Neuropathology and Applied Neurobiology

Abstract Objectives: Amyotrophic lateral sclerosis (ALS) is a clinically heterogeneous neurodegenerative disease requiring reliable biomarkers to improve patient stratification and trial design. While serum neurofilament light chain (sNfL) reflects neuroaxonal stress and disease aggressiveness, troponin T (TnT) may capture complementary aspects of neuromuscular involvement. We assessed the associations of TnT and sNfL with D50-derived measures of disease aggressiveness (D50) and disease accumulation (rD50) in ALS. Material and Methods: In this retrospective observation, TnT and sNfL levels from ALS patients in two independent German cohorts were analyzed using the D50 disease progression model; discovery cohort (Essen, n =433) and validation cohort (Bonn, n =185). Results: In both cohorts TnT demonstrated a robust correlation with rD50-defined phases across all aggressiveness subgroups (p<0.001). There was no consistent pattern regarding sNfL and the rD50 phases. sNfL concentrations demonstrated a significant and inverse correlation with D50 applied for all disease aggressiveness subgroups (p<0.001). Correlations of TnT levels with D50 disease aggressiveness groups were generally less strong and inconsistent between the two cohorts. In the discovery cohort only low aggressiveness subgroups correlated significantly (p<0.001), intermediate aggressiveness subgroups showed only a weak correlation (p<0.05) with TnT levels. High disease aggressiveness subgroups showed no significant correlation with TnT. Conclusion: In application of the D50 disease progression model, TnT was strongly associated with disease accumulation (rD50) across all disease phases, independent of disease aggressiveness (D50), whereas sNfL robustly reflected disease aggressiveness but not overall disease burden. These complementary biomarker profiles highlight the value of an integrated approach for refined disease stratification in ALS. Combining TnT and sNfL may enhance clinical decision-making, improve monitoring of disease progression and treatment response, and support optimized clinical trial design.

TDP-43 dysfunction is a defining feature of amyotrophic lateral sclerosis (ALS), yet no biofluid biomarker directly measures its functional activity. We developed a serum-based homogeneous time-resolved FRET (hTR-FRET) assay that quantifies TDP-43 RNA-binding activity using synthetic UU rich RNA probes. We analyzed 1,080 serum samples from controls, sporadic ALS, and genetic subgroups (C9orf72, SOD1) across multiple biorepositories. Cross-sectionally, TDP-43 ligation activity was elevated in ALS (mean 390 a.u.) versus controls (304 a.u.), yielding AUC = 0.79. Genotype means were 392 a.u. (sporadic), 382 a.u. (C9orf72), and 323 a.u. (SOD1); with a 366 a.u threshold achieved 95% specificity against controls. Longitudinally, Target ALS showed a modest but significant inverse correlation between TDP-43 activity and ALSFRS-R, while other cohorts exhibited similar non-significant trends. Elevated signal likely reflects increased extracellular, probe-competent TDP-43 species. This assay provides direct functional measurement of disease-relevant TDP-43 biology, supporting applications in diagnostic discrimination, genotype stratification, and progression monitoring in prospective studies.

Mislocalization and aggregation of transactive response DNA-binding protein 43 kDa (TDP-43) represent a neuropathological hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) and are increasingly recognized in Alzheimers disease (AD) and limbic-predominant age-related TDP-43 encephalopathy (LATE). However, the in vivo value of CSF TDP-43 as a biomarker and its relation to established markers remains unclear. We quantified CSF concentrations of TDP-43 using ELISA in 25 controls, 32 ALS, 9 probable LATE, and 24 AD patients. CSF TDP-43 levels differed significantly between groups, with the highest concentrations in LATE, exceeding both ALS and AD. ALS and AD showed intermediate, comparable increases versus controls. In parallel, conventional AD biomarkers (t-tau, p-tau, and amyloid-b) showed the expected AD-typical profile but remained largely unaltered in probable LATE, indicating a dissociation between TDP-43 an AD-type pathology. These findings identify CSF TDP-43 as a promising candidate biomarker for LATE, characterized by disproportionate elevation in the absence of AD-type biomarker changes, and neurodegeneration in aging populations.

