Acta Neuropathologica

ObjectiveBrain branks preserve extensive material relevant to neurodegenerative disease research. As these collections age, tissue becomes archival, raising the question of whether long-term fixed and stored human brain tissue remains suitable for contemporary immunohistochemical analyses. Materials and MethodsForty-one autopsy brains collected between 1946 to 1980 were examined. For each case, midbrain and hippocampus were available both as original paraffin-embedded blocks and as tissue stored long term in fixative. New paraffin blocks were prepared from the long-term fixated tissue. Sections from original and newly prepared blocks were immunohistochemically stained for -synuclein, hyperphosphorylated tau and amyloid-{beta}. Immunoreactivity was assessed using semi-quantitative scoring. ResultsOriginal blocks consistently showed good staining intensity and morphological preservation for each protein pathology. Newly prepared blocks showed slightly lower semi-quantitative scores for Lewy-related pathology, without statistically significant differences, except for astrocytic -synuclein in the substantia nigra in cases from the 1960s. Tau pathology displayed modestly reduced labelling, particularly of the neuropil threads and neurofibrillary tangles, most evident in cases from the 1950s. Amyloid-{beta}-positive senile plaques showed similar or slightly higher scores in newly prepared blocks, with no significant differences across regions. ConclusionHuman brain tissue preserved as paraffin-embedded blocks or stored in fixative for up to 78 years remains suitable for immunohistochemical analyses. Adequate-to-good detection of aggregated of -synuclein, hyperphosphorylated tau and amyloid-{beta} is achievable, indicating preserved pathological hallmarks of Lewy Body Disease and Alzheimers Disease in archival tissue.

Meningiomas are the most common primary brain tumors and, despite their benign reputation, often behave aggressively. Meningiomas are morphologically heterogeneous, yet the full significance of their histologic diversity is unclear. This is in large part because many features are not readily quantifiable by traditional observer-based light microscopy. Molecular testing improves prognostic stratification, but is not universally accessible. We therefore sought to determine whether an artificial intelligence (AI)-trained program could predict specific genomic and epigenomic patterns in meningiomas, and whether it could extract more prognostic information out of standard hematoxylin and eosin (H&E) histopathology than the current WHO classification. To do this, we developed Morphologic Set Enrichment (MSE), an interpretable computational pathology framework that quantifies statistical enrichment of morphologic patterns, cells, and tissue architecture from H&E whole-slide images. The MSE meningioma histology program was able to accurately predict DNA methylation subtypes and concurrent chromosome 1p/22q losses, in the process identifying specific morphologic patterns associated with key genomic and epigenomic alterations. It also added prognostic value independent of standard clinical and pathological variables. These results demonstrate that AI-based quantitative morphologic profiling can capture clinically and biologically relevant information that redefines risk stratification for meningiomas, incorporating histological information not included in existing grading schemes.

T-cell lymphomas are often histologically indistinguishable from benign T-cell infiltrates. Clonality testing is frequently required for diagnosis. It lacks the spatial context and is slow and expensive, relying on complex, multiplexed PCR reactions, interpreted by experienced scientists or pathologists. We previously published details of a pair of highly specific monoclonal antibodies against the two alternatively used, but very similar, T-cell receptor {beta} constant regions, TCR{beta}1 and TCR{beta}2. We demonstrated the feasibility of immunohistochemical detection of TCR{beta}1 and TCR{beta}2 in formalin-fixed, paraffin-embedded (FFPE) tissue as a novel diagnostic strategy for T-cell lymphomas. Here we validate an improved pairing of TCR{beta}1/2 rabbit monoclonal antibodies, and demonstrate their utility for single and double immunostaining, including with a chimeric mouse anti-TCR{beta}2 antibody. Finally, we show that this staining is amenable to automated cell counting, permitting accurate calculation of the TCR{beta}2:TCR{beta}1 ratio.

TDP-43 proteinopathy is a neuropathological hallmark of nearly all amyotrophic lateral sclerosis (ALS) and approximately half of frontotemporal dementia (FTD) cases. Nuclear loss of TDP-43 leads to widespread RNA misprocessing, such as the inclusion of cryptic exons that are no longer repressed by TDP-43. Notably, in-frame cryptic exons encode novel cryptic peptides that can be detected in biofluids, including that found in the HDGFL2 transcript. Here, we quantified HDGFL2 cryptic peptide and neurofilament light chain (NfL) in paired cerebrospinal fluid (CSF) and plasma samples from ALS and FTD patients. Cryptic HDGFL2 peptide was detected in the CSF of ALS patients, whereas no significant differences were observed between genetic and behavioral FTD subgroups. In contrast, NfL levels were elevated in both ALS and FTD, although this biomarker does not reflect TDP-43 pathology. Notably, NfL:HDGFL2 cryptic peptide ratio outperformed either marker alone in discriminating ALS and FTD cases from controls, achieving high specificity. Moreover, this ratio correlated with disease progression in ALS, suggesting added prognostic value. Collectively, our findings support the NfL:HDGFL2 cryptic peptide ratio as a promising fluid biomarker that integrates neurodegeneration with TDP-43 dysfunction, potentially improving diagnostic accuracy, disease stratification, and longitudinal monitoring in TDP-43-associated neurodegenerative disorders.

