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.
Lassa fever, a hemorrhagic fever caused by Lassa virus (LASV), is endemic in West Africa. It is difficult to distinguish febrile illnesses that are common in West Africa from Lassa fever based solely ...on a patient's clinical presentation. The field performance of recombinant antigen-based Lassa fever immunoassays was compared to that of quantitative polymerase chain assays (qPCRs) using samples from subjects meeting the case definition of Lassa fever presenting to Kenema Government Hospital in Sierra Leone. The recombinant Lassa virus (ReLASV) enzyme-linked immunosorbant assay (ELISA) for detection of viral antigen in blood performed with 95% sensitivity and 97% specificity using a diagnostic standard that combined results of the immunoassays and qPCR. The ReLASV rapid diagnostic test (RDT), a lateral flow immunoassay based on paired monoclonal antibodies to the Josiah strain of LASV (lineage IV), performed with 90% sensitivity and 100% specificity. ReLASV immunoassays performed better than the most robust qPCR currently available, which had 82% sensitivity and 95% specificity. The performance characteristics of recombinant antigen-based Lassa virus immunoassays indicate that they can aid in the diagnosis of LASV Infection and inform the clinical management of Lassa fever patients.
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.
An increase in Lassa fever cases was identified in Nigeria this year. In this analysis of the infecting viruses, the predominant mode of transmission appeared to be multiple insertions from local ...rodent populations rather than sustained person-to-person spread.
The left ventricular outflow tract (LVOT) and ascending aorta are spatially complex, with distinct pathologies and embryologic origins. Prior work examined the genetics of thoracic aortic diameter in ...a single plane.
We sought to elucidate the genetic basis for the diameter of the LVOT, aortic root, and ascending aorta.
Using deep learning, we analyzed 2.3 million cardiac magnetic resonance images from 43,317 UK Biobank participants. We computed the diameters of the LVOT, the aortic root, and at 6 locations of ascending aorta. For each diameter, we conducted a genome-wide association study and generated a polygenic score. Finally, we investigated associations between these scores and disease incidence.
A total of 79 loci were significantly associated with at least 1 diameter. Of these, 35 were novel, and most were associated with 1 or 2 diameters. A polygenic score of aortic diameter approximately 13 mm from the sinotubular junction most strongly predicted thoracic aortic aneurysm (n = 427,016; mean HR: 1.42 per SD; 95% CI: 1.34-1.50; P = 6.67 × 10
). A polygenic score predicting a smaller aortic root was predictive of aortic stenosis (n = 426,502; mean HR: 1.08 per SD; 95% CI: 1.03-1.12; P = 5 × 10
).
We detected distinct genetic loci underpinning the diameters of the LVOT, aortic root, and at several segments of ascending aorta. We spatially defined a region of aorta whose genetics may be most relevant to predicting thoracic aortic aneurysm. We further described a genetic signature that may predispose to aortic stenosis. Understanding genetic contributions to proximal aortic diameter may enable identification of individuals at risk for aortic disease and facilitate prioritization of therapeutic targets.
Mural cells in ascending aortic aneurysms undergo phenotypic changes that promote extracellular matrix destruction and structural weakening. To explore this biology, we analyzed the transcriptional ...features of thoracic aortic tissue.
Single-nuclear RNA sequencing was performed on 13 samples from human donors, 6 with thoracic aortic aneurysm, and 7 without aneurysm. Individual transcriptomes were then clustered based on transcriptional profiles. Clusters were used for between-disease differential gene expression analyses, subcluster analysis, and analyzed for intersection with genetic aortic trait data.
We sequenced 71 689 nuclei from human thoracic aortas and identified 14 clusters, aligning with 11 cell types, predominantly vascular smooth muscle cells (VSMCs) consistent with aortic histology. With unbiased methodology, we found 7 vascular smooth muscle cell and 6 fibroblast subclusters. Differentially expressed genes analysis revealed a vascular smooth muscle cell group accounting for the majority of differential gene expression. Fibroblast populations in aneurysm exhibit distinct behavior with almost complete disappearance of quiescent fibroblasts. Differentially expressed genes were used to prioritize genes at aortic diameter and distensibility genome-wide association study loci highlighting the genes
(latent transforming growth factor beta-binding protein 1), and
(interleukin 34) in fibroblasts,
(PDZ and LIM domain 5),
(alpha-actinin-4), and
in vascular smooth muscle cells, as well as
in macrophage populations.
Using nuclear RNA sequencing, we describe the cellular diversity of healthy and aneurysmal human ascending aorta. Sporadic aortic aneurysm is characterized by differential gene expression within known cellular classes rather than by the appearance of novel cellular forms. Single-nuclear RNA sequencing of aortic tissue can be used to prioritize genes at aortic trait loci.
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.
Aims
Implementation of guideline‐directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF) remains incomplete. Non‐cardiovascular hospitalization may present ...opportunities for GDMT optimization. We assessed the efficacy and durability of a virtual, multidisciplinary ‘GDMT Team’ on medical therapy prescription for HFrEF.
