Circulation: Genomic and Precision Medicine最新文献

Background: Circulating proteins represent robust drug targets with therapeutic potential. Many discoveries have focused on European-ancestry populations, disregarding minuscule yet substantial proteomic differences that may contribute to disease and alter drug generalizability in other ancestry groups.

Methods: Using 2-sample Mendelian randomization and colocalization, we analyzed the effects of 1562 circulating proteins on 145 cardiometabolic-centric outcomes to identify robust protein-phenotype associations in African-ancestry populations and reveal African-ancestry associations with heterogeneous effects. We further replicated these findings using the proteomic data available from the UK Biobank Pharma Proteomics Project and tested the effect of protein quantity in association with select phenotypes. Population branch statistics were also constructed to examine whether protein-genetic instruments under natural selection could lead to significant protein-outcome associations specific to the African ancestry.

Results: We identified 115 robust protein target-outcome associations in African-ancestry populations. Among these, 51 demonstrated heterogeneous effects between African- and European-ancestry populations. We further replicated 4 cross-platform African-ancestry associations in the UK Biobank Pharma Proteomics Project and also revealed 4 significant, direct associations between protein levels and phenotypes. Ultimately, based on our prioritization criteria, we found that CD36 (glycoprotein IIIb), APOC1 (apolipoprotein C1), GSTA1 (glutathione S-transferase alpha 1), and FOLH1 (folate hydrolase 1) were shown to influence lipids and heart diseases, and were uniquely represented in African-ancestry populations. In addition, using population branch statistics, we showed that 47.5% of the 115 significant protein-outcome associations were possibly driven by cis-acting protein quantitative trait loci under natural selection.

Conclusions: Multiple lines of evidence were used to interrogate proteomic determinants of cardiometabolic diseases and traits in African-ancestry populations. We highlighted actionable circulating protein targets that could represent potential drug targets for cardiovascular diseases specific to populations with African ancestry.

Background: Cardiac involvement is the main determinant of adverse outcomes in Fabry disease. The study aimed to investigate cardiovascular outcomes in patients with Fabry disease.

Methods: This was a multicenter, retrospective, longitudinal study of consecutively referred adult patients with Fabry disease. The primary end point was the occurrence of major adverse cardiovascular events defined as a composite of cardiovascular death, major arrhythmic events, bradyarrhythmias requiring pacemaker implantation, and stroke.

Results: A total of 680 patients (age, 42.3±15.9 years; 41.0% male; 68.7% on disease-specific therapy) were included. During a median follow-up of 7.1 (interquartile range, 3.9-11.6) years, 92 patients (13.5%) experienced a major adverse cardiovascular event. At 10 years, freedom from major adverse cardiovascular event was 85.1% (95% CI, 81.3-88.2) and was lower in males compared with females (76.1% [95% CI, 68.9-81.9] versus 91.3% [95% CI, 87.0-94.2]; log-rank χ²=26.9; P<0.001). On multivariable analysis, age (hazard ratio, 1.04 [95% CI, 1.01-1.06] per 1 year; P<0.001), estimated glomerular filtration rate (hazard ratio, 0.99 [95% CI, 0.98-0.99] per 1 mL/min per 1.73 m²; P<0.001), QRS interval (hazard ratio, 1.02 [95% CI, 1.01-1.03] per 1 ms; P=0.002), and left ventricular mass index (hazard ratio, 1.01 [95% CI, 1.00-1.01] per 1 g/m²; P=0.032) were independent predictors of major adverse cardiovascular events during follow-up.

Conclusions: This study shows that the prevention and treatment of cardiovascular disease remain an unmet need for patients with Fabry disease.

Background: Heart failure (HF) and its main subtypes, heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF), impose an enormous health burden on elders. Assessment of the circulating proteome to illuminate pathogenesis could open new opportunities for treatment.

Methods: We conducted a plasma proteomics screen of incident HF and its subtypes in 2 older population-based cohorts, the CHS (Cardiovascular Health Study) and the AGES-RS (Aging, Gene/Environment Susceptibility-Reykjavik Study). The 2 studies used SomaLogic platforms, with 4404 aptamers in common. Multivariable Cox models were fit to evaluate individual-protein associations with HF, HFpEF, and HFrEF separately in each cohort, and study-specific associations were combined by fixed-effects meta-analysis. Replication was performed in the ARIC (Atherosclerosis Risk in Communities) cohort. Two-sample Mendelian randomization of HF and its subtypes, along with colocalization analysis, was performed to support causal inference.

