Scale Proteomics

OBJECTIVE

To assess the effects of empagliflozin, a selective sodium-glucose cotransporter 2 (SGLT2) inhibitor, on broad biological systems through proteomics.

RESEARCH DESIGN AND METHODS

Aptamer-based proteomics was used to quantify 3,713 proteins in 144 paired plasma samples obtained from 72 participants across the spectrum of glucose tolerance before and after 4 weeks of empagliflozin 25 mg/day. The biology of the plasma proteins significantly changed by empagliflozin (at false discovery rate-corrected P < 0.05) was discerned through Ingenuity Pathway Analysis.

RESULTS

Empagliflozin significantly affected levels of 43 proteins, 6 related to cardiomyocyte function (fatty acid-binding protein 3 and 4 [FABPA], neurotrophic receptor tyrosine kinase, renin, thrombospondin 4, and leptin receptor), 5 to iron handling (ferritin heavy chain 1, transferrin receptor protein 1, neogenin, growth differentiation factor 2 [GDF2], and β2-microglobulin), and 1 to sphingosine/ceramide metabolism (neutral ceramidase), a known pathway of cardiovascular disease. Among the protein changes achieving the strongest statistical significance, insulin-like binding factor protein-1 (IGFBP-1), transgelin-2, FABPA, GDF15, and sulphydryl oxidase 2 precursor were increased, while ferritin, thrombospondin 3, and Rearranged during Transfection (RET) were decreased by empagliflozin administration.

CONCLUSIONS

SGLT2 inhibition is associated, directly or indirectly, with multiple biological effects, including changes in markers of cardiomyocyte contraction/relaxation, iron handling, and other metabolic and renal targets. The most significant differences were detected in protein species (GDF15, ferritin, IGFBP-1, and FABP) potentially related to the clinical and metabolic changes that were actually measured in the same patients. These novel results may inform further studies using targeted proteomics and a prospective design.

Impact of Kidney Function on the Blood Proteome and on Protein Cardiovascular Risk Biomarkers in Patients With Stable Coronary Heart Disease

Background

Chronic kidney disease (CKD) confers increased cardiovascular risk, not fully explained by traditional factors. Proteins regulate biological processes and inform the risk of diseases. Thus, in 938 patients with stable coronary heart disease from the Heart and Soul cohort, we quantified 1054 plasma proteins using modified aptamers (SOMAscan) to: (1) discern how reduced glomerular filtration influences the circulating proteome, (2) learn of the importance of kidney function to the prognostic information contained in recently identified protein cardiovascular risk biomarkers, and (3) identify novel and even unique cardiovascular risk biomarkers among individuals with CKD.

Methods and Results

Plasma protein levels were correlated to estimated glomerular filtration rate (eGFR) using Spearman‐rank correlation coefficients. Cox proportional hazard models were used to estimate the association between individual protein levels and the risk of the cardiovascular outcome (first among myocardial infarction, stroke, heart failure hospitalization, or mortality). Seven hundred and nine (67.3%) plasma proteins correlated with eGFR at P<0.05 (ρ 0.06–0.74); 218 (20.7%) proteins correlated with eGFR moderately or strongly (ρ 0.2–0.74). Among the previously identified 196 protein cardiovascular biomarkers, just 87 remained prognostic after correction for eGFR. Among patients with CKD (eGFR <60 mL/min per 1.73 m²), we identified 21 protein cardiovascular risk biomarkers of which 8 are unique to CKD.

Conclusions

CKD broadly alters the composition of the circulating proteome. We describe protein biomarkers capable of predicting cardiovascular risk independently of glomerular filtration, and those that are prognostic of cardiovascular risk specifically in patients with CKD and even unique to patients with CKD.

Improving Assessment of Drug Safety Through Proteomics: Early Detection and Mechanistic Characterization of the Unforeseen Harmful Effects of Torcetrapib

Supplemental Digital Content is available in the text.

