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Non-suicidal self-injury (NSSI) is a common high-risk behavior in adolescents and it occurs in various psychiatric disorders, especially major depressive disorder (MDD). It remains largely unknown whether and which brain functional networks contribute to NSSI across youth psychiatric disorders.
Objectives
This study aimed to identify common brain functional networks associated with NSSI across youth psychiatric disorders, and to examine their relationships with NSSI behavior, addiction, and its functions. Furthermore, we sought to validate the generalizability of these neural correlates in independent clinical cohorts.
Methods
This study analyzed functional brain imaging data acquired from 156 adolescents (MDD+NSSI group, n = 44, age = 15.32 ± 1.51; MDD-NSSI group, n = 32, age = 15.36 ± 1.96; healthy controls, n = 80, age = 15.92 ± 2.72). NSSI behavior, addiction and its four NSSI functions (internal and external emotion regulation, social influence and sensation seeking) were assessed using the Ottawa Self-injury Inventory. Using support vector machine recursive feature elimination classification and regression models, we investigated the brain functional networks that predicted NSSI. External validations were performed in an ADHD cohort (n = 40) and a transdiagnostic cohort (n = 40).
Results
The brain networks related to NSSI behavior were mainly composed of inter-network connections between the fronto-parietal, motor, limbic, basal ganglia networks. These networks were also associated with NSSI addiction and its four functions. Notably, the fronto-parietal network was involved in all NSSI components. External validations in both the ADHD and the transdiagnostic cohorts validated the associations of these functional networks with NSSI severity.
Conclusions
Our results demonstrate roles of the fronto-parietal, motor, limbic and basal ganglia networks in NSSI across youth psychiatric disorders, which may serve as neural markers and potential targets for prevention and intervention.
Drylands cover 41% of Earth’s land surface, support 36% of the global population and contribute 60% of global food production. Despite these ecosystems’ importance and high vulnerability to droughts and heatwaves, drylands remain some of the most understudied systems on Earth. Monitoring drylands is challenging due to their complex ecosystem structure of visible soil mixed with diverse plant species that respond rapidly to weather and climate. In 2023 and 2024, a NASA scoping study was conducted for a proposed dryland terrestrial ecology field campaign called Adaptation and Response in Drylands (ARID). Thereafter, the NASA ARID scoping team submitted their campaign proposal to NASA Headquarters, providing a study design for how field, aircraft and satellite measurements, as well as modeling, could address the most critical fundamental and applied science questions in drylands. The extensive strategic vision was created by and for the drylands research community, including remote sensors, modelers, experimentalists and ecologists from across the world, and the overall approach can be further utilized and altered for different uses and data information needs. Here, we summarize the final ARID research agenda, including its main objectives, field campaign strategy, data end-user support strategy, and U.S. and global community engagement.
Spectral-line results from a new cryogenic phased array feed (cryoPAF) on the Murriyang telescope at Parkes are presented. This array offers a significant improvement in field of view, aperture efficiency, bandwidth, chromaticity, and survey speed compared with conventional horn-fed receivers. We demonstrate this with measurements of sky calibrators and observations of 21-cm neutral hydrogen (HI) in the Large Magellanic Cloud (LMC) and the nearby galaxy NGC 6744. Within 0.3 deg of the optical axis, the ratio of system temperature to dish aperture efficiency ($T_\mathrm{sys}/\eta_{d}$) is 25 K, and the ratio with beam efficiency ($T_\mathrm{sys}/\eta_\mathrm{mb}$) is 21 K (at 1.4 GHz). For the previously measured $T_\mathrm{sys} = 17$ K, respective efficiency values $\eta_{d} \approx 0.7$ and $\eta_\mathrm{mb} \approx 0.8$ are derived. Our HI observational results are in good agreement with previous results, although detailed comparison with multibeam observations of the LMC suggests that the earlier observations may have missed an extended component of low-column-density gas ($\sim$$8\times 10^{18}$ cm$^{-2}$). We use the cryoPAF zoom-band and wideband data to make a preliminary investigation of whether the large number of simultaneous beams (72) permits the use of novel data reduction methods to reduce the effects of foreground/background continuum contamination and radio-frequency interference (RFI). We also investigate if these methods can better protect against signal loss for the detection of faint, extended cosmological signals such as HI intensity maps. Using robust higher-order singular value decomposition (SVD) techniques, we find encouraging results for the detection of both compact and extended sources, including challenging conditions with high RFI occupancy and significant sky continuum structure. Examples are shown that demonstrate that 3D SVD techniques offer a significant improvement in noise reduction and signal capture compared with more traditional layered 2D techniques.