Results: Among 8599 participants, 1590 experienced incident HF (536 HFpEF, 471 HFrEF). There were 119 proteins associated with HF, 15 proteins with HFpEF, and 11 proteins with HFrEF, at Bonferroni-corrected significance. Among these, 9 have never previously been identified for cardiovascular diseases, and another 61 represent new associations with incident HF or its subtypes. Of these 70 proteins, 55 of the 66 available replicated externally. Mendelian randomization analysis revealed 7 proteins genetically associated with HF at nominal significance; 2 were separately associated with HFpEF, and another 2 with HFrEF. Seven of these 9 proteins (NCDP1, APOF, LMAN2 [lectin, mannose-binding 2], ADIPOQ [adiponectin], CD14 [cluster of differentiation 14], ARHGAP1 [Rho GTPase-activating protein 1], C9 [complement 9]) showed new, possibly causal associations, although we did not detect evidence for colocalization.

Conclusions: In this large-scale proteomic study involving 3 longitudinal cohorts of older adults, we identified and replicated 55 novel protein markers of HF or its subtypes, and 7 new, possibly causal proteins. These proteins may enhance risk prediction, improve understanding of pathobiology, and help prioritize targets for therapeutic development of these foremost disorders in elders.

Background: NPs (natriuretic peptides) are bioactive hormones crucial for regulating blood pressure, glucose homeostasis, and lipid metabolism. Despite the high heritability of circulating NP levels, the genetic determinants of NP regulation, particularly across ancestries and sexes, remain poorly understood. The objective of the current study was to identify genetic variants associated with NT-proBNP (N-terminal pro-B-type NP) levels in a multiancestry study population.

Methods: Whole genome sequencing and array-based data from 81 213 individuals without heart failure were analyzed from the Trans-Omics for Precision Medicine cohorts, UK Biobank, All of Us Research Program, and REGARDS (Reasons for Geographic and Racial Differences in Stroke) study to identify common, rare, and structural variants associated with NT-proBNP levels. The main outcome of the study was log-transformed and standardized NT-proBNP levels. Genetic associations with NT-proBNP were examined, followed by gene prioritization, transcriptome-wide association studies, colocalization, and rare variant analyses.

Results: Nine novel loci and 3 previously reported loci were identified to be associated with NT-proBNP levels. Novel structural variants were detected across 12 loci. Similar effect sizes were observed for both common and rare variants. Key genes such as BAG3 (10q26.11) and SLC39A8 (4q24) were identified through gene prioritization, with prior animal models supporting their therapeutic relevance. Rare variant analysis identified 6 masks with significant associations, specifically noncoding masks, suggesting regulatory modulation of NT-proBNP.

Conclusions: This study identifies novel common, rare, and structural variants associated with NT-proBNP levels, highlighting the contribution of both coding and regulatory noncoding variation. These findings advance our understanding of the genetic architecture of NT-proBNP and may inform future cardiometabolic therapeutic strategies.

Background: TRPC6 (transient receptor potential canonical 6) channels, encoded by the TRPC6 gene, are widely expressed in cardiomyocytes and play a critical role in maintaining intracellular Ca²⁺ homeostasis. Variants in TRPC6 are associated with chemotherapy-related cardiomyopathy. Specifically, the TRPC6 A404V polymorphism, with a minor (404 V) allele frequency of 12% in the general population, has been identified in patients undergoing anthracycline therapy. However, the underlying mechanisms remain largely unexplored.

Methods: Using patch-clamp recordings, Ca²⁺ imaging, computational analysis, and molecular biology techniques, we assessed the effects of doxorubicin and its metabolite, doxorubicinol, on regulating TRPC6 alanine (A) at position 404 replaced by valine (V; A404V) channel expression and function in a heterologous expression system and native cardiac cells.

