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Anthracyclines are a major component of chemotherapies used in many pediatric and adult malignancies. Anthracycline-associated cardiotoxicity (ACT) is a dose-dependent adverse effect that has substantial impact on morbidity and mortality. Therefore, the identification of genetic variants associated with increased risk of ACT has the potential for significant clinical impact to improve patient care. The goal of this review is to summarize the current evidence supporting genetic variants associated with ACT, identify gaps and limitations in current knowledge, and propose future directions for incorporating genetics into clinical practice for patients treated with anthracyclines. We will discuss mechanisms of ACT that could be illuminated by genetics and discuss clinical applications for the cardiologist/cardio-oncologist.

Background Substantial efforts have been dedicated to exploring the link between genetic regulation and the proteome, informing studies of complex trait mechanisms. Most of these efforts have been limited to populations of European ancestry. Results We conduct an Olink protein quantitative trait locus (pQTL) analysis on 1245 proteins involving 1033 self-identified African American (AA) and 1764 non-Hispanic White (NHW) participants from the Women’s Health Initiative and Framingham Heart Study. For replication of candidate pQTLs, we use data from 534 self-identified AA adults from the Jackson Heart Study and protein genome-wide association analysis statistics from the UK Biobank Pharma Proteomics Project, including 54,219 participants, of whom 931 are of African ancestry. In total, we identify and validate 5103 pQTLs (4496 or 88% cis- and 602 or 12% trans-pQTLs) for 983 proteins. Among these, 195 are previously unreported, with most (166 or 85%) identified in our AA sample, many of which were essentially monomorphic in European reference populations. Several of these newly identified African ancestry-specific pQTLs have been reported in ClinVar; our results suggest impact on circulating protein levels, potentially bolstering evidence for clinical significance. We identify a “cis pQTL hotspot” within the leukocyte receptor gene cluster on human chromosome 19q13.4. We also provide examples where a particular cis-pQTL, identified through conditional analysis, offers biological insights into an overlapping GWAS signal for disease susceptibility. Conclusions The identification of previously undescribed African ancestry-specific pQTLs contributes to understanding protein genetic regulation and highlights the significance of proteomic analysis in diverse populations.

There is increasing evidence that HFpEF is a heterogeneous clinical entity and distinct molecular pathways may contribute to pathophysiology. Leveraging unbiased proteomics to identify novel biomarkers, this study seeks to understand the underlying molecular mechanisms of HFpEF. The discovery cohort consisted of HFpEF cases and non-HF controls from the CATHGEN study (N = 176); the validation cohort consisted of participants from the TECOS trial of patients with diabetes (N = 109). Proteins associated with HFpEF were included in a LASSO model to create a discriminative multi-protein model and assessed in the validation cohort. Survival models and meta-analysis were used to test the association of proteins with incident clinical outcomes, including HF hospitalization, mortality and HFpEF hospitalization in CATHGEN, TECOS and the Jackson Heart Study. In the derivation set, 190 proteins were associated with HFpEF in univariate analysis, of which 65 remained significant in the multivariate model. Twenty (30.8%) of these proteins validated in TECOS, including LCN2, U-PAR, IL-1ra, KIM1, CSTB and Gal-9 (OR 1.93–2.77, p  < 0.01). LASSO regression yielded a 13-protein model which, when added to a clinical model inclusive of NT-proBNP, improved the AUC from 0.82 to 0.92 ( p  = 1.5 × 10 –4 ). Five proteins were associated with incident HF hospitalization, four with HFpEF hospitalization and eleven with mortality ( p  < 0.05). We identified and validated multiple circulating biomarkers associated with HFpEF as well as HF outcomes. These biomarkers added incremental discriminative capabilities beyond clinical factors and NT-proBNP.

Regular exercise leads to widespread salutary effects, and there is increasing recognition that exercise-stimulated circulating proteins can impart health benefits. Despite this, limited data exist regarding the plasma proteomic changes that occur in response to regular exercise. Here, we perform large-scale plasma proteomic profiling in 654 healthy human study participants before and after a supervised, 20-week endurance exercise training intervention. We identify hundreds of circulating proteins that are modulated, many of which are known to be secreted. We highlight proteins involved in angiogenesis, iron homeostasis, and the extracellular matrix, many of which are novel, including training-induced increases in fibroblast activation protein (FAP), a membrane-bound and circulating protein relevant in body-composition homeostasis. We relate protein changes to training-induced maximal oxygen uptake adaptations and validate our top findings in an external exercise cohort. Furthermore, we show that FAP is positively associated with survival in 3 separate, population-based cohorts.