ImportanceSome individuals are capable of tolerating Alzheimer disease neuropathological changes (ADNC) without manifesting clinical symptoms. Elucidating the neuropathological, and molecular mediators may facilitate the identification of more accurate in vivo biomarkers and inform the development of targeted therapeutic strategies. ObjectiveTo investigate cellular distribution of tau pathology, microglial responses, and gene expression profiles associated with divergent clinical outcomes (dementia vs. no dementia) in individuals exhibiting comparable ADNC. Design, Setting and ParticipantsWe analyzed postmortem brain tissue from 97 participants from the ROSMAP study:49 with high likelihood of AD (25 demented [demented AD] and 24 cognitively normal [resilient]), and 48 with low likelihood (22 demented [impaired-other (IMP-O)] and 26 cognitively normal [control]). Cases were matched for age, gender, and co-pathologies. Main outcomes and measuresAmyloid-{beta} plaques, phospho-tau pathology (tangles and tau-positive neurites), tau oligomers in synaptic-fractions, tau seeding activity, neurons, synapse density, and astrocyte and microglia activation were quantified. The relationships with bulk and microglia-specific RNA-sequencing were also examined. Statistical analyses employed ANOVA with Tukeys HSD/Bonferroni corrections for pathological and clinical variables, and the Wald test for differential gene expression ResultsDemented AD and resilient brains exhibited comparable tau tangle and amyloid-{beta} plaques; however, demented AD showed higher total pTau burden (tangles and tau-positive neurites) (Mean[SD], 27.39%[21.89%] vs. 10.60%[14.71%]; p= 0.0004) and elevated pTau oligomer levels in synaptic-enriched fractions (0.48[0.52] vs. 0.16[0.19]; p=0.0010). Both demented AD (0.21x107[0.14x107]; p<0.0001) and IMP-O (0.62x107 [0.42x107]; p<0.0001) showed greater synaptic loss than resilient (1.54x107[0.55x107]; p=0.0008) and controls (2.92x107[1.13x107]). CD68+ microglia burden was increased in demented (1.14%[0.27%]; p<0.0001) and IMP-O (0.97%[0.36%]; p<0.0001) but not in resilient (0.72% [0.17%]; p=0.2835) compared to controls (0.59%[0.17%]). Synaptic pTau oligomers and CD68+ microglia were the strongest correlates with antemortem cognition. Resilient brains exhibited downregulation of neuroinflammation-related genes and possessed a distinct microglial subpopulation supporting resilience, characterized by overexpression of CD83, DUSP1, and NAMPT. Conclusion and relevanceOur findings suggest that aberrant accumulation of tau in neurites and synapses, rather than tangles within neuronal soma, may trigger a microglial pro-inflammatory activation linked to synaptic loss and impaired cognition. Cell-specific transcriptomic analysis identified a distinct microglial cell subpopulation associated with resilience to ADNC.

Background Whole-genome sequencing (WGS) has improved the diagnosis of rare genetic disorders, yet interpretation of non-coding variants that affect splicing remains challenging. In silico predictions alone are insufficient, and short-read RNA sequencing may fail to capture complex or low-abundance splicing events. Targeted amplicon-based long-read RNA sequencing (Amp-LRS) offers a cost-effective approach for functional validation of candidate splice-altering variants. Methods We applied Amp-LRS to five patients with neurological disorders (central nervous system, peripheral nervous system, or muscle) harbouring candidate non-coding variants predicted to alter splicing. RNA was extracted from fibroblasts or peripheral blood, and full-length transcript amplicons were sequenced using Oxford Nanopore Technologies. Nonsense-mediated decay (NMD) inhibition was performed on fibroblast cultures using cycloheximide. Results Amp-LRS validated all five candidate variants, including intronic and UTR variants in POLR3A, OPA1, PYROXD1, GDAP1, and SPG11. Aberrant splicing events included exon skipping, intron retention, cryptic splice site activation, and pseudoexon inclusion, often resulting in frameshifts and premature termination codons. For POLR3A and OPA1, multiple abnormal isoforms arose from single variants, highlighting the complexity of splicing disruption. Some pathogenic effects were detectable only in a minority of reads and variably enriched by NMD inhibition, consistent with being hypomorphic. The approach was successfully applied using accessible tissues and enabled multiplexed sequencing at low per-sample cost. Conclusions Amp-LRS is a sensitive, versatile, and cost-effective method for functional assessment of non-coding splice-altering variants identified by WGS. By enabling full-length transcript analysis from accessible tissues, this approach improves interpretation of variants of uncertain significance and could enhance molecular diagnosis in rare neurological diseases.

