Citations

Takayasu arteritis is a chronic, large vessel vasculitis that typically affects the aorta and its main branches. We present a case of a 33-year-old male patient who was diagnosed with Takayasu arteritis after being admitted for acute cardiogenic shock requiring inotropes. Initial transthoracic echocardiography demonstrated severe biventricular dysfunction. Computed tomography imaging of his chest showed pulmonary infarcts. Patient subsequently developed sudden lower extremity weakness and bowel incontinence, and urgent magnetic resonance imaging of his spine demonstrated thoracolumbar vascular myelopathy. Transesophageal echocardiography revealed diffuse symmetrical thickening of the walls of the aorta; findings suggestive of aortitis. Patient was initiated on intravenous corticosteroid and systemic anticoagulation. Subsequent computed tomography angiography demonstrated irregular luminal contour of the aortic arch, and complete occlusion of the left subclavian artery, abdominal aorta, superior mesenteric artery, and left renal artery. He underwent an emergent aortoiliac thrombectomy. He was transitioned to oral prednisone, tocilizumab, and azathioprine with excellent recovery.

Abstract Hip arthroscopy is a technically demanding procedure that can require a substantial volume of irrigation fluid. Techniques should be explored to optimize fluid use while ensuring satisfactory surgical instrumentation and labral repair. In this technical note, we present a method for performing a dry arthroscopic labral repair. This technique can be used in the treatment of a variety of labral pathologies, including primary labral repair with knotless or hand‐tied anchors, revision labral repair, and labral reconstruction, without the need for irrigation fluid. Additionally, we discuss supplemental techniques that can be used during other portions of the arthroscopic hip procedure to limit irrigation fluid use. Technique Video video See video under supplementary data.

Abstract The standard of care for hip labral tears is arthroscopic repair, with labral reconstruction performed more commonly for irreparable tears in order to avoid isolated labral debridement. However, labral reconstruction can be technically demanding. We provide a concise step‐by‐step guide for performing labral reconstruction or augmentation using a modified retrograde pull‐through technique, including tips, tricks, and surgeon pearls, and pitfalls. Despite the procedure's technically challenging nature, we believe our technique highlights several important steps to improve the practicality and efficiency of the case and produce satisfactory patient outcomes. Technique Video video See video under supplementary data.

Bi-allelic disruptive variants (nonsense, frameshift, and splicing variants) in KDM5B have been identified as causative for autosomal recessive intellectual developmental disorder type 65. In contrast, dominant variants, usually disruptive as well, have been more difficult to implicate in a specific phenotype, since some of them have been found in unaffected controls or relatives. Here, we describe individuals with likely pathogenic variants in KDM5B, including eight individuals with dominant missense variants. This study is a retrospective case series of 21 individuals with variants in KDM5B. We performed deep phenotyping and collected the clinical information and molecular data of these individuals’ family members. We compared the phenotypes according to variant type and to those previously described in the literature. The most common features were developmental delay, impaired intellectual development, behavioral problems, autistic behaviors, sleep disorders, facial dysmorphism, and overgrowth. DD, ASD behaviors, and sleep disorders were more common in individuals with dominant disruptive KDM5B variants, while individuals with dominant missense variants presented more frequently with renal and skin anomalies. This study extends our understanding of the KDM5B-related neurodevelopmental disorder and suggests the pathogenicity of certain dominant KDM5B missense variants.

Abstract Background: Immune checkpoint inhibitors (ICIs) have significantly improved outcomes for patients with metastatic non-small cell lung cancer (NSCLC). However, clinical management is challenging. The PD-L1 biomarker does not optimally guide the choice between ICI monotherapy and combination ICI-chemotherapy, and there are currently no biomarkers to predict immune-related adverse events (irAEs). Here, we describe a versatile platform based on plasma proteomics and machine learning for generating predictive tools to support treatment decisions. Methods: Pre-treatment plasma samples were collected from 616 NSCLC patients receiving ICI-based therapy (NCT04056247). Clinical benefit (CB) data and irAEs were recorded. Proteomic profiling of plasma samples was performed using the SomaScan® assay, covering ~7000 proteins per sample. Proteins associated with Clinical Benefit (progression-free survival at 12 months) were classified as resistance-associated proteins (RAPs). Proteins associated with grade ≥3 irAEs occurring within the first 100 days of treatment were classified as toxicity-associated proteins (TAPs). RAPs and TAPs were integrated into two separate machine learning-based models, yielding CB and irAE probabilities, respectively. The CB model used a CB probability threshold to assign patients a PROphet-positive or PROphet-negative result. Bioinformatic analysis was performed on RAPs and TAPs. Results: CB and irAE models displayed strong predictive performance with a high correlation between predicted probability and observed CB or irAE rate (CB model: R2=0.98; p-value<0.0001; irAE model: R2= 0.92; p-value <0.0001). In the CB model, patients classified as PROphet-positive achieved significantly longer overall survival (OS) than PROphet-negative patients, with a median OS of 25.9 vs. 10.8 months (hazard ratio, HR = 0.51; p-value<0.001). Furthermore, patients with PD-L1 ≥50% tumors and a PROphet-negative result had significantly longer OS with ICI-chemotherapy in comparison to ICI monotherapy (HR=0.23, p-value = 0.0003), suggesting that combination therapy is preferable for such patients despite high PD-L1 levels. Bioinformatic analysis showed that RAPs related to immune regulation, angiogenesis, chemo-resistance, and other potential resistance mechanisms displayed higher expression levels in patients who did not benefit from treatment. Neutrophil- and inflammation-related proteins were significantly enriched in patients who experienced irAEs. Conclusions: We describe two machine-learning based predictive tools that may be used separately or in combination to inform treatment decisions based on the patient’s likelihood to benefit from ICI therapy and to develop serious irAEs. Our findings also provide biological insights related to treatment resistance and immune-related toxicity. Citation Format: Michal Harel, Petros Christopoulos, Igor Puzanov, Jair Bar, Iris Kamer, Niels Reinmuth, Ina Koch, Mor Moskovitz, Adva Levy-Barda, Alona Zer, Michal Lotem, David Farrugia, Rivka Katzenelson, Gillian Price, Abed Agbarya, Helen Cheley, Adam Hassani, Mahmoud Abu-Amna, Tom Geldart, Anirban Chatterjee, Andreas Polychronis, Maya Gottfried, Yanyan Lou, Tatiana Harkovsky, Alison Brewster, Ido Wolf, Ella Tepper, Ben Yellin, Itamar Sela, Coren Lahav, Yehonatan Elon, Raya Leibowitz, Adam P. Dicker, Young Kwang Chae, Ryan J. Sullivan, David Carbone, David Gandara, Jarushka Naidoo. Plasma proteomics-based models for predicting therapeutic benefit and immune-related adverse events in non-small cell lung cancer patients treated with immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1208.

