Hemnes, A R

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 Introduction Interstitial lung disease-associated pulmonary hypertension (ILD-PH) is a clinically challenging entity that lies on a pathophysiologic spectrum between pulmonary arterial hypertension (PAH) and interstitial lung disease (ILD). We compared the metabolomes of patients with ILD-PH to those with PAH and ILD to characterize the PAH-ILD axis and determine whether ILD-PH patients can be phenotyped based on their metabolomic similarity to PAH. Methods Using untargeted metabolomics profiles from patients with PAH, ILD, and ILD-PH in the large, U.S.-based, NIH-funded, multi-center PVDOMICS cohort, we trained an anchor-based classifier on PAH and ILD metabolomes using supervised PLS-DA with a 75/25 train/test split. Primary and secondary PH or risk-group classifications in PVDOMICS were based on expert adjudication of clinical data including right heart catheterization hemodynamics, pulmonary function testing, chest imaging, and laboratory results. We then applied the trained model to each ILD-PH patient to assign a PAH similarity score. We classified patients as having a PAH-like or ILD-like metabolomic phenotype using an optimal PAH similarity score cutoff of 0.5 then compared PAH metabolomic similarity to expert-adjudicated primary and secondary WSPH classifications in PVDOMICS. We implemented FELLA, a network-based metabolomics enrichment method, to holistically characterize the biologic underpinnings of PAH, ILD-PH, and ILD metabolomes. Results We analyzed 244 patients with PAH, 54 with ILD, and 47 with ILD-PH. The anchor-based classifier demonstrated high train-test performance with a c-statistic of 0.81 and 78% agreement with expert-adjudicated diagnoses. Among the ILD-PH patients, 23 were classified as PAH-like and 24 as ILD-like (74% agreement with expert adjudication, Cohen’s kappa 0.49, Hedge’s g estimate of 0.86). FELLA enrichment revealed core glycolytic and bioenergetic pathways were enriched in both pure PAH and ILD-PH. Comparison of diffusion Z-scores between groups demonstrated subtle but biologically coherent differences in several reaction-level nodes, including lactate, NADPH oxidoreductase, and phosphofructokinase, which were enriched in ILD-PH. Conclusion Patients with ILD-PH demonstrate clinically relevant metabolomic phenotypes. Examination of the network biology underlying ILD-PH may point to potential therapeutic targets in this vulnerable subgroup with lagging clinical outcomes. This abstract is funded by: Pulmonary Fibrosis Foundation PFF Scholars Program

Abstract Rationale The pathophysiology and clinical impact of liver injury in pulmonary hypertension (PH) is poorly understood. Liver injury in PH is often attributed to hepatic congestion, but some studies have failed to find strong associations with hemodynamics, suggesting alternative mechanisms. We sought to define the prevalence of liver injury and patterns of liver injury across the spectrum of PH and to determine whether patterns of liver injury were associated with clinical characteristics, hemodynamics and outcomes. Methods We performed an analysis of the PVDOMICS study, a multicenter, prospective, longitudinal cohort study that enrolled incident and prevalent patients with PH and disease comparators. The prevalence of liver injury, defined as aspartate or alanine aminotransferase (AST or ALT) or total bilirubin above the upper limit of normal, and different patterns of liver injury [hepatocellular (elevated AST or ALT with normal bilirubin), cholestatic (elevated bilirubin) and no liver injury] was defined among participants with known or suspected PH. Associations between patterns of liver injury with demographics, hemodynamics, right ventricular function, exercise capacity and quality of life (QoL) were assessed. We used Cox proportional hazards models adjusted for age and sex to assess the association of liver injury patterns with transplant-free survival. Results Liver injury was present in 27.8% (288/1036) of participants (19.0% cholestatic and 8.8% hepatocellular). Patients with liver injury were less likely to be female and have prevalent disease with differences in PH classification (Table 1). Patients with hepatocellular liver injury had a higher body mass index. A cholestatic liver injury pattern was most consistently associated with worse functional class, biventricular filling pressures, pulmonary vascular resistance, right ventricular function, natriuretic peptide elevation, exercise capacity, and REVEAL risk scores. Total bilirubin levels and right atrial pressure as a marker of systemic congestion were weakly correlated (r2=0.02, p < 0.0001). Compared to no liver injury, cholestatic liver injury was associated with an increased risk of death in age and sex adjusted models (HR 1.6, 95% CI 1.3-2.1, p < 0.001) but hepatocellular liver injury was not (p > 0.05). Conclusions Liver injury is common among patients with known or suspected PH. In contrast to a hepatocellular injury pattern, a cholestatic liver injury pattern was most consistently associated with worse hemodynamics, exercise capacity, QoL and survival. However, the weak relationship between right atrial pressure and bilirubin suggests that systemic congestion alone is unlikely to completely explain cholestatic liver injury. Further study is needed to uncouple the pathophysiological basis of cholestasis in PH. This abstract is funded by: NHLBI

