Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Observational Study
. 2020 Nov 24;142(21):2029-2044.
doi: 10.1161/CIRCULATIONAHA.120.045810. Epub 2020 Oct 9.

Proteomic Evaluation of the Comorbidity-Inflammation Paradigm in Heart Failure With Preserved Ejection Fraction: Results From the PROMIS-HFpEF Study

Sandra Sanders-van Wijk  1   2 , Jasper Tromp  3 , Lauren Beussink-Nelson  1 , Camilla Hage  4 , Sara Svedlund  5 , Antti Saraste  6 , Stanley A Swat  1 , Cynthia Sanchez  1 , Joyce Njoroge  1 , Ru-San Tan  3 , Maria Lagerström Fermer  7 , Li-Ming Gan  7   8   9 , Lars H Lund  4 , Carolyn S P Lam  3 , Sanjiv J Shah  1
Affiliations
Observational Study

Proteomic Evaluation of the Comorbidity-Inflammation Paradigm in Heart Failure With Preserved Ejection Fraction: Results From the PROMIS-HFpEF Study

Sandra Sanders-van Wijk et al. Circulation. .

Abstract

Background: A systemic proinflammatory state has been hypothesized to mediate the association between comorbidities and abnormal cardiac structure/function in heart failure with preserved ejection fraction (HFpEF). We conducted a proteomic analysis to investigate this paradigm.

Methods: In 228 patients with HFpEF from the multicenter PROMIS-HFpEF study (Prevalence of Microvascular Dysfunction in Heart Failure With Preserved Ejection Fraction), 248 unique circulating proteins were quantified by a multiplex immunoassay (Olink) and used to recapitulate systemic inflammation. In a deductive approach, we performed principal component analysis to summarize 47 proteins known a priori to be involved in inflammation. In an inductive approach, we performed unbiased weighted coexpression network analyses of all 248 proteins to identify clusters of proteins that overrepresented inflammatory pathways. We defined comorbidity burden as the sum of 8 common HFpEF comorbidities. We used multivariable linear regression and statistical mediation analyses to determine whether and to what extent inflammation mediates the association of comorbidity burden with abnormal cardiac structure/function in HFpEF. We also externally validated our findings in an independent cohort of 117 HFpEF cases and 30 comorbidity controls without heart failure.

Results: Comorbidity burden was associated with abnormal cardiac structure/function and with principal components/clusters of inflammation proteins. Systemic inflammation was also associated with increased mitral E velocity, E/e' ratio, and tricuspid regurgitation velocity; and worse right ventricular function (tricuspid annular plane systolic excursion and right ventricular free wall strain). Inflammation mediated the association between comorbidity burden and mitral E velocity (proportion mediated 19%-35%), E/e' ratio (18%-29%), tricuspid regurgitation velocity (27%-41%), and tricuspid annular plane systolic excursion (13%) (P<0.05 for all), but not right ventricular free wall strain. TNFR1 (tumor necrosis factor receptor 1), UPAR (urokinase plasminogen activator receptor), IGFBP7 (insulin-like growth factor binding protein 7), and GDF-15 (growth differentiation factor-15) were the top individual proteins that mediated the relationship between comorbidity burden and echocardiographic parameters. In the validation cohort, inflammation was upregulated in HFpEF cases versus controls, and the most prominent inflammation protein cluster identified in PROMIS-HFpEF was also present in HFpEF cases (but not controls) in the validation cohort.

Conclusions: Proteins involved in inflammation form a conserved network in HFpEF across 2 independent cohorts and may mediate the association between comorbidity burden and echocardiographic indicators of worse hemodynamics and right ventricular dysfunction. These findings support the comorbidity-inflammation paradigm in HFpEF.