Abstract Aims Inflammation has been implicated in the pathogenesis of desmoplakin (DSP) cardiomyopathy, and retrospective studies have described abnormal myocardial fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) findings in symptomatic patients eventually diagnosed with DSP cardiomyopathy. We aimed to prospectively investigate if ambulatory patients with DSP cardiomyopathy had myocardial FDG uptake PET/CT imaging indicative of myocardial inflammation and if they had circulating biomarker evidence of inflammation. Methods We prospectively recruited participants with DSP cardiomyopathy and participants with titin cardiomyopathy as a comparator group. Blood samples for clinical labs and proteomic profiling, myocardial perfusion single-photon emission computed tomography (SPECT) and myocardial FDG PET/CT were obtained for all participants. Results Ten participants with DSP cardiomyopathy (median age 36.5 years (28, 60); 80% female; 100% White and non-Hispanic) and four participants with titin cardiomyopathy (median age 55.5 years [38.5, 64]; 50% female; 100% White and non-Hispanic) were recruited. There were no significant differences between the groups in white blood cell count, ESR, hsCRP or hsTn. Three participants with DSP cardiomyopathy and two participants with titin cardiomyopathy had non-specific myocardial FDG uptake on PET/CT. All other participants had no myocardial FDG uptake. Integration of miRNA differential expression and their predicted targets from the differential expression proteomics data identified a total of 11 inverse miRNA–mRNA pairs potentially involved in the regulation of top 20 significantly enriched pathways, including pathways involved in metabolism, inflammasome/inflammatory signalling and cell death/pyroptosis. Conclusions In a group of ambulatory patients with DSP and titin cardiomyopathy, we found no differences in FDG PET/CT findings or clinical circulating biomarkers of inflammation. However, miRNA-seq/proteomics analyses identified several enriched pathways and unique miRNA–protein pairs between DSP and titin cardiomyopathy, including pathways involved in inflammasome/inflammatory signalling. Future work will centre on evaluation during myocarditis-like episodes.

Background Systematic profiling of plasma proteins in population studies offers a complementary approach to discovery of novel risk factors and may provide new insights into the causes of coronary heart disease. Methods To explore relationships between the circulating proteome and coronary heart disease (CHD), we evaluated associations of 4780 plasma proteins with incident CHD in the Cardiovascular Health Study (CHS, N=2856, 575 CHD events) and replicated significant associations in the Atherosclerosis Risk in Communities Study (ARIC, N = 10456; 1375 events). Results We find that 11 proteins significantly associate with incident CHD after adjusting for risk factors; and eight significantly replicated in ARIC. Several proteins correlate with carotid intimal medial thickness and CHD associations are attenuated in participants without subclinical atherosclerosis. Macrophage metalloelastase (MMP12) is the strongest observed association (Hazard Ratio, 1.31; 95% Confidence Interval, 1.19-1.44). Mendelian randomization (MR) identifies a causal relationship between higher MMP12 and lower CHD (Odds Ratio, OR 0.94) and ischemic stroke (OR 0.90) risk, while reverse MR found that genetic propensity to CHD increased MMP12. Taken together, multivariable MR confirms a direct protective effect of higher plasma MMP12 on CHD risk and a genetic effect of atherosclerosis and CHD on elevating MMP12. Conclusions Proteomic analyses reveal associations with incident CHD and genomic evidence suggests that therapeutic MMP12 inhibition may confer adverse cardiovascular effects. Plain Language Summary Measuring many protein levels in the blood may provide new insights into the causes of heart disease (CHD). We evaluated thousands of plasma proteins in a study of older adults to determine whether any predicted risk of heart attacks or heart-related deaths and confirmed the findings in a second study. Eleven proteins showed evidence of association with CHD; often with stronger effects among those with pre-existing atherosclerosis. The strongest finding was for macrophage metalloelastase (MMP12), an endopeptidase expressed in vascular tissue and atherosclerotic plaque with roles in tissue repair, vascular remodeling, and reduction of inflammation. Our findings point to a complex role for this protein in response to underlying heart disease risk factors. Huber et al. measure 4,780 plasma proteins in the Cardiovascular Health Study to examine the association with incident coronary heart disease. They identify 11 proteins using genomic analyses and show the complexity of MMP12 in response to atherosclerosis and development of heart disease.

