Proteomic Associations of NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) in Heart Failure With Preserved Ejection Fraction.

BACKGROUND: NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels are variably elevated in heart failure with preserved ejection fraction (HFpEF), even in the presence of increased left ventricular filling pressures. NT-proBNP levels are prognostic in HFpEF and have been used as an inclusion criterion for several recent randomized clinical trials. However, the underlying biologic differences between HFpEF participants with high and low NT-proBNP levels remain to be fully understood. METHODS: We measured 4928 proteins using an aptamer-based proteomic assay (SOMAScan) in available plasma samples from 2 cohorts: (1) Participants with HFpEF enrolled in the PHFS (Penn Heart Failure Study; n=253); (2) TOPCAT (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist Trial) participants in the Americas (n=218). We assessed the relationship between SOMAScan-derived plasma NT-proBNP and levels of other proteins available in the SOMAScan assay version 4 using robust linear regression, with correction for multiple comparisons, followed by pathway analysis. RESULTS: NT-proBNP levels exhibited prominent proteome-wide associations in PHFS and TOPCAT cohorts. Proteins most strongly associated with NT-proBNP in both cohorts included SVEP1 (sushi, von Willebrand factor type-A, epidermal growth factor, and pentraxin domain containing 1; ßTOPCAT=0.539; P<0.0001; ßPHFS=0.516; P<0.0001) and ANGPT2 (angiopoietin 2; ßTOPCAT=0.571; P<0.0001; ßPHFS=0.459; P<0.0001). Canonical pathway analysis demonstrated consistent associations with multiple pathways related to fibrosis and inflammation. These included hepatic fibrosis and inhibition of matrix metalloproteases. Analyses using cut points corresponding to estimated quantitative concentrations of 360 pg/mL (and 480 pg/mL in atrial fibrillation) revealed similar proteomic associations. CONCLUSIONS: Circulating NT-proBNP levels exhibit prominent proteomic associations in HFpEF. Our findings suggest that higher NT-proBNP levels in HFpEF are a marker of fibrosis and inflammation. These findings will aid the interpretation of NT-proBNP levels in HFpEF and may guide the selection of participants in future HFpEF clinical trials.

Proteomic Associations of Adverse Outcomes in Human Heart Failure.

BACKGROUND: Identifying novel molecular drivers of disease progression in heart failure (HF) is a high-priority goal that may provide new therapeutic targets to improve patient outcomes. The authors investigated the relationship between plasma proteins and adverse outcomes in HF and their putative causal role using Mendelian randomization. METHODS AND RESULTS: The authors measured 4776 plasma proteins among 1964 participants with HF with a reduced left ventricular ejection fraction enrolled in PHFS (Penn Heart Failure Study). Assessed were the observational relationship between plasma proteins and (1) all-cause death or (2) death or HF-related hospital admission (DHFA). The authors replicated nominally significant associations in the Washington University HF registry (N=1080). Proteins significantly associated with outcomes were the subject of 2-sample Mendelian randomization and colocalization analyses. After correction for multiple testing, 243 and 126 proteins were found to be significantly associated with death and DHFA, respectively. These included small ubiquitin-like modifier 2 (standardized hazard ratio [sHR], 1.56; P<0.0001), growth differentiation factor-15 (sHR, 1.68; P<0.0001) for death, A disintegrin and metalloproteinase with thrombospondin motifs-like protein (sHR, 1.40; P<0.0001), and pulmonary-associated surfactant protein C (sHR, 1.24; P<0.0001) for DHFA. In pathway analyses, top canonical pathways associated with death and DHFA included fibrotic, inflammatory, and coagulation pathways. Genomic analyses provided evidence of nominally significant associations between levels of 6 genetically predicted proteins with DHFA and 11 genetically predicted proteins with death. CONCLUSIONS: This study implicates multiple novel proteins in HF and provides preliminary evidence of associations between genetically predicted plasma levels of 17 candidate proteins and the risk for adverse outcomes in human HF.

Proteomic Correlates of the Urinary Protein/Creatinine Ratio in Heart Failure With Preserved Ejection Fraction.

Proteinuria is common in heart failure with preserved ejection fraction (HFpEF), but its biologic correlates are poorly understood. We assessed the relation between 49 plasma proteins and the urinary protein/creatinine ratio (UPCR) in 365 participants in the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist Trial. Linear regression and network analysis were used to represent relations between protein biomarkers and UPCR. Higher UPCR was associated with older age, a greater proportion of female gender, smaller prevalence of previous myocardial infarction, and greater prevalence of diabetes, insulin use, smoking, and statin use, in addition to a lower estimated glomerular filtration rate, hematocrit, and diastolic blood pressure. Growth differentiation factor 15 (GDF-15; ß = 0.15, p <0.0001), followed by N-terminal proatrial natriuretic peptide (NT-proANP; ß = 0.774, p <0.0001), adiponectin (ß = 0.0005, p <0.0001), fibroblast growth factor 23 (FGF-23, ß = 0.177; p <0.0001), and soluble tumor necrosis factor receptors I (ß = 0.002, p <0.0001) and II (ß = 0.093, p <0.0001) revealed the strongest associations with UPCR. Network analysis showed that UPCR is linked to various proteins primarily through FGF-23, which, along with GDF-15, indicated node characteristics with strong connectivity, whereas UPCR did not. In a model that included FGF-23 and UPCR, the former was predictive of the risk of death or heart-failure hospital admission (standardized hazard ratio 1.83, 95% confidence interval 1.49 to 2.26, p <0.0001) and/or all-cause death (standardized hazard ratio 1.59, 95% confidence interval 1.22 to 2.07, p = 0.0005), whereas UPCR was not prognostic. Proteinuria in HFpEF exhibits distinct proteomic correlates, primarily through its association with FGF-23, a well-known prognostic marker in HFpEF. However, in contrast to FGF-23, UPCR does not hold independent prognostic value.