This study examines Hispanic formal volunteering and the cultural, social, and community context factors that affect their decision to volunteer. Using data from three surveys in the United States, the study finds that religious attendance, cultural background, and education are the most consistent and significant predictors of Hispanic formal volunteering. Religious attendance has a stronger positive impact on Hispanic volunteering than on non-Hispanics. The impacts of income, social resources, and community characteristics on Hispanics’ volunteering vary by surveys. Secular organizations serving children and youth and religious organizations are the favorite organizations for Hispanic volunteers.
To investigate the advantages and disadvantages of two multi-swirl fuel-rich dome configurations, namely the triple-swirler and double-swirler, for a novel high-temperature rise centre-staged combustor, this study employed ANSYS Fluent software. Utilising the Reynolds-averaged Navier-Stokes (RANS) equation as the governing equation, three-dimensional numerical simulations were conducted using the Realisable k-ε turbulence model and non-premixed probability density function (PDF) combustion model to analyse the flow and combustion characteristics of both configurations. A comparative study was then performed to evaluate the performance differences between the two dome configurations under take-off and idle conditions. The results demonstrate that, under both conditions, the fuel-air mixing in the triple-swirler combustor occurs faster and more uniformly. Specifically, during takeoff, the primary zone temperature distribution in the triple-swirler combustor is more uniform, while during idle, the fuel-rich combustion region is more symmetrical. Furthermore, across both conditions, the outlet temperature distribution of the triple-swirler combustor is of superior quality, albeit with equivalent combustion efficiency. Notably, the formation of NOx and soot in the triple-swirler combustor, during takeoff conditions, exceeds that of the double-stage combustor along the flow path, whereas the generation of CO and UHC, during idle conditions, is lower in the former.
Timely dissemination of clinical trial results is essential to advance knowledge, guide practice, and improve outcomes, yet many trials remain unpublished, limiting impact. We examine what drives publication and timelines across three major clinical domains.
Methods:
We analyzed study design and factors associated with dissemination of interventional trials, focusing on cardiovascular disease (CVD), cancer, and COVID-19. A total of 10,785 trials (CVD: 5929; cancer: 4210; COVID-19: 646) were linked to PubMed publications using National Clinical Trial identifiers. Study design, operational, and transparency-related features were assessed as predictors of time to publication, defined as the interval from study completion to first publication, using Cox proportional hazards model.
Results:
COVID-19 trials had the highest publication rate (49.6%), followed by CVD (42.3%) and cancer (32.9%), likely reflecting pandemic-related prioritization. Faster publication was associated with larger enrollment, more sites, result posting, randomization, DMC presence, and higher blinding levels (all p < 0.05). Slower publication was linked to supportive care or diagnostic trials (CVD), basic science (cancer), and later COVID-19 trial completion. In subgroups, U.S. facility presence (CVD) and phase 3 design (cancer) predicted faster publication, while healthy volunteer inclusion (CVD) predicted slower publication. Among DMC trials, more secondary outcomes were linked to faster publication across all disease areas.
Conclusions:
Key study design and operational factors consistently predict whether and when trials are published. Strengthening methodological rigor, result reporting, and multi-site collaboration may accelerate timely dissemination into peer-reviewed literature.
Respiratory virus transmission in healthcare settings is not well understood. To investigate the transmission dynamics of common healthcare-associated respiratory virus infections, we performed retrospective whole genome sequencing (WGS) surveillance at three teaching hospitals.
