Citations

Together, single-cell technologies and systems biology have been used to investigate previously unanswerable questions in biomedicine with unparalleled detail. Despite these advances, gaps in analytical capacity remain. Machine learning, which has revolutionized biomedical imaging analysis, drug discovery, and systems biology, is an ideal strategy to fill these gaps in single-cell studies. Machine learning additionally has proven to be remarkably synergistic with single-cell data because it remedies unique challenges while capitalizing on the positive aspects of single-cell data. In this review, we describe how systems-biology algorithms have layered machine learning with biological components to provide systems level analyses of single-cell omics data, thus elucidating complex biological mechanisms. Accordingly, we highlight the trifecta of single-cell, systems-biology, and machine-learning approaches and illustrate how this trifecta can significantly contribute to five key areas of scientific research: cell trajectory and identity, individualized medicine, pharmacology, spatial omics, and multi-omics. Given its success to date, the systems-biology, single-cell omics, and machine-learning trifecta has proven to be a potent combination that will further advance biomedical research.

AbstractIntroductionThe efficacy of cardiac resynchronization therapy (CRT) has been widely studied in the medical literature; however, about 30% of candidates fail to respond to this treatment strategy. Smart computational approaches based on clinical data can help expose hidden patterns useful for identifying CRT responders.MethodsWe retrospectively analyzed the electronic health records of 1664 patients who underwent CRT procedures from January 1, 2002 to December 31, 2017. An ensemble of ensemble (EoE) machine learning (ML) system composed of a supervised and an unsupervised ML layers was developed to generate a prediction model for CRT response.ResultsWe compared the performance of EoE against traditional ML methods and the state‐of‐the‐art convolutional neural network (CNN) model trained on raw electrocardiographic (ECG) waveforms. We observed that the models exhibited improvement in performance as more features were incrementally used for training. Using the most comprehensive set of predictors, the performance of the EoE model in terms of the area under the receiver operating characteristic curve and F1‐score were 0.76 and 0.73, respectively. Direct application of the CNN model on the raw ECG waveforms did not generate promising results.ConclusionThe proposed CRT risk calculator effectively discriminates which heart failure (HF) patient is likely to respond to CRT significantly better than using clinical guidelines and traditional ML methods, thus suggesting that the tool can enhanced care management of HF patients by helping to identify high‐risk patients.

SummaryBackgroundAlcohol use and alcohol‐associated liver disease (ALD) burden are increasing in young individuals.AimTo assess host factors associated with this burden.MethodsNational Health and Nutrition Examination Survey (NHANES), National Inpatient Sample (NIS), and United Network for Organ Sharing (UNOS) databases (2006‐2016) were used to identify individuals with harmful alcohol use, ALD‐related admissions, and ALD‐related LT listings respectively.ResultsOf 15 981 subjects in NHANES database, weighted prevalence of harmful alcohol use was 17.7%, 29.3% in <35 years (G1) versus 16.9% in 35‐64 years (G2) versus 5.1% in ≥65 years (G3). Alcohol use was about 11 and 4.7 folds higher in G1 and G2 versus G3, respectively. Male gender and Hispanic race associated with harmful alcohol use. Of 593 600 ALD admissions (5%, 77%, and 18% in G1‐G3 respectively), acute on chronic liver failure (ACLF) occurred in 7.2%, (7.2 in G2 vs 6.7% in G1 and G3, P < 0.001). After controlling for other variables, ACLF development among ALD hospitalizations was higher by 14% and 10% in G1 and G2 versus G3, respectively. Female gender and Hispanic race were associated with increased ACLF risk by 8% and 17% respectively. Of 20,245 ALD LT listings (3.4%, 84.4%, and 12.2% in G1‐G3 respectively), ACLF occurred in 28% candidates. Risk of severe (grade 2 or 3) ACLF was higher by about 1.7 fold in G1, 1.5 fold in females and 20% in Hispanics.ConclusionYoung age, female gender, and Hispanic race are independently associated with ALD‐related burden and ACLF in the United States. If these findings are validated in prospective studies, strategies will be needed to reduce alcohol use in high risk individuals to reduce burden from ALD.

