CD1 lipidomes reveal lipid-binding motifs and size-based antigen-display mechanisms.

The CD1 system binds lipid antigens for display to T cells. Here, we solved lipidomes for the four human CD1 antigen-presenting molecules, providing a map of self-lipid display. Answering a basic question, the detection of >2,000 CD1-lipid complexes demonstrates broad presentation of self-sphingolipids and phospholipids. Whereas peptide antigens are chemically processed, many lipids are presented in an unaltered form. However, each type of CD1 protein differentially edits the self-lipidome to show distinct capture motifs based on lipid length and chemical composition, suggesting general antigen display mechanisms. For CD1a and CD1d, lipid size matches the CD1 cleft volume. CD1c cleft size is more variable, and CD1b is the outlier, where ligands and clefts show an extreme size mismatch that is explained by uniformly seating two small lipids in one cleft. Furthermore, the list of compounds that comprise the integrated CD1 lipidome supports the ongoing discovery of lipid blockers and antigens for T cells.

Recurrent Myocarditis in Patients With Desmosomal Pathogenic Variants: Is Self Antigen Presentation the Link?

Myocarditis is frequently associated with viral infections. Increasing evidence points to an association between myocarditis and inherited cardiomyopathies, though it is unclear whether myocarditis is a driver or an accessory. We present a primary vignette and case series highlighting recurrent myocarditis in patients later found to harbor pathogenic desmosomal variants and provide clinical and basic science context, exploring 2 potentially overlapping hypotheses: that stress induces cellular injury and death in structurally abnormal myocytes and that recurrent viral myocardial and truncated desomosomal protein byproducts as 2 hits could lead to loss of immune tolerance and subsequent autoreactivity.

Tuberculostearic Acid Controls Mycobacterial Membrane Compartmentalization.

The intracellular membrane domain (IMD) is a laterally discrete region of the mycobacterial plasma membrane, enriched in the subpolar region of the rod-shaped cell. Here, we report genome-wide transposon sequencing to discover the controllers of membrane compartmentalization in Mycobacterium smegmatis. The putative gene cfa showed the most significant effect on recovery from membrane compartment disruption by dibucaine. Enzymatic analysis of Cfa and lipidomic analysis of a cfa deletion mutant (Δcfa) demonstrated that Cfa is an essential methyltransferase for the synthesis of major membrane phospholipids containing a C19:0 monomethyl-branched stearic acid, also known as tuberculostearic acid (TBSA). TBSA has been intensively studied due to its abundant and genus-specific production in mycobacteria, but its biosynthetic enzymes had remained elusive. Cfa catalyzed the S-adenosyl-l-methionine-dependent methyltransferase reaction using oleic acid-containing lipid as a substrate, and Δcfa accumulated C18:1 oleic acid, suggesting that Cfa commits oleic acid to TBSA biosynthesis, likely contributing directly to lateral membrane partitioning. Consistent with this model, Δcfa displayed delayed restoration of subpolar IMD and delayed outgrowth after bacteriostatic dibucaine treatment. These results reveal the physiological significance of TBSA in controlling lateral membrane partitioning in mycobacteria. IMPORTANCE As its common name implies, tuberculostearic acid is an abundant and genus-specific branched-chain fatty acid in mycobacterial membranes. This fatty acid, 10-methyl octadecanoic acid, has been an intense focus of research, particularly as a diagnostic marker for tuberculosis. It was discovered in 1934, and yet the enzymes that mediate the biosynthesis of this fatty acid and the functions of this unusual fatty acid in cells have remained elusive. Through a genome-wide transposon sequencing screen, enzyme assay, and global lipidomic analysis, we show that Cfa is the long-sought enzyme that is specifically involved in the first step of generating tuberculostearic acid. By characterizing a cfa deletion mutant, we further demonstrate that tuberculostearic acid actively regulates lateral membrane heterogeneity in mycobacteria. These findings indicate the role of branched fatty acids in controlling the functions of the plasma membrane, a critical barrier for the pathogen to survive in its human host.