Replication timing is a costly but powerful tool for characterizing cellular mechanisms that underlie chromatin organization, cancer epigenetics, and genomic instability. Genome-wide replication timing profiles reflect the temporal order of DNA synthesis during S phase and are closely linked to chromatin accessibility, transcriptional activity, and proliferative state. Prior work has demonstrated a robust inverse relationship between replication timing and DNA methylation at the domain scale, enabling methylation-based proxies to approximate replication timing in large cohorts where direct experimental measurement is impractical. Given the tight coupling between replication timing, chromatin structure, and cellular phenotype, we hypothesized that histologic morphology encodes information consistent with replication timing states. To test this hypothesis, we implemented Vision Transformer (ViT) architectures to predict replication timing proxies from whole-slide histopathology images. Patch-level embeddings were extracted using a pretrained ViT and aggregated through attention-based multiple instance learning to predict sample-level replication timing. In parallel, CellViT models were employed to perform cell-level prediction, enabling direct comparison between patch-based and cellular representations. Across both modeling strategies, statistically significant correlations were observed between image-derived features and methylation-based replication timing proxies. Patch-level models achieved correlations of approximately 46%, while cell-level models consistently reached correlations exceeding 50% on the validation cohort. Prediction error remained stable across folds, with mean absolute error and mean squared error values ranging between 0.4 and 0.6. These results demonstrate that replication timing-associated epigenomic states are reflected in tissue morphology and can be inferred using deep learning models applied to routine histopathology. This work establishes a feasible, noninvasive framework for replicosomic inference from whole-slide images and supports future efforts toward spatially resolved replication timing analysis and integrative modeling of replicative stress in cancer.

Advances in transcriptomics have transformed our understanding of amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disease, revealing disrupted gene expression profiles and highlighting the multi-system biology of ALS. Despite major advances, transcriptomic studies have only begun to capture the complexity and the molecular hierarchy of transcriptomic alterations in ALS. To resolve and characterize the transcriptome in ALS, we performed a comprehensive reanalysis of bulk RNA sequencing from the New York Genome Center ALS Consortium cohort across five post-mortem tissues including motor and frontal cortex, cervical and lumbar spinal cord, and cerebellum. By deploying dual analytical pipelines - one reference-based to model canonical events and one de novo to detect transcript structural novelties - we disentangled the quantitative and qualitative architectures of ALS. Our reference-based analysis revealed that ALS transcriptome is defined primarily by splicing failure rather than changes in gene expression. Aberrant splicing events, particularly intron retention, outnumbered differentially expressed genes by an order of magnitude. This widespread loss of fidelity disproportionately affected RNA-binding proteins, suggesting a collapse in their autoregulatory feedback loops. Deconvolution of these signals identified distinct cellular vulnerabilities: transcriptional disruptions were enriched in glial cells in sporadic cases but in neuronal cells in C9ORF72-positive cases. Furthermore, we observed sex-specific dysregulation, with male patients exhibiting greater disruption in guanosine triphosphatase signaling and ciliary organization pathways. In parallel, our de novo analysis uncovered a significant burden of disease-specific gene fusions that were absent in controls. Whole-genome sequencing of the same individuals, together with a larger reference population confirmed that disease-specific fusions do not arise from genomic structural variants, indicating a transcriptional rather than genomic origin. Investigation into the mechanism of these RNA-based fusions revealed a critical deviation in splice site definition: while canonical splice junctions exhibit a high density of binding motifs for polyA-binding or 3-cleaveage proteins approximately 50 base pairs upstream of the splice donor site (left junction), ALS-specific fusion junctions displayed a dramatic depletion of these motifs in the same region. Functionally, the presence of these sparse disease-specific fusions was strongly correlated with severe splicing outliers in genes governing guanosine triphosphatase activity, converging with the tissue- and male-specific defects identified in our reference-based analysis. Altogether, our results delineated a transcriptome characterized by aberrant splicing with tissue-and sex-specific changes and identified structural-variant-independent RNA fusions as candidate disease modifiers that may amplify pathology. This integrated view provides a mechanistic scaffold for splicing-centered and RNA-structural therapeutic strategies for ALS.

