Vertex Pharmaceuticals

Suzetrigine is an oral selective NaV1.8 inhibitor approved for moderate-to-severe acute pain. We evaluated the addition of this to multimodal analgesia after spine surgery. This single-center retrospective prepost cohort included 100 adults undergoing spine surgery (50 suzetrigine, 50 controls). The primary endpoint was cumulative morphine milligram equivalents (MME) within 48 hours. Secondary outcomes included MME at postoperative day (POD) 0 and at discharge, pain scores, length of stay (LOS), bowel function, falls, and 30-day readmission. Multivariable models adjusted for age, BMI, baseline pain, chronic opioid use, instrumentation, and race. Race/ethnicity differed between cohorts (p = .032); most other measured baseline characteristics were similar. In the direct 48-hour analysis (44 vs. 43 patients), MME was lower with suzetrigine (median 20.0 vs. 34.0; p = .032; d = -0.45). An all-patient sensitivity analysis using total inpatient MME through discharge for patients discharged before 48 hours was also significant (20.0 vs. 31.8; p = .021). POD0 MME (5.0 vs. 10.0; p = .010) and discharge MME (5.0 vs. 15.0; p = .014) were lower with suzetrigine. LOS did not differ (p = .171). After adjustment, the suzetrigine coefficient for 48-hour MME did not reach significance (β = -9.45; p = .065), and there was no adjusted LOS association (β = -0.43; p = .171). Suzetrigine was associated with lower unadjusted 48-hour, POD0, and discharge opioid consumption, although the adjusted 48-hour association did not reach statistical significance. No LOS difference was observed. Prospective validation is warranted.

In a cancer clinical trial with an immunotherapy, the treatment often becomes effective after a certain delay time. It is well known that traditional log-rank test no longer provides optimal power in this case. There has been a great interest to search for a more powerful test to detect a truly effective immunotherapy treatment. In this paper, we propose a new testing method based on the maximum value of a set of 0-1 weighted log-rank test statistics and establish useful theoretical results of the relevant test statistics. Extensive simulation studies are conducted to examine the empirical performance of the proposed method. An analysis of the real data from a non-small-cell lung cancer clinical trial is also carried out to further demonstrate the usefulness of the proposed test method. Trial Registration: ClinicalTrials.gov ID: NCT01903993, NCT02008227.

Gastrointestinal symptoms remain common in adults with cystic fibrosis (CF) despite cystic fibrosis transmembrane conductance regulator modulator use, suggesting persistent and heterogeneous gut dysfunction. This prospective observational study tests the hypothesis that distinct gut symptom phenotypes in CF can be observed and linked to underlying mechanisms. Adults from three UK CF centres completed the Gastrointestinal Symptom Rating Scale, Patient Assessment of Constipation Symptoms and a bowel-habit questionnaire. Latent class analysis using an ordinal logistic model was applied to 36 symptom indicators. Associations between phenotypes and demographic, clinical, and treatment variables were examined using generalised linear models. Three hundred participants completed questionnaires (54% male; median 31 years). We identified four symptom phenotypes: mild; moderate-constipation predominant; moderate-diarrhoea predominant and severe. The severe phenotype was associated with gastroesophageal reflux (RRR 2.86; 95%CI: 1.30-6.31; p = 0.009), distal intestinal obstruction syndrome (RRR 2.46; 95%CI: 1.04-5.81; p = 0.04), proton pump inhibitor (RRR 3.29; 95%CI 1.39-7.74; p = 0.007), and laxative use (RRR 6.13; 95%CI 2.54-14.84; p < 0.001). CF-related liver disease was associated with both moderate-constipation and diarrhoea phenotypes, respectively (RRR 2.08; 95%CI 1.13-3.81; p = 0.018; RRR 2.11; 95%CI 1.03-4.29; p = 0.04). There was a lower likelihood of long-term oral antibiotic use in the moderate-constipation phenotype (RRR 0.53; 95%CI 0.3-0.92; p = 0.025) and moderate-diarrhoea phenotype (RRR 0.46; 95%CI 0.24-0.91; p = 0.025). Four distinct symptom phenotypes were identified, independent of demographics and pancreatic status, but associated with specific complications and medication profiles. These phenotypes provide a framework for mechanistic studies within the GRAMPUS-CF cohort and precision management of CF-related gut disease.