Methods:
From January 2, 2018, to January 4, 2020, nasal swab specimens positive for rhinovirus, influenza virus, human metapneumovirus (HMPV), or respiratory syncytial virus (RSV) from patients hospitalized for ≥3 days were sequenced. High-quality genomes were assessed for genetic relatedness using ≤3 single nucleotide polymorphisms (SNPs) as a cutoff, except for rhinovirus (≤10 SNPs). Patient health records were reviewed for genetically related clusters to identify epidemiological connections.
Results:
We collected 436 viral specimens from 359 patients: rhinovirus (n = 291), influenza virus (n = 50), RSV (n = 48), and HMPV (n = 47). Of these, 42%% (152/359 patients) were from a pediatric hospital, and 58% were from adult hospitals. WGS was performed on 61.2% (178/291) rhinovirus, 78% (39/50) influenza virus, 90% (43/48) RSV, and all HMPV specimens. Among high-quality genomes, we identified 14 genetically related clusters involving 36 patients (range: 2–5 patients per cluster). We identified common epidemiological links for 53% (19/36) of clustered patients; 63% (12/19) of patients had same-unit stays, 26% (5/19) had overlapping hospital stays, and 11% (2/19) shared common providers. On average, genetically related clusters spanned 16 days (range: 0 − 55 days).
Conclusion:
WGS offered new insights into respiratory virus transmission dynamics. These advancements could potentially improve infection prevention and control strategies, leading to enhanced patient safety and healthcare outcomes.
Operational roadblocks and organizational delays in multicenter clinical trials have been evident for decades, with the start-up cycle being especially notorious for setbacks. To address these challenges and improve multicenter clinical trial execution, we developed an accelerated start-up (ASU) management strategy – a structured site onboarding approach based on lean management principles.
Methods:
Three elements were integrated into the strategy: a standardized workflow, a dedicated site navigator (SN), and an electronic tracking system. We examined the range, central tendencies, and distribution of site activation times among differing combinations of these three elements. To determine how these combinations affected individual start-up milestones, we fit mixed models to compare percent achievement of predetermined milestone benchmarks and time to completion.
Results:
Thirteen consecutive trials (n = 308 site activations) employed three distinct combinations of the three ASU elements. Trials using all three elements (n = 6) had 160 total site activations in a median of 133 days. Three trials without the SN element had 52 total site activations in a median of 191 days. Four trials without the standardized workflow element had 96 total site activations in a median of 277 days. Significant differences between combinations included times to sIRB submission (p = 0.004), training/certificates completion (p = 0.03), and site activation (p = 0.003). Results suggest sites activated faster and achieved predetermined benchmarks for every milestone more often when three elements were employed.
Conclusion:
This sample trial start-up data supports that sites can meet ambitious timelines, underscoring the strategy’s potential to streamline workflows and improve site team performance.
Foodservice provision is a key contributor to both dietary intake and food waste production(1). The development of ‘root-to-tip’ recipes in foodservice that incorporate more of the plant (i.e. peels and stalks) is being explored to reduce the climate impact of food waste(1) and improve suboptimal population intakes of fruits and vegetables, which provide useful sources of dietary fibre associated with lower risk of all-cause mortality(2). However, given low peels and stalks consumption in the UK(3), the extent to which ‘root-to-tip’ dishes may just shift food waste along the supply chain by increasing plate waste is unknown. The aim of this study is to understand the acceptability of ‘root-to-tip’ dining by exploring consumer attitudes towards food waste and perceived barriers and enablers to eating peels and stalks.