BackgroundPATZ1 fusion-positive central nervous system (CNS) tumors frequently harbor MN1::PATZ1 fusions as driver mutations, provisionally classified as a rare DNA methylation class of low-grade neuroepithelial tumors. Radiographically, they resemble pilocytic astrocytomas with tumor and cystic components, but their supratentorial cortex location and higher recurrence rates are distinguishing features. An intermediate clinical course, despite focal high-grade histopathology, underscores the need for longitudinal molecular and immune analyses to refine classification and standard therapy. Case SummaryA female pediatric patient presented with neurological symptoms, including headache and right upper extremity weakness. MRI revealed a large cystic lesion in the left frontal lobe, leading to a differential diagnosis of low-grade glioma and ependymoma. Genomic analysis identified an MN1::PATZ1 fusion. The tumor recurred after gross total resection prompting a second resection. Transcriptomic and histopathologic assessments identified multiglial lineage, and high-grade features closely related to adult glioblastoma alongside pro-inflammatory activity in the primary tumor. The recurrent tumor showed reduced malignancy, and oligodendroglioma-like features. Increased MHC gene expression, immune checkpoint receptors (PDCD1, CTLA4, TIGIT,TIM3), T cell regulators (CXCR6), and elevated macrophage frequency, coupled with reduced PD-L1 in the recurrent tumor, suggest a complex anti-tumor immune response constrained by T cell dysregulation. This case, along with two other MN1::PATZ1 fusion-positive tumors, identifies a distinct transcriptomic subtype separate from circumscribed astrocytic glioma, highlighting upregulation of growth factor receptor pathways, like PI3K/AKT, and immune dysfunction linked to recurrence. ConclusionLongitudinal multi-omics analyses of recurrent MN1::PATZ1 fusion-positive CNS tumors revealed tumor maturation, immune dysfunction, and potential therapeutic targets. Introductory ParagraphPATZ1 fusion-positive central nervous system (CNS) tumors are rare, predominantly pediatric and frequently recurrent neoplasms provisionally classified as neuroepithelial tumors. Their pronounced histopathological and clinical heterogeneity, along with limited immunological characterization complicates their treatment standardization. We report a new case of an MN1::PATZ1 fusion-positive CNS tumor with recurrence, highlighting its radiographic similarities to low-to-intermediate grade pediatric glioma. Longitudinal multi-omics analyses of this case, along with additional MN1::PATZ1 fusion-positive CNS tumors, however, delineates a transcriptome subtype resembling adult high-grade glioma, with activated oncogenic and pro-inflammatory programs. The recurrent tumor exhibits features of decreased malignancy and enhanced glial differentiation, phenotypically shifting towards oligodendroglioma, suggesting tumor maturation. This was accompanied by increased antigen presentation programs, indicating immune engagement, while increased immune checkpoint expression and microglia/macrophage frequency indicate T cell exhaustion and immunomodulation, respectively. This longitudinal study highlights potential therapeutic strategies targeting both the tumor and its immune environment in MN1::PATZ1 fusion-positive CNS tumors.

Background & AimsThe increasing global prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) including metabolic dysfunction-associated steatohepatitis (MASH) creates an urgent need for objective methods of histopathological assessment. Conventional histological approaches are time-consuming and rely on interpreters experience. Therefore, the results obtained may suffer from high variability and only offer coarse categorisation. In this study, we propose a fully automated, deep-learning-based pipeline for the segmentation and characterisation of histological liver features for MASH/MASLD assessment. MethodsSegmentation was applied to H&E sections from 45 mice and 44 humans with MASH/MASLD. The method, which we named qHisto (quantitative histology), utilises the nnU-Net framework and quantifies key histological components of the MASH score, including macro- and microvesicular steatosis, fibrosis, inflammation, hepatocellular ballooning and glycogenated nuclei. Additionally, we characterized the tissue using novel features that are inaccessible through manual histology, such as the distribution of fat droplet sizes, aspect ratio of nuclei and heatmaps. ResultsqHisto parameters showed strong positive correlations with conventional histology scores (fat area R=0.91, inflammation density R=0.7, ballooning density R=0.49) and also with quantitative magnetic resonance imaging (fat area vs. hepatic fat fraction R=0.87). Our novel scores showed that deformation of nuclei is driven by large fat droplets rather than the overall amount of fat. ConclusionsA key advantage of our method is spatially resolved, precise histological quantification. These features provide a finely resolved assessment of disease severity than conventional categorical scoring. By automating time-consuming and repetitive readouts, qHisto improves standardisation and reproducibility of MASH/MASLD feature quantification and provides scalable, slide-wide readouts that can support histopathologists and enhance clinical assessment and therapeutic development. Impact and ImplicationsThe proposed method provides an objective, automatic tool for comprehensive, histological liver analysis of MASH/MASLD, which can be extended to other diseases and organs. By offering classic and novel quantitative parameters and scores, our method could support histologists in their daily routines and provide researchers with further insight into steatotic liver diseases.

