A Swedish Nationwide Adoption Study of the Heritability of Heart Failure

Familial clustering of unexplained heart failure - A Danish nationwide cohort study

AIMS

To determine whether a family history of unexplained heart failure (HF) in first-degree relatives (children or sibling) increases the rate of unexplained HF.

METHODS AND RESULTS

Using Danish nationwide registry data (1978-2017), we identified patients (probands) diagnosed with first unexplained HF (HF without any known comorbidities) in Denmark, and their first-degree relatives. All first-degree relatives were followed from the HF date of the proband and until an event of unexplained HF, exclusion diagnosis, death, emigration, or study end, whichever occurred first. Using the general population as a reference, we calculated adjusted standardized incidence ratios (SIR) of unexplained HF in the three groups of relatives using Poisson regression models. We identified 55,110 first-degree relatives to individuals previously diagnosed with unexplained HF. Having a family history was associated with a significantly increased unexplained HF rate of 2.59 (95%CI 2.29-2.93). The estimate was higher among siblings (SIR 6.67 [95%CI 4.69-9.48]). Noteworthy, the rate of HF increased for all first-degree relatives when the proband was diagnosed with HF in a young age (≤50 years, SIR of 7.23 [95%CI 5.40-9.68]) and having >1 proband (SIR of 5.28 [95%CI 2.75-10.14]). The highest estimate of HF was observed if the proband was ≤40 years at diagnosis (13.17 [95%CI 8.90-19.49].

CONCLUSION

A family history of unexplained HF was associated with a two-fold increased rate of unexplained HF among first-degree relatives. The relative rate was increased when the proband was diagnosed at a young age. These data suggest that screening families of unexplained HF with onset below 50 years is indicated.

Identification and correction for collider bias in a genome-wide association study of diabetes-related heart failure

Type 2 diabetes (T2D) is a major risk factor for heart failure (HF) and has elevated incidence among individuals with HF. Since genetics and HF can independently influence T2D, collider bias may occur when T2D (i.e., collider) is controlled for by design or analysis. Thus, we conducted a genome-wide association study (GWAS) of diabetes-related HF with correction for collider bias. We first performed a GWAS of HF to identify genetic instrumental variables (GIVs) for HF and to enable bidirectional Mendelian randomization (MR) analysis between T2D and HF. We identified 61 genomic loci, significantly associated with all-cause HF in 114,275 individuals with HF and over 1.5 million controls of European ancestry. Using a two-sample bidirectional MR approach with 59 and 82 GIVs for HF and T2D, respectively, we estimated that T2D increased HF risk (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.04-1.10), while HF also increased T2D risk (OR 1.60, 95% CI 1.36-1.88). Then we performed a GWAS of diabetes-related HF corrected for collider bias due to the study design of index cases. After removing the spurious association of TCF7L2 locus due to collider bias, we identified two genome-wide significant loci close to PITX2 (chromosome 4) and CDKN2B-AS1 (chromosome 9) associated with diabetes-related HF in the Million Veteran Program and replicated the associations in the UK Biobank. Our MR findings provide strong evidence that HF increases T2D risk. As a result, collider bias leads to spurious genetic associations of diabetes-related HF, which can be effectively corrected to identify true positive loci.

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.

The Genetic Factors Influencing Cardiomyopathies and Heart Failure across the Allele Frequency Spectrum

Heart failure (HF) remains a major cause of mortality and morbidity worldwide. Understanding the genetic basis of HF allows for the development of disease-modifying therapies, more appropriate risk stratification, and personalised management of patients. The advent of next-generation sequencing has enabled genome-wide association studies; moving beyond rare variants identified in a Mendelian fashion and detecting common DNA variants associated with disease. We summarise the latest GWAS and rare variant data on mixed and refined HF aetiologies, and cardiomyopathies. We describe the recent understanding of the functional impact of titin variants and highlight FHOD3 as a novel cardiomyopathy-associated gene. We describe future directions of research in this field and how genetic data can be leveraged to improve the care of patients with HF.

A polygenic risk score of atrial fibrillation improves prediction of lifetime risk for heart failure

AIMS

Heart failure (HF) has shared genetic architecture with its risk factors: atrial fibrillation (AF), body mass index (BMI), coronary heart disease (CHD), systolic blood pressure (SBP), and type 2 diabetes (T2D). We aim to assess the association and risk prediction performance of risk-factor polygenic risk scores (PRSs) for incident HF and its subtypes in bi-racial populations.

METHODS AND RESULTS

Five PRSs were constructed for AF, BMI, CHD, SBP, and T2D in White participants of the Atherosclerosis Risk in Communities (ARIC) study. The associations between PRSs and incident HF and its subtypes were assessed using Cox models, and the risk prediction performance of PRSs was assessed using C statistics. Replication was performed in the ARIC study Black and Cardiovascular Health Study (CHS) White participants. In 8624 ARIC study Whites, 1922 (31% cumulative incidence) HF cases developed over 30 years of follow-up. PRSs of AF, BMI, and CHD were associated with incident HF (P < 0.001), where PRSAF showed the strongest association [hazard ratio (HR): 1.47, 95% confidence interval (CI): 1.41-1.53]. Only the addition of PRSAF to the ARIC study HF risk equation improved C statistics for 10 year risk prediction from 0.812 to 0.829 (∆C: 0.017, 95% CI: 0.009-0.026). The PRSAF was associated with both incident HF with reduced ejection fraction (HR: 1.43, 95% CI: 1.27-1.60) and incident HF with preserved ejection fraction (HR: 1.46, 95% CI: 1.33-1.62). The associations between PRSAF and incident HF and its subtypes, as well as the improved risk prediction, were replicated in the ARIC study Blacks and the CHS Whites (P < 0.050). Protein analyses revealed that N-terminal pro-brain natriuretic peptide and other 98 proteins were associated with PRSAF.

CONCLUSIONS

The PRSAF was associated with incident HF and its subtypes and had significant incremental value over an established HF risk prediction equation.

Association between lipoprotein (a) and risk of heart failure: A systematic review and meta-analysis of Mendelian randomization studies

BACKGROUND

Rising incidence of heart failure (HF) in the Western world despite advanced clinical care necessitate exploration of further preventive tools and strategies. Lipoprotein(a) [Lp(a)], recognized as one of the major cardiovascular risk factors has also been implicated as a risk factor for HF. However, existing evidence remains inconclusive and that has led us to perform this meta-analysis.

METHODS

PubMed/Medline, EMBASE and Scopus were systematically searched for studies evaluating an association of Lp(a) with occurrence of HF from inception-till November 2023. Random effects models and I2 statistics were used for pooled odds ratio (OR) and heterogeneity assessment. We performed leave one out sensitivity analyses by sequentially removing one study at a time and recalculating the pooled effect size.

RESULT

Our search rendered in total 360 studies and after final screening this resulted in 7 Mendelian randomization (MR) design. According to the MR analysis, increasing Lp(a) level were significantly associated with increased risk of HF (OR 1.064, 95 % CI: 1.043-1.086, I2= 97.59 %, P < 0.001). In addition, Leave-one-out sensitivity analysis showed that the effect size did not change substantially by removal of any particular study in MR studies and ORs ranged from 1.051 (when excluding Levin) to a maximum of 1.111 (when excluding Wang or Jiang), hereby confirming the association.

