A functional variant of the neuropeptide S receptor-1 gene modulates clinical outcomes and healthcare utilization in patients with systolic heart failure: results from the Interdisciplinary Network Heart Failure (INH) Study

Deep phenotyping as a contribution to personalized depression therapy: the GEParD and DaCFail protocols

Depressive patients suffer from a complex of symptoms of varying intensity compromising their mood, emotions, self-concept, neurocognition, and somatic function. Due to a mosaic of aetiologies involved in developing depression, such as somatic, neurobiological, (epi-)genetic factors, or adverse life events, patients often experience recurrent depressive episodes. About 20-30% of these patients develop difficult-to-treat depression. Here, we describe the design of the GEParD (Genetics and Epigenetics of Pharmaco- and Psychotherapy in acute and recurrent Depression) cohort and the DaCFail (Depression-associated Cardiac Failure) case-control protocol. Both protocols intended to investigate the incremental utility of multimodal biomarkers including cardiovascular and (epi-)genetic markers, functional brain and heart imaging when evaluating the response to antidepressive therapy using comprehensive psychometry. From 2012 to 2020, 346 depressed patients (mean age 45 years) were recruited to the prospective, observational GEParD cohort protocol. Between 2016 and 2020, the DaCFail case-control protocol was initiated integrating four study subgroups to focus on heart-brain interactions and stress systems in patients > 50 years with depression and heart failure, respectively. For DaCFail, 120 depressed patients (mean age 60 years, group 1 + 2), of which 115 also completed GEParD, and 95 non-depressed controls (mean age 66 years) were recruited. The latter comprised 47 patients with heart failure (group 3) and 48 healthy subjects (group 4) of a population-based control group derived from the Characteristics and Course of Heart Failure Stages A-B and Determinants of Progression (STAAB) cohort study. Our hypothesis-driven, exploratory study design may serve as an exemplary roadmap for a standardized, reproducible investigation of personalized antidepressant therapy in an inpatient setting with focus on heart comorbidities in future multicentre studies.

STAT4 and COL1A2 are potential diagnostic biomarkers and therapeutic targets for heart failure comorbided with depression

BACKGROUND

Heart failure (HF) and depression are common disorders that markedly compromise quality of life and impose a great financial burden on the society. Although increasing evidence has supported the closely linkage between the two disorders, the comorbidity mechanisms remain to be fully illuminated. We performed a bioinformatics network analysis to understand potential diagnostic biomarkers and therapeutic targets for HF comorbided with depression.

METHODS

We downloaded the datasets of HF and depression from the Gene Expression Omnibus (GEO) database and constructed co-expression networks by Weighted Gene Co-Expression Network Analysis (WGCNA) to identify key modules. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the common genes existing in the HF and depression related modules. Then, we employed the STRING database to construct the protein-protein interaction (PPI) network and detected the hub genes in the network. Finally, we validated the expression difference of hub genes from additional datasets of HF and depression.

RESULTS

Functional enrichment analysis indicated that platelet activation, chemokine signaling and focal adhesion were probably involved in HF comorbided with depression. PPI network construction indicated that HF comorbided with depression is likely related to 5 hub genes, including STAT4, CD83, CX3CR1, COL1A2, and SH2D1B. In validated datasets, STAT4 and COL1A2 were especially involved in the comorbidity of HF and depression.

CONCLUSION

Our work indicated a total of 5 hub genes including STAT4, CD83, CX3CR1, COL1A2, and SH2D1B, in which STAT4 and COL1A2 especially underlie the comorbidity mechanisms of HF and depression. These shared pathways might provide new targets for further mechanistic studies of the pathogenesis and treatment of HF and depression.

Prediction of HF-Related Mortality Risk Using Genetic Risk Score Alone and in Combination With Traditional Risk Factors

