Myocardial interstitial fibrosis is associated with cardiovascular disease and adverse prognosis. Here, to investigate the biological pathways that underlie fibrosis in the human heart, we developed ...a machine learning model to measure native myocardial T1 time, a marker of myocardial fibrosis, in 41,505 UK Biobank participants who underwent cardiac magnetic resonance imaging. Greater T1 time was associated with diabetes mellitus, renal disease, aortic stenosis, cardiomyopathy, heart failure, atrial fibrillation, conduction disease and rheumatoid arthritis. Genome-wide association analysis identified 11 independent loci associated with T1 time. The identified loci implicated genes involved in glucose transport (SLC2A12), iron homeostasis (HFE, TMPRSS6), tissue repair (ADAMTSL1, VEGFC), oxidative stress (SOD2), cardiac hypertrophy (MYH7B) and calcium signaling (CAMK2D). Using a transforming growth factor β1-mediated cardiac fibroblast activation assay, we found that 9 of the 11 loci consisted of genes that exhibited temporal changes in expression or open chromatin conformation supporting their biological relevance to myofibroblast cell state acquisition. By harnessing machine learning to perform large-scale quantification of myocardial interstitial fibrosis using cardiac imaging, we validate associations between cardiac fibrosis and disease, and identify new biologically relevant pathways underlying fibrosis.
Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending ...thoracic aorta in 4.6 million cardiac magnetic resonance images from the UK Biobank. We then conducted genome-wide association studies in 39,688 individuals, identifying 82 loci associated with ascending and 47 with descending thoracic aortic diameter, of which 14 loci overlapped. Transcriptome-wide analyses, rare-variant burden tests and human aortic single nucleus RNA sequencing prioritized genes including SVIL, which was strongly associated with descending aortic diameter. A polygenic score for ascending aortic diameter was associated with thoracic aortic aneurysm in 385,621 UK Biobank participants (hazard ratio = 1.43 per s.d., confidence interval 1.32-1.54, P = 3.3 × 10
). Our results illustrate the potential for rapidly defining quantitative traits with deep learning, an approach that can be broadly applied to biomedical images.
Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, ...but is challenging to obtain at scale. Here, we use deep learning to enable genome-wide association study of cardiac magnetic resonance-derived left ventricular mass indexed to body surface area within 43,230 UK Biobank participants. We identify 12 genome-wide associations (1 known at TTN and 11 novel for left ventricular mass), implicating genes previously associated with cardiac contractility and cardiomyopathy. Cardiac magnetic resonance-derived indexed left ventricular mass is associated with incident dilated and hypertrophic cardiomyopathies, and implantable cardioverter-defibrillator implant. An indexed left ventricular mass polygenic risk score ≥90
percentile is also associated with incident implantable cardioverter-defibrillator implant in separate UK Biobank (hazard ratio 1.22, 95% CI 1.05-1.44) and Mass General Brigham (hazard ratio 1.75, 95% CI 1.12-2.74) samples. Here, we perform a genome-wide association study of cardiac magnetic resonance-derived indexed left ventricular mass to identify 11 novel variants and demonstrate that cardiac magnetic resonance-derived and genetically predicted indexed left ventricular mass are associated with incident cardiomyopathy.
A hallmark of metastasis is the adaptation of tumor cells to new environments. Metabolic constraints imposed by the serine and glycine-limited brain environment restrict metastatic tumor growth. How ...brain metastases overcome these growth-prohibitive conditions is poorly understood. Here, we demonstrate that 3-phosphoglycerate dehydrogenase (PHGDH), which catalyzes the rate-limiting step of glucose-derived serine synthesis, is a major determinant of brain metastasis in multiple human cancer types and preclinical models. Enhanced serine synthesis proved important for nucleotide production and cell proliferation in highly aggressive brain metastatic cells.
