Influences of amyloid-ß and tau on white matter neurite alterations in dementia with Lewy bodies.

Dementia with Lewy bodies (DLB) is a neurodegenerative condition often co-occurring with Alzheimer's disease (AD) pathology. Characterizing white matter tissue microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) may help elucidate the biological underpinnings of white matter injury in individuals with DLB. In this study, diffusion tensor imaging (DTI) and NODDI metrics were compared in 45 patients within the dementia with Lewy bodies spectrum (mild cognitive impairment with Lewy bodies (n = 13) and probable dementia with Lewy bodies (n = 32)) against 45 matched controls using conditional logistic models. We evaluated the associations of tau and amyloid-ß with DTI and NODDI parameters and examined the correlations of AD-related white matter injury with Clinical Dementia Rating (CDR). Structural equation models (SEM) explored relationships among age, APOE ε4, amyloid-ß, tau, and white matter injury. The DLB spectrum group exhibited widespread white matter abnormalities, including reduced fractional anisotropy, increased mean diffusivity, and decreased neurite density index. Tau was significantly associated with limbic and temporal white matter injury, which was, in turn, associated with worse CDR. SEM revealed that amyloid-ß exerted indirect effects on white matter injury through tau. We observed widespread disruptions in white matter tracts in DLB that were not attributed to AD pathologies, likely due to α-synuclein-related injury. However, a fraction of the white matter injury could be attributed to AD pathology. Our findings underscore the impact of AD pathology on white matter integrity in DLB and highlight the utility of NODDI in elucidating the biological basis of white matter injury in DLB.

Rebound growth of BRAF mutant pediatric glioma cells after MAPKi withdrawal is associated with MAPK reactivation and secretion of microglia-recruiting cytokines.

INTRODUCTION: Patients with pediatric low-grade gliomas (pLGGs), the most common primary brain tumors in children, can often benefit from MAPK inhibitor (MAPKi) treatment. However, rapid tumor regrowth, also referred to as rebound growth, may occur once treatment is stopped, constituting a significant clinical challenge. METHODS: Four patient-derived pediatric glioma models were investigated to model rebound growth in vitro based on viable cell counts in response to MAPKi treatment and withdrawal. A multi-omics dataset (RNA sequencing and LC-MS/MS based phospho-/proteomics) was generated to investigate possible rebound-driving mechanisms. Following in vitro validation, putative rebound-driving mechanisms were validated in vivo using the BT-40 orthotopic xenograft model. RESULTS: Of the tested models, only a BRAFV600E-driven model (BT-40, with additional CDKN2A/Bdel) showed rebound growth upon MAPKi withdrawal. Using this model, we identified a rapid reactivation of the MAPK pathway upon MAPKi withdrawal in vitro, also confirmed in vivo. Furthermore, transient overactivation of key MAPK molecules at transcriptional (e.g. FOS) and phosphorylation (e.g. pMEK) levels, was observed in vitro. Additionally, we detected increased expression and secretion of cytokines (CCL2, CX3CL1, CXCL10 and CCL7) upon MAPKi treatment, maintained during early withdrawal. While increased cytokine expression did not have tumor cell intrinsic effects, presence of these cytokines in conditioned media led to increased attraction of microglia cells in vitro. CONCLUSION: Taken together, these data indicate rapid MAPK reactivation upon MAPKi withdrawal as a tumor cell intrinsic rebound-driving mechanism. Furthermore, increased secretion of microglia-recruiting cytokines may play a role in treatment response and rebound growth upon withdrawal, warranting further evaluation.

Clinicopathologic Heterogeneity and Glial Activation Patterns in Alzheimer Disease.