Background: Common variants may contribute to the variation of prognosis of heart failure (HF) among individual patients, but no systematical analysis was conducted using transcriptomic and whole exome sequencing (WES) data. We aimed to construct a genetic risk score (GRS) and estimate its potential as a predictive tool for HF-related mortality risk alone and in combination with traditional risk factors (TRFs). Methods and Results: We reanalyzed the transcriptomic data of 177 failing hearts and 136 healthy donors. Differentially expressed genes (fold change >1.5 or <0.68 and adjusted P < 0.05) were selected for prognosis analysis using our whole exome sequencing and follow-up data with 998 HF patients. Statistically significant variants in these genes were prepared for GRS construction. Traditional risk variables were in combination with GRS for the construct of the composite risk score. Kaplan-Meier curves and receiver operating characteristic (ROC) analysis were used to assess the effect of GRS and the composite risk score on the prognosis of HF and discriminant power, respectively. We found 157 upregulated and 173 downregulated genes. In these genes, 31 variants that were associated with the prognosis of HF were finally identified to develop GRS. Compared with individuals with low risk score, patients with medium- and high-risk score showed 2.78 (95%CI = 1.82-4.24, P = 2 × 10^-6) and 6.54 (95%CI = 4.42-9.71, P = 6 × 10^-21) -fold mortality risk, respectively. The composite risk score combining GRS and TRF predicted mortality risk with an HR = 5.41 (95% CI = 2.72-10.64, P = 1 × 10^-6) for medium vs. low risk and HR = 22.72 (95% CI = 11.9-43.48, P = 5 × 10^-21) for high vs. low risk. The discriminant power of GRS is excellent with a C statistic of 0.739, which is comparable to that of TRF (C statistic = 0.791). The combination of GRS and TRF could significantly increase the predictive ability (C statistic = 0.853). Conclusions: The 31-SNP GRS could well distinguish those HF patients with poor prognosis from those with better prognosis and provide clinician with reference for the intensive therapy, especially when combined with TRF. Clinical Trial Registration: https://www.clinicaltrials.gov/, identifier: NCT03461107.

[Care of patients with chronic heart failure: an interdisciplinary challenge]

The diverse manifestations of heart failure led to complex treatment guidelines and care scenarios and therefore always require an integrated, multidisciplinary care approach. Patients with chronic heart failure suffer from a large number of cardiac and noncardiac comorbidities. For example, iron deficiency leads to decreased performance and exertional dyspnea and should be diagnosed. Psychological screening questionnaires should be used for the early detection of psychological comorbidities.ARNI and SGLT-inhibitors expand the pharmacotherapeutic possibilities and gain in importance. The constant development of diagnostic possibilities and therapeutic options must be implemented consistently into the care continuum in order to have a lasting effect. The challenge of interdisciplinary coordination can be significantly reduced through jointly agreed process logs (e. g. within the framework of integrated supply contracts or a Heart Failure Unit Network).

Heart and brain interactions : Pathophysiology and management of cardio-psycho-neurological disorders

Cardiovascular diseases (CVD) and mental health disorders (MHD; e.g. depression, anxiety and cognitive dysfunction) are highly prevalent and are associated with significant morbidity and mortality and impaired quality of life. Currently, possible interactions between pathophysiological mechanisms in MHD and CVD are rarely considered during the diagnostic work-up, prognostic assessment and treatment planning in patients with CVD, and research addressing bidirectional disease mechanisms in a systematic fashion is scarce. Besides some overarching pathogenetic principles shared by CVD and MHD, there are specific syndromes in which pre-existing neurological or psychiatric illness predisposes and contributes to CVD development (as in Takotsubo syndrome), or in which the distorted interplay between innate immune and central nervous systems and/or pre-existing CVD leads to secondary MHD and brain damage (as in peripartum cardiomyopathy or atrial fibrillation). Clinical manifestations and phenotypes of cardio-psycho-neurological diseases depend on the individual somatic, psychosocial, and genetic risk profile as well as on personal resilience, and differ in many respects between men and women. In this article, we provide arguments on why, in such conditions, multidisciplinary collaborations should be established to allow for more comprehensive understanding of the pathophysiology as well as appropriate and targeted diagnosis and treatment. In addition, we summarize current knowledge on the complex interactions between the cardiovascular and central nervous systems in Takotsubo syndrome and peripartum cardiomyopathy, and on the neurological and psychiatric complications of atrial fibrillation.

Risk factors for hospital readmission in adult patients with heart failure with reduced ejection fraction: a systematic review

OBJECTIVE

The objective of this review was to identify and synthesize evidence on risk factors associated with hospital readmission within the first year after heart failure hospitalization among patients with heart failure with reduced left ventricular ejection fraction.

INTRODUCTION

Heart failure is associated with a high risk of hospital readmission. Readmissions are associated with higher mortality and health care costs. It is a high health care priority to identify vulnerable patients with heart failure who may potentially benefit from targeted personalized care interventions aiming to reduce readmissions.