, genetic suppression and pharmacologic inhibition of PHGDH attenuated brain metastasis, but not extracranial tumor growth, and improved overall survival in mice. These results reveal that extracellular amino acid availability determines serine synthesis pathway dependence, and suggest that PHGDH inhibitors may be useful in the treatment of brain metastasis. SIGNIFICANCE: Using proteomics, metabolomics, and multiple brain metastasis models, we demonstrate that the nutrient-limited environment of the brain potentiates brain metastasis susceptibility to serine synthesis inhibition. These findings underscore the importance of studying cancer metabolism in physiologically relevant contexts, and provide a rationale for using PHGDH inhibitors to treat brain metastasis.
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High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability
patterned by distinct mutational processes
, tumour heterogeneity
and intraperitoneal spread
. Immunotherapies ...have had limited efficacy in HGSOC
, highlighting an unmet need to assess how mutational processes and the anatomical sites of tumour foci determine the immunological states of the tumour microenvironment. Here we carried out an integrative analysis of whole-genome sequencing, single-cell RNA sequencing, digital histopathology and multiplexed immunofluorescence of 160 tumour sites from 42 treatment-naive patients with HGSOC. Homologous recombination-deficient HRD-Dup (BRCA1 mutant-like) and HRD-Del (BRCA2 mutant-like) tumours harboured inflammatory signalling and ongoing immunoediting, reflected in loss of HLA diversity and tumour infiltration with highly differentiated dysfunctional CD8
T cells. By contrast, foldback-inversion-bearing tumours exhibited elevated immunosuppressive TGFβ signalling and immune exclusion, with predominantly naive/stem-like and memory T cells. Phenotypic state associations were specific to anatomical sites, highlighting compositional, topological and functional differences between adnexal tumours and distal peritoneal foci. Our findings implicate anatomical sites and mutational processes as determinants of evolutionary phenotypic divergence and immune resistance mechanisms in HGSOC. Our study provides a multi-omic cellular phenotype data substrate from which to develop and interpret future personalized immunotherapeutic approaches and early detection research.
Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with ...genetic data provides a unique opportunity to assess the genetic contributions to left atrial structure and function, and understand their relationship with risk for atrial fibrillation. Here, we use deep learning and surface reconstruction models to measure left atrial minimum volume, maximum volume, stroke volume, and emptying fraction in 40,558 UK Biobank participants. In a genome-wide association study of 35,049 participants without pre-existing cardiovascular disease, we identify 20 common genetic loci associated with left atrial structure and function. We find that polygenic contributions to increased left atrial volume are associated with atrial fibrillation and its downstream consequences, including stroke. Through Mendelian randomization, we find evidence supporting a causal role for left atrial enlargement and dysfunction on atrial fibrillation risk.
The Genetic Determinants of Aortic Distention Pirruccello, James P.; Rämö, Joel T.; Choi, Seung Hoan ...
Journal of the American College of Cardiology,
04/2023, Letnik:
81, Številka:
14
Journal Article
Recenzirano
As the largest conduit vessel, the aorta is responsible for the conversion of phasic systolic inflow from ventricular ejection into more continuous peripheral blood delivery. Systolic distention and ...diastolic recoil conserve energy and are enabled by the specialized composition of the aortic extracellular matrix. Aortic distensibility decreases with age and vascular disease.
In this study, we sought to discover epidemiologic correlates and genetic determinants of aortic distensibility and strain.
We trained a deep learning model to quantify thoracic aortic area throughout the cardiac cycle from cardiac magnetic resonance images and calculated aortic distensibility and strain in 42,342 UK Biobank participants.
Descending aortic distensibility was inversely associated with future incidence of cardiovascular diseases, such as stroke (HR: 0.59 per SD; P = 0.00031). The heritabilities of aortic distensibility and strain were 22% to 25% and 30% to 33%, respectively. Common variant analyses identified 12 and 26 loci for ascending and 11 and 21 loci for descending aortic distensibility and strain, respectively. Of the newly identified loci, 22 were not significantly associated with thoracic aortic diameter. Nearby genes were involved in elastogenesis and atherosclerosis. Aortic strain and distensibility polygenic scores had modest effect sizes for predicting cardiovascular outcomes (delaying or accelerating disease onset by 2%-18% per SD change in scores) and remained statistically significant predictors after accounting for aortic diameter polygenic scores.