CONCLUSION

We were able to show that by meta-analysis of MR data, increasing lipoprotein (a) levels are associated with an increased risk of HF. Whether this is due to a direct effect on heart muscle contraction or whether this is due to an increased risk of ischemic cardiac disease remains to be elucidated.

Genomic risk prediction of cardiovascular diseases among type 2 diabetes patients in the UK Biobank

Background: Polygenic risk score (PRS) has proved useful in predicting the risk of cardiovascular diseases (CVD) based on the genotypes of an individual, but most analyses have focused on disease onset in the general population. The usefulness of PRS to predict CVD risk among type 2 diabetes (T2D) patients remains unclear. Methods: We built a meta-PRSCVD upon the candidate PRSs developed from state-of-the-art PRS methods for three CVD subtypes of significant importance: coronary artery disease (CAD), ischemic stroke (IS), and heart failure (HF). To evaluate the prediction performance of the meta-PRSCVD, we restricted our analysis to 21,092 white British T2D patients in the UK Biobank, among which 4,015 had CVD events. Results: Results showed that the meta-PRSCVD was significantly associated with CVD risk with a hazard ratio per standard deviation increase of 1.28 (95% CI: 1.23-1.33). The meta-PRSCVD alone predicted the CVD incidence with an area under the receiver operating characteristic curve (AUC) of 0.57 (95% CI: 0.54-0.59). When restricted to the early-onset patients (onset age ≤ 55), the AUC was further increased to 0.61 (95% CI 0.56-0.67). Conclusion: Our results highlight the potential role of genomic screening for secondary preventions of CVD among T2D patients, especially among early-onset patients.

Genetic and Nongenetic Components of Stroke Family History: A Population Study of Adopted and Nonadopted Individuals

Background Genetic and nongenetic factors account for the association of family history with disease risk. Comparing adopted and nonadopted individuals provides an opportunity to disentangle those factors. Methods and Results We examined associations between family history of stroke and heart disease with incident stroke and myocardial infarction (MI) in 495 640 UK Biobank participants (mean age, 56.5 years; 55% women) stratified by childhood adoption status (5747 adoptees). We estimated hazard ratios (HRs) per affected family member, and for polygenic risk scores in Cox models adjusted for baseline age and sex. A total of 12 518 strokes and 23 923 MIs occurred over a 13-year follow-up. In nonadoptees, family history of stroke and heart disease was associated with increased stroke and MI risk, with the strongest association of family history of stroke for incident stroke (HR, 1.16 [95% CI, 1.12-1.19]) and family history of heart disease for incident MI (HR, 1.48 [95% CI, 1.45-1.50]). In adoptees, family history of stroke associated with incident stroke (HR, 1.41 [95% CI, 1.06-1.86]), but family history of heart disease was not associated with incident MI (P>0.5). Polygenic risk scores showed strong disease-specific associations in both groups. In nonadoptees, the stroke polygenic risk score mediated 6% risk between family history of stroke and incident stroke, and the MI polygenic risk score mediated 13% risk between family history of heart disease and incident MI. Conclusions Family history of stroke and heart disease increases risk for their respective conditions. Family history of stroke contains substantial potentially modifiable nongenetic risk, indicating a need for novel prevention strategies, whereas family history of heart disease represents predominantly genetic risk.

Cardiomyopathy in Asian Cohorts: Genetic and Epigenetic Insights

Previous studies on cardiomyopathies have been particularly valuable for clarifying pathological mechanisms in heart failure, an etiologically heterogeneous disease. In this review, we specifically focus on cardiomyopathies in Asia, where heart failure is particularly pertinent. There has been an increase in prevalence of cardiomyopathies in Asia, in sharp contrast with the decline observed in Western countries. Indeed, important disparities in cardiomyopathy incidence, clinical characteristics, and prognosis have been reported in Asian versus White cohorts. These have been accompanied by emerging descriptions of a distinct rare and common genetic basis for disease among Asian cardiomyopathy patients marked by an increased burden of variants with uncertain significance, reclassification of variants deemed pathogenic based on evidence from predominantly White cohorts, and the discovery of Asian-specific cardiomyopathy-associated loci with underappreciated pathogenicity under conventional classification criteria. Findings from epigenetic studies of heart failure, particularly DNA methylation studies, have complemented genetic findings in accounting for the phenotypic variability in cardiomyopathy. Though extremely limited, findings from Asian ancestry-focused DNA methylation studies of cardiomyopathy have shown potential to contribute to general understanding of cardiomyopathy pathophysiology by proposing disease and cause-relevant pathophysiological mechanisms. We discuss the value of multiomics study designs incorporating genetic, methylation, and transcriptomic information for future DNA methylation studies in Asian cardiomyopathy cohorts to yield Asian ancestry-specific insights that will improve risk stratification in the Asian population.

Correction for Collider Bias in the Genome-wide Association Study of Diabetes-Related Heart Failure due to Bidirectional Relationship between Heart Failure and Type 2 Diabetes

Aims

Type 2 diabetes (T2D) is a major risk factor for heart failure (HF) across demographic groups. On the other hand, metabolic impairment, including elevated T2D incidence is a hallmark of HF pathophysiology. We investigated the bidirectional relationship between T2D and HF, and identified genetic associations with diabetes-related HF after correction for potential collider bias.

Methods

We performed a genome-wide association study (GWAS) of HF to identify genetic instrumental variables (GIVs) for HF, and to enable bidirectional Mendelian Randomization (MR) analysis between T2D and HF. Since genetics and HF can independently influence T2D, collider bias may occur when T2D (i.e., collider) is controlled for by design or analysis. Thus, we conducted GWAS of diabetes-related HF with correction for collider bias.

Results

We first identified 61 genomic loci, including 24 novel loci, significantly associated with all-cause HF in 114,275 HF cases and over 1.5 million controls of European ancestry. Combined with the summary statistics of a T2D GWAS, we obtained 59 and 82 GIVs for HF and T2D, respectively. Using a two-sample bidirectional MR approach, we estimated that T2D increased HF risk (OR 1.07, 95% CI 1.04-1.10), while HF also increased T2D risk (OR 1.60, 95% CI 1.36-1.88). Then we performed a GWAS of diabetes-related HF corrected for collider bias due to prevalent HF affecting incidence of T2D. After removing the spurious association of TCF7L2 locus due to collider bias, we identified two genome-wide significant loci close to PITX2 (chromosome 4) and CDKN2B-AS1 (chromosome 9) associated with diabetes-related HF in the Million Veteran Program, and replicated the associations in the UK Biobank study.

Conclusion

We identified novel HF-associated loci to enable bidirectional MR study of T2D and HF. Our MR findings support T2D as a HF risk factor and provide strong evidence that HF increases T2D risk. As a result, collider bias leads to spurious genetic associations of diabetes-related HF, which can be effectively corrected to identify true positive loci. Evaluation of collider bias should be a critical component when conducting GWAS of complex disease phenotypes such as diabetes-related cardiovascular complications.