ObjectiveHistology reveals that early active multiple sclerosis lesions can be classified into 3 main interindividually heterogeneous but intraindividually stable immunopathological patterns of active demyelination (patterns I–III). In patterns I and II, a T‐cell‐ and macrophage‐associated demyelination is suggested, with pattern II only showing signs of a humoral immune response. Pattern III is characterized by inflammatory lesions with an oligodendrocyte degeneration. Patterns suggest pathogenic heterogeneity, and we postulated that they have distinct magnetic resonance imaging (MRI) correlates that may serve as biomarkers.MethodsWe evaluated in an international collaborative retrospective cohort study the MRI lesion characteristics of 789 conventional prebiopsy and follow‐up MRIs in relation to their histopathologically classified immunopathological patterns (n = 161 subjects) and lesion edge features (n = 112).ResultsA strong association of a ringlike enhancement and a hypointense T2‐weighted (T2w) rim with patterns I and II, but not pattern III, was observed. Only a fraction of pattern III patients showed a ringlike enhancement, and this was always atypical. Ringlike enhancement and T2w rims colocalized, and ringlike enhancement showed a strong association with macrophage rims as shown by histology. A strong concordance of MRI lesion characteristics, meaning that different lesions showed the same features, was found when comparing biopsied and nonbiopsied lesions at a given time point, indicating lesion homogeneity within individual patients.InterpretationWe provide robust evidence that MRI characteristics reflect specific morphological features of multiple sclerosis immunopatterns and that ringlike enhancement and T2w hypointense rims might serve as a valuable noninvasive biomarker to differentiate pathological patterns of demyelination. ANN NEUROL 2021;90:440–454

Introduction: As the US population ages and indications for cardiac device implantation expand, there is a concomitant increase in patients undergoing lead removal/extraction (LR/E).. We sought to examine trends in outcomes and complications associated with LR/E. Methods: We conducted a retrospective analysis using data from a large U.S. commercial insurance database (privately insured and Medicare Advantage patients) identifying all patients undergoing LR/E between 2004 and 2013 with at least one year continuous medical plan enrollment prior to LR/E (to identify baseline comorbidities). Using ICD9 codes and CPT codes, major complications (hemorrhage requiring transfusion, vascular injury, pericardial complications, respiratory complications, cerebrovascular complications, and requirement for cardiac surgery) associated with LR/E and 30-day readmission rates were evaluated. Results: Among 42,878 patients who underwent LR/E (median age of 62 ( 54, 72) years, 70% male); approximately 1 in 40 experienced a major adverse event (2.4%) during the study period. Respiratory complications were the most common complication and 311 patients required cardiac surgery. 30-day readmission occurred in 11.1% of the total population. The most common reasons for readmission were heart failure exacerbation (18.7%) and device related complications (13.2%). Conclusion: The observed complication rates after LE/R in clinical practice are similar to those seen in recent clinical trials and have been relatively stable over the past 10 years.

Introduction: Patients with congenital heart disease (CHD) frequently require implantable cardiac devices. Device infection or malfunction may necessitate lead extraction. Extraction may be challenging due to long lead dwell times, anatomic abnormalities, and prior cardiac surgery. Little is known about extraction outcomes in the CHD population. Methods and Results: This retrospective study included 41 CHD patients and 82 age and gender matched controls that underwent lead extractions at two centers between 2001-2014. Only patients with leads older than 12 months were included. There were 79 leads in CHD patients and 150 in controls. Patients with CHD had a mean age of 39±17 years at extraction and on average their leads had been implanted for 81±84 months, this was not significantly different from the control group. Eighty eight percent of CHD patients had 1 or more cardiac surgeries as compared to only 22% of controls (p<0.001). The number of abandoned leads was also significantly different with 16 abandoned leads in the CHD group and 3 in controls (p<0.001). There was no statistically significant difference in extraction techniques between the groups. Complete extraction was achieved in 94% of patients in both groups. There were no CHD group complications. Control group complications included 3 SVC lacerations requiring sternotomy (one was fatal), and 1 ventricular perforations with tamponade requiring sternotomy. None of these patients had a history of cardiac surgery. The average age of leads in patients with a complication was 15.3 years which was older than the mean lead age seen in the CHD and control populations which was 6.75 and 4.6 years respectively. Conclusions: Lead extraction can be safely performed in patients with CHD. Despite anatomic abnormalities and previous cardiac surgery, the outcome of lead extraction in patients with CHD is comparable to controls. Prior cardiac surgery may lower the risk for extraction complications.

