Citations

AbstractEpilepsy syndromes have been recognized for >50 years, as distinct electroclinical phenotypes with therapeutic and prognostic implications. Nonetheless, no formally accepted International League Against Epilepsy (ILAE) classification of epilepsy syndromes has existed. The ILAE Task Force on Nosology and Definitions was established to reach consensus regarding which entities fulfilled criteria for an epilepsy syndrome and to provide definitions for each syndrome. We defined an epilepsy syndrome as “a characteristic cluster of clinical and electroencephalographic features, often supported by specific etiological findings (structural, genetic, metabolic, immune, and infectious).” The diagnosis of a syndrome in an individual with epilepsy frequently carries prognostic and treatment implications. Syndromes often have age‐dependent presentations and a range of specific comorbidities. This paper describes the guiding principles and process for syndrome identification in both children and adults, and the template of clinical data included for each syndrome. We divided syndromes into typical age at onset, and further characterized them based on seizure and epilepsy types and association with developmental and/or epileptic encephalopathy or progressive neurological deterioration. Definitions for each specific syndrome are contained within the corresponding position papers.

Abstract The International League Against Epilepsy (ILAE) Task Force on Nosology and Definitions proposes a classification and definition of epilepsy syndromes in the neonate and infant with seizure onset up to 2 years of age. The incidence of epilepsy is high in this age group and epilepsy is frequently associated with significant comorbidities and mortality. The licensing of syndrome specific antiseizure medications following randomized controlled trials and the development of precision, gene‐related therapies are two of the drivers defining the electroclinical phenotypes of syndromes with onset in infancy. The principal aim of this proposal, consistent with the 2017 ILAE Classification of the Epilepsies, is to support epilepsy diagnosis and emphasize the importance of classifying epilepsy in an individual both by syndrome and etiology. For each syndrome, we report epidemiology, clinical course, seizure types, electroencephalography (EEG), neuroimaging, genetics, and differential diagnosis. Syndromes are separated into self‐limited syndromes, where there is likely to be spontaneous remission and developmental and epileptic encephalopathies , diseases where there is developmental impairment related to both the underlying etiology independent of epileptiform activity and the epileptic encephalopathy. The emerging class of etiology‐specific epilepsy syndromes, where there is a specific etiology for the epilepsy that is associated with a clearly defined, relatively uniform, and distinct clinical phenotype in most affected individuals as well as consistent EEG, neuroimaging, and/or genetic correlates, is presented. The number of etiology‐defined syndromes will continue to increase, and these newly described syndromes will in time be incorporated into this classification. The tables summarize mandatory features, cautionary alerts, and exclusionary features for the common syndromes. Guidance is given on the criteria for syndrome diagnosis in resource‐limited regions where laboratory confirmation, including EEG, MRI, and genetic testing, might not be available.

Abstract BackgroundFormalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data.MethodsWe optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics.ResultsSamples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation < 0.75), low number of reads mapped to gene regions (< 25 million), or low number of detectable genes (11,400 # of detected genes with CPM > 2). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.7 ng/ul and 1.68 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.58 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.803 in predicting QC status (pass/fail) of FFPE samples. ConclusionsWe provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.8 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis.