In-person focus groups were conducted at a UK university with current students and employees. Convenience sampling was used to recruit between five to eight participants across six focus groups. A semi-structured topic guide with open-ended questions was developed to facilitate discussion. Discussions were audio recorded, transcribed verbatim and an inductive thematic analysis undertaken. The research protocol was approved by the King’s College London Research Ethics Committee (Ref: MRA-24/25-46016; LRS/DP- 24/25-46017)
Six focus group discussions were conducted with forty participants (November 2024 to January 2025), primarily aged 18-25 years (53%) and female (75%). Six preliminary themes were identified: 1) food waste as a structural issue; 2) personal food waste awareness and the intention-behaviour gap; 3) the role of social modelling in ‘root-to-tip’ behaviours; 4) safety and edibility concerns around peels and stalks; 5) knowledge as a facilitator for ‘root-to-tip’ adoption; and 6) the importance of sensory appeal. These themes illustrate consumers’ perception of food waste as primarily occurring up the supply chain prior to the preparation stage, with structural barriers to its reduction. Participants perceive a growing societal and personal consciousness of food waste and desire to reduce its associated negative consequences. However, results highlight social and personal barriers, such as cost and convenience, which may contribute to an intention-behaviour gap. These barriers were referenced regarding the use of peels and stalks specifically, with upbringing, social modelling and food habits described as factors influencing consumption. Improving awareness of the safety and edibility of peels and stalks and practical knowledge related to their use may facilitate adoption of ‘root-to-tip’ behaviours. Anticipation of an unappealing sensory experience was described as a deterrent for consuming ‘root-to-tip’ dishes. Therefore, ensuring ‘root-to-tip’ dishes have sensory appeal is important to increase acceptability and prevent plate waste.
Our findings contribute to the understanding of attitudes towards food waste reduction practices at the preparation stage, in particular the use of peels and stalks, and highlight a need for increased knowledge to facilitate behaviour adoption.
The millisecond pulsar PSR J1713$+$0747 is a high-priority target for pulsar timing array experiments due to its long-term timing stability, and bright, narrow pulse profile. In April 2021, PSR J1713$+$0747 underwent a significant profile change event, observed by several telescopes worldwide. Using the broad bandwidth and polarimetric fidelity of the Ultra-Wideband Low-frequency receiver on Murriyang, CSIRO’s Parkes radio telescope, we investigated the long-term spectro-polarimetric behaviour of this profile change in detail. We highlight the broad-bandwidth nature of the event, which exhibits frequency dependence that is inconsistent with cold-plasma propagation effects. We also find that spectral and temporal variations are stronger in one of the orthogonal polarisation modes than the other and observe mild variations ($\sim 3$ – $5\,\sigma$ significance) in circular polarisation above 1 400 MHz following the event. However, the linear polarisation position angle remained remarkably stable in the profile leading edge throughout the event. With over three years of data post-event, we find that the profile has not yet recovered back to its original state, indicating a long-term asymptotic recovery, or a potential reconfiguration of the pulsar’s magnetic field. These findings favour a magnetospheric origin of the profile change event over a line-of-sight propagation effect in the interstellar medium.
Schizophrenia is a severe psychiatric disorder affecting 50% of patients intermittently and 20% chronically, with high unemployment rates (80-90%) and reduced life expectancy. Although genetic and neurodevelopmental factors are established non-modifiable risk factors, knowledge gaps persist regarding prevention strategies, particularly the combined impact of modifiable risk factors.
Objectives
The aim of this study is to identify the modifiable risk factors and to estimate their joint effect on Schizophrenia.
Methods
We conducted an exposure-wide association study (EWAS) using the UK Biobank cohort to systematically evaluate 206 potentially modifiable factors associated with schizophrenia risk. The study population comprised individuals without schizophrenia at baseline, with diagnoses determined using ICD-10 criteria. We employed Cox proportional hazard regression models with Bonferroni correction (significance threshold: P<1.91×10-4) to identify significant factors. The identified factors were categorized into six domains: lifestyle, local environment, medical history, physical measures, psychosocial factors, and socioeconomic status (SES). Domain-specific, weighed, and standardized scores were calculated based on coefficients from Cox models, adjusting for covariates. Scores were stratified into tertiles (favorable, intermediate, unfavorable) for risk assessment. Population attributable fractions (PAFs) were calculated to quantify prevention potential.