Reliable non-invasive biomarkers for tumor grading and disease monitoring in pediatric brain tumors are an unmet clinical need. Circulating extracellular vesicles (EVs) carrying molecular cargo reflective of tumor biology, offer promise as liquid biopsy tools. We have previously discovered EV-associated Syndecan-1 (SDC1) to be overexpressed in malignant brain tumors, but its value as a biomarker in pediatric disease remains unclear. In this study, plasma EVs were isolated from pediatric brain tumor patients (n=60) by size-exclusion chromatography and characterized using cryo-electron microscopy, nanoflow cytometry, immunoblotting, and single-vesicle total internal reflection fluorescence imaging. EV-associated SDC1 (EV-SDC1) was quantified and analyzed in relation to tumor grade, subtype, surgical resection status, and tumor volume. EV-SDC1 levels were significantly elevated in high-grade (ependymoma, diffuse midline glioma, and atypical teratoid/rhabdoid tumor (AT/RT)) compared with low-grade pilocytic astrocytoma tumors and robustly discriminated grade 3 tumors from pilocytic astrocytoma (AUROC 1.00). Independent validation using transcriptomic data from the Open Pediatric Brain Tumor Atlas showed SDC1 mRNA levels to effectively distinguish high grade (ependymoma, medulloblastoma, diffuse midline glioma, and AT/RT) from pilocytic astrocytoma patients. Furthermore, EV-SDC1 levels decreased following complete tumor resection but remained elevated in patients with residual disease or recurrence. Collectively, circulating SDC1-positive EVs represents a clinically informative biomarker reflecting tumor aggressiveness and treatment response in pediatric brain tumors, supporting their potential for non-invasive disease stratification and monitoring.

Protocadherin-12 (PCDH12), a cell-adhesion protein belonging to the non-clustered protocadherin family, plays a crucial role in the establishment and regulation of neuronal connections and communication. Bi-allelic loss-of-function (LoF) variants in the PCDH12 gene have been associated with several neurodevelopmental disorders (NDDs) such as diencephalic-mesencephalic junction dysplasia (DMJD) syndrome, cerebral palsy, and cerebellar ataxia, often accompanied by ocular abnormalities. However, genotypes exhibit variable expressivity. Affected individuals sharing the same PCDH12 variant presenting differing phenotypic severities have posed major challenges towards identification of the underlying pathogenic mechanisms. Here, we report three affected individuals from two families, each harbouring non-truncating pathogenic missense variants in PCDH12. The patients are compound heterozygous, with each individual carrying one extracellular [c.1742T>G (p.Val581Gly) and c.1861_2del/insCA (p.Ile621His)] and one intracellular variant [c.3370C>T (p.Arg1124Cys) and c.3445G>A (p.Asp1149Asn] on each allele. The children present with a range of phenotypes similar to those associated with LoF variants. One child exhibited microcephaly and seizures, while the two siblings displayed developmental delays and severe behavioral disorders. All three children experienced some degree of visual impairment. The missense variants provided new insights into the neurodevelopmental consequences of compromised PCDH12 function by distinguishing the specific consequences associated with dysfunction in the extracellular versus intracellular domains of PCDH12. All identified missense variants are predicted to be deleterious and destabilizing. The expression of PCDH12 in HEK293T and HeLa cells demonstrated that PCDH12 is expressed effectively, regardless of the presence of missense variants. However, the extracellular variants p.Val581Gly and p.Ile621His compromised the stability of PCDH12's homophilic adhesion. Additionally, we found evidence of an interaction between PCDH12 and the extracellular domain of the epilepsy-associated PCDH19 protein. PCDH12 extracellular missense variants also negatively impact this interaction. Our study provides evidence that PCDH12 mediates both homophilic and heterophilic interactions. Our findings also highlight the importance of stable PCDH12-mediated adhesion, emphasizing the need to further study the functional consequences of PCDH12 missense variants on brain and visual system development.

