Citations

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.

ABSTRACT Prior surveys of chronic automated red blood cell exchange (RCE) for patients with sickle cell disease (SCD) have identified considerable procedural variability, especially with the use of isovolemic hemodilution red blood cell exchange (IHD‐RCE). We conducted a survey of chronic RCE practices among American Society for Apheresis (ASFA) members to identify opportunities for practice harmonization and future studies. The ASFA SCD Research Subcommittee developed a 72‐item survey of chronic RCE practices, with a focus on IHD‐RCE. The survey was validated internally and distributed by email to all ASFA members from September 2024 to February 2025. One survey response from each institution was retained for data analysis. Descriptive statistics were performed. Sixty‐two survey responses, including three from international institutions, were retained for analysis. Sixty‐one percent of respondents (38/62) reported using at least one fixed RCE target, with end hematocrit being the most common fixed parameter (40%, 25/62), followed by fraction of cells remaining (31%, 19/62) and hemoglobin S% (27%, 17/62). Most respondents (60%, 37/61) performed IHD‐RCE at their institution, though other details such as the minimum hematocrit, exclusion criteria, and response to adverse effects were variable. Consistent pre‐ and post‐RCE laboratory monitoring practices were reported. Consistent with earlier surveys, procedural variability in chronic RCE practices for patients with SCD is observed. This highlights opportunities to compare outcomes where practice variability exists. Consensus guidelines based on institutional practices with optimal outcomes should be developed.

Abstract Purpose Elective genomic sequencing (EGS) returns monogenic disease findings in multiple genes, including potentially novel variants, and may also provide participants with carrier status, pharmacogenomic and other health-related information. The PeopleSeq Study assessed participants’ motivations for and concerns about EGS and the associated clinical and psychosocial outcomes across diverse EGS providers. Methods We administered a shared questionnaire to participants who chose to undergo EGS via 18 academic, clinical, or commercial EGS platforms. Results We enrolled 1575 participants, of whom 1147 (72.8%) completed a questionnaire after receiving their EGS results. A majority (60.3%) of the participants who completed a post-result questionnaire self-reported receiving results they assessed as important, including negative findings, and 75.9% reported a form of health-related utility. Among a subset (19.4%) who shared their EGS reports, 16.6% (37 of n =223) received a monogenic finding and self-reported results deemed “important” were consistent with EGS reports. Most participants (74.1%) discussed their results with their family, but fewer discussed their results with a healthcare provider other than the site team (41.7%) or had one or more medical visits as a direct result of their EGS testing (23.1%). Participants expressed diverse motivations for EGS, with 91.4% expressing interest in their personal disease risk and 54% who expressed quasi-indication-based motivations related to family medical history. Individuals motivated by family history reported important results at a significantly higher rate. Conclusions Early adopters of EGS are motivated by general interest in their health as well as quasi-indication-based considerations such as family history. A majority of participants learned results they considered medically important, but a much smaller segment engaged healthcare providers with their results.

Abstract In 2024, the National Academies of Sciences, Engineering, and Medicine (NASEM) published a report entitled Advancing Research on Chronic Conditions in Women. A major purpose of this report was to summarize the current state of research into a series of 21 chronic conditions that affect women differently or that are more common in women. The American Society for Bone and Mineral Research (ASBMR) established a working group to evaluate the NASEM report’s implications for women’s musculoskeletal (MSK) health. This perspective summarizes key research gaps identified in the NASEM report, including the lack of sex-specific data, underrepresentation of women in clinical studies, and minimal integration of MSK health with other chronic conditions. The NASEM report underscores the need for more comprehensive study designs that consider hormonal, genetic, and social determinants of health across the lifespan. In addition to osteoporosis, in this perspective, the ASBMR working group highlights emerging but poorly understood evidence of detrimental effects on musculoskeletal biology in non-MSK, chronic diseases that were identified in the NASEM report to disproportionately affect women. To advance the field, we advocate for better diagnostics, increased investment, and stronger representation of women in research studies. Addressing these gaps is critical for improving prevention, care, and outcomes for chronic conditions that uniquely or disproportionately affect women.

Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) recently celebrated its 20th anniversary, reflecting two decades of major contributions to Alzheimer's research through open data sharing and longitudinal multimodal assessments. This review synthesizes 122 high‐impact studies using ADNI data or biospecimens from 2023 to mid‐2025 to clarify mechanisms of Alzheimer's disease (AD) progression. Studies describe impairment of glymphatic clearance and the impact of cerebral small vessel disease, trajectories of amyloid beta and tau deposition, inflammation, metabolic disturbances, synaptic dysfunction, and neurodegeneration, leading to cognitive impairment and neuropsychiatric symptoms. Multifactorial contributions from genetic and epigenetic influences, co‐pathologies and comorbidities, and mechanisms of resilience modulate disease progression. Finally, heterogeneity of clinical presentation and disease course is described in the context of multiple contributing factors, highlighting the complexity of AD. By integrating imaging, fluid biomarkers, genetics, and clinical measures, ADNI provides a comprehensive research dataset for unraveling mechanisms underlying AD progression.