Methods and results
Consecutive hospitalizations in patients with HFrEF (ejection fraction ≤40%) were prospectively identified from 3 February to 1 March 2020 (usual care group) and 2 March to 28 August 2020 (intervention group). Patients with critical illness, de novo heart failure, and systolic blood pressure <90 mmHg in the preceeding 24 hs prior to enrollment were excluded. In the intervention group, a pharmacist–physician GDMT Team provided optimization suggestions to treating teams based on an evidence‐based algorithm. The primary outcome was a GDMT optimization score, the sum of positive (+1 for new initiations or up‐titrations) and negative therapeutic changes (−1 for discontinuations or down‐titrations) at hospital discharge. Serious in‐hospital safety events were assessed. Among 278 consecutive encounters with HFrEF, 118 met eligibility criteria; 29 (25%) received usual care and 89 (75%) received the GDMT Team intervention. Among usual care encounters, there were no changes in GDMT prescription during hospitalization. In the intervention group, β‐blocker (72% to 88%; P = 0.01), angiotensin receptor–neprilysin inhibitor (6% to 17%; P = 0.03), mineralocorticoid receptor antagonist (16% to 29%; P = 0.05), and triple therapy (9% to 26%; P < 0.01) prescriptions increased during hospitalization. After adjustment for clinically relevant covariates, the GDMT Team was associated with an increase in GDMT optimization score (+0.58; 95% confidence interval +0.09 to +1.07; P = 0.02). There were no serious in‐hospital adverse events.
Conclusions
Non‐cardiovascular hospitalizations are a potentially safe and effective setting for GDMT optimization. A virtual GDMT Team was associated with improved heart failure therapeutic optimization. This implementation strategy warrants testing in a prospective randomized controlled trial.
The IMPLEMENT‐HF pilot study. A physician–pharmacist led fully‐virtual, inpatient guideline‐directed medical therapy (GDMT) Team providing therapeutic optimization suggestions for hospitalized patients with heart failure with reduced ejection fraction (HFrEF) is associated with increases in β‐blocker (BB), mineralocorticoid receptor antagonist (MRA), angiotensin receptor–neprilysin inhibitor (ARNI), and triple therapy rates. HF, heart failure; RASi, renin–angiotensin system inhibitor.
IMPORTANCE: Ascending thoracic aortic disease is an important cause of sudden death in the US, yet most aortic aneurysms are identified incidentally. OBJECTIVE: To develop and validate a clinical ...score to estimate ascending aortic diameter. DESIGN, SETTING, AND PARTICIPANTS: Using an ongoing magnetic resonance imaging substudy of the UK Biobank cohort study, which had enrolled participants from 2006 through 2010, score derivation was performed in 30 018 participants and internal validation in an additional 6681. External validation was performed in 1367 participants from the Framingham Heart Study (FHS) offspring cohort who had undergone computed tomography from 2002 through 2005, and in 50 768 individuals who had undergone transthoracic echocardiography in the Community Care Cohort Project, a retrospective hospital-based cohort of longitudinal primary care patients in the Mass General Brigham (MGB) network between 2001-2018. EXPOSURES: Demographic and clinical variables (11 covariates that would not independently prompt thoracic imaging). MAIN OUTCOMES AND MEASURES: Ascending aortic diameter was modeled with hierarchical group least absolute shrinkage and selection operator (LASSO) regression. Correlation between estimated and measured diameter and performance for identifying diameter 4.0 cm or greater were assessed. RESULTS: The 30 018-participant training cohort (52% women), were a median age of 65.1 years (IQR, 58.6-70.6 years). The mean (SD) ascending aortic diameter was 3.04 (0.31) cm for women and 3.32 (0.34) cm for men. A score to estimate ascending aortic diameter explained 28.2% of the variance in aortic diameter in the UK Biobank validation cohort (95% CI, 26.4%-30.0%), 30.8% in the FHS cohort (95% CI, 26.8%-34.9%), and 32.6% in the MGB cohort (95% CI, 31.9%-33.2%). For detecting individuals with an ascending aortic diameter of 4 cm or greater, the score had an area under the receiver operator characteristic curve of 0.770 (95% CI, 0.737-0.803) in the UK Biobank, 0.813 (95% CI, 0.772-0.854) in the FHS, and 0.766 (95% CI, 0.757-0.774) in the MGB cohorts, although the model significantly overestimated or underestimated aortic diameter in external validation. Using a fixed-score threshold of 3.537, 9.7 people in UK Biobank, 1.8 in the FHS, and 4.6 in the MGB cohorts would need imaging to confirm 1 individual with an ascending aortic diameter of 4 cm or greater. The sensitivity at that threshold was 8.9% in the UK Biobank, 11.3% in the FHS, and 18.8% in the MGB cohorts, with specificities of 98.1%, 99.2%, and 96.2%, respectively. CONCLUSIONS AND RELEVANCE: A prediction model based on common clinically available data was derived and validated to predict ascending aortic diameter. Further research is needed to optimize the prediction model and to determine whether its use is associated with improved outcomes.
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