Keywords: analysis; biomarkers; comorbidity; echocardiography; heart failure; inflammation.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.. Study Design Overview in the PROMIS-HFpEF Derivation Cohort
The analytic approach in the PROMIS-HFpEF derivation cohort started with recapitulating (summarizing) systemic inflammation using both inductive and deductive approaches in step 1. The deductive approach used a priori knowledge of proteins associated with inflammation based on functional annotation in the GO, KEGG, and Reactome databases, followed by principal components analysis. The inductive approach used an unbiased weight co-expression network analysis (WCNA) with clustering, followed by pathway overrepresentation analysis. The resulting principal components and inflammation protein clusters were then used as markers of systemic inflammation in subsequent analyses. In step 2, we used 1-way regression models to determine the association between (A) comorbidity burden with cardiac structure/function; (B) comorbidity burden and systemic inflammation; and (C) systemic inflammation and cardiac structure/function. Finally, in step 3, we performed formal statistical mediation analysis to determine whether markers of systemic inflammation (PCs and protein clusters) mediated the association between comorbidity burden and specific indices and cardiac structure/function. *Selected if annotated as inflammation-related in 2 or more of the databases (GO, KEGG, and Reactome).**These 6 PCs captured 57% of the variation in the 47 selected inflammation-related proteins. †All regression models were adjusted for age, sex, GFR, and study site; LA volume index, LA reservoir strain, e’ velocity, and E/e’ ratio were also further adjusted for atrial fibrillation. ‡ Mediation analysis was only performed for protein PCs/clusters and echocardiographic parameters that fulfilled a valid 3-way association in step 2 (i.e., statistically significant associations with a coherent direction had to be present in regression models corresponding to arrows A, B, and C). Echocardiographic parameters that met these criteria for mediation analysis are represented in bold font. Inflammation protein parameters that met these criteria were PC1, PC5, PC6, the turquoise cluster, and the yellow cluster. Abbreviations: CAD = coronary artery disease; Echo = echocardiographic; LV = left ventricle; LA = left atrial; RV = right ventricular; TAPSE = tricuspid annular plane systolic excursion; TR = tricuspid regurgitation; GO = gene ontology; KEGG = Kyoto Encyclopedia of Genes ad Genomes.
Figure 2.
Figure 2.. Protein Clusters Identified by Weighted Co-expression Network Analyses in PROMIS-HFpEF Derivation Cohort and the Northwestern Validation Cohort
(A) Adjacency network-map of circulating proteins color-coded by cluster assignment by hierarchical clustering-based nearness or co-expression of proteins. For clarity of presentation only nodes (proteins) that were assigned to a cluster are shown (N=159/248); the remaining proteins lie on the outer edges of the network-map. (B) Overrepresented, non-redundant pathways in each cluster with false discovery rate corrected P-values. (C) Detailed network-maps of proteins in the 3 clusters that were representative of inflammation (i.e., overrepresentation of ≥2 inflammatory pathways). Node size reflects intra-cluster connectivity (i.e., the sum of weighted edges [correlations] with all other proteins in the cluster). Node color density reflects the strength of cluster membership. Edge thickness and transparency reflect the adjacency of proteins according to weighted co-expressions. (D) Summary of extracted clusters including (1) the number of assigned proteins per cluster, (2) the main hub (based on intra-cluster connectivity), (3) other exemplar proteins, the primary (most significant) overrepresented pathway; (4) the number of significantly upregulated inflammatory pathway; and (5) the cross-cohort conservation in the HFpEF patients in the Northwestern validation cohort, reflected by the number of overlapping proteins and corresponding P-value (tested under a hypergeometric distribution). (E) Adjacency network-map of circulating proteins in the Northwestern HFpEF patients in the validation cohort. Clusters with most significant overlap were assigned the same color as the corresponding cluster in PROMIS-HFpEF cohort. (F) Adjacency network-map of circulating proteins in the Northwestern control patients in the validation cohort. Cluster preservation was tested against the Northwestern HFpEF patients; clusters with significant overlap were assigned the same color as the corresponding cluster in the Northwestern HFpEF patients.
Figure 3.
Figure 3.. Heatmap of Associations of Comorbidity Burden and Inflammation with Indices of Cardiac Structure and Function in PROMIS-HFpEF.