BackgroundAmyotrophic lateral sclerosis (ALS) is characterized by profound metabolic reprogramming, yet the lack of biomarkers for specific druggable targets remains a major hurdle for precision medicine. We hypothesized that peripheral lipid biosynthetic signatures could serve as both prognostic indicators and a roadmap for identifying novel disease-modifying targets. MethodsWe assessed serum fatty acid (FA) metabolic pathways in two independent longitudinal cohorts (n = 37 and n = 38) using high-dimensional CoxBoost modeling. Primary outcomes were survival and functional staging milestones, including non-invasive ventilation and gastrostomy. The biological relevance of the identified candidate was further assessed through correlation with plasma neurofilament light-chain (NfL) levels. Causality and therapeutic potential were validated in Drosophila melanogaster models of TDP-43 proteinopathy via genetic ablation and pharmacological inhibition. ResultsOur multi-parametric model, comprising two clinical variables and the estimated ELOVL6 (elongation of very long-chain fatty acids protein 6) activity, demonstrated robust prognostic accuracy (Unos C 0.69) across both cohorts; ELOVL6 activity served as a strong independent predictor of mortality and functional decline. Notably, high ELOVL6 activity significantly correlated with elevated plasma NfL levels (p < 0.01), linking peripheral elongation imbalances to central axonal damage. In Drosophila, ELOVL6 overactivation was identified as a conserved pathological consequence of TDP-43 dysfunction, characterized by an increased C18:0/C16:0 ratio in both loss-of-function and gain-of-function models. Inhibition of ELOVL6, either genetically or pharmacologically, rescued neuromuscular junction integrity, prolonged survival, and significantly reduced pathological TDP-43 phosphorylation in glial models. ConclusionThese findings position ELOVL6 as a promising modifiable metabolic node with potential for disease-modifying intervention in ALS. Beyond its potential utility for identifying high-risk metabolic profiles and assisting in prognostic counseling, ELOVL6 bridges systemic lipid dysregulation with TDP-43 proteinopathy. Targeting this pathway offers a dual opportunity: as a biological marker to supplement clinical staging and as a druggable enzymatic target to ameliorate motor neuron degeneration. HIGHLIGHTSO_LISystemic ELOVL6 activity is a robust independent predictor of ALS survival. C_LIO_LIHigh ELOVL6 levels correlate with plasma NfL and functional decline. C_LIO_LIInhibition of ELOVL6 rescues NMJ integrity and survival in Drosophila models. C_LIO_LIPharmacological targeting of ELOVL6 reduces glial TDP-43 phosphorylation. C_LIO_LIELOVL6 represents a druggable metabolic node linking lipids to proteinopathy. C_LI

BackgroundAccurate diagnosis of multiple system atrophy (MSA) is critical for clinical management and efficient trial designs, yet remains challenging, particularly distinguishing MSA (especially cerebellar-subtype [MSA-C]) from sporadic adult-onset ataxia (SAOA). Combining a marker of neuroaxonal degeneration, neurofilament light chain (NfL), with a marker of the pathogenic MSA hallmark, -synuclein seeding activity, may define a mechanistically-informed CSF signature of MSA, enabling sensitive and specific differentiation from SAOA even in early disease. MethodsWe analyzed 60 cross-sectional patient CSF samples (n=32 clinically diagnosed MSA [MSAclin] 22/32 MSA-C; n=28 SAOA) for NfL (Simoa) and -synuclein seeding activity (seed amplification assay [synSAA], Piperazine-N,N-bis(2-ethanesulfonic acid)-based), and assessed diagnostic accuracy, disease-duration correlations, and trial power using biomarker-based stratification. ResultsAge-adjusted NfL was higher in MSAclin than SAOA (3859 vs. 997pg/mL), yielding 96.9% sensitivity and 85.7% specificity. SynSAA was concordant with clinical diagnosis (25/32 MSAclin synSAA-positive; 23/28 SAOA synSAA-negative), with 78.1% sensitivity and 85.2% specificity (all confirmed in MSA-C subgroup). Both biomarkers displayed divergent trajectories with disease duration: NfL peaked early before declining (r=-0.45, p=0.01); whereas synSAA maximum fluorescence intensity increased (r=0.42, p=0.016), suggesting greater synSAA signal with accumulating MSA burden. Integrating both biomarkers in MSA treatment trials allows sample-size reduction by 20% versus NfL alone. ConclusionsCSF NfL and synSAA capture complementary aspects of MSA biology: while NfL provides high diagnostic accuracy for MSAclin, peaking early, synSAA adds mechanistic specificity for -synuclein seeding activity and might allow target engagement assessment. Combined, they might enable biological diagnostic frameworks, molecular trial stratification, and treatment monitoring in MSA. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSWhile highly warranted for clinical management and efficient treatment trial design, accurate diagnosis of multiple system atrophy (MSA) against overlapping and reciprocally mimicking conditions such as sporadic adult-onset ataxia (SAOA) remains clinically challenging, especially in early disease stages. A mechanistically informed biofluid signature of MSA might enable sensitive and specific differentiation from SAOA, even in early disease stage. Recently merging molecular markers reflecting neuroaxonal damage (NfL) and -synuclein seeding activity (measured by the seed amplification assay; synSAA) might here show particular promise. What this study addsThis is the first study to systematically assess the ability of both CSF NfL and CSF -synuclein seeding activity to distinguish clinically diagnosed MSA (MSAclin) from SAOA, thereby offering a window into underlying MSA biology in patients in vivo. Our findings suggest that the rate of axonal degeneration is most pronounced in early MSA disease stages but decreases with longer disease duration; whereas -synuclein seeding signal activity increases as MSA-related disease burden accumulates. Finally, it demonstrates the impact of a combined molecular fluid signature of MSA for improving trial design: a biomarker-based stratification of MSA subjects in future MSA treatment trials combining NfL plus -synuclein seeding activity allows to reduce sample sizes by 20% compared to NfL alone. How this study might affect research, practice or policyThe findings from this study may help to molecularly diagnose patients with MSA against overlapping and reciprocally mimicking conditions such as SAOA, in particular and even in early disease stages. Moreover, they might lay the foundation for a future biologically-informed diagnostic framework of MSA; support trial stratification for more efficient upcoming MSA treatment trials; and might facilitate molecular treatment effect monitoring in MSA, in particular in synuclein-targeted treatment trials.