Importance: Factors associated with clinical heterogeneity in Alzheimer disease (AD) lay along a continuum hypothesized to associate with tangle distribution and are relevant for understanding glial activation considerations in therapeutic advancement. Objectives: To examine clinicopathologic and neuroimaging characteristics of disease heterogeneity in AD along a quantitative continuum using the corticolimbic index (CLix) to account for individuality of spatially distributed tangles found at autopsy. Design, Setting, and Participants: This cross-sectional study was a retrospective medical record review performed on the Florida Autopsied Multiethnic (FLAME) cohort accessioned from 1991 to 2020. Data were analyzed from December 2022 to December 2023. Structural magnetic resonance imaging (MRI) and tau positron emission tomography (PET) were evaluated in an independent neuroimaging group. The FLAME cohort includes 2809 autopsied individuals; included in this study were neuropathologically diagnosed AD cases (FLAME-AD). A digital pathology subgroup of FLAME-AD cases was derived for glial activation analyses. Main Outcomes and Measures: Clinicopathologic factors of heterogeneity that inform patient history and neuropathologic evaluation of AD; CLix score (lower, relative cortical predominance/hippocampal sparing vs higher, relative cortical sparing/limbic predominant cases); neuroimaging measures (ie, structural MRI and tau-PET). Results: Of the 2809 autopsied individuals in the FLAME cohort, 1361 neuropathologically diagnosed AD cases were evaluated. A digital pathology subgroup included 60 FLAME-AD cases. The independent neuroimaging group included 93 cases. Among the 1361 FLAME-AD cases, 633 were male (47%; median [range] age at death, 81 [54-96] years) and 728 were female (53%; median [range] age at death, 81 [53-102] years). A younger symptomatic onset (Spearman ρ = 0.39, P < .001) and faster decline on the Mini-Mental State Examination (Spearman ρ = 0.27; P < .001) correlated with a lower CLix score in FLAME-AD series. Cases with a nonamnestic syndrome had lower CLix scores (median [IQR], 13 [9-18]) vs not (median [IQR], 21 [15-27]; P < .001). Hippocampal MRI volume (Spearman ρ = -0.45; P < .001) and flortaucipir tau-PET uptake in posterior cingulate and precuneus cortex (Spearman ρ = -0.74; P < .001) inversely correlated with CLix score. Although AD cases with a CLix score less than 10 had higher cortical tangle count, we found lower percentage of CD68-activated microglia/macrophage burden (median [IQR], 0.46% [0.32%-0.75%]) compared with cases with a CLix score of 10 to 30 (median [IQR], 0.75% [0.51%-0.98%]) and on par with a CLix score of 30 or greater (median [IQR], 0.40% [0.32%-0.57%]; P = .02). Conclusions and Relevance: Findings show that AD heterogeneity exists along a continuum of corticolimbic tangle distribution. Reduced CD68 burden may signify an underappreciated association between tau accumulation and microglia/macrophages activation that should be considered in personalized therapy for immune dysregulation.

Reliability and Validity of Smartphone Cognitive Testing for Frontotemporal Lobar Degeneration.

Importance: Frontotemporal lobar degeneration (FTLD) is relatively rare, behavioral and motor symptoms increase travel burden, and standard neuropsychological tests are not sensitive to early-stage disease. Remote smartphone-based cognitive assessments could mitigate these barriers to trial recruitment and success, but no such tools are validated for FTLD. Objective: To evaluate the reliability and validity of smartphone-based cognitive measures for remote FTLD evaluations. Design, Setting, and Participants: In this cohort study conducted from January 10, 2019, to July 31, 2023, controls and participants with FTLD performed smartphone application (app)-based executive functioning tasks and an associative memory task 3 times over 2 weeks. Observational research participants were enrolled through 18 centers of a North American FTLD research consortium (ALLFTD) and were asked to complete the tests remotely using their own smartphones. Of 1163 eligible individuals (enrolled in parent studies), 360 were enrolled in the present study; 364 refused and 439 were excluded. Participants were divided into discovery (n = 258) and validation (n = 102) cohorts. Among 329 participants with data available on disease stage, 195 were asymptomatic or had preclinical FTLD (59.3%), 66 had prodromal FTLD (20.1%), and 68 had symptomatic FTLD (20.7%) with a range of clinical syndromes. Exposure: Participants completed standard in-clinic measures and remotely administered ALLFTD mobile app (app) smartphone tests. Main Outcomes and Measures: Internal consistency, test-retest reliability, association of smartphone tests with criterion standard clinical measures, and diagnostic accuracy. Results: In the 360 participants (mean [SD] age, 54.0 [15.4] years; 209 [58.1%] women), smartphone tests showed moderate-to-excellent reliability (intraclass correlation coefficients, 0.77-0.95). Validity was supported by association of smartphones tests with disease severity (r range, 0.38-0.59), criterion-standard neuropsychological tests (r range, 0.40-0.66), and brain volume (standardized ß range, 0.34-0.50). Smartphone tests accurately differentiated individuals with dementia from controls (area under the curve [AUC], 0.93 [95% CI, 0.90-0.96]) and were more sensitive to early symptoms (AUC, 0.82 [95% CI, 0.76-0.88]) than the Montreal Cognitive Assessment (AUC, 0.68 [95% CI, 0.59-0.78]) (z of comparison, -2.49 [95% CI, -0.19 to -0.02]; P = .01). Reliability and validity findings were highly similar in the discovery and validation cohorts. Preclinical participants who carried pathogenic variants performed significantly worse than noncarrier family controls on 3 app tasks (eg, 2-back ß = -0.49 [95% CI, -0.72 to -0.25]; P < .001) but not a composite of traditional neuropsychological measures (ß = -0.14 [95% CI, -0.42 to 0.14]; P = .32). Conclusions and Relevance: The findings of this cohort study suggest that smartphones could offer a feasible, reliable, valid, and scalable solution for remote evaluations of FTLD and may improve early detection. Smartphone assessments should be considered as a complementary approach to traditional in-person trial designs. Future research should validate these results in diverse populations and evaluate the utility of these tests for longitudinal monitoring.