Stroke and Noninfective Native Valvular Disease.

PURPOSE OF REVIEW: Embolic stroke of undetermined source is a challenging clinical entity. While less common than atrial fibrillation and endocarditis, many noninfective heart valve lesions have been associated with stroke and may be considered as culprits for cerebral infarcts when other more common causes are excluded. This review discusses the epidemiology, pathophysiology, and management of noninfective valvular diseases that are commonly associated with stroke. RECENT FINDINGS: Calcific debris from degenerating aortic and mitral valves may embolize to the cerebral vasculature causing small- or large-vessel ischemia. Thrombus which may be adherent to calcified valvular structures or left-sided cardiac tumors may also embolize resulting in stroke. Tumors themselves, most commonly myxomas and papillary fibroelastomas, may fragment and travel to the cerebral vasculature. Despite this broad differential, many types of valve diseases are highly comorbid with atrial fibrillation and vascular atheromatous disease. Thus, a high index of suspicion for more common causes of stroke is needed, especially given that treatment for valvular lesions typically involves cardiac surgery whereas secondary prevention of stroke due to occult atrial fibrillation is readily accomplished with anticoagulation.

Deep learning augmented ECG analysis to identify biomarker-defined myocardial injury.

Chest pain is a common clinical complaint for which myocardial injury is the primary concern and is associated with significant morbidity and mortality. To aid providers' decision-making, we aimed to analyze the electrocardiogram (ECG) using a deep convolutional neural network (CNN) to predict serum troponin I (TnI) from ECGs. We developed a CNN using 64,728 ECGs from 32,479 patients who underwent ECG within 2 h prior to a serum TnI laboratory result at the University of California, San Francisco (UCSF). In our primary analysis, we classified patients into groups of TnI < 0.02 or ≥ 0.02 µg/L using 12-lead ECGs. This was repeated with an alternative threshold of 1.0 µg/L and with single-lead ECG inputs. We also performed multiclass prediction for a set of serum troponin ranges. Finally, we tested the CNN in a cohort of patients selected for coronary angiography, including 3038 ECGs from 672 patients. Cohort patients were 49.0% female, 42.8% white, and 59.3% (19,283) never had a positive TnI value (≥ 0.02 µg/L). CNNs accurately predicted elevated TnI, both at a threshold of 0.02 µg/L (AUC = 0.783, 95% CI 0.780-0.786) and at a threshold of 1.0 µg/L (AUC = 0.802, 0.795-0.809). Models using single-lead ECG data achieved significantly lower accuracy, with AUCs ranging from 0.740 to 0.773 with variation by lead. Accuracy of the multi-class model was lower for intermediate TnI value-ranges. Our models performed similarly on the cohort of patients who underwent coronary angiography. Biomarker-defined myocardial injury can be predicted by CNNs from 12-lead and single-lead ECGs.

A terpene nucleoside from M. tuberculosis induces lysosomal lipid storage in foamy macrophages.

Induction of lipid-laden foamy macrophages is a cellular hallmark of tuberculosis (TB) disease, which involves the transformation of infected phagolysosomes from a site of killing into a nutrient-rich replicative niche. Here, we show that a terpenyl nucleoside shed from Mycobacterium tuberculosis, 1-tuberculosinyladenosine (1-TbAd), caused lysosomal maturation arrest and autophagy blockade, leading to lipid storage in M1 macrophages. Pure 1-TbAd, or infection with terpenyl nucleoside-producing M. tuberculosis, caused intralysosomal and peribacillary lipid storage patterns that matched both the molecules and subcellular locations known in foamy macrophages. Lipidomics showed that 1-TbAd induced storage of triacylglycerides and cholesterylesters and that 1-TbAd increased M. tuberculosis growth under conditions of restricted lipid access in macrophages. Furthermore, lipidomics identified 1-TbAd-induced lipid substrates that define Gaucher's disease, Wolman's disease, and other inborn lysosomal storage diseases. These data identify genetic and molecular causes of M. tuberculosis-induced lysosomal failure, leading to successful testing of an agonist of TRPML1 calcium channels that reverses lipid storage in cells. These data establish the host-directed cellular functions of an orphan effector molecule that promotes survival in macrophages, providing both an upstream cause and detailed picture of lysosome failure in foamy macrophages.