Synucleinopathies are a group of neurodegenerative diseases characterized by the presence of misfolded -synuclein inclusions which cause progressive disease by spreading throughout the brain in a prion-like manner. Throughout the neurodegenerative disease field, the ability of a single protein to give rise to multiple distinct clinical disorders is explained by the strain hypothesis, or the idea that the misfolded protein conformation determines the resulting disease. This was initially shown using transmission studies in cell lines and mouse models; more recently cryo-electron microscopy (cryo-EM) validated this idea by identifying distinct -synuclein filament folds in brain tissues from patients with Parkinsons disease, multiple system atrophy (MSA), and juvenile-onset synucleinopathy. However, very little is known about the -synuclein filament structures that form in animal models of these disorders, and thus their relevance to human disease and suitability as models for therapeutic development remains a question. Here we report the first atomic resolution cryo-EM structures of -synuclein fibrils from an MSA patient sample before and after transmission to a transgenic mouse model of disease. Our findings indicate that while distinct adaptations occur during fibril replication in the mouse host, key structural facets are maintained, validating the merits of this transmission model for supporting preclinical research on MSA.

Friedreichs ataxia (FA) is a rare autosomal recessive neurodegenerative disorder caused by reduced expression of frataxin, a mitochondrial protein important for iron-sulfur cluster assembly and mitochondrial homeostasis. Although FA has traditionally been attributed to neuronal dysfunction, increasing evidence suggests that glial cells play a critical role in disease progression, although their contribution remains poorly defined. Using the FXNI151F mouse model, we investigated cell-type-specific metabolic and redox alterations in neurons and glial populations from the cerebrum, cerebellum, and dorsal root ganglia (DRG). Neuronal and glial-enriched fractions were isolated by immunomagnetic separation and analyzed for mitochondrial function, iron metabolism and reactive oxygen species (ROS). The analyses identified the DRG as the most severely affected region, exhibiting early and pronounced mitochondrial respiratory deficits, increased ROS, mitochondrial iron accumulation, lipid peroxidation, and reduced levels of glutathione peroxidase 4 and nuclear factor erythroid 2-related factor 2 in both neuronal and non-neuronal cells. These results highlight the vulnerability of sensory neurons and their supporting satellite glial cells. In contrast, in the cerebrum and cerebellum, astrocytes displayed earlier and more severe alterations than neurons, including impaired respiratory chain efficiency, disrupted complex I-III supercomplex interaction, elevated ROS, and hallmarks of ferroptosis. Neuronal abnormalities emerged later, suggesting that glial dysfunction precedes -or drives- neuronal pathology within the central nervous system. Overall, these findings reveal pronounced region and cell-type-specific vulnerabilities in FA and support the importance of targeting glial mechanisms--particularly iron dysregulation, oxidative stress, and ferroptosis-- as targets for potential therapeutic strategies.