Improving Genetic Association Studies with a Novel Methodology that Unveils the Hidden Complexity of All-Cause Heart Failure

Motivation

Genome-Wide Association Studies (GWAS) commonly assume phenotypic and genetic homogeneity that is not present in complex conditions. We designed Transformative Regression Analysis of Combined Effects (TRACE), a GWAS methodology that better accounts for clinical phenotype heterogeneity and identifies gene-by-environment (GxE) interactions. We demonstrated with UK Biobank (UKB) data that TRACE increased the variance explained in All-Cause Heart Failure (AHF) via the discovery of novel single nucleotide polymorphism (SNP) and SNP-by-environment (i.e. GxE) interaction associations. First, we transformed 312 AHF-related ICD10 codes (including AHF) into continuous low-dimensional features (i.e., latent phenotypes) for a more nuanced disease representation. Then, we ran a standard GWAS on our latent phenotypes to discover main effects and identified GxE interactions with target encoding. Genes near associated SNPs subsequently underwent enrichment analysis to explore potential functional mechanisms underlying associations. Latent phenotypes were regressed against their SNP hits and the estimated latent phenotype values were used to measure the amount of AHF variance explained.

Results

Our method identified over 100 main GWAS effects that were consistent with prior studies and hundreds of novel gene-by-smoking interactions, which collectively accounted for approximately 10% of AHF variance. This represents an improvement over traditional GWAS whose results account for a negligible proportion of AHF variance. Enrichment analyses suggested that hundreds of miRNAs mediated the SNP effect on various AHF-related biological pathways. The TRACE framework can be applied to decode the genetics of other complex diseases.

Availability

All code is available at https://github.com/EpistasisLab/latent_phenotype_project.

Clinical characteristics of heart failure with reduced ejection fraction patients with rare pathogenic variants in dilated cardiomyopathy-associated genes: A subgroup analysis of the PARADIGM-HF trial

AIMS

To evaluate the prevalence of pathogenic variants in genes associated with dilated cardiomyopathy (DCM) in a clinical trial population with heart failure and reduced ejection fraction (HFrEF) and describe the baseline characteristics by variant carrier status.

METHODS AND RESULTS

This was a post hoc analysis of the Phase 3 PARADIGM-HF trial. Forty-four genes, divided into three tiers, based on definitive, moderate or limited evidence of association with DCM, were assessed for rare predicted loss-of-function (pLoF) variants, which were prioritized using ClinVar annotations, measures of gene transcriptional output and evolutionary constraint, and pLoF confidence predictions. Prevalence was reported for pLoF variant carriers based on DCM-associated gene tiers. Clinical features were compared between carriers and non-carriers. Of the 1412 HFrEF participants with whole-exome sequence data, 68 (4.8%) had at least one pLoF variant in the 8 tier-1 genes (definitive/strong association with DCM), with Titin being most commonly affected. The prevalence increased to 7.5% when considering all 44 genes. Among patients with idiopathic aetiology, 10.0% (23/229) had tier-1 variants only and 12.6% (29/229) had tier-1, -2 or -3 variants. Compared to non-carriers, tier-1 carriers were younger (4 years; adjusted p-value [padj ] = 4 × 10-3 ), leaner (27.8 kg/m2 vs. 29.4 kg/m2 ; padj  = 3.2 × 10-3 ), had lower ejection fraction (27.3% vs. 29.8%; padj  = 5.8 × 10-3 ), and less likely to have ischaemic aetiology (37.3% vs. 67.4%; padj  = 4 × 10-4 ).

CONCLUSION

Deleterious pLoF variants in genes with definitive/strong association with DCM were identified in ∼5% of HFrEF patients from a PARADIGM-HF trial subset, who were younger, had lower ejection fraction and were less likely to have had an ischaemic aetiology.

Lipoprotein(a), family history of cardiovascular disease, and incidence of heart failure

Lipoprotein(a) (Lp(a)) is a largely genetically determined biomarker for cardiovascular disease (CVD), while its potential interplay with family history (FHx) of CVD, a measure of both genetic and environmental exposures, remains unclear. We examined the associations of Lp(a) in terms of circulating concentration or polygenetic risk score (PRS), and FHx of CVD with risk of incident heart failure (HF). Included were 299,158 adults from the UK Biobank without known HF and CVD at baseline. Hazards ratios (HRs) and 95% Cls were estimated by Cox regression models adjusted for traditional risk factors defined by the Atherosclerosis Risk in Communities study HF risk score. During the 11.8-year follow-up, 5,502 incidents of HF occurred. Higher levels of circulating Lp(a), Lp(a) PRS, and positive FHx of CVD were associated with higher risks of HF. Compared with individuals who had lower circulating Lp(a) and no FHx, HRs (95% CIs) of HF were 1.36 (1.25, 1.49), 1.31 (1.19, 1.43), and 1.42 (1.22, 1.67) for those with higher Lp(a) and a positive history of CVD for all family members, parents, and siblings, respectively; similar results were observed by using Lp(a) PRS. The risk estimates for HF associated with elevated Lp(a) and positive FHx were attenuated after excluding those with incident myocardial infarction (MI) during follow-up. Lp(a) and FHx of CVD were independent risk factors for incident HF, and the highest risk of HF was observed among individuals with both risk factors. The association may be partly mediated by myocardial infarction.

Genetic and non-genetic components of family history of stroke and heart disease: a population-based study among adopted and non-adopted individuals

Background

It is increasingly clear that genetic and non-genetic factors account for the association of family history with disease risk in offspring. We sought to distinguish the genetic and non-genetic contributions of family history of stroke and heart disease on incident events by examining adopted and non-adopted individuals.

Methods

We examined associations between family history of stroke and heart disease with incident stroke and myocardial infarction (MI) in 495,640 participants of the UK Biobank (mean age 56.5 years, 55% female) stratified by early childhood adoption status into adoptees (n=5,747) and non-adoptees (n=489,893). We estimated hazard ratios (HRs) per affected nuclear family member, and for polygenic risk scores (PRS) for stroke and MI in Cox models adjusted for baseline age and sex.

Results

12,518 strokes and 23,923 MIs occurred over a 13-year follow-up. In non-adoptees, family history of stroke and heart disease were associated with increased stroke and MI risk, with the strongest association of family history of stroke for incident stroke (HR 1.16 [1.12, 1.19]) and family history of heart disease for incident MI (HR 1.48 [1.45, 1.50]). In adoptees, family history of stroke associated with incident stroke (HR 1.41 [1.06, 1.86]), but family history of heart disease did not associate with incident MI (p>0.5). PRS showed strong disease-specific associations in adoptees and non-adoptees. In non-adoptees, the stroke PRS mediated 6% risk between family history of stroke and incident stroke, and the MI PRS mediated 13% risk between family history of heart disease and MI.

Conclusions

Family history of stroke and heart disease increase risk for their respective conditions. Family history of stroke contains a substantial proportion of potentially modifiable non-genetic risk, indicating a need for further research to elucidate these elements for novel prevention strategies, whereas family history of heart disease represents predominantly genetic risk.

The potential of integrating human and mouse discovery platforms to advance our understanding of cardiometabolic diseases

Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery.

The causal relationship between allergic diseases and heart failure: Evidence from Mendelian randomization study

Background

Emerging evidence shows allergic diseases, such as atopic dermatitis and asthma, are risk factors of heart failure. However, the causal relationship between allergic diseases and heart failure is not clear.

