Citations

Background: Age is the strongest factor determining disease expression in multiple sclerosis (MS). We previously demonstrated biological age acceleration in pediatric-onset MS (POMS) compared to controls with both epigenetic clocks (DNAm) and telomere length (TL). It is unknown whether these markers report overlapping or distinct aging-related processes. Objectives: To determine the correlation between DNAm and TL aging markers. Methods: We conducted a cross-sectional case–control study within the US Network of Pediatric MS Centers. We calculated age acceleration residuals for the Horvath, Hannum, PhenoAge, and GrimAge epigenetic clocks and measured TL from whole blood samples to estimate telomere to somatic DNA ratios (T/S ratio). We employed multivariable analysis of covariance to assess the correlation between DNAm estimates and TL. Results: We analyzed biological ages in 270 participants (125 POMS, mean 15.7 years; 145 controls, mean 15.3 years). There were moderate correlations among the different DNAm clocks, but no correlations between DNAm clocks and TL in pooled analyses. In a stratified analysis, only the control group showed a modest correlation between TL and PhenoAge clock ( r = 0.2, p = 0.06). Conclusions: DNAm did not correlate with TL in this sample of POMS and controls, suggesting that these biomarkers may capture complementary and non-overlapping elements of aging-related biology.

Objective To assess real‐world effectiveness of switching disease‐modifying therapy (DMT) in pediatric multiple sclerosis (MS) and clinically isolated syndrome (CIS) initially treated with platform injectables on disease activity. Methods Of 2615 pediatric‐onset demyelinating disease patients at 12 clinics in the United States (US) Network of Pediatric MS Centers, those with MS/CIS on initial therapy with a platform injectable who switched to another class of platform injectable, oral or infusion DMT were analyzed. Relapse rate was modeled with negative binomial regression, adjusted for preidentified confounders. Results A total of 212 children switched DMT before age 18 (67% female, 95% MS). Ninety‐three switched from injectable to injectable, 76 injectable to oral, and 43 injectable to infusion. Switchers to oral or infusion were older at onset (injectable 12.3 years, oral 13.5 years, and infusion 14.2 years) and switch (injectable 14.6 years, oral 16.0 years, and infusion 15.7 years). Switchers to infusion DMT were more likely to have enhancing lesions (injectable 45%, oral 28%, and infusion 67%). Compared to injectable (annualized relapse rate [ARR] = 0.88, 95% confidence interval [CI] = 0.52–1.48), relapse rates were lower for injectable to oral (ARR = 0.34, 95% CI = 0.20–0.57; rate ratio: 0.38, 95% CI = 0.21–0.69) and injectable to infusion (ARR = 0.18, 95% CI = 0.09–0.37; rate ratio: 0.21, 95% CI = 0.10–0.44) ( p < 0.001). Adjusted number needed to treat in person‐years to prevent 1 relapse with oral over injectable was 1.84 (95% CI = 1.03–8.69) and infusion over injectable 1.43 (95% CI = 1.00–3.88). Interpretation Switching from platform injectable to oral or infusion compared to other platform injectable DMT led to better disease control in pediatric MS. Long‐term safety data are required. ANN NEUROL 2026;99:715–729

Decades of research on biomarker identification and integration in Alzheimer’s disease (AD) have helped to advance biologically driven disease models, disease subtypes, and disease-modifying treatments. Key lessons learned from AD biomarker development include the need for integration of new biological insights, investment in large cross-sectional and longitudinal studies, a multicomponent biomarker approach, and recruitment of clinical trial cohorts and biosamples that are representative of the target population. We describe how these lessons are being applied in Parkinson’s disease, Huntington’s disease, multiple sclerosis, and psychotic disorders as use cases to inform biomarker-based approaches across central nervous system disorders.

Abstract The addition of pembrolizumab to preoperative radiotherapy (RT) improved disease-free survival (DFS) for patients with stage III undifferentiated pleomorphic sarcoma (UPS) and dedifferentiated/pleomorphic liposarcoma (LPS) in the randomized SU2C-SARC032 trial. To precisely identify patients who benefit from pembrolizumab and RT, we performed comprehensive multi-omics profiling of pre- and post-treatment tumor and blood samples, including bulk RNA-seq, flow cytometry, and cytometry by time of flight. Additionally, we built a single-cell RNA-seq atlas spanning 65,786 cells from UPS and LPS to recover single-cell states in bulk tumor samples using digital cytometry. Two opposing tumor microenvironments (TMEs), immune-cold sarcoma ecotype 1 (SE1) and immune-hot sarcoma immune class E (SIC E), benefited from pembrolizumab. Pembrolizumab combined with RT caused an overall increase in activated CD8 + T cells, CD56 low NK cells, and T cell receptor diversity, while diminishing matrix-remodeling stromal cells and sarcoma cells. Our findings identify different mechanisms of response to pembrolizumab in localized, high-risk UPS/LPS and suggest that sarcoma TME signatures may identify patients most likely to benefit from adding pembrolizumab to preoperative RT.