Results: Both additive and recessive models demonstrated a significant association between the TRPC6 A404V variant and doxorubicin-related cardiomyopathy. The TRPC6 A404V channel exhibited higher membrane expression levels compared with the wild-type (WT) control. Patch-clamp recordings showed that both TRPC6 WT and A404V channels remained mostly inactive at baseline. Application of 50 μmol/L 1-oleoyl acetyl-sn-glycerol (OAG), a TRPC6 activator, significantly increased the inward- and outward-current densities of WT and A404V channels. Furthermore, a 24-hour treatment with 0.5 μmol/L doxorubicin enhanced TRPC6 mRNA expression and potentiated the OAG effects on both WT and A404V channels, with a more pronounced response in A404V channels. Treatment with 0.5 μmol/L doxorubicinol had no effect on OAG-induced current densities in either WT or A404V channels. Doxorubicin effects on intracellular Ca²⁺ levels were confirmed by Ca²⁺ imaging in native cardiac cells. Computational modeling revealed that the A404V mutation induces a conformational change in the OAG-binding pocket, enhancing its interaction with OAG in the A404V protein compared with the WT control.

Conclusions: The TRPC6 A404V is a gain-of-function variant that exhibits enhanced activity in the presence of doxorubicin. Therefore, the TRPC6 A404V variant represents a risk factor for anthracycline-induced cardiotoxicity in patients with cancer.

Background: Atrial fibrillation (AF) is a common and clinically heterogeneous arrhythmia. Machine learning algorithms can define data-driven disease subtypes in an unbiased fashion, but whether these AF subgroups align with underlying mechanisms, such as polygenic liability to AF or inflammation, and associate with clinical outcomes is unclear.

Methods: We identified individuals with AF in a large biobank linked to electronic health records and genome-wide genotyping. We applied an unsupervised coclustering machine learning algorithm to 35 curated and uncorrelated clinical features to identify distinct phenotypic AF clusters. The clinical inflammatory status of the clusters was defined using measured biomarkers (CRP, ESR, WBC, Neutrophil %, Platelet count, RDW) within 6 months of first AF mention. Polygenic risk scores for AF and for cytokine levels were used to assess the genetic liability of clusters to AF and inflammation, respectively. Clinical outcomes were collected from electronic health records up to the last medical contact.

Results: The analysis included 23 271 subjects with AF, of which 6023 had available genome-wide genotyping. The machine learning algorithm identified 3 phenotypic clusters that were distinguished by increasing prevalence of comorbidities, particularly renal disease and coronary artery disease. Polygenic liability to AF across clusters was highest in the low comorbidity cluster. Clinically measured inflammatory biomarkers were highest in the high comorbidity cluster. There was no difference between groups in genetically predicted levels of inflammatory biomarkers. Cluster assignment was associated with mortality, stroke, bleeding, and use of cardiac implantable electronic devices after AF diagnosis.

Conclusions: Patients with AF subgroups identified by clustering were distinguished by comorbidity burden and associated with risk of clinically important outcomes, polygenic liability to AF, and clinical inflammation, but not with genetically predicted inflammatory cytokine levels. Our study empirically demonstrates the complementary roles of comorbidity and genetic liability as major drivers of AF phenotypic variability using hypothesis-free methods.

In vitro functional modeling of genetic variants has revolutionized our understanding of which variants can cause cardiac disorders, providing insights into their molecular underpinnings. This review provides an overview of high-throughput methods used for the functional assessment of variants implicated in inherited cardiac diseases. Advances in gene-editing technology now enable the efficient generation of cells expressing individual genetic variants or libraries of variants for robust functional studies. We discuss innovative assays that can evaluate dozens or hundreds of variants sequentially. For example, the electrophysiological properties of numerous cardiac ion channel variants in genes linked to inherited arrhythmias can be characterized using automated patch clamping. The mechanical properties of cardiomyocytes expressing candidate cardiomyopathy variants can be assessed using techniques such as atomic force microscopy, traction force microscopy, and impedance-based methods. Multiplexed assays of variant effect are an emerging family of techniques that use gene-specific or general assays, combined with next-generation sequencing, to characterize hundreds or thousands of pooled genetic variants. We examine the key advantages and limitations of each method and outline future goals for the field. Innovative in vitro studies of cardiac genetic variants will enhance our understanding of variant-disease relationships and improve diagnosis, screening, and treatment options for these disorders.