Ventriculoperitoneal shunt placement safety in idiopathic Normal Pressure Hydrocephalus: Anticoagulated versus non-anticoagulated patients.

BACKGROUND: Many patients with idiopathic normal pressure hydrocephalus (iNPH) have medical comorbidities requiring anticoagulation that could negatively impact outcomes. This study evaluated the safety of ventriculoperitoneal shunt (VPS) placement in iNPH patients on systemic anticoagulation versus those not on anticoagulation. METHODS: Patients > 60 years of age with iNPH who underwent shunting between 2018 and 2022 were retrospectively reviewed. Baseline demographics, comorbidities (quantified by modified Frailty Index (mFI) and Charlson Comorbidity Index (CCI)), anticoagulant/antiplatelet agent use (other than aspirin), operative details, and complications were collected. Outcomes of interest were the occurrence of postoperative hemorrhage and overdrainage. RESULTS: A total of 234 patients were included in the study (mean age 75.22 ± 6.04 years; 66.7% male); 36 were on anticoagulation/antiplatelet therapy (excluding aspirin). This included 6 on Warfarin, 19 on direct Xa inhibitors, 10 on Clopidogrel, and one on both Clopidogrel and Warfarin. Notably, 70% of patients (164/234) used aspirin alone or combined with anticoagulation or clopidogrel. Baseline mFI was similar between groups, but those on anticoagulant/antiplatelet therapy had a higher mean CCI (2.67±1.87 vs. 1.75±1.84; p=0.001). Patients on anticoagulants were more likely to experience tract hemorrhage (11.1 vs. 2.5%; p=0.03), with no significant difference in the rates of intraventricular hemorrhage or overdrainage related subdural fluid collection. CONCLUSIONS: Anticoagulant and antiplatelet agents are common in the iNPH population, and patients on these agents experienced higher rates of tract hemorrhage following VPS placement; however, overall hemorrhagic complication rates were similar.

Clinicoradiological and neuropathological evaluation of primary progressive aphasia.

BACKGROUND: Primary progressive aphasia (PPA) defines a group of neurodegenerative disorders characterised by language decline. Three PPA variants correlate with distinct underlying pathologies: semantic variant PPA (svPPA) with transactive response DNA-binding protein of 43 kD (TDP-43) proteinopathy, agrammatic variant PPA (agPPA) with tau deposition and logopenic variant PPA (lvPPA) with Alzheimer's disease (AD). Our objectives were to differentiate PPA variants using clinical and neuroimaging features, assess progression and evaluate structural MRI and a novel 18-F fluorodeoxyglucose positron emission tomography (FDG-PET) image decomposition machine learning algorithm for neuropathology prediction. METHODS: We analysed 82 autopsied patients diagnosed with PPA from 1998 to 2022. Clinical histories, language characteristics, neuropsychological results and brain imaging were reviewed. A machine learning framework using a k-nearest neighbours classifier assessed FDG-PET scans from 45 patients compared with a large reference database. RESULTS: PPA variant distribution: 35 lvPPA (80% AD), 28 agPPA (89% tauopathy) and 18 svPPA (72% frontotemporal lobar degeneration-TAR DNA-binding protein (FTLD-TDP)). Apraxia of speech was associated with 4R-tauopathy in agPPA, while pure agrammatic PPA without apraxia was linked to 3R-tauopathy. Longitudinal data revealed language dysfunction remained the predominant deficit for patients with lvPPA, agPPA evolved to corticobasal or progressive supranuclear palsy syndrome (64%) and svPPA progressed to behavioural variant frontotemporal dementia (44%). agPPA-4R-tauopathy exhibited limited pre-supplementary motor area atrophy, lvPPA-AD displayed temporal atrophy extending to the superior temporal sulcus and svPPA-FTLD-TDP had severe temporal pole atrophy. The FDG-PET-based machine learning algorithm accurately predicted clinical diagnoses and underlying pathologies. CONCLUSIONS: Distinguishing 3R-taupathy and 4R-tauopathy in agPPA may rely on apraxia of speech presence. Additional linguistic and clinical features can aid neuropathology prediction. Our data-driven brain metabolism decomposition approach effectively predicts underlying neuropathology.