Respiratory biomarkers have the potential to identify airway injury by revealing inflammatory processes within the respiratory tract. Currently, there are no respiratory biomarkers suitable for clinical use to identify patients that warrant further diagnostic work‐up, counseling, and treatment for toxic inhalant exposures or chronic airway disease. Using a novel, noninvasive method of sampling the nasal epithelial lining fluid, we aimed to investigate if nasal biomarker patterns could distinguish healthy nonsmoking adults from active smokers and those with chronic upper and lower airway disease in this exploratory study. We compared 28 immune mediators from healthy nonsmoking adults (n = 32), former smokers with COPD (n = 22), chronic rhinosinusitis (CRS) (n = 22), and smoking adults without airway disease (n = 13). Using ANOVA, multinomial logistic regressions, and weighted gene co‐expression network analysis (WGCNA), we determined associations between immune mediators and each cohort. Six mediators (IL‐7, IL‐10, IL‐13, IL‐12p70, IL‐15, and MCP‐1) were lower among disease groups compared to healthy controls. Participants with lower levels of IL‐10, IL‐12p70, IL‐13, and MCP‐1 in the nasal fluid had a higher odds of being in the COPD or CRS group. The cluster analysis identified groups of mediators that correlated with disease status. Specifically, the cluster of IL‐10, IL‐12p70, and IL‐13, was positively correlated with healthy and negatively correlated with COPD groups, and two clusters were correlated with active smoking. In this exploratory study, we preliminarily identified groups of nasal mucosal mediators that differed by airway disease and smoking status. Future prospective, age‐matched studies that control for medication use are needed to validate these patterns and determine if nasosorption has diagnostic utility for upper and lower airway disease or injury. Respiratory biomarkers have the potential to identify airway injury by revealing inflammatory processes within the respiratory tract. Using a novel, noninvasive method of sampling the nasal epithelial lining fluid, we aimed to investigate if nasal biomarker patterns could distinguish healthy nonsmoking adults from active smokers and those with chronic upper and lower airway disease. In this exploratory study, we identified groups of nasal mucosal mediators that differed by airway disease and smoking status.

Inherited cardiomyopathies are genetic diseases that can lead to heart failure and sudden cardiac death. These conditions tend to run in families, following an autosomal dominant pattern where first-degree relatives have a 50% chance of carrying the pathogenic variant. Despite significant advancements and increased accessibility of genetic testing, accurately predicting the phenotypic expression of these conditions remains challenging due to the inherent variability in their clinical manifestations and the incomplete penetrance observed. This poses challenges in providing patient care and effectively communicating the potential risk of future disease to patients and their families. To address these challenges, this review aims to synthesize the available evidence on penetrance, expressivity, and factors influencing disease expression to improve communication and risk assessment for patients with inherited cardiomyopathies and their family members.

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics 1 . Here we examine a large cohort (the INTERVAL study 2 ; n  = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n  = 3,175; Olink, n  = 4,822), plasma metabolomics (Metabolon HD4, n  = 8,153), serum metabolomics (Nightingale, n  = 37,359) and whole-blood Illumina RNA sequencing ( n  = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank 3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK–STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores. A machine learning approach is used to analyse multi-omics (proteomics, metabolomics and transcriptomics) data, producing genetic scores for more than 17,000 biomolecular traits in human blood, and identifying possible associations with disease.

Cardiac involvement in systemic amyloidosis (AL) occurs in ~50% of all AL patients. However once symptomatic heart failure develops, therapeutic options are limited thereby conferring a poor overall prognosis. The median survival is <6 months when AL patients are untreated for the underlying plasma cell dyscrasia. We thus sought to identify risk factors of increased mortality in treatment - naïve , AL cardiac amyloidosis with heart failure. Patients with biopsy-proven AL cardiac amyloid, who presented with heart failure and did not received prior AL treatment, were enrolled between 2004–2014, at the initial visit to the Amyloidosis Center at Boston University Medical Center. Routine laboratory tests, physical examination and echocardiography data were collected. There were 165 predominantly white (76.4%), and male (61%) patients, with a mean age of 61.6 ± 9.5 years. Median survival was 10.9 months (95% CI 6.2–14.7). By multivariate analysis increased relative wall thickness (RWT) [HR 6.70; 95% CI 2.45–18.30), older age (HR 1.04; 95% CI 1.01–1.06), higher New York Heart Association (NYHA) functional class (HR 1.50; 95% CI 1.02–2.2), log brain natriuretic peptide (BNP) levels (HR 1.45; 95% CI 1.15–1.81) and C-reactive protein (CRP) levels (HR 1.02; 95% CI 1.00–1.04) were significant predictors for increased mortality. In conclusion, in treatment-naïve, AL cardiac amyloidosis patients with heart failure symptoms who lack these high-risk features may have a better outcome. These findings might allow for better risk stratification although outcomes are still poor.