BackgroundHuntington disease (HD) is a neurological disorder caused by an aberrant CAG expansion in the HTT gene, producing a mutant protein (mHTT). Although HD is classically characterized by adult-onset cortical and striatal degeneration, accumulating evidence suggests that altered cortical development may also contribute to disease pathogenesis. ObjectiveWe sought to investigate the impact of mHTT on neocortical patterning, which is a largely unexplored aspect of HD. MethodsUsing the HdhQ140 HD knock-in mouse model, we performed immunofluorescence and in situ hybridization to analyze the patterning of the cortex from embryonic day 10 to postnatal day 7. ResultsDuring embryogenesis, HTT expression exhibited a high medial-to-low lateral gradient in the neocortex, like that observed for key transcription factors involved in cortical patterning. Notably, HTT expression was absent from the cortical hem, a critical patterning center. In HD, the protein gradient remained unchanged whereas the expression in medial pallium seemed increased. During the early development of the cerebral hemispheres, the expression of morphogens and signaling pathways, including Shh, Fgf8, and Wnt/BMP genes, were disrupted in organizing centers, leading to altered expression of major neocortical transcription factors. At postnatal stages, the motor and somatosensory cortical areas were misplaced. These developmental alterations were associated with postnatal sensorimotor deficits relevant to HD. ConclusionsOur findings demonstrate that HD-related neurodevelopmental alterations arise as early as embryonic day 10 in mice. This supports previous work suggesting that defects in brain development contribute to HD pathogenesis prior to clinical onset.

CLN3 disease is an inherited neurodegenerative disease, typically with childhood onset, and characterized by vision loss, seizures, cognitive decline, and difficulties. The CLN3 Staging System (CLN3SS) characterizes disease progression. Our aim was to assess differences in cognitive test scores in relation to CLN3SS among individuals with CLN3 disease. We evaluated the relationship between cognitive test performance and the CLN3SS in individuals with genetically confirmed CLN3 disease. Participants completed tasks of verbal reasoning, vocabulary knowledge, attention, fund of information, and ability to recite the alphabet. One-way ANOVA testing assessed differences in mean cognitive test score among CLN3SS score groups, and Chi-square testing was used to compare the proportion in each CLN3SS group that could recite the alphabet. Data were evaluated from a sample of 85 individuals with a total 245 CLN3SS assessments conducted within 6 months of their cognitive testing, A significant decrease in test scores was found between CLN3SS Stages 1 (vision loss present) and 2 (vision loss and seizures present) for each of the cognitive tests. The proportion of participants able to recite the alphabet also decreased from Stage 1 to Stage 2 (X2=12.1, p<.01). Cognitive ability declines with advanced disease severity in CLN3 disease, though motor disability in Stage 3 likely contributes to difficulty participating in cognitive assessment at this later disease stage. Understanding the relationship between cognition and CLN3 disease stage may help guide decision making, i.e., determining who could or should undergo cognitive assessment for clinical care or for group stratification in disease modifying clinical trials.

Accurate in vivo prediction of neuropathology is critical for advancing diagnosis and treatment of Alzheimers disease and related dementias (ADRDs). As many individuals with ADRDs have mixed pathologies ({beta}-amyloid, pathologic tau, cerebrovascular disease, vascular brain injury, pathologic TDP-43, hippocampal sclerosis, Lewy bodies), there is interest in determining how accurately we can infer these pathologic changes from clinical data, biofluid assays (e.g., CSF), and neuroimaging. Here we evaluated automated machine learning models trained on data curated by the AD Sequencing Project Phenotype Harmonization Consortium (N=7,894 individuals), to predict 26 autopsy-confirmed neuropathological outcomes. Predictors included in vivo clinical and cognitive composite scores, brain measures from 3D structural MRI and diffusion tensor imaging, image-derived measures of white matter hyperintensities (WMH), and CSF biomarkers. Predictive models were trained using ensemble learning with stratified cross-validation. We assessed performance using Spearmans rank correlation and Matthews correlation coefficient, to accommodate co-occurring pathologic changes. The added value of neuroimaging and CSF versus clinical features alone was quantified. Braak stage was among the most consistently predicted outcomes. CSF biomarkers best predicted {beta}-amyloid and tau pathology, but diffusion MRI metrics best captured vascular brain injury and white matter injury, and outperformed clinical and cognitive measures and anatomical MRI in predicting Lewy body disease. Anatomical measures from structural MRI outperformed standard clinical assessments in assessing neurodegeneration and hippocampal sclerosis, and WMH complemented cognitive measures in predicting TDP-43 pathology. These results establish a baseline for comparing modalities for inferring neuropathology.