The values in the cells represent p-values for the associations. The color and intensity of each cell depicts the standardized β-coefficients from linear regression models adjusted for age, gender, glomerular filtration rate, and study site (and atrial fibrillation, for LA indices and E/e’ ratio). Echocardiographic indices that were significantly associated with both comorbidity burden and inflammation (and thus fulfilling the assumptions for mediation analysis) are marked by red font. PC2, PC4, and the red cluster are not shown because of their lack of association with comorbidity burden; PC3 is not shown because all associations had P-values >0.20. Of the statistically significant associations (P<0.05), the yellow cluster was no longer associated with TAPSE after adjustment for inflammatory (autoimmune disease) and/or malignancy. Of the statistically significant associations (P<0.05), the following were no longer significant after correction for multiple testing (false discovery rate): PC1 and relative wall thickness; PC5 and mitral E velocity; PC5 and RV free wall strain; PC6 and RV free wall strain; turquoise cluster and relative wall thickness; turquoise cluster and E/e’ ratio; and turquoise cluster and TR velocity. LV = left ventricular; LA = left atrial; RV = right ventricular; TAPSE = tricuspid annular plane systolic excursion; TR = tricuspid regurgitation; PC = principal component.
Figure 4.
Figure 4.. Mediation Analysis of Inflammation Principal Components/Clusters as Mediators of the Association Between Comorbidity Burden and Mitral E Velocity in PROMIS-HFpEF
Mediation modeling including testing of underlying assumptions. Mitral E velocity was used as an example outcome measure. Values adjacent to the arrows in (A) and (B) depict standardized β-coefficients (95% CIs) and P-values from linear regression models adjusted for age, gender, glomerular filtration rate, study site, and atrial fibrillation. (A) Total effect of the association of comorbidity burden with mitral E velocity on linear regression analysis, a prerequisite for mediation analysis. (B) Investigating the assumptions that comorbidity burden is associated with increased inflammation (reflected by protein PCs/clusters) and that inflammation is associated with increased mitral E velocity in HFpEF. Mediators in light blue do not fulfill the assumptions for mediation analysis because there is no statistically significant effect between predictor and mediator and/or between mediator and outcome. (C) Mediated effect in mediation analysis of parameters fulfilling the underlying assumptions, indicating that 19–35% of the association of comorbidity burden with increased mitral E velocity is mediated by systemic inflammation. *P>0.05 after false discovery rate correction. **Percent mediated = mediated effect / total effect × 100.
Figure 5.
Figure 5.. Inflammation in HFpEF Patients versus Comorbidity Controls in the Northwestern Validation Cohort
(A) Volcano plot showing the upregulated proteins in HFpEF versus comorbidity control patients in the Northwestern validation cohort. Dashed lines show the cut-off used for defining upregulation (false discovery rate-corrected P<0.01 and a > 1.5 fold-change). (B) Significantly overrepresented pathways in HFpEF patients versus comorbidity controls based on the upregulated proteins, indicating upregulation of several inflammatory pathways. (C) Principal component scores summarizing circulating inflammation proteins in HFpEF patients (red) versus comorbidity controls (turquoise). Boxes depict 25th-75th percentiles, horizontal lines through the box depict the median (50th percentile), whiskers depict the upper and lower extremes, and dots depict outliers.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Paulus WJ, Tschope C. A novel paradigm for heart failure with preserved ejection fraction: comorbidities drive myocardial dysfunction and remodeling through coronary microvascular endothelial inflammation. J Am Coll Cardiol. 2013;62:263–271. - PubMed
    1. Komajda M, Carson PE, Hetzel S, McKelvie R, McMurray J, Ptaszynska A, Zile MR, Demets D, Massie BM. Factors associated with outcome in heart failure with preserved ejection fraction: findings from the Irbesartan in Heart Failure with Preserved Ejection Fraction Study (I-PRESERVE). Circ Heart Fail. 2011;4:27–35. - PubMed
    1. Kristensen SL, Mogensen UM, Jhund PS, Petrie MC, Preiss D, Win S, Kober L, McKelvie RS, Zile MR, Anand IS, Komajda M, Gottdiener JS, Carson PE, McMurray JJ. Clinical and Echocardiographic Characteristics and Cardiovascular Outcomes According to Diabetes Status in Patients With Heart Failure and Preserved Ejection Fraction: A Report From the I-Preserve Trial (Irbesartan in Heart Failure With Preserved Ejection Fraction). Circulation. 2017;135:724–735. - PubMed
    1. Ather S, Chan W, Bozkurt B, Aguilar D, Ramasubbu K, Zachariah AA, Wehrens XH, Deswal A. Impact of noncardiac comorbidities on morbidity and mortality in a predominantly male population with heart failure and preserved versus reduced ejection fraction. J Am Coll Cardiol. 2012;59:998–1005. - PMC - PubMed
    1. Hage C, Michaelsson E, Linde C, Donal E, Daubert JC, Gan LM, Lund LH. Inflammatory Biomarkers Predict Heart Failure Severity and Prognosis in Patients With Heart Failure With Preserved Ejection Fraction: A Holistic Proteomic Approach. Circ Cardiovasc Genet. 2017;10:e001633. - PubMed

Publication types

MeSH terms

Substances