CRLF3 plays a key role in the final stage of platelet genesis and is a potential therapeutic target for thrombocythemia.

The process of platelet production has so far been understood to be a 2-stage process: megakaryocyte maturation from hematopoietic stem cells followed by proplatelet formation, with each phase regulating the peripheral blood platelet count. Proplatelet formation releases into the bloodstream beads-on-a-string preplatelets, which undergo fission into mature platelets. For the first time, we show that preplatelet maturation is a third, tightly regulated, critical process akin to cytokinesis that regulates platelet count. We show that deficiency in cytokine receptor-like factor 3 (CRLF3) in mice leads to an isolated and sustained 25% to 48% reduction in the platelet count without any effect on other blood cell lineages. We show that Crlf3-/- preplatelets have increased microtubule stability, possibly because of increased microtubule glutamylation via the interaction of CRLF3 with key members of the Hippo pathway. Using a mouse model of JAK2 V617F essential thrombocythemia, we show that a lack of CRLF3 leads to long-term lineage-specific normalization of the platelet count. We thereby postulate that targeting CRLF3 has therapeutic potential for treatment of thrombocythemia.

Novel manifestations of immune dysregulation and granule defects in gray platelet syndrome.

Gray platelet syndrome (GPS) is a rare recessive disorder caused by biallelic variants in NBEAL2 and characterized by bleeding symptoms, the absence of platelet α-granules, splenomegaly, and bone marrow (BM) fibrosis. Due to the rarity of GPS, it has been difficult to fully understand the pathogenic processes that lead to these clinical sequelae. To discern the spectrum of pathologic features, we performed a detailed clinical genotypic and phenotypic study of 47 patients with GPS and identified 32 new etiologic variants in NBEAL2. The GPS patient cohort exhibited known phenotypes, including macrothrombocytopenia, BM fibrosis, megakaryocyte emperipolesis of neutrophils, splenomegaly, and elevated serum vitamin B12 levels. Novel clinical phenotypes were also observed, including reduced leukocyte counts and increased presence of autoimmune disease and positive autoantibodies. There were widespread differences in the transcriptome and proteome of GPS platelets, neutrophils, monocytes, and CD4 lymphocytes. Proteins less abundant in these cells were enriched for constituents of granules, supporting a role for Nbeal2 in the function of these organelles across a wide range of blood cells. Proteomic analysis of GPS plasma showed increased levels of proteins associated with inflammation and immune response. One-quarter of plasma proteins increased in GPS are known to be synthesized outside of hematopoietic cells, predominantly in the liver. In summary, our data show that, in addition to the well-described platelet defects in GPS, there are immune defects. The abnormal immune cells may be the drivers of systemic abnormalities such as autoimmune disease.

Nbeal2 interacts with Dock7, Sec16a, and Vac14.

Mutations in NBEAL2, the gene encoding the scaffolding protein Nbeal2, are causal of gray platelet syndrome (GPS), a rare recessive bleeding disorder characterized by platelets lacking α-granules and progressive marrow fibrosis. We present here the interactome of Nbeal2 with additional validation by reverse immunoprecipitation of Dock7, Sec16a, and Vac14 as interactors of Nbeal2. We show that GPS-causing mutations in its BEACH domain have profound and possible effects on the interaction with Dock7 and Vac14, respectively. Proximity ligation assays show that these 2 proteins are physically proximal to Nbeal2 in human megakaryocytes. In addition, we demonstrate that Nbeal2 is primarily localized in the cytoplasm and Dock7 on the membrane of or in α-granules. Interestingly, platelets from GPS cases and Nbeal2-/- mice are almost devoid of Dock7, resulting in a profound dysregulation of its signaling pathway, leading to defective actin polymerization, platelet activation, and shape change. This study shows for the first time proteins interacting with Nbeal2 and points to the dysregulation of the canonical signaling pathway of Dock7 as a possible cause of the aberrant formation of platelets in GPS cases and Nbeal2-deficient mice.

Comprehensive analysis of the editing window of C-to-T TALE base editors.