Genetic determinants of aortic function influence risk for stroke and coronary artery disease and may lead to novel targets for medical intervention.
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We compared heart rate variability (HRV) in sudden unexpected death in epilepsy (SUDEP) cases and living epilepsy controls.
This international, multicenter, retrospective, nested case-control study ...examined patients admitted for video-EEG monitoring (VEM) between January 1, 2003, and December 31, 2014, and subsequently died of SUDEP. Time domain and frequency domain components were extracted from 5-minute interictal ECG recordings during sleep and wakefulness from SUDEP cases and controls.
We identified 31 SUDEP cases and 56 controls. Normalized low-frequency power (LFP) during wakefulness was lower in SUDEP cases (median 42.5, interquartile range IQR 32.6-52.6) than epilepsy controls (55.5, IQR 40.7-68.9;
= 0.015, critical value = 0.025). In the multivariable model, normalized LFP was lower in SUDEP cases compared to controls (contrast -11.01, 95% confidence interval CI -20.29 to 1.73;
= 0.020, critical value = 0.025). There was a negative correlation between LFP and the latency to SUDEP, where each 1% incremental reduction in normalized LFP conferred a 2.7% decrease in the latency to SUDEP (95% CI 0.95-0.995;
= 0.017, critical value = 0.025). Increased survival duration from VEM to SUDEP was associated with higher normalized high-frequency power (HFP;
= 0.002, critical value = 0.025). The survival model with normalized LFP was associated with SUDEP (
statistic 0.66, 95% CI 0.55-0.77), which nonsignificantly increased with the addition of normalized HFP (
statistic 0.70, 95% CI 0.59-0.81;
= 0.209).
Reduced short-term LFP, which is a validated biomarker for sudden death, was associated with SUDEP. Increased HFP was associated with longer survival and may be cardioprotective in SUDEP. HRV quantification may help stratify individual SUDEP risk.
This study provides Class III evidence that in patients with epilepsy, some measures of HRV are associated with SUDEP.
Introduction
The pivotal study of the extravascular implantable cardioverter‐defibrillator (EV ICD) recently demonstrated primary efficacy and safety endpoints comparable to previous ICD systems. ...Patient experience with this novel device has not been reported. The current study examined the standardized patient‐reported outcome (PRO) metrics of quality of life (QOL) and patient acceptance of the device.
Methods
The EV ICD Pivotal Study was a prospective, single‐arm, nonrandomized, global, premarket approval trial. Patients completed the 12‐Item Short Form Survey (SF‐12) QOL surveys at baseline and at 6 months following implant. Additionally, patients completed the Florida Patient Acceptance Survey (FPAS) QOL survey at 6 months.
Results
From baseline to 6 months, patients within the EV ICD Pivotal Study (n = 247) reported statistically significant SF‐12 improvements in physical QOL (45.4 ± 9.4 vs. 46.8 ± 9.1 respectively, p = .020) and no changes in mental QOL (49.3 ± 10.4 vs. 50.5 ± 9.7, p = .061). No differences were noted by sex, atrial fibrillation, or the experience of ICD shock. EV ICD patients reported better total FPAS patient acceptance of their ICD than TV‐ICD or S‐ICD patients using historical norms comparisons (80.4 ± 15.7 vs. 70.2 ± 17.8, p < .0001 for S‐ICD and 73.0 ± 17.4, p = .004 for TV‐ICD).
Conclusion
The initial PROs for EV ICD patients indicated that patients had improvements in physical QOL from baseline to 6‐month follow‐up and markedly better overall acceptance of their ICD compared to a previous study with S‐ICD and TV‐ICD data. These initial results suggest that the EV ICD is evaluated positively by patients.
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