Biotin-dependent cell envelope remodelling is required for Mycobacterium abscessus survival in lung infection.

Mycobacterium abscessus is an emerging pathogen causing lung infection predominantly in patients with underlying structural abnormalities or lung disease and is resistant to most frontline antibiotics. As the pathogenic mechanisms of M. abscessus in the context of the lung are not well-understood, we developed an infection model using air-liquid interface culture and performed a transposon mutagenesis and sequencing screen to identify genes differentially required for bacterial survival in the lung. Biotin cofactor synthesis was required for M. abscessus growth due to increased intracellular biotin demand, while pharmacological inhibition of biotin synthesis prevented bacterial proliferation. Biotin was required for fatty acid remodelling, which increased cell envelope fluidity and promoted M. abscessus survival in the alkaline lung environment. Together, these results indicate that biotin-dependent fatty acid remodelling plays a critical role in pathogenic adaptation to the lung niche, suggesting that biotin synthesis and fatty acid metabolism might provide therapeutic targets for treatment of M. abscessus infection.

Toward ECG-based analysis of hypertrophic cardiomyopathy: a novel ECG segmentation method for handling abnormalities.

OBJECTIVE: Abnormalities in impulse propagation and cardiac repolarization are frequent in hypertrophic cardiomyopathy (HCM), leading to abnormalities in 12-lead electrocardiograms (ECGs). Computational ECG analysis can identify electrophysiological and structural remodeling and predict arrhythmias. This requires accurate ECG segmentation. It is unknown whether current segmentation methods developed using datasets containing annotations for mostly normal heartbeats perform well in HCM. Here, we present a segmentation method to effectively identify ECG waves across 12-lead HCM ECGs. METHODS: We develop (1) a web-based tool that permits manual annotations of P, P', QRS, R', S', T, T', U, J, epsilon waves, QRS complex slurring, and atrial fibrillation by 3 experts and (2) an easy-to-implement segmentation method that effectively identifies ECG waves in normal and abnormal heartbeats. Our method was tested on 131 12-lead HCM ECGs and 2 public ECG sets to evaluate its performance in non-HCM ECGs. RESULTS: Over the HCM dataset, our method obtained a sensitivity of 99.2% and 98.1% and a positive predictive value of 92% and 95.3% when detecting QRS complex and T-offset, respectively, significantly outperforming a state-of-the-art segmentation method previously employed for HCM analysis. Over public ECG sets, it significantly outperformed 3 state-of-the-art methods when detecting P-onset and peak, T-offset, and QRS-onset and peak regarding the positive predictive value and segmentation error. It performed at a level similar to other methods in other tasks. CONCLUSION: Our method accurately identified ECG waves in the HCM dataset, outperforming a state-of-the-art method, and demonstrated similar good performance as other methods in normal/non-HCM ECG sets.

Acute coronary syndrome in patients with hemophilia: a delicate balancing act.

Therapeutic advances have resulted in increased life expectancy in patients with hemophilia. Consequently, the prevalence of coronary artery disease in this population is increasing. Little is known about the optimal management of acute coronary syndrome in these patients. Current guidelines for the management of this condition are based mainly on expert opinion and generally recommend administration of the clotting factor prior to the anticoagulant, antiplatelet, and interventional therapies. We report a case that illustrates the potential harm that may come from this approach: evolution of non-ST-segment elevation acute coronary syndrome into ST-elevation acute coronary syndrome during the administration of recombinant clotting factor. We review available literature and describe the refined informatics-based guidelines for managing acute coronary syndrome in patients with hemophilia we developed in response to the presented clinical case. We propose adopting this novel informatics-based approach, which aids in the identification and early treatment of these patients, operationalizes timely involvement of hematology experts, and gathers data for further study.