One of the most recent advances in the genome editing field has been the addition of "TALE Base Editors", an innovative platform for cell therapy that relies on the deamination of cytidines within double strand DNA, leading to the formation of an uracil (U) intermediate. These molecular tools are fusions of transcription activator-like effector domains (TALE) for specific DNA sequence binding, split-DddA deaminase halves that will, upon catalytic domain reconstitution, initiate the conversion of a cytosine (C) to a thymine (T), and an uracil glycosylase inhibitor (UGI). We developed a high throughput screening strategy capable to probe key editing parameters in a precisely defined genomic context in cellulo, excluding or minimizing biases arising from different microenvironmental and/or epigenetic contexts. Here we aimed to further explore how target composition and TALEB architecture will impact the editing outcomes. We demonstrated how the nature of the linker between TALE array and split DddAtox head allows us to fine tune the editing window, also controlling possible bystander activity. Furthermore, we showed that both the TALEB architecture and spacer length separating the two TALE DNA binding regions impact the target TC editing dependence by the surrounding bases, leading to more restrictive or permissive editing profiles.

Non-viral DNA delivery and TALEN editing correct the sickle cell mutation in hematopoietic stem cells.

Sickle cell disease is a devastating blood disorder that originates from a single point mutation in the HBB gene coding for hemoglobin. Here, we develop a GMP-compatible TALEN-mediated gene editing process enabling efficient HBB correction via a DNA repair template while minimizing risks associated with HBB inactivation. Comparing viral versus non-viral DNA repair template delivery in hematopoietic stem and progenitor cells in vitro, both strategies achieve comparable HBB correction and result in over 50% expression of normal adult hemoglobin in red blood cells without inducing ß-thalassemic phenotype. In an immunodeficient female mouse model, transplanted cells edited with the non-viral strategy exhibit higher engraftment and gene correction levels compared to those edited with the viral strategy. Transcriptomic analysis reveals that non-viral DNA repair template delivery mitigates P53-mediated toxicity and preserves high levels of long-term hematopoietic stem cells. This work paves the way for TALEN-based autologous gene therapy for sickle cell disease.

Immune dysregulation, autoimmunity, and granule defects in gray platelet syndrome.

Since the description of the first case with gray platelet syndrome (GPS) in 1971, this rare inherited platelet disorder has been the focus of extensive clinical and basic research. These studies have not only increased our knowledge about the clinical manifestations of GPS but also deepened our understanding of the biogenesis of platelet α-granules and their pathophysiology in hemostasis and thrombosis. The discovery of the causal gene, neurobeachin-like 2, in 2011 was a milestone in hematology. Following this was the rapid diagnosis and phenotyping of many new patients and the further development of experimental models to characterize the pathophysiological relevance of neurobeachin-like 2 in hemostasis and immunity. The impact of altered protein function on cells other than platelets became apparent, including defects in the granules of neutrophils and monocytes and changes in the transcriptomic and proteomic profiles of other immune cells such as T lymphocytes. Besides the previously recognized clinical manifestations of macrothrombocytopenia, splenomegaly, and early-onset bone marrow fibrosis, we now recognize that immunologic abnormalities, including autoimmune diseases and recurrent infections, affect a proportion of patients with GPS. There is a proinflammatory signature of the plasma in GPS, with quantitative alterations of multiple proteins, including many produced by the liver. This review will cover the classical features of GPS and then focus on additional clinical manifestations of immune dysregulation and cellular defects beyond platelets in patients with this rare disorder.

Analysis of the amplified p-wave enables identification of patients with atrial fibrillation during sinus rhythm.

Aim: This study sought to develop and validate diagnostic models to identify individuals with atrial fibrillation (AF) using amplified sinus-p-wave analysis. Methods: A total of 1,492 patients (491 healthy controls, 499 with paroxysmal AF and 502 with persistent AF) underwent digital 12-lead-ECG recording during sinus rhythm. The patient cohort was divided into training and validation set in a 3:2 ratio. P-wave indices (PWI) including duration of standard p-wave (standard PWD; scale at 10 mm/mV, sweep speed at 25 mm/s) and amplified sinus-p-wave (APWD, scale at 60-120 mm/mV, sweep speed at 100 mm/s) and advanced inter-atrial block (aIAB) along with other clinical parameters were used to develop diagnostic models using logistic regression. Each model was developed from the training set and further tested in both training and validation sets for its diagnostic performance in identifying individuals with AF. Results: Compared to standard PWD (Reference model), which achieved an AUC of 0.637 and 0.632, for training and validation set, respectively, APWD (Basic model) importantly improved the accuracy to identify individuals with AF (AUC = 0.86 and 0.866). The PWI-based model combining APWD, aIAB and body surface area (BSA) further improved the diagnostic performance for AF (AUC = 0.892 and 0.885). The integrated model, which further combined left atrial diameter (LAD) with parameters of the PWI-based model, achieved optimal diagnostic performance (AUC = 0.916 and 0.902). Conclusion: Analysis of amplified p-wave during sinus rhythm allows identification of individuals with atrial fibrillation.