Background: Quantitative genome wide association studies (GWAS) primarily rely on additive linear models that compare average phenotypic differences between genotype groups. While effective for detecting common variants of moderate effect in large sample sizes, such approaches inherently reduce high resolution phenotypic data to summary statistics (group averages), potentially limiting the detection of subtle genotype phenotype relationships. Genomic Informational Field Theory (GIFT) is a recently developed methodology that preserves the fine-grained informational structure of quantitative traits by analysing ranked phenotypic configurations rather than relying solely on mean differences. Methods: We applied GIFT to genetic and neuropathological data from the Brains for Dementia Research cohort, a well characterised dataset of 563 individuals, and compared its performance with conventional GWAS. Principal component analysis (PCA) derived matrix was used to derive independent quantitative traits linked to from Alzheimer disease (AD) neuropathology measures (CERAD, Thal, Braak staging), with and without inclusion of age at death. Principal component analyses were performed using GWAS and GIFT frameworks on the same filtered genotype dataset. Results: Both GWAS and GIFT identified genome-wide significant associations (pvalue<0.000001) within the APOE locus (NECTIN2/TOMM40/APOE/APOC1), demonstrating concordance with established AD genetic variants. However, GIFT detected additional significant 19 SNPs beyond those identified by GWAS. Variants associated with AD pathology implicated genes involved in amyloid processing, neuronal apoptosis, synaptic function, neuroinflammation, and metabolic regulation. Notably, GIFT identified 29 loci associated with age at death related variation that were not detected by GWAS, highlighting genes linked to lipophagy, mitochondrial quality control, sphingolipid metabolism, frailty, and aging-related processes. Conclusions: GIFT recapitulates canonical GWAS findings while uncovering additional biologically relevant associations. By preserving the fine-grained structure of phenotypic data distributions and detecting non random genotype segregation across ranked trait values, GIFT enables the identification of associations that remained undetected by traditional average based GWAS approaches. These results demonstrate that rethinking analytical representation, rather than solely increasing sample size, can expand discovery potential of genetic association studies, offering a transparent and complementary framework for quantitative genomics in deeply phenotyped datasets.

1Amyotrophic lateral sclerosis (ALS) is highly heritable, yet the vast majority of cases lack an identifiable genetic cause and clinical progression remains largely unpredictable. To connect noncoding and rare genetic variation to disease phenotypes in a relevant cell type, we generated a multi-omic quantitative trait locus (QTL) atlas from 594 induced-pluripotent-stem-cell-derived human motor neuron lines (522 ALS patients, 72 controls). By mapping cis-QTLs for chromatin accessibility, splicing and gene expression from whole-genome sequencing, we identify common and rare variants on the wild-type C9orf72 allele that form regulatory haplotypes. These haplotypes influence C9orf72 expression levels in motor neurons and stratify C9-ALS patients into four subgroups; using clinical disease duration data and longitudinal ALSFRS-R scores, we show that these subgroups exhibit different survival trajectories, indicating that wild-type C9orf72 expression acts as a genetic modifier of disease duration. Beyond the C9orf72 locus, we detect ultra-rare intronic variants that create cryptic exons and structural and nonsense variants in established ALS genes, providing likely genetic explanations for disease in additional patients who previously lacked a molecular diagnosis. Our results show that QTL mapping in patient-derived motor neurons can reveal regulatory modifiers of progression and hidden pathogenic events in ALS, providing a framework for genetically informed risk attribution and patient stratification in complex neurological diseases.

Stromal tumor-infiltrating lymphocytes (sTILs) are promising biomarkers for predicting therapeutic outcomes in triple-negative breast cancer (TNBC), with higher sTIL levels correlating with improved chemotherapy response and survival outcomes. Currently, sTILs are manually evaluated by pathologists, which is prone to inter-reader variability. In this study, we have developed an AI-driven TIL segmentation pipeline to process entire diagnostic hematoxylin-and-eosin-stained whole slide images for reproducible scoring (global TILseg scoring) and reliable prognostication. This pipeline was optimized and tested using two independent TNBC patient cohorts (n = 57 in the discovery cohort, n = 43 in the validation cohort) with clinical outcomes and follow-up data. The global scores generated by TILseg showed moderate to high concordance with expert scoring (Spearman R = 0.84-0.89) and improved patient stratification (p-value = 0.0191) as compared to manual scoring (p-value = 0.0663). Additionally, we investigate how the spatial localization of sTILs (spatial TILseg) impact survival outcomes by identifying TILs in selected stromal subsets (0.02-2 mm from the epithelial clusters). Our findings have shown that TILs up to 50 {micro}m from epithelial regions prove to be most prognostic in predicting recurrence-free survival post-neoadjuvant chemotherapy with higher statistical significance than both manual and global TILseg scoring. Further, spatial TILseg scoring was more significantly associated with pathological complete response status in both patient cohorts. In summary, we present an AI-based digital tool for robust sTIL scoring and spatial mapping to enhance its potential as both a diagnostic and prognostic biomarker, particularly in TNBC patients. SIGNIFICANCEAn automated and spatially resolved AI tool for sTILs scoring enhances patient risk stratification based on both response to treatment and recurrence-free survival, establishing its relevance as an independent prognostic marker.