Identifying risk of adverse outcomes in COVID-19 patients via artificial intelligence-powered analysis of 12-lead intake electrocardiogram.

BACKGROUND: Adverse events in COVID-19 are difficult to predict. Risk stratification is encumbered by the need to protect healthcare workers. We hypothesize that artificial intelligence (AI) can help identify subtle signs of myocardial involvement in the 12-lead electrocardiogram (ECG), which could help predict complications. OBJECTIVE: Use intake ECGs from COVID-19 patients to train AI models to predict risk of mortality or major adverse cardiovascular events (MACE). METHODS: We studied intake ECGs from 1448 COVID-19 patients (60.5% male, aged 63.4 ± 16.9 years). Records were labeled by mortality (death vs discharge) or MACE (no events vs arrhythmic, heart failure [HF], or thromboembolic [TE] events), then used to train AI models; these were compared to conventional regression models developed using demographic and comorbidity data. RESULTS: A total of 245 (17.7%) patients died (67.3% male, aged 74.5 ± 14.4 years); 352 (24.4%) experienced at least 1 MACE (119 arrhythmic, 107 HF, 130 TE). AI models predicted mortality and MACE with area under the curve (AUC) values of 0.60 ± 0.05 and 0.55 ± 0.07, respectively; these were comparable to AUC values for conventional models (0.73 ± 0.07 and 0.65 ± 0.10). There were no prominent temporal trends in mortality rate or MACE incidence in our cohort; holdout testing with data from after a cutoff date (June 9, 2020) did not degrade model performance. CONCLUSION: Using intake ECGs alone, our AI models had limited ability to predict hospitalized COVID-19 patients' risk of mortality or MACE. Our models' accuracy was comparable to that of conventional models built using more in-depth information, but translation to clinical use would require higher sensitivity and positive predictive value. In the future, we hope that mixed-input AI models utilizing both ECG and clinical data may be developed to enhance predictive accuracy.

Genetic modifiers regulating DNA replication and double-strand break repair are associated with differences in mammary tumors in mouse models of Li-Fraumeni syndrome.

Breast cancer is the most common tumor among women with inherited variants in the TP53 tumor suppressor, but onset varies widely suggesting interactions with genetic or environmental factors. Rodent models haploinsufficent for Trp53 also develop a wide variety of malignancies associated with Li-Fraumeni syndrome, but BALB/c mice are uniquely susceptible to mammary tumors and is genetically linked to the Suprmam1 locus on chromosome 7. To define mechanisms that interact with deficiencies in p53 to alter susceptibility to mammary tumors, we fine mapped the Suprmam1 locus in females from an N2 backcross of BALB/cMed and C57BL/6J mice. A major modifier was localized within a 10 cM interval on chromosome 7. The effect of the locus on DNA damage responses was examined in the parental strains and mice that are congenic for C57BL/6J alleles on the BALB/cMed background (SM1-Trp53+/-). The mammary epithelium of C57BL/6J-Trp53+/- females exhibited little radiation-induced apoptosis compared to BALB/cMed-Trp53+/- and SM1-Trp53+/- females indicating that the Suprmam1B6/B6 alleles could not rescue repair of radiation-induced DNA double-strand breaks mostly relying on non-homologous end joining. In contrast, the Suprmam1B6/B6 alleles in SM1-Trp53+/- mice were sufficient to confer the C57BL/6J-Trp53+/- phenotypes in homology-directed repair and replication fork progression. The Suprmam1B6/B6 alleles in SM1-Trp53+/- mice appear to act in trans to regulate a panel of DNA repair and replication genes which lie outside the locus.

Implementation of a fully remote randomized clinical trial with cardiac monitoring.

