The genomics of heart failure: design and rationale of the HERMES consortium

Genetic susceptibility to chronic diseases leads to heart failure among Europeans: the influence of leukocyte telomere length

BACKGROUND

Genetic susceptibility to various chronic diseases has been shown to influence heart failure (HF) risk. However, the underlying biological pathways, particularly the role of leukocyte telomere length (LTL), are largely unknown. We investigated the impact of genetic susceptibility to chronic diseases and various traits on HF risk, and whether LTL mediates or modifies the pathways.

METHODS

We conducted prospective cohort analyses on 404 883 European participants from the UK Biobank, including 9989 incident HF cases. Multivariable Cox regression was used to estimate associations between HF risk and 24 polygenic risk scores (PRSs) for various diseases or traits previously generated using a Bayesian approach. We assessed multiplicative interactions between the PRSs and LTL previously measured in the UK Biobank using quantitative PCR. Causal mediation analyses were conducted to estimate the proportion of the total effect of PRSs acting indirectly through LTL, an integrative marker of biological aging.

RESULTS

We identified 9 PRSs associated with HF risk, including those for various cardiovascular diseases or traits, rheumatoid arthritis (P = 1.3E-04), and asthma (P = 1.8E-08). Additionally, longer LTL was strongly associated with decreased HF risk (P-trend = 1.7E-08). Notably, LTL strengthened the asthma-HF relationship significantly (P-interaction = 2.8E-03). However, LTL mediated only 1.13% (P < 0.001) of the total effect of the asthma PRS on HF risk.

CONCLUSIONS

Our findings shed light onto the shared genetic susceptibility between HF risk, asthma, rheumatoid arthritis, and other traits. Longer LTL strengthened the genetic effect of asthma in the pathway to HF. These results support consideration of LTL and PRSs in HF risk prediction.

Biomarkers of heart failure: advances in omics studies

Heart failure is a complex syndrome characterized by progressive circulatory dysfunction, manifesting clinically as pulmonary and systemic venous congestion, alongside inadequate tissue perfusion. The early identification of HF, particularly at the mild and moderate stages (stages B and C), presents a clinical challenge due to the overlap of signs, symptoms, and natriuretic peptide levels with other cardiorespiratory pathologies. Nonetheless, early detection coupled with timely pharmacological intervention is imperative for enhancing patient outcomes. Advances in high-throughput omics technologies have enabled researchers to analyze patient-derived biofluids and tissues, discovering biomarkers that are sensitive and specific for HF diagnosis. Due to the diversity of HF etiology, it is insufficient to study the diagnostic data of early HF using a single omics technology. This study reviewed the latest progress in genomics, transcriptomics, proteomics, and metabolomics for the identification of HF biomarkers, offering novel insights into the early clinical diagnosis of HF. However, the validity of biomarkers depends on the disease status, intervention time, genetic diversity and comorbidities of the subjects. Moreover, biomarkers lack generalizability in different clinical settings. Hence, it is imperative to conduct multi-center, large-scale and standardized clinical trials to enhance the diagnostic accuracy and utility of HF biomarkers.

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.

Unraveling the relationships between alpha- and beta-adrenergic modulation and the risk of heart failure

Background

The effects of α and ß adrenergic receptor modulation on the risk of developing heart failure (HF) remains uncertain due to a lack of randomized controlled trials. This study aimed to estimate the effects of α and ß adrenergic receptors modulation on the risk of HF and to provide proof of principle for genetic target validation studies in HF.

Methods

Genetic variants within the cis regions encoding the adrenergic receptors α1A, α2B, ß1, and ß2 associated with blood pressure in a 757,601-participant genome-wide association study (GWAS) were selected as instruments to perform a drug target Mendelian randomization study. Effects of these variants on HF risk were derived from the HERMES GWAS (542,362 controls; 40,805 HF cases).

Results

Lower α1A or ß1 activity was associated with reduced HF risk: odds ratio (OR) 0.83 (95% CI 0.74-0.93, P = 0.001) and 0.95 (95% CI 0.93-0.97, P = 8 × 10-6). Conversely, lower α2B activity was associated with increased HF risk: OR 1.09 (95% CI 1.05-1.12, P = 3 × 10-7). No evidence of an effect of lower ß2 activity on HF risk was found: OR 0.99 (95% CI 0.92-1.07, P = 0.95). Complementary analyses showed that these effects were consistent with those on left ventricular dimensions and acted independently of any potential effect on coronary artery disease.

Conclusions

This study provides genetic evidence that α1A or ß1 receptor inhibition will likely decrease HF risk, while lower α2B activity may increase this risk. Genetic variant analysis can assist with drug development for HF prevention.

Exploring novel biomarkers in dilated cardiomyopathy‑induced heart failure by integrated analysis and in vitro experiments

Despite the availability of several effective and promising treatment methods, heart failure (HF) remains a significant public health concern that requires advanced therapeutic strategies and techniques. Dilated cardiomyopathy (DCM) is a crucial factor that contributes to the development and deterioration of HF. The aim of the present study was to identify novel biomarkers and biological pathways to enhance the diagnosis and treatment of patients with DCM-induced HF using weighted gene co-expression network analysis (WGCNA). A total of 24 co-expressed gene modules connected with DCM-induced HF were obtained by WGCNA. Among these, the blue module had the highest correlation with DCM-induced HF (r=0.91; P<0.001) and was enriched in the AGE-RAGE signaling pathway in diabetic complications, the p53 and MAPK signaling pathway, adrenergic signaling in cardiomyocytes, the Janus kinase-STAT signaling pathway and cGMP/PKG signaling. Eight key genes, including secreted protein acidic and rich in cysteine-related modular calcium-binding protein 2 (SMOC2), serpin family A member 3 (SERPINA3), myosin heavy chain 6 (MYH6), S100 calcium binding protein A9 (S100A9), tubulin α (TUBA)3E, TUBA3D, lymphatic vessel endothelial hyaluronic acid receptor 1 (LYVE1) and phospholipase C ε1 (PLCE1), were selected as the therapeutic targets of DCM-induced HF based on WGCNA and differentially expressed gene analysis. Immune cell infiltration analysis revealed that the proportion of naive B cells and CD4-activated memory T cells was markedly upregulated in DCM-induced HF tissues compared with tissues from healthy controls. Furthermore, reverse transcription-quantitative PCR in AC16 human cardiomyocyte cells treated with doxorubicin showed that among the eight key genes, only SERPINA3, MYH6, S100A9, LYVE1 and PLCE1 exhibited expression levels identical to those revealed by bioinformatics analysis, suggesting that these genes may be involved in the development of DCM-induced HF.

Treating chronic diseases without tackling excess adiposity promotes multimorbidity

Few people now reach old age without taking multiple drugs, often attending various clinics, and undergoing secondary or tertiary investigations. Most chronic conditions are, to differing extents, caused or exacerbated by excess adiposity, but weight management is rarely discussed or attempted for patients. Furthermore, progressive symptoms usually attributed to ageing (eg, musculoskeletal pains, fatigue, and breathlessness), and which create considerable health-care demands, can also be attributed to the accumulation of body fat over time. For many symptoms and diseases that are more frequently reported in people with excess adiposity (such as depression), there exist potentially multidirectional, causal relationships that generate a cycle of clinical and social deterioration. There is insufficient research on the effects of effective weight management on these clinically demanding, age and weight-mediated symptoms. Based on current evidence, we suggest that policy makers need to be more proactive in obesity prevention and effective weight management should receive research funding to match the search for novel therapeutics for secondary chronic diseases.