Background: Post-treatment prognosis and monitoring are critical for determining the timing of salvage treatment in glioblastoma patients but has been challenging due to difficulties differentiating progression from treatment effects in conventional images. This exploratory study aimed to establish the correlation of radiomics image features from time series of amino acid tracer 18F-DOPA PET images, with outcomes, using machine learning and dimension reduction analysis. Methods: 18F-DOPA PET images were collected for a patient cohort with wild-type IDH and unmethylated MGMT who underwent dose-escalated radiation therapy. Quantitative features were derived from the high uptake region (T/N > 2.0) in pre- and post-radiation therapy follow-up 18F-DOPA PET images. A customized workflow was utilized for pre-selecting predictive features, followed by manifold learning. Machine learning algorithms were employed to establish associations between imaging features and remaining survival (RS), defined as the time between a follow-up scan and date of death. Results: The ML models exhibited 81–83% ROC_AUC in predicting RS evaluated on an independent test dataset. A RS map is proposed for monitoring tumor alterations through serial 18F-DOPA PET scans, demonstrating superior sensitivity and better correlation with survival compared to the RANO criteria. Conclusions: Our study demonstrates that ML models utilizing FU 18F-DOPA PET images have the potential to effectively predict future survival outcomes in patients with glioblastoma treated with dose-escalated radiation therapy. The capability to assess changes in tumor over time through imaging can potentially assist in patient stratification and the selection of salvage treatments, while also aiding in distinguishing treatment effects from genuine tumor progression.

Background/Objectives: Erythromelalgia is a rare condition characterized by burning pain, redness, and warmth primarily in the extremities, usually worsened by heat and alleviated by cold. The objective of this study was to identify the top 10 priorities in pediatric erythromelalgia from multiple perspectives, including clinicians, people with lived experience of childhood-onset erythromelalgia, and their family members. Methods: A modified James Lind Alliance Priority-Setting Process was conducted. The top priorities were identified through four phases: (1) an international online survey to gather priorities, (2) data processing, (3) an interim prioritization online survey, and (4) a virtual workshop to set the final priorities. Results: In phase 1, 185 potential priorities were submitted by 74 respondents (53% patients, 24% family members, and 23% clinicians) that were developed into 68 unique research questions (phase 2). In phase 3, of the 68 questions, 50 were rated for importance by 58 participants (38% patients, 36% family members, and 26% clinicians), reducing the list to 25 questions. In phase 4, the top 10 was reached through consensus by 12 participants (33% patients, 25% family members, and 42% clinicians) across Canada, South Africa, the United States of America, and the United Kingdom. Conclusions: The final priorities focused on the treatment of erythromelalgia, understanding underlying mechanisms, the association of erythromelalgia with various body systems, and generating awareness. This list is the first international patient-centered research agenda for childhood-onset erythromelalgia and a call to action from key partners to improve future research and care.

Background: A key determinant of prognosis in pulmonary hypertension (PH) is the right ventricle’s (RV) ability to adapt to increased pulmonary vascular resistance. Consequently, markers of RV-pulmonary artery (PA) coupling may improve prognostic prediction in PH. The ratio of tricuspid annular plane systolic excursion (TAPSE) to systolic PA pressure (sPAP) has been proposed as a surrogate for RV-PA coupling and a reliable prognostic marker, however, the existing data on the prognostic value of the ratio between RV longitudinal strain (RVLS) and sPAP as a surrogate for RV-PA coupling is scarce. Hypothesis: To evaluate the prognostic role of RVLS/RVSP in PH patients and to compare this novel marker with established markers of RV-PA coupling. Methods: This is a single-center study that included adult patients with PH classified as group I or IV, all of whom had undergone a transthoracic echocardiogram (TTE) within one year prior to the initiation of PH-specific treatment. Certified sonographers procured RV strain measurements using a specific software (Epsilon Imaging, Ann Arbor, MI). Receiver operating characteristic (ROC) analysis was used to determine the best cutoff for predicting all-cause mortality at one-year for RVLS/RVSP and TAPSE/RVSP. The association of RVLS/RVSP and TAPSE/RVSP with mortality at one year was assessed using the Kaplan-Meier analysis and multivariate Cox regression analysis (adjusted for REVEAL LITE 2.0 risk score). Results: A total of 160 patients were included with a median age of 67.2 (56.8, 73.7) years and 47 (29.2%) were male . ROC analysis revealed optimal cutoffs of 0.265 (AUC = 0.83) for RVLS/RVSP and 0.185 (AUC = 0.77) for TAPSE/RVSP to predict all-cause mortality at one year. One-year cumulative incidence of all-cause mortality was lower among patients with RVLS/RVSP ≥ 0.265 (0 % vs 13.7 %, p = 0.001) and patients with TAPSE/RVSP ≥ 0.185 (1.8 % vs 16.7 %, p = 0.001) (Figure 1) . In the multivariate analysis, RVLS/RVSP < 0.265 was associated with higher risk of mortality at one year (HR: 2.38, 95 % CI: 1.05 to 5.38, p = 0.036) while TAPSE/RVSP < 0.185 was not (HR: 2.01, 95 % CI: 0.93 to 4.31, p = 0.072). Conclusions: RVLS/ RVSP may be a valuable prognostic marker in PH patients and could outperform conventional TTE parameters as a surrogate for detecting RV-PA coupling.