Background: The coronavirus disease 2019 (COVID-19) pandemic has challenged researchers performing clinical trials to develop innovative approaches to mitigate infectious risk while maintaining rigorous safety monitoring. Methods: In this report we describe the implementation of a novel exclusively remote randomized clinical trial (ClinicalTrials.gov NCT04354428) of hydroxychloroquine and azithromycin for the treatment of the SARS-CoV-2-mediated COVID-19 disease which included cardiovascular safety monitoring. All study activities were conducted remotely. Self-collected vital signs (temperature, respiratory rate, heart rate, and oxygen saturation) and electrocardiographic (ECG) measurements were transmitted digitally to investigators while mid-nasal swabs for SARS-CoV-2 testing were shipped. ECG collection relied on a consumer device (KardiaMobile 6L, AliveCor Inc.) that recorded and transmitted six-lead ECGs via participants' internet-enabled devices to a central core laboratory, which measured and reported QTc intervals that were then used to monitor safety. Results: Two hundred and thirty-one participants uploaded 3245 ECGs. Mean daily adherence to the ECG protocol was 85.2% and was similar to the survey and mid-nasal swab elements of the study. Adherence rates did not differ by age or sex assigned at birth and were high across all reported race and ethnicities. QTc prolongation meeting criteria for an adverse event occurred in 28 (12.1%) participants, with 2 occurring in the placebo group, 19 in the hydroxychloroquine group, and 7 in the hydroxychloroquine + azithromycin group. Conclusions: Our report demonstrates that digital health technologies can be leveraged to conduct rigorous, safe, and entirely remote clinical trials.

Echocardiographic assessment of pulmonary arterial capacitance predicts mortality in pulmonary hypertension.

BACKGROUND: Pulmonary arterial capacitance (PAC) is one of the strongest predictors of clinical outcomes in patients with pulmonary hypertension (PH). We examined the value of an echocardiographic surrogate for PAC (ePAC) as a predictor of mortality in patients with PH. METHODS: We performed a retrospective study of 302 patients with PH managed at a PH comprehensive care center over a cumulative follow-up time of 858 patient-years. Charts from 2004 to 2018 were reviewed to identify patients in whom a right heart catheterization (RHC) was performed within two months of an echocardiogram. Standard invasive, non-invasive, functional, and biochemical prognostic markers were extracted from the time of RHC. The primary outcome was all-cause mortality. Cox proportional hazards models were used to model the time from RHC to the primary outcome or last medical contact. RESULTS: Variables associated with all-cause mortality included ePAC [standardized hazard ratio (HR) 0.68, 95% CI 0.48-0.98, p = 0.036], RHC-PAC (HR 0.68, 95% CI 0.48-0.96, p = 0.027), echocardiographic pulmonary vascular resistance (HR 1.29, 95% CI 1.05-1.60, p = 0.017), six-minute walk distance (HR 0.43, 95% CI 0.23-0.82, p = 0.01), and B-type natriuretic peptide (HR 1.29, 95% CI 1.03-1.62, p = 0.027). In multivariable-adjusted Cox analysis, ePAC predicted all-cause mortality independently of age, gender, and multiple comorbidities. There was a graded and stepwise association between low (<0.15 cm/mmHg), medium (0.15-0.25 cm/mmHg), and high (>0.25 cm/mmHg) tertiles of ePAC and all-cause mortality. CONCLUSIONS: We have demonstrated that ePAC is a readily available echocardiographic marker that independently predicts mortality in PH, and have provided clinically relevant ranges by which to risk-stratify patients and predict mortality.

Evolution of acute ST-segment elevation myocardial infarction in a patient with ventricular preexcitation.

Wolff-Parkinson-White pattern is a relatively common electrocardiographic phenomenon caused by accessory atrioventricular (AV) conduction, which can make the diagnosis of acute myocardial infarction challenging. There is little existing literature regarding the interpretation of electrocardiograms in patients with accessory AV conduction pathways who present with acute myocardial infarction. We describe a case of electrocardiographic evolution of acute ST-segment elevation myocardial infarction in a patient with Wolff-Parkinson-White pattern, review pseudo-infarction patterns, and discuss proposed mechanisms for these repolarization abnormalities.