Longitudinal default mode sub-networks in the language and visual variants of Alzheimer's disease.

Disruption of the default mode network is a hallmark of Alzheimer's disease, which has not been extensively examined in atypical phenotypes. We investigated cross-sectional and 1-year longitudinal changes in default mode network sub-systems in the visual and language variants of Alzheimer's disease, in relation to age and tau. Sixty-one amyloid-positive Alzheimer's disease participants diagnosed with posterior cortical atrophy (n = 33) or logopenic progressive aphasia (n = 28) underwent structural MRI, resting-state functional MRI and [18F]flortaucipir PET. One-hundred and twenty-two amyloid-negative cognitively unimpaired individuals and 60 amyloid-positive individuals diagnosed with amnestic Alzheimer's disease were included as controls and as a comparison group, respectively, and had structural and resting-state functional MRI. Forty-one atypical Alzheimer's disease participants, 26 amnestic Alzheimer's disease participants and 40 cognitively unimpaired individuals had one follow-up functional MRI ∼1-2 years after the baseline scan. Default mode network connectivity was calculated using the dual regression method for posterior, ventral, anterior ventral and anterior dorsal sub-systems derived from independent component analysis. A global measure of default mode network connectivity, the network failure quotient, was also calculated. Linear mixed-effects models and voxel-based analyses were computed for each connectivity measure. Both atypical and amnestic Alzheimer's disease participants had lower cross-sectional posterior and ventral and higher anterior dorsal connectivity and network failure quotient relative to cognitively unimpaired individuals. Age had opposite effects on connectivity in Alzheimer's disease participants and cognitively unimpaired individuals. While connectivity declined with age in cognitively unimpaired individuals, younger Alzheimer's disease participants had lower connectivity than the older ones, particularly in the ventral default mode network. Greater baseline tau-PET uptake was associated with lower ventral and anterior ventral default mode network connectivity in atypical Alzheimer's disease. Connectivity in the ventral default mode network declined over time in atypical Alzheimer's disease, particularly in older participants, with lower tau burden. Voxel-based analyses validated the findings of higher anterior dorsal default mode network connectivity, lower posterior and ventral default mode network connectivity and decline in ventral default mode network connectivity over time in atypical Alzheimer's disease. Visuospatial symptoms were associated with default mode network connectivity disruption. In summary, default mode connectivity disruption was similar between atypical and amnestic Alzheimer's disease variants, and discriminated Alzheimer's disease from cognitively unimpaired individuals, with decreased posterior and increased anterior connectivity and with disruption more pronounced in younger participants. The ventral default mode network declined over time in atypical Alzheimer's disease, suggesting a shift in default mode network connectivity likely related to tau pathology.

Heterogeneity of DNA methylation profiles and copy number alterations in 10782 adult-type glioblastomas, IDH-wildtype.