Methods

We performed a two-sample Mendelian randomization analysis between allergic diseases and heart failure using summary statistics of genome-wide association studies from large GWAS consortia, with total sample size of 1.2 million. Independent instrumental variables for asthma and atopic dermatitis (P<1×10−5) were used as the exposure. We applied five models for the Mendelian randomization analysis. Finally, we performed the sensitivity analyses to assess the robustness of the results.

Results

We have identified 55 independent single nucleotide polymorphisms (SNPs) for asthma 54 independent SNPs for atopic dermatitis as our instrumental variables. The inverse variance-weighted (IVW) analysis showed asthma was significantly associated with increased risk of heart failure (ORIVW = 1.04, 95% CI, 1.01–1.07, P = 0.03). The Mendelian randomization analysis using the other four models also showed consistent results with the IVW analysis. Similarly, atopic dermatitis was also significantly associated with an increased risk of heart failure (ORIVW = 1.03, 95% CI, 1.01–1.06, P = 0.01), consistent with the other four models. The sensitivity analysis showed no evidence of horizontal pleiotropy or results were driven by single SNPs.

Conclusion

Our study identified asthma and atopic dermatitis as a causal risk factor for heart failure and suggest inflammatory pathogenesis as a key factor contributing to the underlying mechanism. These findings emphasize the importance of asthma and allergy control in the prevention and management of heart failure.

Associations Between Vitamin D Levels and Risk of Heart Failure: A Bidirectional Mendelian Randomization Study

Background

Although studies suggest that concentrations of serum 25-hydroxyvitamin D (25(OH)D) are lower in individuals with Heart Failure (HF), the beneficial effects of vitamin D supplementation are controversial. Therefore, in this study, we aimed to determine whether there is a causal relationship between serum Vitamin D (VD) levels and HF.

Methods

We obtained genetic instruments from the largest available genome-wide association study (GWAS) of European descent for 25(OH)D (443, 734 individuals) to investigate the association with HF (47,309 cases, 930,014 controls), and vice versa. Two-sample bidirectional Mendelian Randomization (MR) analysis was performed to infer the causality. In addition to the primary analysis using inverse variance-weighted (IVW) MR, we applied five additional methods to control for pleiotropy [MR-Egger, weighted median, Maximum-likelihood, MR-robust adjusted profile score (MR-RAPS) and MR-pleiotropy residual sum and outlier (MR-PRESSO)] and compared their respective MR estimates. We also performed a sensitivity analysis to ensure that our results were robust.

Results

Mendelian randomized analysis showed that increased serum 25(OH)D was associated with a lower risk of HF in the IVW method (odds ratio [OR] = 0. 81;95%CI, 0.70–0.94, P = 0.006). In the reverse MR analyses, the genetic predisposition to HF was negatively correlated with serum 25(OH)D level (OR = 0. 89;95%CI, (0.82–0.97), P = 0.009).

Conclusion

Our study revealed the possible causal role of 25(OH)D on decreasing the risk for HF. Meanwhile, reverse MR analysis suggested that HF may be associated with lower vitamin D levels, it could be the potential implications for dietary recommendations.

Multivariable prognostic model for heart failure in Chinese Han population-based setting

Aims

The prognosis of heart failure (HF) depends on genetic predisposition, and recent studies have shown that impaired autophagy is involved in HF. This study was aimed to construct a prognostic model combining polygenetic background based on the autophagy pathway and other traditional risk factors (TRF) of HF prognosis.

Methods and results

Via re‐analysing the transcriptomic data of 50 failing and 14 non‐failing donors, differentially expressed autophagy‐related genes (ARGs) were chosen for further comparison and analysis with whole exome sequencing and follow‐up data of 1000 HF patients. By searching from reported articles, prognosis‐related polymorphisms were identified. ARGs and prognosis‐related polymorphisms were used to develop genetic risk score (GRS) and genetic risk factor (GRF), respectively. We compared the predictive power of five models [Model 1, GRS; Model 2, composite of TRF and N‐terminal B‐type natriuretic peptide (NT‐proBNP); Model 3, composite of TRF, NT‐proBNP, and GRS; Model 4, composite of TRF, NT‐proBNP, and GRF; and Model 5, composite of TRF, NT‐proBNP, GRF, and GRS] by applying receiver operating characteristic curves. Twenty‐four prognosis‐related polymorphisms were used to construct GRF and 11 variants among 48 differentially expressed ARGs associated with clinical outcomes of HF patients were applied for GRS. GRS was strongly associated with cardiac mortality of HF patients, independent of TRF and GRF (95% confidence interval 1.273–1.739, P = 5.78 × 10⁻⁷). Comparing with patients with lowest GRS tertile, those with highest tertile had higher risks of developing worse clinical outcomes (hazard ratio = 1.866; 95% confidence interval 1.352–2.575, P = 1.47 × 10⁻⁴). The discrimination power of the model including GRS, TRF, GRF, and NT‐proBNP is most considerable (area under curve = 0.777), especially in men, patients over 60, patients with hypertension, patients without diabetes or hyperlipidaemia.

Conclusions

The model combining autophagy‐related GRS, TRF, GRF, and NT‐proBNP performs well in distinguishing between worse‐prognosis and better‐prognosis HF patients, leading a promising strategy for HF treatment and HF prevention.

Disparities in prevalence of heart failure according to age, multimorbidity level and socioeconomic status in southern Sweden: a cross-sectional study

OBJECTIVE

The aim of this study was to compare the prevalence of heart failure (HF) in relation to age, multimorbidity and socioeconomic status of primary healthcare centres in southern Sweden.

DESIGN

A cross-sectional study.

SETTING

The data were collected concerning diagnoses at each consultation in all primary healthcare centres and secondary healthcare in the southernmost county of Sweden at the end of 2015.

PARTICIPANTS

The individuals living in southern Sweden in 2015 aged 20 years and older. The study population of 981 383 inhabitants was divided into different categories including HF, multimorbidity, different levels of multimorbidity and into 10 CNI (Care Need Index) groups depending on the socioeconomic status of their listed primary healthcare centre.

OUTCOMES

Prevalence of HF was presented according to age, multimorbidity level and socioeconomic status. Logistic regression was used to further analyse the associations between HF, age, multimorbidity level and socioeconomic status in more complex models.

RESULTS

The total prevalence of HF in the study population was 2.06%. The prevalence of HF increased with advancing age and the multimorbidity level. 99.07% of the patients with HF fulfilled the criteria for multimorbidity. The total prevalence of HF among the multimorbid patients was only 5.30%. HF had a strong correlation with the socioeconomic status of the primary healthcare centres with the most significant disparity between 40 and 80 years of age: the prevalence of HF in primary healthcare centres with the most deprived CNI percentile was approximately twice as high as in the most affluent CNI percentile.

CONCLUSION

The patients with HF were strongly associated with having multimorbidity. HF patients was a small group of the multimorbid population associated with socioeconomic deprivation that challenges efficient preventive strategies and health policies.