Echocardiographic and Electrocardiographic Determinants of Atrial Cardiomyopathy Identify Patients with Atrial Fibrillation at Risk for Left Atrial Thrombogenesis.

Objective: Atrial cardiomyopathy (ACM) is associated with development of AF, left atrial (LA) thrombogenesis, and stroke. Diagnosis of ACM is feasible using both echocardiographic LA strain imaging and measurement of the amplified p-wave duration (APWD) in digital 12-lead-ECG. We sought to determine the thresholds of LA global longitudinal strain (LA-GLS) and APWD that identify patients with AF at risk for LA appendage (LAA) thrombogenesis. Methods: One hundred and twenty-eight patients with a history of AF were included. Left atrial appendage maximal flow velocity (LAA-Vel, in TEE), LA-GLS (TTE), and APWD (digital 12-lead-ECG) were measured in all patients. ROC analysis was performed for each method to determine the thresholds for LA-GLS and the APWD, enabling diagnosis of patients with LAA-thrombus. Results: Significant differences in LA-GLS were found during both rhythms (SR and AF) between the thrombus group and control group: LA-GLS in SR: 14.3 ± 7.4% vs. 24.6 ± 9.0%, p < 0.001 and in AF: 11.4 ± 4.2% vs. 16.1 ± 5.0%, p = 0.045. ROC analysis revealed a threshold of 17.45% for the entire cohort (AUC 0.82, sensitivity: 84.6%, specificity: 63.6%, Negative Predictive Value (NPV): 94.3%) with additional rhythm-specific thresholds: 19.1% in SR and 13.9% in AF, and a threshold of 165 ms for APWD (AUC 0.90, sensitivity: 88.5%, specificity: 75.5%, NPV: 96.2%) as optimal discriminators of LAA-thrombus. Moreover, both LA-GLS and APWD correlated well with the established contractile LA-parameter LAA-Vel in TEE (r = 0.39, p < 0.001 and r = −0.39, p < 0.001, respectively). Conclusion: LA-GLS and APWD are valuable diagnostic predictors of left atrial thrombogenesis in patients with AF.

Machine Learning Using a Single-Lead ECG to Identify Patients With Atrial Fibrillation-Induced Heart Failure.

Aims: Atrial fibrillation (AF) and heart failure often co-exist. Early identification of AF patients at risk for AF-induced heart failure (AF-HF) is desirable to reduce both morbidity and mortality as well as health care costs. We aimed to leverage the characteristics of beat-to-beat-patterns in AF to prospectively discriminate AF patients with and without AF-HF. Methods: A dataset of 10,234 5-min length RR-interval time series derived from 26 AF-HF patients and 26 control patients was extracted from single-lead Holter-ECGs. A total of 14 features were extracted, and the most informative features were selected. Then, a decision tree classifier with 5-fold cross-validation was trained, validated, and tested on the dataset randomly split. The derived algorithm was then tested on 2,261 5-min segments from six AF-HF and six control patients and validated for various time segments. Results: The algorithm based on the spectral entropy of the RR-intervals, the mean value of the relative RR-interval, and the root mean square of successive differences of the relative RR-interval yielded an accuracy of 73.5%, specificity of 91.4%, sensitivity of 64.7%, and PPV of 87.0% to correctly stratify segments to AF-HF. Considering the majority vote of the segments of each patient, 10/12 patients (83.33%) were correctly classified. Conclusion: Beat-to-beat-analysis using a machine learning classifier identifies patients with AF-induced heart failure with clinically relevant diagnostic properties. Application of this algorithm in routine care may improve early identification of patients at risk for AF-induced cardiomyopathy and improve the yield of targeted clinical follow-up.

Validating left atrial fractionation and low-voltage substrate during atrial fibrillation and sinus rhythm-A high-density mapping study in persistent atrial fibrillation.