Herpes Simplex virus type 1 (HSV-1) is a highly prevalent neurotropic virus from the alphaherpesviruses family. In recent years, a growing body of research has focused on the potential role of HSV-1 infections and recurrent reactivations in the pathophysiology of Alzheimers disease (AD). In particular, it has been hypothesized that HSV-1 could initiate or amplify the formation of neuropathological lesions characteristic of AD. To explore further this hypothesis, we adopted an integrated approach aiming at deciphering the impact of HSV-1 infection on AD molecular markers (A{beta} and Tau pathologies) and combining experimental animal models of in vivo infection, postmortem neuropathological analysis of AD brains, as well as in-vivo clinical analysis in AD patients. In animal models of peripheral (labial) infection with HSV-1 virus, we analyzed viral dissemination from peripheral tissues to the CNS, and the associated neuropathological consequences. Histological and molecular analyses revealed the occurrence of viral material (RNA, proteins) in the brainstem, the primary site of viral neuroinvasion, and in more anterior regions of the brain. Viral signatures were accompanied by early abnormal deposits of A{beta} peptides and accumulation of phosphoTau (pTau) proteins in various brain areas. Neuropathological examination of AD/control participants also underlined the presence of HSV-1 DNA in the human brainstem (pons) that was always associated with local A{beta}/Tau aggregates. Finally, in AD patients, associations were found between HSV-1 seropositivity and neuropathological lesion burden (region-specific Tau and A{beta} deposition detected by neuroimaging). Taken together, these data provide new evidence in favor of the involvement of HSV-1 in the pathophysiology of AD, stressing a possible causal link between HSV-1 infection, neuroinvasion and AD neuropathological hallmarks (A{beta} lesions and tauopathy).

Alzheimer's disease (AD) is characterized by complex alterations in synaptic, glial, neuronal and inflammatory markers. Given its emerging role at the interface of synaptic dysfunction and inflammation, the astrocytic marker GFAP may represent a cross-domain hub linking synaptic, neuronal and inflammatory alterations. Using multivariate and network-based analyses we examined the relationships among cerebrospinal fluid (CSF) biomarkers of astrocytic activation and synaptic failure, inflammation, and neurodegeneration in biologically confirmed AD patients and healthy controls (HC). We studied 60 AD patients and 40 HC. CSF concentrations of Neurogranin, SNAP-25, CAP2, NfL, GFAP, IL-1 , IL-1{beta}, IL-8, MCP-1, TNF were measured. Associations were assessed using Spearman correlations, LASSO regression, and network analysis to characterize multivariate dependency structures. Compared with controls, AD patients showed significantly higher CSF levels of Neurogranin, SNAP-25, CAP2, NfL, GFAP, IL-1{beta}, TNF- .. In AD, synaptic biomarkers were strongly intercorrelated and associated with astroglial activation, inflammatory markers, and tau-related pathology. Network analysis identified GFAP as a cross-domain hub linking synaptic, inflammatory, and neurodegenerative domains in AD. In controls, GFAP was mainly associated with neuronal injury markers. Network-based modelling revealed a disease-related reorganization of biomarker connectivity in AD, with GFAP occupying a central cross-domain position, supporting a systems-level view of AD pathophysiology.