Derivation and Validation of Genome-Wide Polygenic Score for Ischemic Heart Failure

Background Despite advances in cardiovascular disease and risk factor management, mortality from ischemic heart failure (HF) in patients with coronary artery disease (CAD) remains high. Given the partial role of genetics in HF and lack of reliable risk stratification tools, we developed and validated a polygenic risk score for HF in patients with CAD, which we term HF-PRS. Methods and Results Using summary statistics from a recent genome-wide association study for HF, we developed candidate PRSs in the Mount Sinai BioMe CAD patient cohort (N=6274) by using the pruning and thresholding method and LDPred. We validated the best score in the Penn Medicine BioBank (N=7250) and performed a subgroup analysis in a high-risk cohort who had undergone coronary catheterization. We observed a significant association between HF-PRS score and ischemic HF even after adjusting for evidence of obstructive CAD in patients of European ancestry in both BioMe (odds ratio [OR], 1.14 per SD; 95% CI, 1.05-1.24; P=0.003) and Penn Medicine BioBank (OR, 1.07 per SD; 95% CI, 1.01-1.13; P=0.016). In European patients with CAD in Penn Medicine BioBank who had undergone coronary catheterization, individuals in the top 10th percentile of PRS had a 2-fold increased odds of ischemic HF (OR, 2.0; 95% CI, 1.1-3.7; P=0.02) compared with the bottom 10th percentile. Conclusions A PRS for HF enables risk stratification in patients with CAD. Future prospective studies aimed at demonstrating clinical utility are warranted for adoption in the patient setting.

Towards precision medicine in heart failure

The number of therapies for heart failure (HF) with reduced ejection fraction has nearly doubled in the past decade. In addition, new therapies for HF caused by hypertrophic and infiltrative disease are emerging rapidly. Indeed, we are on the verge of a new era in HF in which insights into the biology of myocardial disease can be matched to an understanding of the genetic predisposition in an individual patient to inform precision approaches to therapy. In this Review, we summarize the biology of HF, emphasizing the causal relationships between genetic contributors and traditional structure-based remodelling outcomes, and highlight the mechanisms of action of traditional and novel therapeutics. We discuss the latest advances in our understanding of both the Mendelian genetics of cardiomyopathy and the complex genetics of the clinical syndrome presenting as HF. In the phenotypic domain, we discuss applications of machine learning for the subcategorization of HF in ways that might inform rational prescribing of medications. We aim to bridge the gap between the biology of the failing heart, its diverse clinical presentations and the range of medications that we can now use to treat it. We present a roadmap for the future of precision medicine in HF.

Using a Two-Sample Mendelian Randomization Method in Assessing the Causal Relationships Between Human Blood Metabolites and Heart Failure

Background: Heart failure (HF) is the main cause of morbidity and mortality worldwide, and metabolic dysfunction is an important factor related to HF pathogenesis and development. However, the causal effect of blood metabolites on HF remains unclear.

Objectives: Our chief aim is to investigate the causal relationships between human blood metabolites and HF risk.

Methods: We used an unbiased two-sample Mendelian randomization (MR) approach to assess the causal relationships between 486 human blood metabolites and HF risk. Exposure information was obtained from Sample 1, which is the largest metabolome-based genome-wide association study (mGWAS) data containing 7,824 Europeans. Outcome information was obtained from Sample 2, which is based on the results of a large-scale GWAS meta-analysis of HF and contains 47,309 cases and 930,014 controls of Europeans. The inverse variance weighted (IVW) model was used as the primary two-sample MR analysis method and followed the sensitivity analyses, including heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis.

Results: We observed that 11 known metabolites were potentially related to the risk of HF after using the IVW method (P < 0.05). After adding another four MR models and performing sensitivity analyses, we found a 1-SD increase in the xenobiotics 4-vinylphenol sulfate was associated with ~22% higher risk of HF (OR [95%CI], 1.22 [1.07–1.38]).

Conclusions: We revealed that the 4-vinylphenol sulfate may nominally increase the risk of HF by 22% after using a two-sample MR approach. Our findings may provide novel insights into the pathogenesis underlying HF and novel strategies for HF prevention.

Exploring the Pleiotropic Genes and Therapeutic Targets Associated with Heart Failure and Chronic Kidney Disease by Integrating metaCCA and SGLT2 Inhibitors' Target Prediction

Background

Previous studies have shown that heart failure (HF) and chronic kidney disease (CKD) have common genetic mechanisms, overlapping pathophysiological pathways, and therapeutic drug—sodium-glucose cotransporter 2 (SGLT2) inhibitors.

Methods

The genetic pleiotropy metaCCA method was applied on summary statistics data from two independent meta-analyses of GWAS comprising more than 1 million people to identify shared variants and pleiotropic effects between HF and CKD. Targets of SGLT2 inhibitors were predicted by SwissTargetPrediction and DrugBank databases. To refine all genes, we performed using versatile gene-based association study 2 (VEGAS2) and transcriptome-wide association studies (TWAS) for HF and CKD, respectively. Gene enrichment and KEGG pathway analyses were used to explore the potential functional significance of the identified genes and targets.

Results

After metaCCA analysis, 4,624 SNPs and 1,745 genes were identified to be potentially pleiotropic in the univariate and multivariate SNP-multivariate phenotype analyses, respectively. 21 common genes were detected in both metaCCA and SGLT2 inhibitors' target prediction. In addition, 169 putative pleiotropic genes were identified, which met the significance threshold both in metaCCA analysis and in the VEGAS2 or TWAS analysis for at least one disease.

Conclusion

We identified novel variants associated with HF and CKD using effectively incorporating information from different GWAS datasets. Our analysis may provide new insights into HF and CKD therapeutic approaches based on the pleiotropic genes, common targets, and mechanisms by integrating the metaCCA method, TWAS and VEGAS2 analyses, and target prediction of SGLT2 inhibitors.

Artificial Intelligence-Assisted Identification of Genetic Factors Predisposing High-Risk Individuals to Asymptomatic Heart Failure

Heart failure (HF) is a global pandemic public health burden affecting one in five of the general population in their lifetime. For high-risk individuals, early detection and prediction of HF progression reduces hospitalizations, reduces mortality, improves the individual’s quality of life, and reduces associated medical costs. In using an artificial intelligence (AI)-assisted genome-wide association study of a single nucleotide polymorphism (SNP) database from 117 asymptomatic high-risk individuals, we identified a SNP signature composed of 13 SNPs. These were annotated and mapped into six protein-coding genes (GAD2, APP, RASGEF1C, MACROD2, DMD, and DOCK1), a pseudogene (PGAM1P5), and various non-coding RNA genes (LINC01968, LINC00687, LOC105372209, LOC101928047, LOC105372208, and LOC105371356). The SNP signature was found to have a good performance when predicting HF progression, namely with an accuracy rate of 0.857 and an area under the curve of 0.912. Intriguingly, analysis of the protein connectivity map revealed that DMD, RASGEF1C, MACROD2, DOCK1, and PGAM1P5 appear to form a protein interaction network in the heart. This suggests that, together, they may contribute to the pathogenesis of HF. Our findings demonstrate that a combination of AI-assisted identifications of SNP signatures and clinical parameters are able to effectively identify asymptomatic high-risk subjects that are predisposed to HF.

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

Aims

The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure.