Results
The study cohort included 498,351 participants (54.45% female; mean age: 56.55 years) followed for a mean duration of 14.37 years, during which 1,345 participants developed schizophrenia. We identified 86 significant modifiable factors, with disability (HR 6.23, 95% CI 5.48-7.07), depression (HR 5.06, 95% CI 4.93-5.20), and anxiety disorders (HR 3.69, 95% CI 3.12-4.36) showing the strongest associations. Our analyses suggested that transitioning unfavorable profiles to intermediate and favorable status (Estimation 1) could prevent 59.6% of schizophrenia cases, while shifting both intermediate and unfavorable profiles to favorable (Estimation 2) could prevent 90.4% of cases. In Estimation 2, the preventive potential was highest for SES (18.0%), followed by medical history (17.5%), lifestyle factors (17.0%), psychosocial factors (14.3%), physical measures (12.8%), and local environment (10.8%).
Image:
Conclusions
This analysis identifies multiple modifiable risk factors for schizophrenia, demonstrating substantial prevention potential through multi-domain interventions. Socioeconomic, medical, and lifestyle factors emerge as key targets for prevention strategies. The consistency of associations across genetic risk strata suggests interventions could be beneficial regardless of genetic predisposition, informing targeted prevention strategies and public health policies.
Electronic Health Record (EHR) data are critical for advancing translational research and AI technologies. The ENACT network offers access to structured EHR data across 57 CTSA hubs. However, substantial information is contained in clinical narratives, requiring natural language processing (NLP) for research. The ENACT NLP Working Group was formed to make NLP-derived clinical information accessible and queryable across the network.
Methods:
We established the ENACT NLP Working Group with 13 sites selected based on criteria including clinical notes access, IT infrastructure, NLP expertise, and institutional support. We divided sites into five focus groups targeting clinical tasks within disease contexts. Each focus group consisted of two development sites and two validation sites. We extended the ENACT ontology to standardize NLP-derived data and conducted multisite evaluations using the Open Health Natural Language Processing (OHNLP) Toolkit.
Results:
The working group achieved 100% site retention and deployed NLP infrastructure across all sites. We developed and validated NLP algorithms for rare disease phenotyping, social determinants of health, opioid use disorder, sleep phenotyping, and delirium phenotyping. Performance varied across sites (F1 scores 0.53–0.96), highlighting data heterogeneity impacts. We extended the ENACT common data model and ontology to incorporate NLP-derived data while maintaining Shared Health Research Informatics NEtwork (SHRINE) compatibility.
Conclusion:
This demonstrates feasibility of deploying NLP infrastructure across large, federated networks. The focus group approach proved more practical than general-purpose approaches. Key lessons include the challenge of data heterogeneity and importance of collaborative governance. This work also provides a foundation that other networks can build on to implement NLP capabilities for translational research.
Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group.
Methods
T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9).
Results
PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges’ g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges’ g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (pcorrected = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (pcorrected = .001).
Conclusions
PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.
During the COVID-19 pandemic, the United States Centers for Disease Control and Prevention provided strategies, such as extended use and reuse, to preserve N95 filtering facepiece respirators (FFR). We aimed to assess the prevalence of N95 FFR contamination with SARS-CoV-2 among healthcare personnel (HCP) in the Emergency Department (ED).
Design:
Real-world, prospective, multicenter cohort study. N95 FFR contamination (primary outcome) was measured by real-time quantitative polymerase chain reaction. Multiple logistic regression was used to assess factors associated with contamination.
Setting:
Six academic medical centers.
Participants:
ED HCP who practiced N95 FFR reuse and extended use during the COVID-19 pandemic between April 2021 and July 2022.
Primary exposure:
Total number of COVID-19-positive patients treated.
Results:
Two-hundred forty-five N95 FFRs were tested. Forty-four N95 FFRs (18.0%, 95% CI 13.4, 23.3) were contaminated with SARS-CoV-2 RNA. The number of patients seen with COVID-19 was associated with N95 FFR contamination (adjusted odds ratio, 2.3 [95% CI 1.5, 3.6]). Wearing either surgical masks or face shields over FFRs was not associated with FFR contamination, and FFR contamination prevalence was high when using these adjuncts [face shields: 25% (16/64), surgical masks: 22% (23/107)].