Introduction: Conduction disturbance after transcatheter aortic valve replacement (TAVR) remains a common complication. Predictive tools to identify conduction disturbance requiring pacing are limited. Our main objective was to develop a deep learning model to predict the need for a permanent pacemaker. Hypothesis: An electrocardiogram (ECG) based deep learning algorithm can predict the need for permanent pacemaker post TAVR. Methods: We evaluated patients who had TAVR at Mayo Clinic between June 2010 and May 2021. Digital ECGs done on the TAVR date or within 24 hours post procedure were partitioned into training, validation, and testing datasets. We trained a deep learning algorithm on the training data and optimized hyperparameters against the validation data. All model performance metrics are based on the reserved test data that were estimated once model architecture was optimized. Need for permanent pacemaker, defined as pacemaker placement due to development of conduction disturbance post TAVR and at least 1% ventricular pacing on device interrogation done at least 2 weeks post pacemaker implantation, was the training target. Results: A total of 3021 patients were evaluated for inclusion and 2,407 cases were available for modeling (exclusions: prior pacemaker (n=419), unsuccessful TAVR (n=27) and no ECG within the pre-specified period (n=168)). Overall, the median age was 82 (Q1: 76, Q3: 86) and 41% were female. In the withheld test data, 15% had a permanent pacemaker with at least 1% ventricular pacing. The algorithm detected the need for pacemaker in the test set with an AUC of 0.83 (95% CI: 0.73 to 0.92). Accuracy, sensitivity, specificity, positive and negative predictive were 80%, 72%, 81%, 41% and 94%, respectively. Conclusions: This study demonstrates the ability of a deep learning model based on ECG data to assist in making the decision to implant a pacemaker following TAVR with a high negative predictive value. Larger validation studies are warranted.

Introduction: Obesity is common in heart failure with preserved ejection fraction (HFpEF) and is directly linked with lower levels of physical activity (PA). Visceral adiposity (VAT) is more common in HFpEF than controls and may play a role in its pathogenesis, characterized by impaired exercise capacity (peak VO 2 ). The direct relationship between VAT and PA in HFpEF is unknown. Hypothesis: Compared to controls, HFpEF patients will have excess regional adiposity (VAT, subcutaneous (SAT), and intramuscular (IMAT)), and these fat depots will be associated with lower levels of chronic physical activity. Methods: HFpEF patients (n=51; age 70±9) and non-HFpEF controls (n=49; age 65±5) prospectively underwent body composition measurement by dual-energy x-ray absorptiometry and magnetic resonance imaging. Peak VO 2 was measured by standard cardiopulmonary exercise testing. PA was monitored continuously via accelerometry over two weeks. Data were binned in arbitrary accelerometry units, averaged and stored in 30-second epochs (counts per epoch, CPE). Models were adjusted for age, sex, and ideal body weight. Results: HFpEF were less active overall (3.15±0.80 vs 3.59±0.73 CPE), had less moderate intensity PA (10.13±0.04 vs 10.15±0.03 CPE), and less morning (3.83±1.15 vs 4.24±1.09 CPE) and afternoon (3.84± 1.20 vs 4.53± 0.97 CPE) (p<0.05 for all) PA. Patients with HFpEF spent a greater proportion of time sedentary (0.71±0.08 vs 0.67±0.08 CPE) and less time in moderate (0.04±0.03 vs 0.06±0.03 CPE) and vigorous (0.02±0.01 vs 0.03±0.03 CPE) PA (p<0.01 for all). Chronic PA was significantly associated with regional fat depots (VAT β= -0.003, 95% CI: -0.004-0.001; SAT β= -0.003, 95%CI: -0.004-0.001; IMAT β=-0.02, 95% CI: -0.04—0.01) as a combined cohort (p<0.01 for all). Muscle quality (β=0.28, 95%CI: 0.15-0.40), peak VO 2 (β=0.08, 95% CI: 0.03-0.13), and peak watts (β=0.01, 95% CI: -0.004-0.02) were associated with PA in HFpEF only (p≤0.01 for all). Conclusions: The amount and pattern of PA differs between HFpEF and controls, as do relationships between regional fat depots and PA, and the relationship of PA and peak VO 2 . Further investigation is needed to better understand the temporality and mechanisms related to the pathophysiology and severity of HFpEF.