Methods and results

The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome‐wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow‐up following heart failure diagnosis ranged from 2 to 116 months. Forty‐nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34–90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low‐frequency variants (allele frequency 0.01–0.05) at P < 5 × 10⁻⁸ under an additive genetic model.

Conclusions

HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.

Technological readiness and implementation of genomic-driven precision medicine for complex diseases

The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data.

Endotyping in Heart Failure - Identifying Mechanistically Meaningful Subtypes of Disease

Endotyping is an emerging concept in which diseases are classified into distinct subtypes based on underlying molecular mechanisms. Heart failure (HF) is a complex clinical syndrome that encompasses multiple endotypes with differential risks of adverse events, and varying responses to treatment. Identifying these distinct endotypes requires molecular-level investigation involving multi-"omics" approaches, including genomics, transcriptomics, proteomics, and metabolomics. The derivation of these HF endotypes has important implications in promoting individualized treatment and facilitating more targeted selection of patients for clinical trials, as well as in potentially revealing new pathways of disease that may serve as therapeutic targets. One challenge in the integrated analysis of high-throughput omics and detailed clinical data is that it requires the ability to handle "big data", a task for which machine learning is well suited. In particular, unsupervised machine learning has the ability to uncover novel endotypes of disease in an unbiased approach. In this review, we will discuss recent efforts to identify HF endotypes and cover approaches involving proteomics, transcriptomics, and genomics, with a focus on machine-learning methods.

Functional dynamic genetic effects on gene regulation are specific to particular cell types and environmental conditions

Genetic effects on gene expression and splicing can be modulated by cellular and environmental factors; yet interactions between genotypes, cell type, and treatment have not been comprehensively studied together. We used an induced pluripotent stem cell system to study multiple cell types derived from the same individuals and exposed them to a large panel of treatments. Cellular responses involved different genes and pathways for gene expression and splicing and were highly variable across contexts. For thousands of genes, we identified variable allelic expression across contexts and characterized different types of gene-environment interactions, many of which are associated with complex traits. Promoter functional and evolutionary features distinguished genes with elevated allelic imbalance mean and variance. On average, half of the genes with dynamic regulatory interactions were missed by large eQTL mapping studies, indicating the importance of exploring multiple treatments to reveal previously unrecognized regulatory loci that may be important for disease.

Shared genetic etiology and causality between body fat percentage and cardiovascular diseases: a large-scale genome-wide cross-trait analysis

BACKGROUND

Accumulating evidences have suggested that high body fat percentage (BF%) often occurs in parallel with cardiovascular diseases (CVDs), implying a common etiology between them. However, the shared genetic etiology underlying BF% and CVDs remains unclear.

METHODS

Using large-scale genome-wide association study (GWAS) data, we investigated shared genetics between BF% (N = 100,716) and 10 CVD-related traits (n = 6968-977,323) with linkage disequilibrium score regression, multi-trait analysis of GWAS, and transcriptome-wide association analysis, and evaluated causal associations using Mendelian randomization.

RESULTS

We found strong positive genetic correlations between BF% and heart failure (HF) (Rg = 0.47, P = 1.27 × 10^- 22) and coronary artery disease (CAD) (Rg = 0.22, P = 3.26 × 10^- 07). We identified 5 loci and 32 gene-tissue pairs shared between BF% and HF, as well as 16 loci and 28 gene-tissue pairs shared between BF% and CAD. The loci were enriched in blood vessels and brain tissues, while the gene-tissue pairs were enriched in the nervous, cardiovascular, and exo-/endocrine system. In addition, we observed that BF% was causally related with a higher risk of HF (odds ratio 1.63 per 1-SD increase in BF%, P = 4.16 × 10-04) using a MR approach.

CONCLUSIONS

Our findings suggest that BF% and CVDs have shared genetic etiology and targeted reduction of BF% may improve cardiovascular outcomes. This work advances our understanding of the genetic basis underlying co-morbid obesity and CVDs and opens up a new way for early prevention of CVDs.

Assessing the Role of Rare Genetic Variation in Patients With Heart Failure

Importance

Sequencing studies have identified causal genetic variants for distinct subtypes of heart failure (HF) such as hypertrophic or dilated cardiomyopathy. However, the role of rare, high-impact variants in HF, for which ischemic heart disease is the leading cause, has not been systematically investigated.

Objective

To assess the contribution of rare variants to all-cause HF with and without reduced left ventricular ejection fraction.

Design, Setting, and Participants

This was a retrospective analysis of clinical trials and a prospective epidemiological resource (UK Biobank). Whole-exome sequencing of patients with HF was conducted from the Candesartan in Heart Failure-Assessment of Reduction in Mortality and Morbidity (CHARM) and Controlled Rosuvastatin Multinational Trial in Heart Failure (CORONA) clinical trials. Data were collected from March 1999 to May 2003 for the CHARM studies and September 2003 to July 2007 for the CORONA study. Using a gene-based collapsing approach, the proportion of patients with HF and controls carrying rare and presumed deleterious variants was compared. The burden of pathogenic variants in known cardiomyopathy genes was also investigated to assess the diagnostic yield. Exome sequencing data were generated between January 2018 and October 2018, and analysis began October 2018 and ended April 2020.

Main Outcomes and Measures

Odds ratios and P values for genes enriched for rare and presumed deleterious variants in either patients with HF or controls and diagnostic yield of pathogenic variants in known cardiomyopathy genes.

Results

This study included 5942 patients with HF and 13 156 controls. The mean (SD) age was 68.9 (9.9) years and 4213 (70.9%) were male. A significant enrichment of protein-truncating variants in the TTN gene (P = 3.35 × 10-13; odds ratio, 2.54; 95% CI, 1.96-3.31) that was further increased after restriction to variants in exons constitutively expressed in the heart (odds ratio, 4.52; 95% CI, 3.10-6.68). Validation using UK Biobank data showed a similar enrichment (odds ratio, 4.97; 95% CI, 3.94-6.19 after restriction). In the clinical trials, 201 of 5916 patients with HF (3.4%) had a pathogenic or likely pathogenic cardiomyopathy variant implicating 21 different genes. Notably, 121 of 201 individuals (60.2%) had ischemic heart disease as the clinically identified etiology for the HF. Individuals with HF and preserved ejection fraction had only a slightly lower yield than individuals with midrange or reduced ejection fraction (20 of 767 [2.6%] vs 15 of 392 [3.8%] vs 166 of 4757 [3.5%]).

Conclusions and Relevance

An increased burden of diagnostic mendelian cardiomyopathy variants in a broad group of patients with HF of mostly ischemic etiology compared with controls was observed. This work provides further evidence that mendelian genetic conditions may represent an important subset of complex late-onset diseases such as HF, irrespective of the clinical presentation.

Prevalence of heart failure and left ventricular dysfunction in China: the China Hypertension Survey, 2012-2015

BACKGROUND

Heart failure (HF) is a major health burden worldwide. However, there is no nationwide epidemiological data on HF in China after 2000. The aims of this study are (i) to determine the prevalence of left ventricular (LV) dysfunction and HF (with reduced, mid-range, and preserved ejection fraction) in a nationally representative Chinese population, and (ii) to investigate the treatment and control of hypertension in HF patients.