Background: Low-voltage-substrate (LVS)-guided ablation for persistent atrial fibrillation (AF) has been described either in sinus rhythm (SR) or AF. Prolonged fractionated potentials (PFPs) may represent arrhythmogenic slow conduction substrate and potentially co-localize with LVS. We assess the spatial correlation of PFP identified in AF (PFP-AF) to those mapped in SR (PFP-SR). We further report the relationship between LVS and PFPs when mapped in AF or SR. Materials and methods: Thirty-eight patients with ablation naïve persistent AF underwent left atrial (LA) high-density mapping in AF and SR prior to catheter ablation. Areas presenting PFP-AF and PFP-SR were annotated during mapping on the LA geometry. Low-voltage areas (LVA) were quantified using a bipolar threshold of 0.5 mV during both AF and SR mapping. Concordance of fractionated potentials (CFP) (defined as the presence of PFPs in both rhythms within a radius of 6 mm) was quantified. Spatial distribution and correlation of PFP and CFP with LVA were assessed. The predictors for CFP were determined. Results: PFPs displayed low voltages both during AF (median 0.30 mV (Q1-Q3: 0.20-0.50 mV) and SR (median 0.35 mV (Q1-Q3: 0.20-0.56 mV). The duration of PFP-SR was measured at 61 ms (Q1-Q3: 51-76 ms). During SR, most PFP-SRs (89.4 and 97.2%) were located within LVA (<0.5 mV and <1.0 mV, respectively). Areas presenting PFP occurred more frequently in AF than in SR (median: 9.5 vs. 8.0, p = 0.005). Both PFP-AF and PFP-SR were predominantly located at anterior LA (>40%), followed by posterior LA (>20%) and septal LA (>15%). The extent of LVA < 0.5 mV was more extensive in AF (median: 25.2% of LA surface, Q1-Q3:16.6-50.5%) than in SR (median: 12.3%, Q1-Q3: 4.7-29.4%, p = 0.001). CFP in both rhythms occurred in 80% of PFP-SR and 59% of PFP-AF (p = 0.008). Notably, CFP was positively correlated to the extent of LVA in SR (p = 0.004), but not with LVA in AF (p = 0.226). Additionally, the extent of LVA < 0.5 mV in SR was the only significant predictor for CFP, with an optimal threshold of 16% predicting high (>80%) fractionation concordance in AF and SR. Conclusion: Substrate mapping in SR vs. AF reveals smaller areas of low voltage and fewer sites with PFP. PFP-SR are located within low-voltage areas in SR. There is a high degree of spatial agreement (80%) between PFP-AF and PFP-SR in patients with moderate LVA in SR (>16% of LA surface). These findings should be considered when substrate-based ablation strategies are applied in patients with the left atrial low-voltage substrate with recurrent persistent AF.

Structural and electrophysiological determinants of atrial cardiomyopathy identify remodeling discrepancies between paroxysmal and persistent atrial fibrillation.

Background: Progressive atrial fibrotic remodeling has been reported to be associated with atrial cardiomyopathy (ACM) and the transition from paroxysmal to persistent atrial fibrillation (AF). We sought to identify the anatomical/structural and electrophysiological factors involved in atrial remodeling that promote AF persistency. Methods: Consecutive patients with paroxysmal (n = 134) or persistent (n = 136) AF who presented for their first AF ablation procedure were included. Patients underwent left atrial (LA) high-definition mapping (1,835 ± 421 sites/map) during sinus rhythm (SR) and were randomized to training and validation sets for model development and evaluation. A total of 62 parameters from both electro-anatomical mapping and non-invasive baseline data were extracted encompassing four main categories: (1) LA size, (2) extent of low-voltage-substrate (LVS), (3) LA voltages and (4) bi-atrial conduction time as identified by the duration of amplified P-wave (APWD) in a digital 12-lead-ECG. Least absolute shrinkage and selection operator (LASSO) and logistic regression were performed to identify the factors that are most relevant to AF persistency in each category alone and all categories combined. The performance of the developed models for diagnosis of AF persistency was validated regarding discrimination, calibration and clinical usefulness. In addition, HATCH score and C2HEST score were also evaluated for their performance in identification of AF persistency. Results: In training and validation sets, APWD (threshold 151 ms), LA volume (LAV, threshold 94 mL), bipolar LVS area < 1.0 mV (threshold 4.55 cm2) and LA global mean voltage (GMV, threshold 1.66 mV) were identified as best determinants for AF persistency in the respective category. Moreover, APWD (AUC 0.851 and 0.801) and LA volume (AUC 0.788 and 0.741) achieved better discrimination between AF types than LVS extent (AUC 0.783 and 0.682) and GMV (AUC 0.751 and 0.707). The integrated model (combining APWD and LAV) yielded the best discrimination performance between AF types (AUC 0.876 in training set and 0.830 in validation set). In contrast, HATCH score and C2HEST score only achieved AUC < 0.60 in identifying individuals with persistent AF in current study. Conclusion: Among 62 electro-anatomical parameters, we identified APWD, LA volume, LVS extent, and mean LA voltage as the four determinant electrophysiological and structural factors that are most relevant for AF persistency. Notably, the combination of APWD with LA volume enabled discrimination between paroxysmal and persistent AF with high accuracy, emphasizing their importance as underlying substrate of persistent AF.