Background:

Early detection of adverse effects of novel therapies and understanding of their mechanisms could improve the safety and efficiency of drug development. We have retrospectively applied large-scale proteomics to blood samples from ILLUMINATE (Investigation of Lipid Level Management to Understand its Impact in Atherosclerotic Events), a trial of torcetrapib (a cholesterol ester transfer protein inhibitor), that involved 15 067 participants at high cardiovascular risk. ILLUMINATE was terminated at a median of 550 days because of significant absolute increases of 1.2% in cardiovascular events and 0.4% in mortality with torcetrapib. The aims of our analysis were to determine whether a proteomic analysis might reveal biological mechanisms responsible for these harmful effects and whether harmful effects of torcetrapib could have been detected early in the ILLUMINATE trial with proteomics.

Methods:

A nested case-control analysis of paired plasma samples at baseline and at 3 months was performed in 249 participants assigned to torcetrapib plus atorvastatin and 223 participants assigned to atorvastatin only. Within each treatment arm, cases with events were matched to controls 1:1. Main outcomes were a survey of 1129 proteins for discovery of biological pathways altered by torcetrapib and a 9-protein risk score validated to predict myocardial infarction, stroke, heart failure, or death.

Results:

Plasma concentrations of 200 proteins changed significantly with torcetrapib. Their pathway analysis revealed unexpected and widespread changes in immune and inflammatory functions, as well as changes in endocrine systems, including in aldosterone function and glycemic control. At baseline, 9-protein risk scores were similar in the 2 treatment arms and higher in participants with subsequent events. At 3 months, the absolute 9-protein derived risk increased in the torcetrapib plus atorvastatin arm compared with the atorvastatin-only arm by 1.08% (P=0.0004). Thirty-seven proteins changed in the direction of increased risk of 49 proteins previously associated with cardiovascular and mortality risk.

Conclusions:

Heretofore unknown effects of torcetrapib were revealed in immune and inflammatory functions. A protein-based risk score predicted harm from torcetrapib within just 3 months. A protein-based risk assessment embedded within a large proteomic survey may prove to be useful in the evaluation of therapies to prevent harm to patients.

Clinical Trial Registration:

URL: https://www.clinicaltrials.gov. Unique identifier: NCT00134264.

An engineered bivalent neuregulin protects against doxorubicin-induced cardiotoxicity with reduced proneoplastic potential

BACKGROUND

Doxorubicin (DOXO) is an effective anthracycline chemotherapeutic, but its use is limited by cumulative dose-dependent cardiotoxicity. Neuregulin-1β is an ErbB receptor family ligand that is effective against DOXO-induced cardiomyopathy in experimental models but is also proneoplastic. We previously showed that an engineered bivalent neuregulin-1β (NN) has reduced proneoplastic potential in comparison with the epidermal growth factor-like domain of neuregulin-1β (NRG), an effect mediated by receptor biasing toward ErbB3 homotypic interactions uncommonly formed by native neuregulin-1β. Here, we hypothesized that a newly formulated, covalent NN would be cardioprotective with reduced proneoplastic effects in comparison with NRG.

METHODS AND RESULTS

NN was expressed as a maltose-binding protein fusion in Escherichia coli. As established previously, NN stimulated antineoplastic or cytostatic signaling and phenotype in cancer cells, whereas NRG stimulated proneoplastic signaling and phenotype. In neonatal rat cardiomyocytes, NN and NRG induced similar downstream signaling. NN, like NRG, attenuated the double-stranded DNA breaks associated with DOXO exposure in neonatal rat cardiomyocytes and human cardiomyocytes derived from induced pluripotent stem cells. NN treatment significantly attenuated DOXO-induced decrease in fractional shortening as measured by blinded echocardiography in mice in a chronic cardiomyopathy model (57.7±0.6% versus 50.9±2.6%, P=0.004), whereas native NRG had no significant effect (49.4±3.7% versus 50.9±2.6%, P=0.813).

CONCLUSIONS

NN is a cardioprotective agent that promotes cardiomyocyte survival and improves cardiac function in DOXO-induced cardiotoxicity. Given the reduced proneoplastic potential of NN versus NRG, NN has translational potential for cardioprotection in patients with cancer receiving anthracyclines.