METHODS AND RESULTS

Data from the China Hypertension Survey (CHS) and 22 158 participants were eligible for analysis in this study. For each participant, a self-reported history of HF and any other cardiovascular diseases was acquired. Two-dimensional and Doppler echocardiography was used to assess LV dysfunction. Overall, 1.3% (estimated 13.7 million) of the Chinese adult population aged ≥35 years had HF, 1.4% of participants had LV systolic dysfunction (ejection fraction <50%), and 2.7% were graded as having 'moderate' or 'severe' LV diastolic dysfunction. The weighted prevalence of HF was similar between urban and rural residents (1.6% vs. 1.1%, P = 0.266), and between men and women (1.4% vs. 1.2%, P = 0.632). In addition, among HF patients with hypertension, 57.7% received antihypertensive medication, and 14.5% had their blood pressure controlled <140/90 mmHg.

CONCLUSIONS

In summary, there was an increase in the prevalence of HF, and LV dysfunction was very common in China. However, treatment and control of hypertension in participants with HF were low.

CLINICAL TRIAL REGISTRATION NUMBER

ChiCTR-ECS-14004641.

Sibling history is associated with heart failure after a first myocardial infarction

Objective

Morbidity and mortality due to heart failure (HF) as a complication of myocardial infarction (MI) is high, and remains among the leading causes of death and hospitalisation. This study investigated the association between family history of MI with or without HF, and the risk of developing HF after first MI.

Methods

Through nationwide registries, we identified all individuals aged 18-50 years hospitalised with first MI from 1997 to 2016 in Denmark. We identified 13 810 patients with MI, and the cohort was followed until HF diagnosis, second MI, 3 years after index MI, emigration, death or the end of 2016, whichever occurred first. HRs were estimated by Cox hazard regression models adjusted for sex, age, calendar year and comorbidities (reference: patients with no family history of MI).

Results

After adjustment, we observed an increased risk of MI-induced HF for those having a sibling with MI with HF (HR 2.05, 95% CI 1.02 to 4.12). Those having a sibling with MI without HF also had a significant, but lower increased risk of HF (HR 1.39, 95% CI 1.05 to 1.84). Parental history of MI with or without HF was not associated with HF.

Conclusion

In this nationwide cohort, sibling history of MI with or without HF was associated with increased risk of HF after first MI, while a parental family history was not, suggesting that shared environmental factors may predominate in the determination of risk for developing HF.

[Heritability of obesity in children aged 30-36 months and an analysis of single nucleotide polymorphisms at four loci in Xi'an, China]

OBJECTIVE

To study the heritability of obesity in children aged 30-36 months in Xi'an, China, as well as the role of four single nucleotide polymorphisms (SNPs) associated with body mass index in the susceptibility to obesity in children.

METHODS

Random sampling was performed to select 1 637 children, aged 30-36 months, from four communities of Xi'an from March 2017 to December 2018. Physical assessment was performed for these children, and a questionnaire survey was conducted for parents. Then the Falconer regression method was used to calculate the heritability of childhood obesity. Venous blood samples were collected from 297 children who underwent biochemical examinations, among whom there were 140 children with obesity/overweight (obesity/overweight group) and 157 with normal body weight (normal body weight group). The MassARRAY RS1000 typing technique was used to detect CDKAL1 gene rs2206734, KLF9 gene rs11142387, PCSK1 gene rs261967, and GP2 gene rs12597579. The distribution of alleles and genotypes was compared between the obesity/overweight and normal body weight groups. An unconditional logistic regression model was used to investigate the benefits of dominant and recessive genetic models.

RESULTS

For the 1 637 children, the heritability of obesity from the parents was 83%±8%, and the heritability from mother was slightly higher than that from father (86%±11% vs 78%±12%). There were significant differences in the distribution of rs2206734 alleles and genotypes and rs261967 genotypes between the obesity/overweight and normal body weight groups (P<0.0125). The children carrying T allele at rs2206734 had a significantly higher risk of obesity than those carrying CC (OR=0.24, P<0.0125), and the children carrying GG at rs261967 had a significantly higher risk of obesity than those carrying A allele (OR=4.11, P<0.0125).

CONCLUSIONS

Genetic factors play an important role in the pathogenesis of obesity in children, and the SNPs of CDKAL1 rs2206734 and PCSK1 rs261967 are associated with the susceptibility to obesity in children aged 30-36 months in Xi'an.

[Heritability of obesity in children aged 30-36 months and an analysis of single nucleotide polymorphisms at four loci in Xi'an, China]

OBJECTIVE

To study the heritability of obesity in children aged 30-36 months in Xi'an, China, as well as the role of four single nucleotide polymorphisms (SNPs) associated with body mass index in the susceptibility to obesity in children.

METHODS

Random sampling was performed to select 1 637 children, aged 30-36 months, from four communities of Xi'an from March 2017 to December 2018. Physical assessment was performed for these children, and a questionnaire survey was conducted for parents. Then the Falconer regression method was used to calculate the heritability of childhood obesity. Venous blood samples were collected from 297 children who underwent biochemical examinations, among whom there were 140 children with obesity/overweight (obesity/overweight group) and 157 with normal body weight (normal body weight group). The MassARRAY RS1000 typing technique was used to detect CDKAL1 gene rs2206734, KLF9 gene rs11142387, PCSK1 gene rs261967, and GP2 gene rs12597579. The distribution of alleles and genotypes was compared between the obesity/overweight and normal body weight groups. An unconditional logistic regression model was used to investigate the benefits of dominant and recessive genetic models.

RESULTS

For the 1 637 children, the heritability of obesity from the parents was 83%±8%, and the heritability from mother was slightly higher than that from father (86%±11% vs 78%±12%). There were significant differences in the distribution of rs2206734 alleles and genotypes and rs261967 genotypes between the obesity/overweight and normal body weight groups (P<0.0125). The children carrying T allele at rs2206734 had a significantly higher risk of obesity than those carrying CC (OR=0.24, P<0.0125), and the children carrying GG at rs261967 had a significantly higher risk of obesity than those carrying A allele (OR=4.11, P<0.0125).

CONCLUSIONS

Genetic factors play an important role in the pathogenesis of obesity in children, and the SNPs of CDKAL1 rs2206734 and PCSK1 rs261967 are associated with the susceptibility to obesity in children aged 30-36 months in Xi'an.

Genome-wide association and multi-omic analyses reveal ACTN2 as a gene linked to heart failure

Heart failure is a major public health problem affecting over 23 million people worldwide. In this study, we present the results of a large scale meta-analysis of heart failure GWAS and replication in a comparable sized cohort to identify one known and two novel loci associated with heart failure. Heart failure sub-phenotyping shows that a new locus in chromosome 1 is associated with left ventricular adverse remodeling and clinical heart failure, in response to different initial cardiac muscle insults. Functional characterization and fine-mapping of that locus reveal a putative causal variant in a cardiac muscle specific regulatory region activated during cardiomyocyte differentiation that binds to the ACTN2 gene, a crucial structural protein inside the cardiac sarcolemma (Hi-C interaction p-value = 0.00002). Genome-editing in human embryonic stem cell-derived cardiomyocytes confirms the influence of the identified regulatory region in the expression of ACTN2. Our findings extend our understanding of biological mechanisms underlying heart failure.