The TREM2 R47H variant increases the risk of Alzheimers disease (AD), yet its functional impact in aged mouse models remains incompletely understood. We generated a humanized Trem2 R47H knock-in (KI) line on the AppNL-F background and compared it with a Trem2 knockout (KO) line to assess the degree of TREM2 functional impairment. Accumulation of amyloid {beta} 42 and formation of dystrophic neurites were increased in Trem2 KO mice but not in Trem2 R47H KI mice at 18 or 24 months. qPCR and transcriptomic analyses revealed Trem2 KO mice showed deficits in upregulation of microglial genes while Trem2 R47H KI mice showed a response similar to control mice. Differential gene expression analysis identified altered expressions of genes responsible for ER stress/unfolded protein response and intracellular signalling in Trem2 R47H KI mice. Among the differentially expressed genes, Pmel and Gpnmb were or tended to be downregulated in Trem2 R47H KI as well as in Trem2 KO mice indicating their involvement in AD pathogenesis. These results clearly indicate that the TREM2 R47H variant confers a mild, rather than null, effect on microglial alterations during AD development and that Trem2 R47H KI mice should be used to understand pathological mechanism elicited by TREM2. Further identification and characterization of genes differentially expressed in Trem2 R47H KI mice will provide important insights into how the TREM2 risk variant modulates Alzheimers disease-related pathology. HighlightsO_LIExon2-humanized Trem2 R47H knock-in mice are established, which will serve as a platform to study the role of TREM2 in Alzheimers disease development. C_LIO_LITrem2 knockout mice exhibit deficits in clearance of highly aggregated A{beta}42, suppression of dystrophic neurites and regulation of microglial genes in AppNL-F mice, whereas Trem2 R47H knock-in mice do not. C_LIO_LIRNA-seq reveals transcriptional profiles of Trem2 R47H knock-in mice C_LIO_LIqPCR confirms that Gpnmb and Pmel are or tended to be downregulated in Trem2 R47H knock-in mice. C_LIO_LIFindings demonstrate that TREM2 R47H is hypomorphic rather than loss of function. C_LI

Multiple plasma phosphorylated tau assays are now commercially available for detection of Alzheimers disease (AD) pathology, yet clinical laboratories lack a comprehensive comparative evaluation to guide implementation decisions. Diagnostic accuracy and analytical performance were assessed in a cohort of 273 participants with paired EDTA plasma and CSF specimens. CSF AD core biomarkers were used as the reference standard, and index tests included three plasma pTau217 assays by Roche, Fujirebio, and Meso Scale Discovery [MSD], and a pTau181 assay by Roche. Participants had a median age of 70 [IQR: 64-76] years, 42% were female and 60% were AD-positive. Diagnostic performance was statistically similar across all pTau217 assays (range: 0.88-0.89 area under the receiver operating characteristic curve [AUC]) with the pTau181 assay having lower accuracy (AUC = 0.85). All assays were resistant to hemolysis, icterus, and lipemia. Automated assays (Roche, Fujirebio) showed superior analytical precision and freeze/thaw stability ([&ge;]6 cycles) compared to the manual MSD assay (2 cycles). Given that plasma pTau217 assays demonstrated high and comparable accuracy in this head-to-head comparison, their differences in analytical performance characteristics and general clinical laboratory suitability became the differentiating factors for clinical implementation.

Background: Non-invasive diagnosis, reliable recurrence surveillance remain critical unmet needs in gliomas. Glioma induces profound systemic immune alterations despite its anatomical confinement to the central nervous system. Circulating immune cells, particularly monocytes, are key mediators of tumor-host crosstalk and may retain tumor-induced transcriptional imprints. However, their potential clinical utility as blood-based biomarkers for detection and monitoring, remain largely unexplored. Methods and findings: In this study, we performed integrated single-cell RNA sequencing of blood immune cells and demonstrated that circulating CD14+ monocytes are significantly expanded in glioma patients, exhibiting features of differentiation arrest and increased transcriptional plasticity. These cells harbor glioma-specific molecular signatures distinct from those observed in healthy controls and patients with other tumors. Leveraging these findings, we developed an ensemble machine learning diagnostic model based on transcriptomic profiles of circulating CD14+ monocytes (training cohort, n=107), which achieved a mean area under the receiver operating characteristic curve (AUC) of 0.971 during cross-validation. In an independent cohort of 567 participants, the model maintained high diagnostic accuracy, yielding an AUC of 0.877 for distinguishing glioma from controls and other tumors. And it achieved a recurrence detection AUC of 0.969 in 51 postoperative samples. Moreover, in a prospective follow-up study involving 30 glioma patients, lower model-derived scores of postoperation were significantly associated with prolonged progression-free survival (log-rank test, P=0.043), supporting its prognostic utility. Conclusion: We demonstrate circulating CD14+ monocytes undergo glioma-specific transcriptional reprogramming, generating systemic tumor-associated signal captured via transcriptomic profiling. This blood-based diagnostic model provides non-invasive, scalable approach for glioma detection, recurrence surveillance, outcome prediction.

