Citations

Abstract Amyotrophic lateral sclerosis (ALS) is a fatal, rapidly progressive neurodegenerative disease of motor neurons for which therapeutics are limited. Improved biomarkers are imperative to improve patient care and therapeutic development. Here, we employed 35-plex isobaric tandem mass tag labeling based on isobutyl-proline reporter group (TMTpro) to perform unbiased proteomic analysis of cerebrospinal fluid (CSF) and plasma from control (n= 28, n= 31) and sporadic ALS (sALS) (n= 39, n= 41), from the Target ALS Global Natural History Study (TALS GNHS). We identified 2,875 proteins in CSF and 1,118 proteins in plasma and identified known and novel differentially expressed proteins (DEPs) between controls and sALS, some of which were orthogonally validated using immunoassay. Comparison of TMTpro-MS and Olink proximity extension assay proteomics revealed common and non-overlapping differentially expressed proteins illustrating strengths unique to each platform. This initial cross-sectional proteomic study of biofluids from the TALS GNHS, with unrestricted availability of study results to the research community, highlights the potential of this resource as a potent platform for ALS biomarker discovery.

Through a Delphi process, all 33 panelists reached consensus on topics relating to MRI reporting of knee meniscus lesions, demonstrating that interdisciplinary and multi-institutional standardization is possible.

ABSTRACT Background Pulmonary arterial hypertension (PAH) is characterized by circulating metabolic alterations, but whether these reflect disease-specific metabolic programs or reorganization of normal metabolic architecture, and how they relate to right ventricular-pulmonary vascular function (RV-PV), remains unclear. We hypothesized that the PAH metabolome is organized into biologically coherent, co-regulated metabolic modules whose relationships to RV-PV function would provide insight into known and novel metabolic pathways. Methods We applied weighted gene co-expression network analysis (WGCNA) to untargeted metabolomic data from 412 PAH patients enrolled in the multicenter PVDOMICS study. Module preservation analysis was performed in 85 healthy controls, with external replication in an independent single-center pulmonary hypertension cohort of 89 patients. Results WGCNA identified 16 distinct metabolic modules organized around biologically coherent programs. A coherent fatty acid axis, spanning substrate pools, β-oxidation intermediates, and conjugated fatty acid disposal products, formed a central organizing structure, with downstream fatty acid oxidation modules strongly associated with adverse hemodynamics and worse RV-pulmonary artery (PA) coupling. Acylcholine-enriched and 5α-reduced androgen metabolite modules were associated with favorable hemodynamic indices. Module architecture was largely preserved in healthy controls, with subtle disease-associated modular reorganization, rather than emergence of novel modules, observed in PAH. Core modules were recovered in the replication cohort with conserved hub metabolites. Conclusions These findings establish a systems-level framework demonstrating that PAH involves structured intensification and reorganization of interconnected metabolic programs associated with favorable and adverse RV-PV phenotypes. This work provides new insight into the metabolic architecture underlying PAH and identifies coordinated metabolic pathways linked to pulmonary vascular and right ventricular function.

Abstract Myelodysplastic syndromes (MDS) are clinically and biologically diverse disorders, emphasizing the need for personalized treatment approaches. The International Working Group for Prognostication of MDS (IWG_PM) recently introduced a molecular classification, referred to as the MDS taxonomy, that categorizes patients into 16 subgroups based on 21 gene mutations, 6 cytogenetic abnormalities, and loss of heterozygosity (LOH) at TP53 and TET2 loci. This study sought to validate and enhance the clinical relevance of the MDS taxonomy by analyzing a large retrospective cohort ( n = 5136) and transcriptomic data from a prospective cohort ( n = 477). The taxonomy successfully identified subgroups with distinct clinical characteristics and disease progression patterns. However, incorporating gene interactions from taxonomy subgroups did not improve the prognostic performance of the Molecular International Prognostic Scoring System (IPSS‐M). We further assessed whether the taxonomy could guide management in patients receiving disease‐modifying therapies. Except for the “ TP53 ‐complex” subgroup, taxonomy classifications were not predictive of hypomethylating agent response or transplant outcomes. Nonetheless, they correlated with overall survival, suggesting that while both IPSS‐M and the taxonomy capture disease biology, other non‐genetic factors may influence treatment response. RNA sequencing confirmed the biological distinctiveness of the taxonomy groups. Transcriptomic profiling of CD34+ bone marrow cells revealed unique, homogeneous gene expression patterns, particularly within the AML‐like, bi TET2 , SF3B1 , and TP53 ‐complex subgroups. Further integration of multi‐omics data may refine MDS classification, improving clinical decision‐making and guiding the development of targeted therapies.