Heart failure has a heterogeneous etiology and the genetic underpinnings are not well understood. Here, Arvanitis et al. perform GWAS meta-analysis including 10,976 heart failure cases and 437,573 controls, identify new loci near ABO and ACTN2 and show that deletion of a ACTN2 enhancer leads to reduced ACTN2 expression in differentiating cardiomyocytes.

Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.

Integrated Multiomics Approach to Identify Genetic Underpinnings of Heart Failure and Its Echocardiographic Precursors

Background:

Heart failure (HF) may arise from alterations in metabolic, structural, and signaling pathways, but its genetic architecture is incompletely understood. To elucidate potential genetic contributors to cardiac remodeling and HF, we integrated genome-wide single-nucleotide polymorphisms, gene expression, and DNA methylation using a transomics analytical approach.

Methods:

We used robust rank aggregation (where the position of a certain gene in a rank order list [based on statistical significance level] is tested against a randomly shuffled rank order list) to derive an integrative transomic score for each annotated gene associated with a HF trait.

Results:

We evaluated ≤8372 FHS (Framingham Heart Study) participants (54% women; mean age, 55±17 years). Of these, 62 (0.7%) and 35 (0.4%) had prevalent HF with reduced ejection fraction and HF with preserved left ventricular ejection fraction, respectively. During a mean follow-up of 8.5 years (minimum–maximum, 0.005–18.6 years), 223 (2.7%) and 234 (2.8%) individuals developed incident HF with reduced ejection fraction and HF with reduced ejection fraction, respectively. Top genes included MMP20 and MTSS1 (promotes actin assembly at intercellular junctions) for left ventricular systolic function; ITGA9 (receptor for VCAM1 [vascular cell protein 1]) and C5 for left ventricular remodeling; NUP210 (expressed during myogenic differentiation) and ANK1 (cytoskeletal protein) for diastolic function; TSPAN16 and RAB11FIP3 (involved in regulation of actin cytoskeleton) for prevalent HF with reduced ejection fraction; ANKRD13D and TRIM69 for incident HF with reduced ejection fraction; HPCAL1 and PTTG1IP for prevalent HF with reduced ejection fraction; and ZNF146 (close to the COX7A1 enzyme) and ZFP3 (close to SLC52A1 —the riboflavin transporter) for incident HF with reduced ejection fraction. We tested the HF-related top single-nucleotide polymorphisms in the UK biobank, where rs77059055 in TPM1 (minor allele frequency, 0.023; odds ratio, 0.83; P =0.002) remained statistically significant upon Bonferroni correction.

Conclusions:

Our integrative transomics approach offers insights into potential molecular and genetic contributors to HF and its precursors. Although several of our candidate genes have been implicated in HF in animal models, independent replication is warranted.

Familial Mortality Risks in Patients With Heart Failure-A Swedish Sibling Study

Background

The influence of familial factors on the prognosis of heart failure (HF) is unknown. This nationwide follow‐up study aimed to determine familial mortality risks of HF among Swedish siblings hospitalized for HF.

Methods and Results

We linked several Swedish nationwide registers for individuals aged 0 to 80 years. The study population consisted of 373 people hospitalized for HF for the first time between 2000 and 2012 with 1 proband sibling previously hospitalized for HF for the first time between 2000 and 2007. Families with congenital heart disease were excluded. Familial hazard ratios (HRs) for mortality after first HF hospitalization were determined with Cox regression. The influence of proband survival was categorized as short survival (<5 years) or long survival (≥5 years) and determined continuously for the initial 5 years of proband survival. Adjustments were made for age, sex, time period, and common HF comorbidities. Short proband survival was associated with a HR of 2.02 (95% confidence interval, 1.32–3.09) for overall mortality. This HR was 2.35 (95% confidence interval, 1.18–4.67) in patients without preceding coronary heart disease, whereas patients with ischemic HF had an HR of 1.84 (95% confidence interval, 1.05–3.23). For each year of proband survival, the risk of death decreased, with a HR of 0.86 (95% confidence interval, 0.77–0.98).

Conclusions

Our results suggest that family history of poor survival in specific relation to HF is an important risk factor for death in HF patients. Additional studies are needed to characterize the molecular underpinnings and detailed phenotypic characteristics of such patients.

Genetic risk scores to predict the prognosis of chronic heart failure patients in Chinese Han

Chronic heart failure (CHF) has poor prognosis and polygenic heritability, and the genetic risk score (GRS) to predict CHF outcome has not yet been researched comprehensively. In this study, we sought to establish GRS to predict the outcomes of CHF. We re-analysed the proteomics data of failing human heart and combined them to filter the data of high-throughput sequencing in 1000 Chinese CHF cohort. Cox hazards models were used based on single nucleotide polymorphisms (SNPs) to estimate the association of GRS with the prognosis of CHF, and to analyse the difference between individual SNPs and tertiles of genetic risk. In the cohort study, GRS encompassing eight SNPs harboured in seven genes were significantly associated with the prognosis of CHF (P = 2.19 × 10^-10 after adjustment). GRS was used in stratifying individuals into significantly different CHF risk, with those in the top tertiles of GRS distribution having HR of 3.68 (95% CI: 2.40-5.65 P = 2.47 × 10^-10 ) compared with those in the bottom. We developed GRS and demonstrated its association with first event of heart failure endpoint. GRS might be used to stratify individuals for CHF prognostic risk and to predict the outcomes of genomic screening as a complement to conventional risk and NT-proBNP.

Mortality risks associated with sibling heart failure

BACKGROUND

The mortality in individuals with a family history of heart failure (HF) has not been determined. This nationwide sib-pair study aimed to determine mortality in individuals with a sibling affected with HF.

METHODS

Sib-pairs were linked using the Swedish Multi-Generation Register, the Hospital Discharge Register and the Cause of Death Register for the period 1987-2012. Families with cardiomyopathy or congenital heart disease were excluded. Mortality hazard ratios (HRs) were calculated for siblings of individuals who had been diagnosed with HF compared with siblings of individuals unaffected by HF as the reference group. Similar analyses were made for spouses. HRs were determined for overall mortality, cardiovascular mortality, and death of unknown cause.

RESULTS

Among siblings, the adjusted HR for overall mortality was 1.21 (95% CI 1.18-1.25). This risk remained (HR = 1.19, 95% CI 1.15-1.23) also among subjects without HF themselves. The adjusted HRs for cardiovascular mortality and death of unknown cause were 1.39 (95% CI 1.32-1.45) and 1.58 (95% CI 1.29-1.95), respectively. The mortality risk associations with spousal HF were all minimal, with an overall mortality HR of 1.02 (1.01-1.02). Early sibling age of onset of HF < 50 years was associated with higher HRs for overall mortality, cardiovascular mortality, and death of unknown cause, 1.33 (1.27-1.41), 1.54 (1.40-1.68) and 1.84 (1.27-2.67), respectively.

CONCLUSIONS

Sibling HF, especially early-onset HF, is associated with increased mortality. The low risk in spouses suggests genetic factors might be of importance. Screening for HF, and cardiovascular disease in general, in these individuals may be warranted.