PURPOSE Current guidelines for the management of metastatic non–small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions. PATIENTS AND METHODS We conducted a multicenter observational trial (ClinicalTrials.gov identifier: NCT04056247 ) of patients undergoing PD-1/PD-L1 inhibitor–based therapy (n = 540) and an additional patient cohort receiving chemotherapy (n = 85) who consented to pretreatment plasma and clinical data collection. Plasma proteome profiling was performed using SomaScan Assay v4.1. RESULTS Our test demonstrates a strong association between model output and clinical benefit (CB) from PD-1/PD-L1 inhibitor–based treatments, evidenced by high concordance between predicted and observed CB ( R 2 = 0.98, P < .001). The test categorizes patients as either PROphet-positive or PROphet-negative and further stratifies patient outcomes beyond PD-L1 expression levels. The test successfully differentiates between PROphet-negative patients exhibiting high tumor PD-L1 levels (≥50%) who have enhanced overall survival when treated with a combination of immunotherapy and chemotherapy compared with immunotherapy alone (hazard ratio [HR], 0.23 [95% CI, 0.1 to 0.51], P = .0003). By contrast, PROphet-positive patients show comparable outcomes when treated with immunotherapy alone or in combination with chemotherapy (HR, 0.78 [95% CI, 0.42 to 1.44], P = .424). CONCLUSION Plasma proteome–based testing of individual patients, in combination with standard PD-L1 testing, distinguishes patient subsets with distinct differences in outcomes from PD-1/PD-L1 inhibitor–based therapies. These data suggest that this approach can improve the precision of first-line treatment for metastatic NSCLC.

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1 *04 subtypes best accounted for the association, strongest with HLA-DRB1 *04:04 and HLA-DRB1 *04:07, and intermediary with HLA-DRB1 *04:01 and HLA-DRB1 *04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1 *04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1 *04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.

Abstract Aims Evidence regarding the role of serial measurements of biomarkers for risk assessment in post-acute coronary syndrome (ACS) patients is limited. The aim was to explore the prognostic value of four, serially measured biomarkers in a large, real-world cohort of post-ACS patients. Methods and results BIOMArCS is a prospective, multi-centre, observational study in 844 post-ACS patients in whom 12 218 blood samples (median 17 per patient) were obtained during 1-year follow-up. The longitudinal patterns of high-sensitivity cardiac troponin T (hs-cTnT), N-terminal-pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity C-reactive protein (hs-CRP), and growth differentiation factor 15 (GDF-15) were analysed in relation to the primary endpoint (PE) of cardiovascular mortality and recurrent ACS using multivariable joint models. Median age was 63 years, 78% were men and the PE was reached by 45 patients. The average biomarker levels were systematically higher in PE compared with PE-free patients. After adjustment for 6-month post-discharge Global Registry of Acute Coronary Events score, 1 standard deviation increase in log[hs-cTnT] was associated with a 61% increased risk of the PE [hazard ratio (HR) 1.61, 95% confidence interval (CI) 1.02–2.44, P = 0.045], while for log[GDF-15] this was 81% (HR 1.81, 95% CI 1.28–2.70, P = 0.001). These associations remained significant after multivariable adjustment, while NT-proBNP and hs-CRP were not. Furthermore, GDF-15 level showed an increasing trend prior to the PE (Structured Graphical Abstract). Conclusion Longitudinally measured hs-cTnT and GDF-15 concentrations provide prognostic value in the risk assessment of clinically stabilized patients post-ACS. Clinical Trial Registration The Netherlands Trial Register. Currently available at URL https://trialsearch.who.int/; Unique Identifiers: NTR1698 and NTR1106.