Background: Myocarditis may predispose to dilated cardiomyopathy (DCM) and sudden cardiac death (SCD). Familial data indicate a potential genetic susceptibility shared with arrhythmogenic cardiomyopathy (ACM). We present the first large-scale genotype-phenotype study of adults with acute myocarditis. Methods: A cohort comprising 336 consecutive patients with acute myocarditis was enrolled in London and Maastricht. All participants underwent targeted DNA sequencing for well-characterised cardiomyopathy-associated genes. The burden of rare protein altering variants (PAV) in ACM genes, DCM genes, and TTN specifically, were compared with local healthy controls sequenced on the same platform (n=1053). Case ascertainment was assessed against national hospital admission data. Results: We identified rare protein-altering variants in 23% of cases compared to 16% in controls (Δ+6.8%; p=0.021), with rare truncating variants (tv) in 6% of cases compared to <1% of controls ((Δ+5%; p=0.0097). In London (n=230; median left ventricular ejection fraction (LVEF) 63%), which was representative of national myocarditis admissions, 4.8% of cases carried rare tv, particularly within ACM genes (3% cases vs 0% controls; odds ratio 8.2; p=0.001). This was predominantly driven by desmoplakin (DSP)-tv in patients with normal LVEF. In Maastricht (n=106; median LVEF 30%), rare tv in DCM genes were enriched, particularly TTN-tv found in 7% (all with LVEF<50%) compared to 1% in controls (OR 3.6; p=0.0116). During a median follow-up of 1.9 years, all-cause mortality was greatest in those with a DCM variant (18% vs 4% with no variant; OR 5.0; p=0.004). Conclusion: We identified enrichment of cardiomyopathy gene variants in acute myocarditis patients, dominated by DSP-tv in those with normal LVEF and TTN-tv in those with reduced LVEF. Incorporation of genetic testing may be beneficial to identify such high-risk individuals and guide family screening in acute myocarditis patients.

Asthma is a chronic inflammatory lung disease with intermittent flares predominately mediated through memory T cells. Yet, the identity of long-term memory cells that mediate allergic recall responses is not well defined. In this report, using a mouse model of chronic allergen exposure followed by an allergen-free rest period, we characterized a subpopulation of CD4 + T cells that secreted IL-9 as an obligate effector cytokine. IL-9–secreting cells had a resident memory T cell phenotype, and blocking IL-9 during a recall challenge or deleting IL-9 from T cells significantly diminished airway inflammation and airway hyperreactivity. T cells secreted IL-9 in an allergen recall–specific manner, and secretion was amplified by IL-33. Using scRNA-seq and scATAC-seq, we defined the cellular identity of a distinct population of T cells with a proallergic cytokine pattern. Thus, in a recall model of allergic airway inflammation, IL-9 secretion from a multicytokine-producing CD4 + T cell population was required for an allergen recall response.

AbstractThe efficacy of COVID‐19 convalescent plasma (CCP) as a treatment for hospitalized patients with COVID‐19 remains somewhat controversial; however, many studies have not evaluated CCP documented to have high neutralizing antibody titer by a highly accurate assay. To evaluate the correlation of the administration of CCP with titer determined by a live viral neutralization assay with 7‐ and 28‐day death rates during hospitalization, a total of 23 118 patients receiving a single unit of CCP were stratified into two groups: those receiving high titer CCP (>250 50% inhibitory dilution, ID50; n = 13 636) or low titer CCP (≤250 ID50; n = 9482). Multivariable Cox regression was performed to assess risk factors. Non‐intubated patients who were transfused with high titer CCP showed 1.1% and 1.7% absolute reductions in overall 7‐ and 28‐day death rates, respectively, compared to those non‐intubated patients receiving low titer CCP. No benefit of CCP was observed in intubated patients. The relative benefit of high titer CCP was confirmed in multivariable Cox regression. Administration of CCP with high titer antibody content determined by live viral neutralization assay to non‐intubated patients is associated with modest clinical efficacy. Although shown to be only of modest clinical benefit, CCP may play a role in the future should viral variants develop that are not neutralized by other available therapeutics.