BackgroundChitinases, including chitotriosidase (CHIT1) and chitinase-3-like protein 1 (CHI3L1), are markers of neuroinflammation, a key process in amyotrophic lateral sclerosis (ALS). Tear fluid (TF) can be collected non-invasively and may represent a promising alternative to CSF or blood to study chitinases. MethodsTF was collected from 50 ALS patients and 50 control subjects using Schirmer strips. CHIT1 and CHI3L1 levels in TF, serum, and CSF were quantified using ELISA. Serum NfL was measured using SIMOA. The frequency of a 24 bp-duplication polymorphism in the CHIT1 gene influencing CHIT1 expression was assessed by PCR. ResultsNo group differences in the distribution of the CHIT1 polymorphism were detected. Carriers of the polymorphism in both ALS and controls showed lower CHIT1 levels in serum and TF. CHI3L1 levels in TF were higher in ALS patients compared to controls (p = 0.007), consistent with changes in CSF but not serum. In ALS, males showed higher TF CHIT1-values compared to females (p = 0.009). Combining TF chitinase values with serum NfL values improved discrimination between ALS and controls. ConclusionsChitinases are detectable in TF, and CHI3L1 levels recapitulate changes observed in CSF, highlighting its potential for non-invasive longitudinal assessment. Furthermore, chitinase values in TF, together with serum NfL, may act complementary by capturing distinct aspects of the disease, neuroinflammation and axonal damage. These results suggest TF chitinases and serum NfL could complementarily contribute to the diagnosis and monitoring of the disease, and call for further evaluation of TF as a biomarker source in ALS.

Glycoprotein nonmetastatic melanoma B (GPNMB), encoded by the target gene (GPNMB) of a Parkinsons disease (PD) risk locus, acts as a secreted factor mediating inflammatory effects in the context of immunity and cancer. In a neurodegenerative disease context, GPNMB is critical to cellular uptake of pathological forms of alpha-synuclein (aSyn), the hallmark disease protein that misfolds and accumulates in PD. Here, we demonstrate that the non-membrane-anchored, extracellular domain of GPNMB, shed into conditioned medium or added as recombinant protein, enables uptake of aSyn fibrils in a non-cell-autonomous manner. In human postmortem brain, GPNMB is widely expressed in neurons and microglia, with increased microglial expression in the setting of neurodegenerative disease. In microglial cell lines and induced pluripotent stem cell-derived microglia (iMicroglia), GPNMB expression and secretion increases with exposure to apoptotic neurons. In the aSyn-fibril seeded model of PD, iMicroglia-derived GPNMB allows for development of aSyn pathology in GPNMB knockout neurons, while conditioned medium from GPNMB knockout iMicroglia lacks this effect. Conversely, treatment with anti-GPNMB antibodies rescues neurons from development of aSyn pathology in this model. Finally, in 1675 human postmortem cases, GPNMB genotypes conferring higher GPNMB expression associate with more widespread aSyn pathology, without affecting beta-amyloid or tau pathology. Taken together, our data suggest a positive feedback model, where neuronal death triggers increased GPNMB expression and secretion by microglia, leading to increased uptake of pathological forms of aSyn by neurons, leading to more neuronal death. Importantly, this cycle can be interrupted by anti-GPNMB antibodies, offering an avenue for therapeutic development. One Sentence SummaryThe extracellular domain of GPNMB enhances uptake of fibrillar alpha-synuclein in a non-cell-autonomous process that can be blocked by anti-GPNMB antibodies. HighlightsO_LIThe extracellular domain of GPNMB confers capacity for uptake of alpha-synuclein fibrils to iPSC-derived neurons (iNeurons) lacking GPNMB expression. C_LIO_LIGPNMB is widely expressed in neurons and microglia in human brain, with more expression in microglia, particularly in Parkinsons disease brain. C_LIO_LIiPSC-derived microglia (iMicroglia) secrete GPNMB in response to neurodegeneration-related insults, and iMicroglia-derived GPNMB enhances development of alpha-synuclein pathology in iNeurons. C_LIO_LIAnti-GPNMB antibodies rescue iNeurons from development of synuclein pathology. C_LIO_LIExpression quantitative trait loci (eQTLs) for GPNMB associate with extent of alpha-synuclein pathology in human neurodegenerative disease. C_LI

An overlap syndrome of myositis and/or myocarditis associated with myasthenia gravis (MG) has emerged as a life-threatening immune-related adverse event (irAE) in cancer patients treated with immune checkpoint inhibitors (ICIs). This syndrome closely resembles a rare form of idiopathic inflammatory myopathy (IIM) seen in a subset of MG patients. In this systematic review, we searched PubMed for reports of concurrent MG and IIM as well as ICI-related overlap syndromes. By integrating clinical, serological, and pathological observations, we delineated a previously unrecognized clinicopathological subtype of myositis that overlaps with MG. This entity is defined by a strong association with striational antibodies (StrAbs) and frequent co- occurrence with thymoma as a paraneoplastic process, and we classify it as StrAb-associated myositis. The idiopathic and ICI-induced forms share similar, though not identical, clinical, serological, and histopathological characteristics. We found that AChR antibody positivity, independent of established clinical risk factors such as respiratory or cardiac involvement, predicted more severe ICI-myotoxicity. Together with supporting evidence, our findings suggest a pathogenic model in which thymoma-driven cytotoxic T-cell responses trigger secondary AChR autoimmunity. These results highlight the potential utility of StrAbs and anti-AChR antibodies as practical biomarkers for diagnosis, risk stratification, and early intervention in patients at risk for severe neuromuscular irAEs.