Abstract Rationale Pulmonary hypertension (PH) is a heterogeneous condition classified into 5 WSPH groups but lacking detailed molecular distinction. The PVDOMICS cohort includes all PH groups alongside healthy and disease comparators, is deeply clinically phenotyped and has RNA sequencing data. Pseudogenes are conserved genome elements that due to sequence-defects cannot be translated into functional proteins. Some pseudogenes never-the-less produce RNA-transcripts which can regulate the expression of other, protein coding genes. Therefore, our study was focused on identifying differentially expressed pseudogene-transcripts within the dataset from the PVDOMICS study and gaining insights into their potential function. Methods Peripheral venous whole blood was collected from PVDOMICS participants [n = 525 PH patients; n = 312 controls without PH who were comparators (n = 256) or healthy (n = 56)]. RNA was isolated, RNA sequencing was performed. After quality control, differential transcript expression between PH and control groups was analyzed using the limma-voom pipeline, rSEA with adjustment for age, sex, race, smoking, WSPH group, latent factors and false discovery rate. We focused on a) transcripts expressed at increased levels (n = 218): the first 200 DEG (differentially-expressed-genes)-transcripts based on log2 difference plus increased DEG within the first 200 most significant p-values; and b) transcripts expressed at decreased levels (n = 292): last 200 DEG based on log2 difference plus decreased DEG within the first 200 most significant p-values. Results Six pseudogene transcripts were among the increased and 35 pseudogene transcripts were among the decreased DEG in the PH group compared to controls. Some of the differentially expressed pseudogenes (DEP) belonged to gene families, like the ribosomal protein family (7 DEP), mitochondria expressed transcripts (3 DEP), zinc finger proteins (2 DEP). Associations of pseudogenes with biological function or disease were extracted via GeneCards(R) and information from GWAS analysis. The DUSP8P5 pseudogene was among the DEP and is known for its association with left heart disease and hypertension; 2 additional DEP have known association with hypertension. Further known associations were with inhibitory or inflammatory immune processes (8 DEP), bone density (6 DEP), metabolism and diabetes (6 DEP), respiratory function or disease (4 DEP), erythrocyte biology (3 DEP), cancer (5 DEP), kidney disease (1 DEP), and demographic parameters like eye or hair color (2 DEP). Ten DEP had no known association with function or disease. Conclusions We identified pseudogene RNA-transcripts associated with PH across WSPH groups. The local vs. systemic effects of these pseudogene transcripts on PH remain to be determined and regulators of pseudogene-transcript expression (e.g. environmental exposures) identified. This abstract is funded by: 1 X01 HL148611 (TopMed), PVDOMICS NHLBI, PVDOMICS Pulmonary Hypertension Association, HT9425-25-1-0533 (GG), 1R21OH012955-01 (GG)