Abstract Background: Hormone receptor-positive (HR+) breast cancer (BC) accounts for ~60-70% of all BC cases. CDK4/6i combined with endocrine therapy (ET) is the standard of care for first- and second-line therapy of patients with HR+ metastatic breast cancer (MBC) based on substantial improvements in progression free survival (PFS) and overall survival compared to ET alone. Unfortunately, most patients (pts) develop resistance to CDK4/6i. The mechanisms underlying CDK4/6i resistance have not been fully elucidated. Robust in vivo CDK4/6i resistant animal models from pts with de novo and acquired CDK 4/6i resistance are lacking. Patient-derived xenografts (PDXs) are important preclinical tools in oncology to advance our understanding of cancer biology and to evaluate drug response phenotypes. Unfortunately, the establishment of sustainable PDXs from pts with HR+ BC is much more difficult than from HR-negative BC. In order to obtain clinically relevant models that can be utilized to better understand mechanisms of primary and acquired resistance to ET and CDK4/6i, we report the development of PDXs from a prospective study in which percutaneous biopsies were obtained from women receiving palbociclib for the treatment of HR+ advanced or MBC (PROMISE; NCT03281902). Methods: PROMISE (Prospective Study to Evaluate the Role of Tumor Sequencing in Women Receiving Palbociclib for Advanced Hormone Receptor (HR)-Positive Breast Cancer) is a prospective trial which enrolled pts with HR+, HER2-negative MBC who planned to start treatment with palbociclib and letrozole (1st line [FL]) or palbociclib and fulvestrant (2nd line [SL]). For pts enrolled at Mayo Clinic Rochester (MCR), serial tumor biopsies were obtained prior to the start of treatment and at disease progression to establish PDXs. Because baseline take rate was low, we amended the protocol to attempt PDX generation after the 2nd cycle (C2) of therapy. Tissues were received within an hour of excision and were orthotopically implanted in the mammary fat pad of 6~8-week-old nonobese diabetic (NOD)/SCID/IL-2g-receptor null (NSG) mice. Tumor growth was defined as tumor volume ≥ 50 mm3. Tumor take rate was defined as percent of patients with development of at least one stably transplantable (passed at least for two generations) xenograft that was pathologically confirmed as BC. Results: Of the 50 pts enrolled at MCR, 37 were FL pts (2 ineligible) and 13 were SL pts (1 ineligible). Fresh tumor samples obtained pre-treatment from 43 eligible pts (32 FL), after C2 from 17 eligible pts (13 FL), and at disease progression from 10 eligible pts (5 FL) were implanted. Tumor growth was seen in at least one mouse from a pre-treatment specimen in 1 (3.1%) FL pt (confirmed BC) and 4 (36.4%) SL pts (2 confirmed BC); from end of C2 specimens in 2 (15.4%) FL pts and 2 (50%) SL pts (1 confirmed BC); and at progression in 1 (20%) FL pt and 2 (40%) SL pts (1 confirmed BC). The take rate from pre-treatment samples among FL pts was 1/32 (3.1%; 95% CI: 0.08-16.2%). Take rates in other groups are pending histological review. Discussion: In pts receiving palbociclib for HR+ MBC, the take rate using a pre-treatment percutaneous biopsy was low (3.1%) in the FL setting. However, higher growth rates were seen in the SL setting. The observation of higher growth rates at the end of C2 and at progression may relate to the activation of G1/S that occurs with withdrawal of palbociclib, and should be further studied. PDX remains a valuable tool for the evaluation of tumor biology and the development of new therapeutics, especially for those models established from pts with palbociclib and ET resistance. Proteogenomic and sequencing studies are ongoing to fully characterize these PDXs. Citation Format: Jia Yu, Vera J. Suman, Jun He, Jason P. Sinnwell, Ann M. Moyer, Bo Qin, Yayun Gu, Huan Zhang, Jodi M. Carter, Krishna R. Kalari, Brendan P. McMenomy, Minetta C. Liu, Tufia C. Haddad, Kathryn J. Ruddy, Fergus J. Couch, Alvaro Moreno-Aspitia, Donald W. Northfelt, Richard Weinshilboum, Ciara O'Sullivan, Matthew P. Goetz, Liewei Wang. Patient-derived xenografts (PDXs) generated from hormone receptor-positive breast cancer (BC) before and after cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i) treatment: Initial findings from the PROMISE study [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-01-07.