Background: Reliable biomarkers for Parkinson's disease (PD) pathology detection are essential for research. The alpha-synuclein (aSyn) seed amplification assay (SAA) is a validated biomarker for misfolded aSyn. Objectives: To assess the association between aSyn SAA and LRRK2-related PD (LRRK2-PD) and its link to mitochondrial genetic burden. Methods: We included N=76 LRRK2 p.Gly2019Ser variant carriers (N=22 affected, N=54 unaffected), N=714 patients with idiopathic PD (iPD), and N=411 controls from Norway. We analyzed cerebrospinal fluid (CSF)-based aSyn SAA in N=10 PD patients and N=30 unaffected LRRK2 p.Gly2019Ser carriers, alongside N=6 controls and N=56 iPD patients. A mitochondrial polygenic score (MGS) was derived from genotyping data, using PPMI as an additional cohort (iPD: N=355, LRRK2-PD: N=118). Results: Seeding was observed in 80% of patients with LRRK2-PD, and in one unaffected variant carrier (AUC=0.97, CI 0.92-1.00). In a meta-analysis across two PD cohorts, higher MGS was associated with increased aSyn seeding (pooled beta=0.38, p=0.028). Conclusions: CSF-based aSyn SAA can discriminate between LRRK2-PD and unaffected carriers. Our findings support an association with mitochondrial burden and aSyn seeding.

Guillain-Barre syndrome is an acute immune-mediated polyradiculoneuropathy with heterogeneous outcomes and limited molecular biomarkers for diagnosis, disease monitoring, and prognosis. To elucidate the circulating proteomic profile of this disorder and identify candidate biomarkers associated with disease activity and recovery, we measured over 6,500 proteins using an aptamer-based proteomic platform. We analysed paired, longitudinal sera from 20 patients at disease onset and one-year follow-up, alongside 15 healthy controls. Unbiased differential protein abundance and gene-set enrichment analyses were performed. Candidate proteins were validated using conventional immunoassays in a cohort including healthy and disease controls. We identified 39 differentially abundant proteins between the acute and recovery phases and 248 proteins altered in acute Guillain-Barre syndrome compared to controls. The acute phase was characterised by a marked enrichment in systemic immune cascades and muscle sarcomere proteins, alongside a significant depletion of axonal adhesion molecules. Serum amyloid A1 (SAA1) emerged as the most strongly increased protein in the acute phase. Validation through independent immunoassays confirmed robust serum amyloid A elevations at disease onset relative to the one-year recovery phase, healthy controls, and relevant post-infectious and neuromuscular disease controls (acute disseminated encephalomyelitis and myasthenia gravis), underscoring a peripheral nerve-specific inflammatory response. Furthermore, unexpected elevations of cardiac troponin T (cTnT) were observed at disease onset. Clinical validation using high-sensitivity assays demonstrated that cTnT exceeded the diagnostic 99th percentile upper reference limit in 25.5% of acute Guillain-Barre syndrome patients. A similarly high frequency of elevation in the myasthenia gravis disease control group (42.1%) suggests these increases predominantly reflect neuromuscular damage rather than myocardial injury. Finally, Mendelian randomisation provided causal genetic evidence linking specific systemic proteins to disease susceptibility, identifying robust roles for SERPING1 (plasma protease C1 inhibitor), CNDP1 (an antioxidant protein), and CRISPLD2 (a lipopolysaccharide-binding protein that regulates endotoxin function). Together, this comprehensive proteomic characterisation reveals distinct, stage-specific molecular signatures in Guillain-Barre syndrome. Importantly, it suggests SAA1 as a robust marker of acute peripheral nerve inflammation and challenges the conventional interpretation of elevated cTnT in severe neuropathies and neuromuscular disorders. Furthermore, this work provides a novel dataset to explore future targeted therapeutic development in Guillain-Barre syndrome.