Abstract Rationale Pulmonary hypertension (PH) is classified into five groups. Diagnosis requires multiple tests delaying treatment. This study compared patient and diagnostic characteristics for pulmonary arterial hypertension (PAH; Group 1 PH), Group 2-5 PH, and non-PH using machine-learning in an Electronic Health Record (EHR) dataset. This is novel as prior studies use claims data which may lack hemodynamic parameters. Methods This study analyzed adult patient records from a HIPPA-complaint EHR dataset from Mayo Clinic (2015-2024). Cohort definitions: PAH: right heart catheterization (RHC) data [mPAP>20 mmHg, PVR>2 WU, PCWP≤15 mmHg]; ≥2 PAH ICD diagnosis codes or positive natural language processing (NLP) sentiments separated by ≥ 30 days; and use of at least one PAH medication within six months after index date. Group 2-5 PH: RHC (mPAP>20mmHg) and ICD codes or positive NLP sentiment separated by ≥ 30 days for corresponding PH subtype. Non-PH: mPAP ≤ 20 mmHg and/or TRV ≤ 2.8 m/s. Index was the earliest NLP or ICD for PAH, earliest RHC for group 2-5 PH and most recent TRV/ mPAP for the non-PH cohort. Clinical variables were analyzed one-year before study index acknowledging data missingness as a limitation of retrospective dataset studies. Results 593 PAH, 817 Group 2-5 PH (67% with group 2 PH), and 11,600 non-PH patients (1:10 propensity-matched) were identified. Age, race, and symptoms were similar across cohorts. PAH had the highest proportion of females (60%) [Group 2-5 PH (50%) and non-PH cohort (53%)]. Clinical characteristic comparison is presented in Table 1. Comorbidities differed across cohorts. RHC: As expected, compared to Group 2-5, the PAH cohort had higher mPAP and PVR and lower PCWP. confirming a distinctly pre-capillary profile. ECHO: Compared to Group 2-5 PH, the PAH cohort had more pronounced right ventricular (RV) pressure overload and dysfunction and more impaired RV longitudinal strain, while TAPSE was similar. At the same time, left heart structure was less affected in PAH compared to Group 2-5. Among laboratory tests, serum creatinine was higher in Group 2-5 and ANA was higher in PAH cohort. Compared to the no-PH cohort, PAH and Group 2-5 cohorts exhibited clinically non-normal RHC and ECHO findings. Conclusion Although symptoms and demographic characteristics were similar among patients with and without PAH, unique RHC, ECHO, laboratory profiles and comorbidities differentiated PAH patients. Screening techniques using these distinct profiles could be considered to facilitate earlier diagnosis and treatment of PAH in clinical settings. This abstract is funded by: Merck & Co., Inc., Rahway, NJ, USA

Abstract Rationale Pulmonary arterial hypertension (PAH) is a rare and progressive disease, where the guideline-recommended diagnostic confirmation is via right heart catheterization (RHC). However, due to non-specific symptomology, patients often experience delays in diagnosis that potentially impact disease outcomes. We sought to develop a machine learning (ML) based approach for early and appropriate detection of PAH. Methods Three cohorts were derived from Mayo Clinic electronic health record (EHR): confirmed PAH (N = 1,169), No PH (N = 11,600) and Other PH (Group 2-5 PH, N = 817), based on 2022 ESC/ERS guidelines. The study index was defined as the earliest diagnosis dates for PH cohorts (PAH & Other PH) or the latest PH negative echocardiogram (ECHO) or RHC for the No-PH cohort. Patients included in the study had at least one symptom (dyspnea, fatigue, syncope, chest pain, or lower extremity swelling) within one year prior to the study index. A two-step sequential ML modelling strategy was applied: Step 1 differentiated PH (PAH + Other PH) from No PH and step 2 differentiated PAH from Other PH. Models were trained using a combination of structured data, unstructured clinical notes to detect symptoms using natural language processing and ECG waveforms captured one year prior to study index. Models were tested both with and without ECHO parameters. SHAP (SHapley Additive explanations) values were used to determine important features contributing to models (without ECG waveforms). Results Models including ECHO parameters performed better compared to those without (Figure 1). The top feature impacting model without ECHO parameters was dyspnea in the preceding three months followed by heart failure and systolic blood pressure for the PH vs no PH; and T wave peak in V1 and ANA level in PAH vs other PH cohort. The top feature impacting model with ECHO was tricuspid regurgitation velocity followed by heart failure and right atrial pressure for the PH vs no PH; and mean blood pressure and left ventricular diameter in the PAH vs other PH cohort. Figure 1: Model performance in the two-step sequential approach PR-AUC=Precision Recall-Area Under Curve Conclusion This study demonstrates that ML models can aid in the identification of PAH in symptomatic patient populations. While ECG can identify patients for further testing, ECHO can further increase the accuracy and the need to refer patients to RHC for confirming diagnosis of PAH. This abstract is funded by: Merck & Co., Inc., Rahway, NJ, USA