The morphological patterns leading to the diagnosis of glioblastoma may also commonly be observed in several other distinct tumor entities, which can result in a mixed bag of tumors subsumed under this diagnosis. The 2021 WHO Classification of CNS Tumors has separated several of these entities from the diagnosis of glioblastoma, IDH-wildtype. This study determines the DNA methylation classes most likely receiving the diagnosis glioblastoma, IDH wildtype according to the definition by the WHO 2021 Classification and provides comparative copy number analyses. We identified 10782 methylome datasets uploaded to the web page www.molecularneuropathology.org with a calibrated score of ≥0.9 by the Heidelberg Brain Tumor Classifier version v12.8. These methylation classes were characterized by the diagnosis glioblastoma being the most frequent classification encountered in each of the classes according to the WHO 2021 definition. Further, methylation classes selected for this study predominantly contained adult patients. Unsupervised clustering confirmed the presence of nine methylation classes containing tumors most likely receiving the diagnosis glioblastoma, IDH-wildtype according to the WHO 2021 definition. Copy number analysis and a focus on genes with typical numerical alterations in glioblastoma revealed clear differences between the nine methylation classes. Although great progress in diagnostic precision has been achieved over the last decade, our data clearly demonstrate that glioblastoma, IDH-wildtype still is a heterogeneous group in need of further stratification.

Plasma biomarkers of Alzheimer's disease in the continuum of dementia with Lewy bodies.

INTRODUCTION: Patients with dementia with Lewy bodies (DLB) may have Alzheimers disease (AD) pathology that can be detected by plasma biomarkers. Our objective was to evaluate plasma biomarkers of AD and their association with positron emission tomography (PET) biomarkers of amyloid and tau deposition in the continuum of DLB, starting from prodromal stages of the disease. METHODS: The cohort included patients with isolated rapid eye movement (REM) sleep behavior disorder (iRBD), mild cognitive impairment with Lewy bodies (MCI-LB), or DLB, with a concurrent blood draw and PET scans. RESULTS: Abnormal levels of plasma glial fibrillary acidic protein (GFAP) were found at the prodromal stage of MCI-LB in association with increased amyloid PET. Abnormal levels of plasma phosphorylated tau (p-tau)-181 and neurofilament light (NfL) were found at the DLB stage. Plasma p-tau-181 showed the highest accuracy in detecting abnormal amyloid and tau PET in patients with DLB. DISCUSSION: The range of AD co-pathology can be detected with plasma biomarkers in the DLB continuum, particularly with plasma p-tau-181 and GFAP.

Clinical and molecular study of radiation-induced gliomas.

In this study, we provide a comprehensive clinical and molecular biological characterization of radiation-induced gliomas (RIG), including a risk assessment for developing gliomas. A cohort of 12 patients who developed RIG 9.5 years (3-31 years) after previous cranial radiotherapy for brain tumors or T-cell acute lymphoblastic leukemia was established. The derived risk of RIG development based on our consecutive cohort of 371 irradiated patients was 1.6% at 10 years and 3.02% at 15 years. Patients with RIG glioma had a dismal prognosis with a median survival of 7.3 months. We described radiology features that might indicate the suspicion of RIG rather than the primary tumor recurrence. Typical molecular features identified by molecular biology examination included the absence of Histon3 mutation, methylation profile of pedHGG-RTK1 and the presence of recurrent PDGFRA amplification and CDKN2A/B deletion. Of the two long-term surviving patients, one had gliomatosis cerebri, and the other had pleomorphic xanthoastrocytoma with BRAF V600E mutation. In summary, our experience highlights the need for tissue diagnostics to allow detailed molecular biological characterization of the tumor, differentiation of the secondary tumor from the recurrence of the primary disease and potentially finding a therapeutic target.

LOGGIC/FIREFLY-2: a phase 3, randomized trial of tovorafenib vs. chemotherapy in pediatric and young adult patients with newly diagnosed low-grade glioma harboring an activating RAF alteration.