Conclusions:
Exposure to patients with known COVID-19 was independently associated with N95 FFR contamination. Face shields and overlying surgical masks were not associated with N95 FFR contamination. N95 FFR reuse and extended use should be avoided due to the increased risk of contact exposure from contaminated FFRs.
Background: TERT promoter mutation (TPM) is an established biomarker in meningiomas associated with aberrant TERT expression and reduced progression-free survival (PFS). TERT expression, however, has also been observed even in tumours with wildtype TERT promoters (TP-WT). This study aimed to examine TERT expression and clinical outcomes in meningiomas. Methods: TERT expression, TPM status, and TERT promoter methylation of a multi-institutional cohort of meningiomas (n=1241) was assessed through nulk RNA sequencing (n=604), Sanger sequencing of the promoter (n=1095), and methylation profiling (n=1218). 380 Toronto meningiomas were used for discovery, and 861 external institution samples were compiled as a validation cohort. Results: Both TPMs and TERTpromoter methylation were associated with increased TERT expression and may represent independent mechanisms of TERT reactivation. TERT expression was detected in 30.4% of meningiomas that lacked TPMs, was associated with higher WHO grades, and corresponded to shorter PFS, independent of grade and even among TP-WT tumours. TERT expression was associated with a shorter PFS equivalent to those of TERT-negative meningiomas of one higher grade. Conclusions: Our findings highlight the prognostic significance of TERT expression in meningiomas, even in the absence of TPMs. Its presence may identify patients who may progress earlier and should be considered in risk stratification models.
Background: Meningiomas are the most common intracranial tumors. Radiotherapy (RT) serves as an adjunct following surgical resection; however, response varies. RTOG-0539 is a prospective, phase 2, trial that stratified patients risk groups based on clinical and pathological criteria, providing key benchmarks for RT outcomes. This is the first study that aims to characterize the molecular landscape of an RT clinical trial in meningiomas. Methods: Tissue from 100 patients was analyzed using DNA methylation, RNA sequencing, and whole-exome sequencing. Copy number variations and mutational profiles were assessed to determine associations with meningioma aggressiveness. Tumors were molecularly classified and pathway analyses were conducted to identify biological processes associated with RT response. Results: High-risk meningiomas exhibited cell cycle dysregulation and hypermetabolic pathway upregulation. 1p loss and 1q gain were more frequent in aggressive meningiomas, and NF2 and non-NF2 mutations co-occurred in some high-risk tumors. Molecular findings led to the reclassification of several cases, highlighting the limitations of histopathologic grading alone. Conclusions: This is the first study to comprehensively characterize the molecular landscape of any RT trial in meningioma, integrating multi-omic data to refine treatment stratification. Findings align with ongoing genomically driven meningioma clinical trials and underscore the need for prospective tissue banking to enhance biomarker-driven treatment strategies.
Background: The WHO grade of meningioma was updated in 2021 to include homozygous deletions of CDKN2A/B and TERT promotor mutations. Previous work including the recent cIMPACT-NOW statement have discussed the potential value of including chromosomal copy number alterations to help refine the current grading system. Methods: Chromosomal copy number profiles were inferred from from 1964 meningiomas using DNA methylation. Regularized Cox regresssion was used to identify CNAs independenly associated with post-surgical and post-RT PFS. Outcomes were stratified by WHO grade and novel CNAs to assess their potential value in WHO critiera. Results: Patients with WHO grade 1 tumours and chromosome 1p loss had similar outcomes to those with WHO grade 2 tumours (median PFS 5.83 [95% CI 4.36-Inf] vs 4.48 [4.09-5.18] years). Those with chromosome 1p loss and 1q gain had similar outcomes to those with WHO grade 3 cases regardless of initial grade (median PFS 2.23 [1.28-Inf] years WHO grade 1, 1.90 [1.23-2.25] years WHO grade 2, compared to 2.27 [1.68-3.05] years in WHO grade 3 cases overall). Conclusions: We advocate for chromosome 1p loss being added as a criterion for a CNS WHO grade of 2 meningioma and addition of 1q gain as a criterion for a CNS WHO grade of 3.