Abstract Rationale Seralutinib is an investigational, first-in-class tyrosine kinase inhibitor designed for inhalation and selective for PDGFRα, PDGFRβ, CSF1R, and cKIT, targeting proliferation, inflammation, and fibrosis ─ three core drivers of pulmonary vascular remodeling in PAH. The phase 2 TORREY trial of seralutinib added to standard-of-care treatment in adults with PAH WHO FC II or III met its primary endpoint of a statistically significant reduction in pulmonary vascular resistance (PVR) vs. placebo at 24 weeks. Methods PROSERA (NCT05934526), a phase 3, randomized, double-blind, placebo-controlled, multicenter trial, evaluated the efficacy and safety of inhaled seralutinib in PAH patients treated for up to 48 weeks. Eligible patients (WHO Group 1 PH, FC II or III; REVEAL Lite 2 Risk Score ≥5 or NT-proBNP ≥300 ng/L or PVR ≥800 dyne•s/cm5) on standard background therapy were randomized 1:1 to seralutinib 90 mg or placebo delivered by dry powder inhaler twice daily. The primary endpoint was change in six-minute walk distance (6MWD) from baseline to week 24 in the seralutinib treatment group vs. placebo. Key secondary endpoints included: time to clinical worsening (TTCW), proportion of patients with clinical improvement at week 24, change in NT-proBNP from baseline to week 24, and proportion of patients with ≥1-point decrease from baseline in REVEAL Lite 2 Risk Score at week 24. Safety endpoints included incidence of treatment-emergent adverse events (TEAEs) and serious TEAEs (SAEs). Patients who completed blinded treatment could be eligible to participate in an open-label extension study. Preliminary Blinded Results 390 patients were randomized at 132 sites worldwide. At baseline, mean age was 50.0 years. PAH etiologies included 61.0% idiopathic, 9.7% heritable, and 22.3% associated with connective tissue disease. 25.6% of patients were WHO FC II and 74.4% FC III. Mean time from diagnosis was TBD years. Most patients were receiving 2 (39.2%) or ≥ 3 (54.6%) PAH medications, 29.2% were receiving parenteral prostacyclin. Baseline PVR was 798.4 dyne•s/cm5, 6MWD was 373.7 m, and NT-proBNP was 986.8 ng/L. The difference in 6MWD from baseline to week 24 between seralutinib and placebo was TBD [SD] m (p=TBD). Secondary endpoints of TTCW, clinical improvement, NT-proBNP, and REVEAL Lite 2 Risk Score will be reported. The most common AEs were TBD (x%) and TBD (y%). SAEs and discontinuations related to AE will be reported. Conclusions The PROSERA study demonstrates⋯ [to be updated following unblinding of the data]. Funding Gossamer Bio, Inc. This abstract is funded by: Gossamer Bio, Inc.

Abstract Introduction Insulin resistance is prevalent in pulmonary arterial hypertension (PAH) and is associated with worse health outcomes. The triglyceride-glucose (TyG) index as a measure of insulin resistance is superior to HOMA-IR in predicting metabolic syndrome. This study utilizes the Redefining Pulmonary Hypertension through Pulmonary Vascular Disease Phenomics (PVDOMICS) data registry to further examine the relationship between TyG index and reported quality of life (QOL) in patients with PAH. Methods 327 patients with a diagnosis of PAH in PVDOMICS were stratified into insulin resistant (IR) (TyG index >8.55) and insulin sensitive (IS) (TyG < 8.55) groups where TyG = (ln[triglyceride*glucose/2]. QOL measures assessed were the Minnesota Living With Heart Failure (MLHF) Physical and Emotional domain surveys, Short Form (36) (SF-36) Physical and Mental Component Health Surveys (PCS and MCS, respectively), and emPHasis-10 (E10). Reported measures between groups were compared using least squares means adjusted for age, sex, fat mass index (FMI), PAH etiology, 6-minute walk distance (6MWD) and NT-pro-brain natriuretic peptide (NTproBNP). Kaplan-Meier curves and Cox proportional hazards models adjusted for these same variables were performed to assess difference in survival between groups. Results 155 patients with PAH (47%) were classified as IR. Patients with IR were more likely to be female (79% vs 69%, p = 0.04), more likely to be non-Hispanic white, and less likely to be non-Hispanic Black (p = 0.045). There were no differences in age or etiology of PAH between groups. Patients with IR had higher body mass index (30.9 vs 27.3 kg/m2, p < 0.001) with higher FMI (16.2 vs 13.2 kg/m2, p < 0.001). Patients with IR were more likely to have diabetes mellitus (24% vs 11%, p = 0.004). Compared to their IS counterparts and after adjusting for possible confounders, patients with IR had higher (worse QOL) MLHF physical domain (p = 0.04), higher (worse QOL) emPhasis-10 scores (p = 0.03), and lower (worse QOL) SF36 physical component scores (p = 0.03) (Figure). IR and IS groups had no significant differences in the MLHF emotional domain and SF36 mental component scores. After multivariable adjustment, there was no difference in survival between groups (HR 0.91, 95% CI 0.56-1.46). Conclusion Patients with PAH and IR had worse QOL compared to their IS counterparts but no difference in survival in this large prospective cohort. This abstract is funded by: This work was supported by the National Institutes of Health grants K23HL 141584, R01 HL173533