BACKGROUND: Pediatric low-grade glioma (pLGG) is essentially a single pathway disease, with most tumors driven by genomic alterations affecting the mitogen-activated protein kinase/ERK (MAPK) pathway, predominantly KIAA1549::BRAF fusions and BRAF V600E mutations. This makes pLGG an ideal candidate for MAPK pathway-targeted treatments. The type I BRAF inhibitor, dabrafenib, in combination with the MEK inhibitor, trametinib, has been approved by the United States Food and Drug Administration for the systemic treatment of BRAF V600E-mutated pLGG. However, this combination is not approved for the treatment of patients with tumors harboring BRAF fusions as type I RAF inhibitors are ineffective in this setting and may paradoxically enhance tumor growth. The type II RAF inhibitor, tovorafenib (formerly DAY101, TAK-580, MLN2480), has shown promising activity and good tolerability in patients with BRAF-altered pLGG in the phase 2 FIREFLY-1 study, with an objective response rate (ORR) per Response Assessment in Neuro-Oncology high-grade glioma (RANO-HGG) criteria of 67%. Tumor response was independent of histologic subtype, BRAF alteration type (fusion vs. mutation), number of prior lines of therapy, and prior MAPK-pathway inhibitor use. METHODS: LOGGIC/FIREFLY-2 is a two-arm, randomized, open-label, multicenter, global, phase 3 trial to evaluate the efficacy, safety, and tolerability of tovorafenib monotherapy vs. current standard of care (SoC) chemotherapy in patients < 25 years of age with pLGG harboring an activating RAF alteration who require first-line systemic therapy. Patients are randomized 1:1 to either tovorafenib, administered once weekly at 420 mg/m2 (not to exceed 600 mg), or investigator's choice of prespecified SoC chemotherapy regimens. The primary objective is to compare ORR between the two treatment arms, as assessed by independent review per RANO-LGG criteria. Secondary objectives include comparisons of progression-free survival, duration of response, safety, neurologic function, and clinical benefit rate. DISCUSSION: The promising tovorafenib activity data, CNS-penetration properties, strong scientific rationale combined with the manageable tolerability and safety profile seen in patients with pLGG led to the SIOPe-BTG-LGG working group to nominate tovorafenib for comparison with SoC chemotherapy in this first-line phase 3 trial. The efficacy, safety, and functional response data generated from the trial may define a new SoC treatment for newly diagnosed pLGG. TRIAL REGISTRATION: ClinicalTrials.gov: NCT05566795. Registered on October 4, 2022.

Pineal anlage tumor: clinical and diagnostic features, and rationales for treatment.

PURPOSE: To provide a treatment-focused review and develop basic treatment guidelines for patients diagnosed with pineal anlage tumor (PAT). METHODS: Prospectively collected data of three patients with pineal anlage tumor from Germany was combined with clinical details and treatment information from 17 published cases. RESULTS: Overall, 20 cases of PAT were identified (3 not previously reported German cases, 17 cases from published reports). Age at diagnosis ranged from 0.3 to 35.0 (median: 3.2 ± 7.8) years. All but three cases were diagnosed before the age of three years. For three cases, metastatic disease at initial staging was described. All patients underwent tumor surgery (gross-total resection: 9, subtotal resection/biopsy: 9, extent of resection unknown: 2). 15/20 patients were alive at last follow-up. Median follow-up for 10/15 surviving patients with available follow-up and treatment data was 2.4 years (0.3-6.5). Relapse was reported for 3 patients within 0.8 years after diagnosis. Five patients died, 3 after relapse and 2 from early postoperative complications. Two-year-progression-free- and -overall survival were 65.2 ± 12.7% and 49.2 ± 18.2%, respectively. All 4 patients who received intensive chemotherapy including high-dose chemotherapy combined with radiotherapy (2 focal, 2 craniospinal [CSI]) had no recurrence. Focal radiotherapy- and CSI-free survival rates in 13 evaluable patients were 46.2% (6/13) and 61.5% (8/13), respectively. CONCLUSION: PAT is an aggressive disease mostly affecting young children. Therefore, adjuvant therapy using intensive chemotherapy and considering radiotherapy appears to comprise an appropriate treatment strategy. Reporting further cases is crucial to evaluate distinct treatment strategies.

Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage.

Medulloblastomas with extensive nodularity are cerebellar tumors characterized by two distinct compartments and variable disease progression. The mechanisms governing the balance between proliferation and differentiation in MBEN remain poorly understood. Here, we employ a multi-modal single cell transcriptome analysis to dissect this process. In the internodular compartment, we identify proliferating cerebellar granular neuronal precursor-like malignant cells, along with stromal, vascular, and immune cells. In contrast, the nodular compartment comprises postmitotic, neuronally differentiated malignant cells. Both compartments are connected through an intermediate cell stage resembling actively migrating CGNPs. Notably, we also discover astrocytic-like malignant cells, found in proximity to migrating and differentiated cells at the transition zone between the two compartments. Our study sheds light on the spatial tissue organization and its link to the developmental trajectory, resulting in a more benign tumor phenotype. This integrative approach holds promise to explore intercompartmental interactions in other cancers with varying histology.