Introduction Multi-detector computed tomography (MDCT) is commonly used to identify pulmonary vein and left atrial anatomy prior to catheter ablation for atrial fibrillation (CAAF). Additionally, transesophageal echocardiography (TEE) is utilized to exclude left atrial/left atrial appendage thrombus (ICT). Whether MDCT alone can be used to exclude thrombus obviating the need for TEE is unknown. Methods All Pts referred for CAAF at Mayo Clinic between March 2004 and October 2006 were included. Clinical data (including CHADS score), 64 slice MDCT (non-ECG gated), TEE and intra-cardiac echocardiograph (ICE) were all performed and recorded. Image data was reviewed independently and blinded. The left atrial appendage (LAA) was defined as fully opacified or underfilled. An underfilled LAA was further interrogated using a region of interest over the filling defect and mean attenuation in Hounsfield Units (HU) were recorded. Results In total 400 Pts (mean age 56 ± 10 yrs; 76% male; EF 56 ± 10 % ) were included. 362 had no ICT by TEE nor filling defect by MDCT. 38 patients had an underfilled LAA in whom ICT was confirmed by TEE in 7. Sensitivity and specificity of MDCT for ICT was 100% and 92% respectively with a NPV of 100%. In 19 Pts with underfilled LAA’s, a mean LAA emptying velocity was found to be significantly reduced at 26 cm/s (6 – 61 cm/s). Those with a thrombus had a mean attenuation value below 70 HU. CHADS2 score was higher (2.0 versus 1.0) in Pts with LAA filling defect versus those without LAA filling defect. All Pts with confirmed thrombus were taking Warfarin. ICT was not seen in any Pts aged <52 yrs with CHADS score ≤1. Conclusions Sensitivity and specificity of MDCT for detection of LAA thrombus is high. LAA filling defects on MDCT correlate with low emptying velocities by TEE and low attenuation value in HU. These data would suggest that in the absence of MDCT filling defect, no further imaging is required. TEE should be utilized prior to CAAF to investigate MDCT filling defects. Multidetector Computed Tomography for the Detection of LAA Thrombus

Background : Lipid lowering therapy reduces mortality in patients with both ischemic and nonischemic cardiomyopathies and recently has been shown to decrease ICD shocks. Radiofrequency ablation (RFA) of recurrent VT in patients with an ICD also reduces shocks following intervention. It is unclear if statin therapy after VT RFA will further impact ICD shock rates. Methods : All patients from 1993–2005 who underwent a RFA procedure for recurrent VT at the Mayo Clinic with an ICD were included. Patient records were extracted for medical and procedural details and all ICD interrogations were reviewed for VT recurrence and therapies. Results: 63 patients (age 62±15 years) were followed over 3.9±3.6 years. Comorbid diseases included: coronary artery disease 37(58%, 34 prior myocardial infarction), ARVD/C 6(10%), nonischemic dilated cardiomyopathy 7(11%), moderate-severe valve disease 14(22%), hypertension 34(54%), and hyperlipidemia 35(56%). Ejection fraction was <0.35 in 34(56%). VT was induced in all patients (LV 55 (LVOT 1), RV 8 (RVOT 3) with multiple inducible VTs in 21(33%). VT was noninducible after RFA in 39(62%) patients. Dismissal medications included: statins 19(30%), beta blockers 40(66%), ACE/ARB 37(61%), diuretics 34(55%), and digoxin 23(37%). 5-year overall survival was 63%(95% CI 55–71). Age, diabetes, and renal insufficiency were associated with increased post ablation mortality, with no medication improving survival. 5-year survival free of ICD shocks was 31%(95% CI 24–38). Only statin therapy at discharge was associated with a decreased risk of ICD shocks [5(26%) versus 26(59%), p=0.020]. 7 additional patients received statins during follow-up, but not at discharge, of these 5(71%) had shocks. Conclusion : Statin use at discharge in patients with an ICD undergoing RFA for refractory VT significantly reduced recurrent ventricular arrhythmias and ICD shocks. Although the mechanism underlying the effects of statins on arrhythmic recurrence early after RFA requires further study, these data support aggressive therapy of the underlying substrate responsible for the VT.