Leucine-rich repeat kinase 2 (LRRK2) variants are the most common cause of inherited Parkinsons disease (PD), and the hyperactivity of the LRRK2 variants represent a validated drug target for PD. The penetration of common LRRK2 variants is incomplete, underscoring the need for molecular biomarkers that predict disease onset and guide therapeutics development. Here, we analyzed large datasets of cerebrospinal fluid (CSF) and urinary proteomics from the Parkinsons Progression Markers Initiative (PPMI) and identified distinct lysosomal and immune protein signatures as potential biomarkers for LRRK2-linked PD (LRRK2 PD). Longitudinal analysis revealed that levels of specific lysosomal and immune proteins remained elevated in CSF during the prodromal phase but declined following clinical symptom onset. Furthermore, examination of multiple brain cell types from Lrrk2 mutant mice carrying disease variant (G2019S) showed heightened secretion of lysosomal proteins in microglia and astrocytes, but not neurons, supporting a glial origin and intrinsic LRRK2 mutant activity responsible for the elevated CSF lysosomal proteins. Furthermore, proteomics analysis of urine from humanized LRRK2G2019Stransgenic mice identified lysosome and glycosphingolipid protein signatures shared with human LRRK2 PD patients. Collectively, our integrated proteomics reveals dynamic changes of functional biofluid signatures for LRRK2 PD, which enables the determination of biomarkers for early disease onset. The humanized LRRK2G2019S mice provide a valuable platform for biomarker refinement and therapeutic development. One Sentence SummaryIntegrated human and mouse proteomic analyses identify dynamic lysosomal and immune biofluid signatures, possibly of glial origin, as functional biomarkers of LRRK2-linked Parkinsons disease progression, supported by a novel humanized LRRK2G2019S mouse model that recapitulates key urinary biomarker profiles.

Lysosomal dysfunction is central to Parkinsons disease pathogenesis, with GBA1 as the strongest established genetic risk factor. Numerous other genes involved in lysosomal sphingolipid, glycosphingolipid and ceramide metabolism have been proposed as contributors to Parkinsons disease, underscoring the need for comprehensive genetic analyses across these pathways. We analysed rare variants (minor allele frequency < 0.01) across 36 lysosomal genes (excluding GBA1) in 8,267 individuals with Parkinsons disease and 68,208 controls, including a subset of 793 early-onset Parkinsons disease ([&le;]50 years) cases. Targeted sequencing was performed in four cohorts at McGill University (3,456 Parkinsons disease patients and 2,664 controls) and results were combined with whole-genome sequencing data from the UK Biobank (2,848 cases, 62,451 controls), and from the Accelerating Medicines Partnership - Parkinsons Disease (1,963 cases, 3,093 controls). We analysed the association of rare variants in these genes with Parkinsons disease using Sequence Kernel Association Test-Optimal (SKAT-O) across variant classes (all rare variants, nonsynonymous, loss-of-function and predicted damaging variants with a Combined Annotation Dependent Depletion (CADD) score >20), with meta-analysis across cohorts. We additionally performed per-domain analyses for variants in gene segments encoding functional domains. False discovery rate correction was applied. Meta-analysis identified a significant association between rare variants in ST3GAL3 and Parkinsons disease (Pfdr=0.04). Several additional lysosomal genes showed nominal associations (P<0.05), including HGSNAT, ASAH1, CTSD, HEXA, ST3GAL4 and SGPP1. Domain-based analyses identified a strong enrichment of nonsynonymous variants within the beta-acetyl-hexosaminidase-like domain of HEXA (P = 8.0 x 10), although this signal did not survive correction for multiple testing (Pfdr=0.154). In early-onset Parkinsons disease, domain-based analyses revealed significant associations in NAGLU (Pfdr=7.3x10) and ST3GAL5 (Pfdr=0.03). Together, these results provide genetic evidence that rare variants across multiple lysosomal pathways, particularly those related to sialylation, ganglioside metabolism, ceramide biology, and lysosomal proteolysis, may contribute to Parkinsons disease susceptibility beyond GBA1, highlighting biologically coherent pathways for future replication and functional investigation.