Clonal hematopoiesis (CH), characterized by clonal expansion of hematopoietic stem cells harboring preleukemic mutations, is an emerging cardiovascular disease risk factor. The American Heart Association's Life's Essential 8 (LE8) score is the contemporary standard for quantifying cardiovascular health. However, the interplay between this novel genetic risk factor and classical health metrics remains unknown. This study sought to examine the association between LE8 score and CH prevalence, and determine their joint effects on incident coronary artery disease (CAD). We analyzed 427,295 UK Biobank participants. Exposures included LE8 score and CH (evaluated as a composite and by common drivers: DNMT3A, TET2, ASXL1). Associations with CH prevalence and incident CAD over a median 13.6-year follow-up were evaluated using multivariable regression. CH prevalence was 3.4%. A higher LE8 score was associated with significantly lower odds of CH and examined driver mutations, strongest for ASXL1 (OR: 0.79; 95% CI: 0.75-0.83; P < 0.001). CH significantly modified the protective effect of LE8 on CAD incidence on multiplicative and additive scales. A 1-SD increase in LE8 yielded an adjusted CAD HR of 0.74 (95% CI: 0.70-0.78) in CH carriers vs 0.68 (95% CI: 0.67-0.69) in noncarriers (Pinteraction = 0.005). Participants with ASXL1 CH subtype and low LE8 scores experienced the highest absolute CAD risk (18.7 vs 2.0 events/1,000 person-years in noncarriers with high LE8). Optimal cardiovascular health is associated with a lower prevalence of CH. Although maintaining ideal cardiovascular health is associated with lower CAD risk in CH carriers, this protective benefit is attenuated compared with noncarriers.

Right ventricular (RV) size and function inform prognosis in many cardiovascular diseases, but assessment by two-dimensional transthoracic echocardiography is challenging. Here we show that a deep learning model, Dimensional Reconstruction of Imaging Data-Right Ventricle (DROID-RV), can estimate RV end-diastolic diameter and identify RV systolic dysfunction from transthoracic echocardiography videos. We trained DROID-RV in 17,141 ambulatory cardiology patients (51,188 studies and 383,881 video clips) and validated model predictions in 9,112 primary care patients and 831 patients with RV ejection fraction assessed by three-dimensional transthoracic echocardiography. Across multiple test samples, DROID-RV accurately estimates RV end-diastolic diameter and identifies RV dysfunction, although model prediction error increases at extremes of RV size and function. We additionally show that RV size and function predictions are associated with incident mortality, atrial fibrillation and heart failure. Our work demonstrates how deep learning can automate RV assessment and risk stratification at scale using two-dimensional echocardiography.

Somatic mosaicism is increasingly recognized as a fundamental feature of human biology, yet the detection of somatic mutations remains challenging. The Somatic Mosaicism across Human Tissues (SMaHT) Network conducted large-scale benchmarking experiments involving cell lines and donor tissues to evaluate sequencing technologies, experimental approaches, and computational methods for detecting different types of somatic mutations, generating community resources with >1,000× short-read and 100-400× long-read data for nine analyzed samples. We determined effective strategies for utilizing short- and long-read sequencing for mutation detection and demonstrated that using donor-specific and pangenome-inferred diploid assemblies improved calling, extending mutation catalogs to challenging genomic regions. We benchmarked six duplex technologies and showed that single-cell sequencing resolves cell-type-specific mutational patterns and heterogeneity. Our results indicate that bulk, single-cell, and duplex analyses are complementary and that leveraging all three provides comprehensive characterization of mosaicism within tissues. Together, these findings provide the scientific and clinical communities with a roadmap for accurate genome-wide somatic mutation analysis.

Preterm birth is associated with breakdown of maternal-fetal tolerance and remains the leading cause of global mortality in young children. However, the role of self-reactive antibodies has been limited to a handful of pathogenic allo- and autoantibodies linked to pregnancy complications. Here we identify a shared autoreactive signature of pregnancy in pregnant sera (n = 2,719) relative to never-pregnant controls (n = 130), using proteome-wide autoantibody profiling. Across eight human pregnancy cohorts, we define autoreactivities associated with preterm birth by comparing preterm (n = 688) and term (n = 1,505) pregnancies. Within the signature, antibodies to IL1 receptor antagonist (IL1RA) induce resorption, inflammation and vascular malperfusion in pregnant mice. IL1RA localizes to placental endothelial adherens junctions, suggesting a role in vascular integrity. These findings identify a term pregnancy humoral immune program and shared changes preceding preterm delivery, including anti-IL1RA, which may have direct pathogenic consequences.