Patients with normal pressure hydrocephalus have fewer enlarged perivascular spaces in the centrum semiovale compared to cognitively unimpaired individuals.

INTRODUCTION: Enlarged perivascular spaces (ePVS) may be an indicator of glymphatic dysfunction. Limited studies have evaluated the role of ePVS in idiopathic normal pressure hydrocephalus (iNPH). We aimed to characterize the distribution and number of ePVS in iNPH compared to controls. METHODS: Thirty-eight patients with iNPH and a pre-shunt MRI were identified through clinical practice. Age- and sex-matched controls who had negative MRIs screening for intracranial metastases were identified through a medical record linkage system. The number of ePVS were counted in the basal nuclei (BN) and centrum semiovale (CS) using the Wardlaw method blinded to clinical diagnosis. Imaging features of disproportionately enlarged subarachnoid space hydrocephalus (DESH), callosal angle, Fazekas white matter hyperintensity (WMH) grade, and the presence of microbleeds and lacunes were also evaluated. RESULTS: Both iNPH patients and controls had a mean age of 74 ± 7 years and were 34% female with equal distributions of hypertension, dyslipidemia, diabetes, stroke, and history of smoking. There were fewer ePVS in the CS of patients with iNPH compared to controls (12.66 vs. 20.39, p < 0.001) but the same in the BN (8.95 vs. 11.11, p = 0.08). This remained significant in models accounting for vascular risk factors (p = 0.002) and MRI features of DESH and WMH grade (p = 0.03). CONCLUSIONS: Fewer centrum semiovale ePVS may be a biomarker for iNPH. This pattern may be caused by mechanical obstruction due to upward displacement of the brain leading to reduced glymphatic clearance.

Conumee 2.0: enhanced copy-number variation analysis from DNA methylation arrays for humans and mice.

MOTIVATION: Copy-number variations (CNVs) are common genetic alterations in cancer and their detection may impact tumor classification and therapeutic decisions. However, detection of clinically relevant large and focal CNVs remains challenging when sample material or resources are limited. This has motivated us to create a software tool to infer CNVs from DNA methylation arrays which are often generated as part of clinical routines and in research settings. RESULTS: We present our R package, conumee 2.0, that combines tangent normalization, an adjustable genomic binning heuristic, and weighted circular binary segmentation to utilize DNA methylation arrays for CNV analysis and mitigate technical biases and batch effects. Segmentation results were validated in a lung squamous cell carcinoma dataset from TCGA (n = 367 samples) by comparison to segmentations derived from genotyping arrays (Pearson's correlation coefficient of 0.91). We further introduce a segmented block bootstrapping approach to detect focal alternations that achieved 60.9% sensitivity and 98.6% specificity for deletions affecting CDKN2A/B (60.0% and 96.9% for RB1, respectively) in a low-grade glioma cohort from TCGA (n = 239 samples). Finally, our tool provides functionality to detect and summarize CNVs across large sample cohorts. AVAILABILITY AND IMPLEMENTATION: Conumee 2.0 is available under open-source license at: https://github.com/hovestadtlab/conumee2.

Pediatric low-grade glioma: State-of-the-art and ongoing challenges.

The most common childhood central nervous system (CNS) tumor is pediatric low-grade glioma (pLGG), representing 30%-40% of all CNS tumors in children. Although there is high associated morbidity, tumor-related mortality is relatively rare. pLGG is now conceptualized as a chronic disease, underscoring the importance of functional outcomes and quality-of-life measures. A wealth of data has emerged about these tumors, including a better understanding of their natural history and their molecular drivers, paving the way for the use of targeted inhibitors. While these treatments have heralded tremendous promise, challenges remain about how to best optimize their use, and the long-term toxicities associated with these inhibitors remain unknown. The International Pediatric Low-Grade Glioma Coalition (iPLGGc) is a global group of physicians and scientists with expertise in pLGG focused on addressing key pLGG issues. Here, the iPLGGc provides an overview of the current state-of-the-art in pLGG, including epidemiology, histology, molecular landscape, treatment paradigms, survival outcomes, functional outcomes, imaging response, and ongoing challenges. This paper also serves as an introduction to 3 other pLGG manuscripts on (1) pLGG preclinical models, (2) consensus framework for conducting early-phase clinical trials in pLGG, and (3) pLGG resistance, rebound, and recurrence.

Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning.

Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.

Neurite-based white matter alterations in MAPT mutation carriers: A multi-shell diffusion MRI study in the ALLFTD consortium.

We assessed white matter (WM) integrity in MAPT mutation carriers (16 asymptomatic, 5 symptomatic) compared to 31 non-carrier family controls using diffusion tensor imaging (DTI) (fractional anisotropy; FA, mean diffusivity; MD) and neurite orientation dispersion and density imaging (NODDI) (neurite density index; NDI, orientation and dispersion index; ODI). Linear mixed-effects models accounting for age and family relatedness revealed alterations across DTI and NODDI metrics in all mutation carriers and in symptomatic carriers, with the most significant differences involving fronto-temporal WM tracts. Asymptomatic carriers showed higher entorhinal MD and lower cingulum FA and patterns of higher ODI mostly involving temporal areas and long association and projections fibers. Regression models between estimated time to or time from disease and DTI and NODDI metrics in key regions (amygdala, cingulum, entorhinal, inferior temporal, uncinate fasciculus) in all carriers showed increasing abnormalities with estimated time to or time from disease onset, with FA and NDI showing the strongest relationships. Neurite-based metrics, particularly ODI, appear to be particularly sensitive to early WM involvement in asymptomatic carriers.

Assessing network degeneration and phenotypic heterogeneity in genetic frontotemporal lobar degeneration by decoding FDG-PET.

Genetic mutations causative of frontotemporal lobar degeneration (FTLD) are highly predictive of a specific proteinopathy, but there exists substantial inter-individual variability in their patterns of network degeneration and clinical manifestations. We collected clinical and 18Fluorodeoxyglucose-positron emission tomography (FDG-PET) data from 39 patients with genetic FTLD, including 11 carrying the C9orf72 hexanucleotide expansion, 16 carrying a MAPT mutation and 12 carrying a GRN mutation. We performed a spectral covariance decomposition analysis between FDG-PET images to yield unbiased latent patterns reflective of whole brain patterns of metabolism ("eigenbrains" or EBs). We then conducted linear discriminant analyses (LDAs) to perform EB-based predictions of genetic mutation and predominant clinical phenotype (i.e., behavior/personality, language, asymptomatic). Five EBs were significant and explained 58.52 % of the covariance between FDG-PET images. EBs indicative of hypometabolism in left frontotemporal and temporo-parietal areas distinguished GRN mutation carriers from other genetic mutations and were associated with predominant language phenotypes. EBs indicative of hypometabolism in prefrontal and temporopolar areas with a right hemispheric predominance were mostly associated with predominant behavioral phenotypes and distinguished MAPT mutation carriers from other genetic mutations. The LDAs yielded accuracies of 79.5 % and 76.9 % in predicting genetic status and predominant clinical phenotype, respectively. A small number of EBs explained a high proportion of covariance in patterns of network degeneration across FTLD-related genetic mutations. These EBs contained biological information relevant to the variability in the pathophysiological and clinical aspects of genetic FTLD, and for offering valuable guidance in complex clinical decision-making, such as decisions related to genetic testing.

Significance of a positive tau PET scan with a negative amyloid PET scan.

INTRODUCTION: The implications of positive tau positron emission tomography (T) with negative beta amyloid positron emission tomography (A) are not well understood. We investigated cognitive performance in participants who were T+ but A-. METHODS: We evaluated 98 participants from the Mayo Clinic who were T+ and A-. Participants were matched 2:1 to A- and T- cognitively unimpaired (CU) controls. Cognitive test scores were compared between different groups. RESULTS: The A-T+ group demonstrated lower performance than the A-T- group on the Mini-Mental Status Exam (MMSE) (p < 0.001), Wechsler Memory Scale-Revised Logical Memory I (p < 0.001) and Logical Memory II (p < 0.001), Auditory Verbal Learning Test (AVLT) delayed recall (p = 0.004), category fluency (animals p = 0.005; vegetables p = 0.021), Trail Making Test A and B (p < 0.001), and others. There were no significant differences in demographic features or apolipoprotein E (APOE) e4 genotype between CU A-T+ and CI A-T+. DISCUSSION: A-T+ participants show an association with lower cognitive performance.