Abstract Senescent cells accumulate with age and contribute to tissue dysfunction, yet their identification in tissues is challenging due to low abundance, heterogeneous phenotypes, and the lack of specific markers. Senescence-associated features span multiple subcellular compartments, including nuclear DNA damage foci, cytosolic protein changes, and perinuclear alterations, each requiring tailored detection strategies. To overcome these challenges, we developed SenoQuant ( https://github.com/HaamsRee/senoquant ), a versatile software designed for comprehensive, accurate, and unbiased spatial quantification and prediction of senescence markers across diverse tissue contexts. Utilizing AI models, SenoQuant enables precise nuclear and cytoplasmic segmentation and detection of senescence markers across low- and high-plex imaging modalities, applicable to cultured cells and tissue sections from mice and humans. The platform also supports custom AI models; for example, we built SenCeption, a proof-of-concept predictor of single-cell p21 status from DAPI-stained nuclei in human skin. Available as a free napari plugin, SenoQuant is widely accessible to researchers. By providing a unified approach to senescence analysis and prediction, SenoQuant opens new opportunities for exploring the complex biology of senescence and its impacts on aging and disease.

BACKGROUND: Some symptomatic patients manifest pulmonary hypertension (PH), despite normal pulmonary vascular resistance and pulmonary artery wedge pressure—a condition termed unclassified PH. Although hypothesized to reflect increased flow as seen in congenital heart disease, broader clinical implications remain unknown. METHODS: The current analysis included pulmonary vascular disease phenomics participants with either no PH or unclassified PH who underwent dynamic right heart catheterization and transpulmonary metabolomics. In a validation cohort, patients with no PH or unclassified PH underwent exercise right heart catheterization. In exploratory cohorts to understand the impact of increased flow, the prevalence of unclassified PH was assessed in (1) adult congenital heart disease and (2) high output heart failure. RESULTS: The overall prevalence of unclassified PH in pulmonary vascular disease phenomics (n=1046) and the validation cohort (n=1202) was 7.8% (175/2248), which was comparable to the 6.6% (66/1005) prevalence in adult congenital heart disease (n=1005), and lower than high output heart failure (n=159, prevalence 14.5% [23/159]; P =0.006). Increased flow occurred in a minority of unclassified PH from both pulmonary vascular disease phenomics (28%; 15/53) and the validation cohort (11%; 13/122). Unclassified PH (n=53) was associated with greater adiposity, higher heart failure with preserved ejection fraction (HFpEF)–age, body mass index, atrial fibrillation score probability, and more left heart remodeling compared with those with no PH (n=216). Metabolomics revealed lower glycine metabolites in unclassified PH indicative of metabolic dysfunction. Left heart remodeling, quality of life, exercise capacity, and glycine levels were all abnormal in unclassified PH relative to healthy controls (n=96). In the validation cohort, pulmonary artery wedge pressure, pulmonary vascular resistance, and pulmonary artery compliance were subtly abnormal at rest in unclassified PH (n=122) compared with no PH (n=312). With exercise testing, 59% (72/122) with unclassified PH had exertional pulmonary artery wedge pressure elevation consistent with undiagnosed HFpEF. CONCLUSIONS: The presence of PH without obvious cause most often reflects subclinical left heart and metabolic dysfunction consistent with unrecognized early-stage HFpEF. Dynamic provocation during right heart catheterization can unmask unrecognized HFpEF in over half of unclassified PH, which may help guide appropriate initiation of proven HFpEF therapies to improve symptoms and functional status. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02980887.

Context: Early palliative care can improve end-of-life outcomes, but referrals to palliative care specialists can be delayed in the primary care setting. Objective: This pilot study assessed the effect of a machine-learning algorithm on time to palliative care in a primary care population. Methods: Patients (aged ≥18 years) were eligible if they were empaneled with a primary care provider (PCP) from July 20, 2020, through May 30, 2021. The algorithm evaluated their health records and presented patients who were predicted to have the greatest need for palliative care. Records were then reviewed by palliative care specialists, and patients were randomized in a stepped-wedge fashion to have a referral notification sent to their PCPs if unmet palliative care needs were verified. Time-to-event outcomes were evaluated with Poisson regression models. Results: Of the 127,080 patients evaluated, 934 had their health records presented for review. Some patients were repeatedly presented by the algorithm (total presentations: 1592). In the intervention arm, PCPs were prompted to order a palliative care consultation for 142 patients. The time to 0.1% of the population receiving a palliative care consultation was 60.9 days for the intervention arm versus 71.8 days for the control arm (probability of a shorter time with the intervention, 0.88). Conclusion: A machine-learning algorithm to identify palliative care needs was successfully integrated into a primary care practice. More work is needed to improve the workflow.