Background: ACTA2 pathogenic variants predispose to thoracic aortic disease, and a subset of variants lead to early onset atherosclerotic cardiovascular disease (ASCVD). The molecular pathway linking misfolded SMA (α-smooth muscle actin) monomers to augmented atherosclerosis-associated smooth muscle cell phenotypic modulation can be modeled in vitro by stably expressing the ACTA2 p.R149C variant in Acta2^-/- smooth muscle cells.

Methods: The Montalcino Aortic Consortium patient registry was used to identify cases with ACTA2 pathogenic/likely pathogenic missense variants. These patients were surveyed, and their medical records were reviewed to identify cases with early onset ASCVD. The variants for these cases, as well as other recurrent ACTA2 missense variants, were individually expressed in Acta2^-/- smooth muscle cells, and transcript and protein levels, HSF1 (heat shock factor 1) activation, HMGCR (3-hydroxy-3-methylglutaryl-coenzyme A reductase) expression and activity, cholesteryl ester levels, and downstream smooth muscle cell phenotypic modulation were assessed.

Results: Early onset ASCVD included coronary artery disease, peripheral vascular disease, and atherosclerotic plaques identified by imaging in the arch, descending, or abdominal aorta, along with the celiac, iliac, renal, or vertebral arteries. Twelve ACTA2 variants were identified to be associated with early onset ASCVD. Early onset ASCVD was correlated with HSF1 activation (P=0.035), cellular cholesteryl ester levels (P=0.0031), and having one family member with the specific ACTA2 pathogenic variant who had early onset ASCVD (P=0.0001).

Conclusions: Assays assessing the molecular mechanism that leads to early onset ASCVD can identify which ACTA2 pathogenic variants will trigger this condition. Ultimately, this information informs precision medical care for individuals with ACTA2 pathogenic variants, with the ultimate goal of preventing thoracic aortic disease and ASCVD.

Background: The analysis of the circulating proteome can identify translational modifiers and biomarkers of disease expressivity and severity at a given time point. Here, we explore the relationships between protein measures implicated in cardiovascular disease and whether they mediate causal relationships between cardiovascular risk factors and disease development.

Methods: To understand the relationships between circulating biomarkers and genetic variants, medications, anthropometric traits, lifestyle factors, imaging-derived measures, and diagnoses of cardiovascular disease, we undertook in-depth analyses of measures of 9 plasma proteins with a priori roles in genetic and structural cardiovascular disease or treatment pathways (ACE2 [angiotensin-converting enzyme 2], ACTA2 [actin alpha 2], ACTN4 [actinin alpha 4], BAG3 [BAG cochaperone 3], BNP [B-type natriuretic peptide], CDKN1A [cyclin-dependent kinase inhibitor 1A], NOTCH1 [neurogenic locus notch homolog protein 1], NT-proBNP [N-terminal pro-B-type natriuretic peptide], and TNNI3 [troponin I]) from the Pharma Proteomics Project of the UK Biobank cohort (over 45 000 participants sampled at recruitment).

Results: We identified significant variability in circulating proteins with age, sex, ancestry, alcohol intake, smoking, and medication intake. Phenome-wide association studies highlighted the range of cardiovascular clinical features with relationships to protein levels. Genome-wide genetic association studies identified variants near GCKR, APOE, and SERPINA1, that modified multiple circulating protein levels (BAG3, CDKN1A, and NOTCH1). NT-proBNP and BNP levels associated with variants in BAG3. ACE2 levels were increased with a diagnosis of hypertension or diabetes, particularly in females, and were influenced by variants in genes associated with diabetes (HNF1A and HNF4A). Two-sample Mendelian randomization identified ACE2 as protective for systolic blood pressure and type-2 diabetes.

Conclusions: From a panel of circulating proteins, the results from this observational study provide evidence that ACE2 is causally protective for hypertension and diabetes. This suggests that ACE2 treatment may provide additional protection from these cardiovascular diseases. This study provides an improved understanding of the circulating pathways depicting cardiovascular disease dynamics.