We investigated whether people with Parkinson's disease who are dual GBA1+LRRK2 carriers have a milder, LRRK2-like phenotype as previously reported. This was accomplished by comparing clinical features and alpha-synuclein seed amplification assay (SAA) positivity rates between dual GBA1+LRRK2-PD(n=13), GBA1-PD(n=169) and LRRK2-PD(n=175) carriers in a cross-sectional retrospective study of Parkinson's Progression Markers Initiative (PPMI) data. Our results show that GBA1+LRRK2-PD rate(83%) is closer to GBA1-PD rate(87%) rather than LRRK2-PD rate (62%mp-value>0.05). GBA1+LRRK2-PD have both non-motor and motor phenotypic similarity of GBA1-PD(p-value>0.05). This small PPMI cohort indicates that dual GBA1+LRRK2-PD carriers' SAA positivity and phenotype are aligned with GBA1-PD.

INTRODUCTION: Synaptic markers are altered in the CSF of Alzheimer's disease (AD) patients, but their quantification in plasma remains challenging. We evaluated plasma synaptic markers in MCI and mild AD using the nucleic acid linked immunosandwich assay (NULISA) and their correlation with APOE genotype. METHODS: 272 participants (154 CSF confirmed AD, 118 controls) underwent plasma assessment with the NULISA CNS panel. A subset (n=48) also had CSF measurements. Analyses were adjusted for age, sex, comorbidity, and renal function. RESULTS: NULISA revealed plasma alterations in NPTX2, NPTXR, SNAP25, and VSNL1 in AD, with SNAP25 and NPTXR already altered at MCI stage. APOE e4/e4 carriers showed higher plasma SNAP25. Plasma SNAP25 and NPTXR correlated positively with pTau217. No plasma/CSF concordance was observed. DISCUSSION: NULISA identifies plasma synaptic biomarker alterations in early AD, with APOE e4 influencing SNAP25 levels. Associations with pTau217 suggest a link between synaptic damage and tau phosphorylation. Longitudinal studies are warranted.

BackgroundPrevious machine learning models to intraoperatively predict the molecular status of gliomas using stimulated Raman histology (SRH), such as DeepGlioma, have achieved high performance (91.5% accuracy) on curated datasets. However, when used intraoperatively, DeepGlioma (162M parameters) runs slowly on current SRH hardware and underperforms due to its lack of an image rejection mechanism and its validation on curated images. Here, we introduce SRH-Informed Glioma classificatioN with Attention Learning (SIGNAL) (27M parameters), a lighter model with a built-in attention-based rejection mechanism that outperforms DeepGlioma on uncurated clinical datasets. MethodsSIGNAL was developed using 1.56 million SRH fields-of-view from 967 adult diffuse glioma patients collected between December 2017 and July 2025. We used 412 patients from NYU for training and internal validation and a multi-institutional, international cohort of 555 patients for testing. SIGNAL uses a ResNet50 backbone pretrained using a hierarchical contrastive loss function followed by a multi-head multi-layer perceptron (MLP). Using a patch-based attention threshold of 0.6, a final MLP was trained to predict glioma subtypes: glioblastoma, oligodendroglioma, or astrocytoma. ResultsSIGNAL outperformed DeepGlioma, achieving greater overall accuracy (90.10% vs. 72.59%) while running faster (16.0 vs. 6.7 patches/s). SIGNAL also outperformed DeepGlioma on all three molecular classification tasks, including IDH mutation (accuracy: 93.51% vs. 79.22%), 1p19q codeletion (93.51% vs. 88.31%), and ATRX loss (89.61% vs. 83.98%). SIGNALs attention mechanism had a strong positive linear correlation with mean patch cellularity (r=0.96, p<0.001) and a strong negative correlation with patch blood coverage (r=-0.99,p<0.001). Finally, subtype and molecular accuracy between tumor core and margin samples were equivalent despite significantly lower patch retention in tumor margins (44.5% vs 60.2%, p<0.0001). ConclusionSIGNAL is a lightweight model for intraoperative molecular classification of gliomas using SRH imaging. Its attention-based image quality filter allows for excellent performance, quick processing, and highly interpretable outputs critical for reliable use in intraoperative workflows. Brief 1-2 Sentence DescriptionWe present SIGNAL, a lightweight machine learning model for intraoperative molecular classification of diffuse gliomas using stimulated Raman histology, whose core innovation is a learned attention mechanism that filters diagnostically uninformative tissue, such as blood and acellular regions, before classification, enabling robust real-world generalizability. Validated on 555 patients across four international centers, SIGNAL outperforms the previous state-of-the-art model DeepGlioma on glioma subtype classification (90.10% vs. 72.59% accuracy) while running 2.4 times faster on intraoperative hardware.