Background: We previously developed a DNA methylation-based risk predictor for meningioma, which has been used locally in a prospective fashion. As a follow-up, we validate this model using a large prospective cohort and introduce a streamlined next-generation model compatible with newer methylation arrays. Methods: The performance of our next-generation predictor was compared with our original model and standard-of-care 2021 WHO grade using time-dependent receiver operating characteristic curves. A nomogram was generated by incorporating our methylation predictor with WHO grade and extent of resection. Results: A total of 1347 meningioma cases were utilized in the study, including 469 prospective cases from 3 institutions and a retrospective cohort of 100 WHO grade 2 cases for model validation. Both the original and next-generation models significantly outperformed 2021 WHO grade in predicting postoperative recurrence. Dichotomizing into grade-specific risk subgroups was predictive of outcome within both WHO grades 1 and 2 tumours (log-rank p<0.05). Multivariable Cox regression demonstrated benefit of adjuvant radiotherapy in high-risk cases specifically, reinforcing its informative role in clinical decision making. Conclusions: This next-generation DNA methylation-based meningioma outcome predictor significantly outperforms 2021 WHO grading in predicting time to recurrence. This will help improve prognostication and inform patient selection for RT.
Background: Meningiomas exhibit considerable heterogeneity. We previously identified four distinct molecular groups (immunogenic, NF2-wildtype, hypermetabolic, proliferative) which address much of this heterogeneity. Despite their utility, the stochasticity of clustering methods and the requirement of multi-omics data limits the potential for classifying cases in the clinical setting. Methods: Using an international cohort of 1698 meningiomas, we constructed and validated a machine learning-based molecular classifier using DNA methylation alone. Original and newly-predicted molecular groups were compared using DNA methylation, RNA sequencing, whole exome sequencing, and clinical outcomes. Results: Group-specific outcomes in the validation cohort were nearly identical to those originally described, with median PFS of 7.4 (4.9-Inf) years in hypermetabolic tumors and 2.5 (2.3-5.3) years in proliferative tumors (not reached in the other groups). Predicted NF2-wildtype cases had no NF2 mutations, and 51.4% had others mutations previously described in this group. RNA pathway analysis revealed upregulation of immune-related pathways in the immunogenic group, metabolic pathways in the hypermetabolic group and cell-cycle programs in the proliferative group. Bulk deconvolution similarly revealed enrichment of macrophages in immunogenic tumours and neoplastic cells in hypermetabolic/proliferative tumours. Conclusions: Our DNA methylation-based classifier faithfully recapitulates the biology and outcomes of the original molecular groups allowing for their widespread clinical implementation.
Background: The combination of PARP inhibitor and immune checkpoint inhibitors have been proposed as a potentially synergistic combinatorial treatment in IDH mutant glioma, targeting dysregulated homologous recombination repair pathways. This study analyzed the cell-free DNA methylome of patients in a phase 2 trial using the PARP inhibitor Olaparib and the PD-1 inhibitor Durvalumab. Methods: Patients with recurrent high-grade IDH-mutant gliomas were enrolled in a phase II open-label study (NCT03991832). Serum was collected at baseline and monthly and cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) was performed. Binomial GLMnet models were developed and model performance was assessed using validation set data. Results: 29 patients were enrolled between 2020–2023. Patients received olaparib 300mg twice daily and durvalumab 1500mg IV every 4 weeks. The overall response rate was 10% via RANO criteria. 144 plasma samples were profiled with cfMeDIP-seq along with 30 healthy controls. The enriched circulating tumour DNA methylome during response periods exhibited a highly specific signature, accurately discriminating response versus failure (AUC 0.98 ± 0.03). Additionally, samples that were taken while on treatment were able to be discriminated from samples off therapy (AUC 0.74 ± 0.11). Conclusions: The cell-free plasma DNA methylome exhibits highly specific signatures that enable accurate prediction of response to therapy.