INCLUSION CRITERIA

This review considered studies including adult patients who had heart failure with a reduced left ventricular ejection fraction ≤ 40% who were discharged after a heart failure hospitalization. The authors included studies with experimental and observational designs evaluating risk factors for i) all-cause hospital readmission, ii) heart failure hospital readmission, and iii) composite outcomes within seven, 15, 30, 60, 90, 180, and 365 days after hospital discharge. Composite outcomes included end points where all-cause readmission and/or heart failure readmission were part of a defined end point (i.e. all-cause readmission or mortality; heart failure readmission or mortality; cardiovascular readmission; cardiovascular readmission or mortality; and readmission, mortality, or cardiac transplant). Studies reporting all-cause readmission and/or heart failure readmission as a primary outcome, secondary outcome, or part of a composite outcome were included.

METHODS

PubMed, Embase, CINAHL, Cochrane CENTRAL, PsycINFO, OpenGrey, MedNar, DART-Europe, ProQuest Dissertations and Theses, and the Grey Literature Report in Public Health were searched to find both published and unpublished studies in English, Swedish, Norwegian, or Danish from 2000 to June 2018. Study selection, critical appraisal, data extraction, and data synthesis followed the JBI approach for systematic reviews. Statistical pooling was not possible due to clinical and methodological heterogeneity of the studies included and the lack of risk factors reported more than once. A narrative summary of the findings was performed.

RESULTS

Fifty-two studies, including one randomized controlled trial and 51 cohort studies with a total of 128,186 participants, were included. Risk factors for readmission were reported for 30-day outcome in 16 studies, 60-day in three studies, 90-day in 15 studies, 180-day in 12 studies, and 365-day outcome in 15 studies. Based on multivariable analyses from 43 cohort studies and results from one randomized controlled trial, the authors identified several factors associated with higher risk of all-cause readmission, heart failure readmission, and composite outcomes (e.g. readmission or death) within 30, 60, 90, 180, and 365 days after discharge for a heart failure hospitalization.

CONCLUSIONS

This review provides a comprehensive overview of factors associated with a clinical outcome after a heart failure hospitalization in patients with heart failure with left ventricular ejection fraction ≤ 40%. Owing to the heterogeneity of variables investigated and the lack of comparability of findings, the clinical impact of the identified risk factors remains uncertain. This review highlights research gaps and the need for a standardized way to define and measure all-cause readmission, heart failure readmission, and composite end points in clinical research to improve study quality and enable comparison of findings between studies.

Invasive hemodynamics and cardiac biomarkers to predict outcomes after percutaneous edge-to-edge mitral valve repair in patients with severe heart failure

BACKGROUND

Percutaneous mitral valve repair (PMVR) via MitraClip implantation is a therapeutic option for high-risk or non-surgical candidates with severe mitral regurgitation (MR) and advanced stages of heart failure (HF). However, these patients have a high mortality despite PMVR, and predictors for outcomes are not well established. Here, we evaluated invasive hemodynamics, echocardiography parameters, and biomarkers to predict outcomes after PMVR in severe HF patients.

METHODS

Patients with reduced ejection fraction (EF) and severe and moderate-to-severe MR undergoing PMVR at our centre between September 2009 and January 2016 were analysed retrospectively. Inclusion criteria were: left ventricular EF < 45%, preoperative right heart catheterization, successful MitraClip deployment ("technical success"), and follow-up for at least 1 year after the procedure. Data from preoperative right heart catheterization, echocardiography, and biomarkers were assessed. Primary endpoint was all-cause mortality at 1 year after PMVR. We performed univariate and multivariate Cox regression analyses and generated a risk score to predict outcomes.

RESULTS

Of 174 patients with PMVR and severe HF, 79.9% had functional MR. Mean EF was 25% (17.2; 30.7) and advanced New York Heart Association functional class was prevalent (class II: 13%; class III: 70%; and class IV: 17%). The cumulative incidences of all-cause death were 6.9% and 17.8% at 30 days and 1 year, respectively. In the Cox multivariate model, high-sensitive troponin T [hsTnT; hazard ratio (HR) 1.01; confidence interval (CI) 1.01-1.02; p < 0.0001] and mixed venous O₂-saturation (HR 0.92; CI 0.89-0.96; p < 0.0001) were found to significantly and independently predict outcomes. A simple risk score including these two parameters was sufficient to discriminate between low- and high-risk patients (HR 7.22; CI 3.4-15.5; p < 0.001).

CONCLUSION

In a cohort of patients with severe HF undergoing PMVR, patients with elevated hsTnT and reduced mixed venous O₂-saturation carried the worst prognosis. A simple risk score including these two parameters may improve patient selection and outcomes after PMVR.