Abstract Purpose: Polatuzumab vedotin (polatuzumab) was approved for up-front treatment of diffuse large B-cell lymphoma in combination with chemoimmunotherapy (Pola-R-CHP) based on the POLARIX trial. However, when stratified by cell of origin (COO), polatuzumab seems to have greater efficacy in activated B-cell than germinal center B-cell (GCB) subtype disease. Most studies of polatuzumab used RNA expression to assess COO, whereas in routine clinical practice, the immunohistochemistry-based Hans algorithm is used. Experimental Design: To assess the impact of COO by immunohistochemistry on polatuzumab efficacy, we conducted a multicenter real-world study of adults with large B-cell lymphoma (LBCL) receiving polatuzumab from 2015 to 2024, split by receipt of polatuzumab in first-line versus relapsed/refractory settings. The primary endpoint was overall response rate (ORR) to polatuzumab-based treatment in GCB versus non-GCB relapsed/refractory LBCL. Results: Of 740 patients, 305 received polatuzumab in the first-line setting and 435 in the relapsed/refractory setting. In the relapsed/refractory cohort, the ORR in non-GCB versus GCB LBCL was 59.7% versus 36.3% [OR, 2.6; 95% confidence interval (CI), 1.77–3.84; P &lt; 0.0001], with a complete response rate of 35.7% versus 17.7% (OR, 2.6; 95% CI, 1.66–4.02; P &lt; 0.0001). Progression-free survival was longer for patients with non-GCB versus GCB COO (HR, 0.64; 95% CI, 0.5–0.83; P = 0.0006). In the first-line cohort, ORR, complete response rate, and progression-free survival were similar in non-GCB versus GCB LBCL, as hypothesized based on outcomes in the Pola-R-CHP arm of POLARIX, suggesting that the addition of polatuzumab overcomes the adverse risk of non-GCB COO in patients receiving R-CHOP. Conclusions: Based on these data, COO classification by the Hans algorithm is a strong predictor of polatuzumab efficacy in LBCL, informing real-world treatment decisions.

Objective: The specialty of critical care in the United States currently lacks a single, broad, unified database. We conducted a scoping review of existing established national ICU databases, describing national and international patterns of critical care delivery. Data Sources: A systematic literature search was undertaken using MEDLINE, Embase, and Web of Science search engines. Study Selection: Projects describing national critical care delivery (including any subspecialty) published in any language were included. Titles, abstracts, and full-text manuscripts were reviewed in duplicate for inclusion. Data Extraction: National database characteristics were collected, including the number and subspecialty of ICUs, the inaugural year, data entry methodology, the number of episodes of care included, and captured clinical data elements. Data Synthesis: Of 24,003 abstracts screened, 185 manuscripts were eligible for inclusion. Thirty countries were identified as having established national ICU registries: Argentina, Australia/New Zealand, Austria, Belgium, Brazil, Canada, Denmark, Ecuador, Finland, Germany, Iceland, India, Ireland, Italy, Japan, Kenya, Malaysia, Mexico, Nepal, Netherlands, Norway, Pakistan, Paraguay, Spain, Sri Lanka, Sweden, Switzerland, United Kingdom, United States and Uruguay. Data entry commonly incorporates a combination of automated data abstraction from electronic healthcare systems and manual data entry, followed by independent validation. Frequently recorded variables include patient demographics; admission vital signs and laboratory data; comorbidities; admission source and diagnoses; ICU diagnoses, treatments, and complications; illness severity scores; and clinically relevant outcomes including discharge disposition, functional status, lengths of stay, and mortality. Conclusions: Insights and experience gained from the study of mature national ICU registries may be used to guide an equivalent U.S. multidisciplinary program aimed at benchmarking, needs assessment, quality improvement, and research facilitation