Heterogeneity in phenotype, disease progression and drug response in type 2 diabetes.

Type 2 diabetes (T2D) is a complex chronic disease characterized by considerable phenotypic heterogeneity. In this study, we applied a reverse graph embedding method to routinely collected data from 23,137 Scottish patients with newly diagnosed diabetes to visualize this heterogeneity and used partitioned diabetes polygenic risk scores to gain insight into the underlying biological processes. Overlaying risk of progression to outcomes of insulin requirement, chronic kidney disease, referable diabetic retinopathy and major adverse cardiovascular events, we show how these risks differ by patient phenotype. For example, patients at risk of retinopathy are phenotypically different from those at risk of cardiovascular events. We replicated our findings in the UK Biobank and the ADOPT clinical trial, also showing that the pattern of diabetes drug monotherapy response differs for different drugs. Overall, our analysis highlights how, in a European population, underlying phenotypic variation drives T2D onset and affects subsequent diabetes outcomes and drug response, demonstrating the need to incorporate these factors into personalized treatment approaches for the management of T2D.

The impact of phenotype, ethnicity and genotype on progression of type 2 diabetes mellitus.

AIM: To conduct a comprehensive review of studies of glycaemic deterioration in type 2 diabetes and identify the major factors influencing progression. METHODS: We conducted a systematic literature search with terms linked to type 2 diabetes progression. All the included studies were summarized based upon the factors associated with diabetes progression and how the diabetes progression was defined. RESULTS: Our search yielded 2785 articles; based on title, abstract and full-text review, we included 61 studies in the review. We identified seven criteria for diabetes progression: 'Initiation of insulin', 'Initiation of oral antidiabetic drug', 'treatment intensification', 'antidiabetic therapy failure', 'glycaemic deterioration', 'decline in beta-cell function' and 'change in insulin dose'. The determinants of diabetes progression were grouped into phenotypic, ethnicity and genotypic factors. Younger age, poorer glycaemia and higher body mass index at diabetes diagnosis were the main phenotypic factors associated with rapid progression. The effect of genotypic factors on progression was assessed using polygenic risk scores (PRS); a PRS constructed from the genetic variants linked to insulin resistance was associated with rapid glycaemic deterioration. The evidence of impact of ethnicity on progression was inconclusive due to the small number of multi-ethnic studies. CONCLUSION: We have identified the major determinants of diabetes progression-younger age, higher BMI, higher HbA1c and genetic insulin resistance. The impact of ethnicity is uncertain; there is a clear need for more large-scale studies of diabetes progression in different ethnic groups.

Efficacy of Modern Diabetes Treatments DPP-4i, SGLT-2i, and GLP-1RA in White and Asian Patients With Diabetes: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

BACKGROUND: The pathophysiology of type 2 diabetes differs markedly by ethnicity. PURPOSE: A systematic review and meta-analysis was conducted to assess the impact of ethnicity on the glucose-lowering efficacy of the newer oral agents, sodium-glucose cotransporter 2 inhibitors (SGLT-2i), glucagon-like peptide 1 receptor agonists (GLP-1RA), and dipeptidyl peptidase 4 inhibitors (DPP-4i), using evidence from randomized clinical trials (RCTs). DATA SOURCES: A literature search was conducted in PubMed of all randomized, placebo-controlled trials of DPP-4i, SGLT-2i, and GLP-1RA. The search strategy was developed based on Medical Subject Headings (MeSH) terms and keywords. STUDY SELECTION: A total of 64 studies that qualified for meta-analysis after full-text review based on predefined inclusion and exclusion criteria-RCTs with at least 50 patients in each arm, >70% of population from Asian or white group, duration ≥24 weeks, and publication up to March 2019-were selected for systematic review and meta-analysis. DATA EXTRACTION: Data extraction was done for aggregated study-level data by two independent researchers. Absolute changes in HbA1c (%) from baseline to 24 weeks between the drug and placebo were considered as the primary end point of the study. DATA SYNTHESIS: Change in HbA1c was evaluated by computing mean differences and 95% CIs between treatment and placebo arms. LIMITATIONS: The study is based on summarized data and could not be separated based on East Asians and South Asians. CONCLUSIONS: The glucose-lowering efficacy of SGLT-2i, and to a lesser extent DPP-4i, was greater in studies of predominantly Asian ethnicity compared with studies of predominantly white ethnicity. There was no difference seen by ethnicity for GLP-1RA.

PheGWAS: a new dimension to visualize GWAS across multiple phenotypes.

MOTIVATION: PheGWAS was developed to enhance exploration of phenome-wide pleiotropy at the genome-wide level through the efficient generation of a dynamic visualization combining Manhattan plots from GWAS with PheWAS to create a 3D 'landscape'. Pleiotropy in sub-surface GWAS significance strata can be explored in a sectional view plotted within user defined levels. Further complexity reduction is achieved by confining to a single chromosomal section. Comprehensive genomic and phenomic coordinates can be displayed. RESULTS: PheGWAS is demonstrated using summary data from Global Lipids Genetics Consortium GWAS across multiple lipid traits. For single and multiple traits PheGWAS highlighted all 88 and 69 loci, respectively. Further, the genes and SNPs reported in Global Lipids Genetics Consortium were identified using additional functions implemented within PheGWAS. Not only is PheGWAS capable of identifying independent signals but also provides insights to local genetic correlation (verified using HESS) and in identifying the potential regions that share causal variants across phenotypes (verified using colocalization tests). AVAILABILITY AND IMPLEMENTATION: The PheGWAS software and code are freely available at (https://github.com/georgeg0/PheGWAS). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.