Neuropathology and Applied Neurobiology

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.

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.

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.

BACKGROUND: Dementia with Lewy bodies shares clinical and pathological features with both Parkinson's disease and Alzheimer's disease, but the local biological factors that render specific cortical regions vulnerable to atrophy remain poorly defined. In particular, it is unclear whether cortical thinning in dementia with Lewy bodies reflects generic neurodegenerative mechanisms, processes shared with Parkinson's disease and Alzheimer's disease, or dementia with Lewy bodies-specific molecular and network susceptibilities. METHODS: A total of 89 patients with dementia with Lewy bodies and 89 matched controls underwent T1-weighted brain MRI. Scans were processed to generate surface-based cortical thickness maps. Regional cortical thickness estimates, after slice-by-slice manual correction, were mapped to gene expression data from healthy postmortem human brains to identify transcriptomic signatures associated with decreased thickness in dementia with Lewy bodies. We assessed whether genes whose expression was increased with regional thinning converged onto established Parkinson's disease- and Alzheimer's disease-related pathways and isolated genes uniquely implicated in dementia with Lewy bodies. Spatial annotation mapping was then used to test whether patterns of cortical thinning overlapped with in vivo neurotransmitter system distributions and whether the observed thickness pattern was constrained by large-scale structural connectivity, consistent with a network-based propagation process. RESULTS: Cortical thinning predominated in regions that, in the healthy brain, show higher expression of genes involved in mitochondrial function and synaptic transmission. The transcriptomic profile associated with thinning significantly overlapped with genes belonging to Parkinson's disease and Alzheimer's disease pathways, supporting shared pathogenic mechanisms across Lewy body and Alzheimer-type neurodegeneration. However, 90 genes associated with cortical thinning did not overlap with Parkinson's disease or Alzheimer's disease pathways and were enriched for GABAergic signalling. Spatial mapping analyses showed that regions with greatest thickness reductions colocalized with GABAA, serotoninergic 5-HT1A, 5-HT1B, 5-HT4, and dopaminergic D2 receptor distributions, and that the thickness pattern followed structural connectivity. CONCLUSIONS: MRI-derived cortical thickness changes in dementia with Lewy bodies reflect selective molecular and network vulnerabilities rather than a non-specific degenerative process. Mitochondrial and synaptic genes, together with a distinct GABAergic association and connectivity constraints, delineate mechanisms explaining why some cortical territories are more affected in dementia with Lewy bodies.

Background: Frontotemporal dementia (FTD) lacks widely accessible disease-specific biomarkers. Optical coherence tomography (OCT) and OCT angiography (OCTA) may provide non-invasive measures of retinal changes associated with neurodegeneration. We conducted a systematic review and meta-analysis evaluating retinal biomarkers in FTD compared with Alzheimer disease (AD) and controls. Methods: A systematic search of PubMed and Embase was conducted through April 25, 2026 according to PRISMA guidelines. Studies evaluating OCT/OCTA biomarkers in FTD with comparator groups were included. Inverse weighted random-effects models, publication bias assessments, and meta-regressions were performed. Results: Ten studies involving 139 individuals with FTD, 87 with AD, 29 with mild cognitive impairment, 14 with TDP-43 proteinopathy, 5 with tauopathy, and 255 controls were included in the systematic review; five studies were eligible for meta-analysis. Compared with AD, individuals with FTD demonstrated significantly thinner retinal nerve fiber layer (RNFL) thickness (SMD = -0.61, 95% CI -0.98, -0.24). Compared with controls, individuals with FTD exhibited significantly thinner ganglion cell layer-inner plexiform layer (GCL-IPL) thickness (SMD = -0.55, 95% CI -1.02, -0.08), whereas pooled analyses across multiple retinal biomarkers were non-significant (SMD = -0.19, 95% CI -0.52, 0.14). RNFL thickness correlated negatively with female % in FTD and positively with age in both AD and controls. Conclusions: Individuals with FTD exhibit lower RNFL thickness than AD and lower GCL-IPL thickness than controls, suggesting retinal alterations may reflect neurodegeneration. However, larger longitudinal studies with standardized OCT/OCTA protocols are needed to determine the diagnostic and prognostic utility of retinal biomarkers in FTD

Background: Extent of resection remains central to meningioma management, yet Simpson grading is subjective and may not reflect measurable postoperative residual disease. We compared surgeon-reported Simpson grade, report-derived radiological grading, and residual tumour volumetry across a multicentre cohort. Methods: We performed a retrospective study across two tertiary neurosciences centres comprising four hospitals, including patients undergoing primary cranial meningioma resection from 2006 to 2025. Postoperative magnetic resonance imaging (MRI) reports were harmonised using weakly supervised natural language processing based on term frequency-inverse document frequency (TF-IDF) and a linear support vector machine classifier. Residual tumour volume was segmented from contrast-enhanced postoperative MRI and log-transformed. Concordance between Simpson and radiological gross-total/subtotal resection classification was assessed using absolute agreement and prevalence-adjusted bias-adjusted kappa (PABAK). Cox models assessed recurrence-free survival, with bootstrap validation and anatomical and scan-timing sensitivity analyses. Results: Among 912 patients, recurrence or residual progression occurred in 281. Surgical-radiological agreement was substantial but imperfect (absolute agreement 74%; PABAK 0.61), with lower agreement in skull-base and parafalcine-parasagittal tumours. In adjusted models, recurrence hazard increased with Simpson grade (hazard ratio 1.54, 95% confidence interval 1.37-1.72), radiological grade (1.92, 1.68-2.20), and log-transformed residual volume (1.20, 1.16-1.24; all p<0.0005). Optimism corrected concordance increased from Simpson grade to radiological grade and log-volumetry (0.692, 0.733, and 0.748), with this ranking preserved across sensitivity analyses. Conclusions: Imaging-based postoperative residual disease measures outperformed Simpson grade. TF-IDF-assisted report-derived grading provides a scalable bridge to volumetry, while quantitative residual volume offers the strongest prognostic representation.

Introduction: Incomplete recovery from relapses contributes to long-term disability accumulation in relapsing remitting multiple sclerosis (RRMS), yet the relationship between immune regulation and relapse recovery remains poorly defined. Objective: To longitudinally characterize regulatory/effector immune cell dynamics in untreated RRMS patients and assess their association with immune balance and relapse recovery. Methods: Monocytic myeloid-derived suppressor cells (M MDSCs), regulatory T cells (Treg), and effector CD4 T cell subsets were measured in blood from 69 untreated RRMS patients sampled during relapse or remission and reevaluated after 12 months. Associations with clinical recovery after relapse were examined. Results: During relapse, patients exhibited higher M MDSC and Treg frequencies than in remission, while effector T cell subsets remained unchanged. Over one year, M-MDSCs increased consistently regardless of baseline clinical status, whereas Treg frequencies remained stable. Effector to M MDSC ratios were markedly elevated during relapse and declined over time, while effector-to-Treg ratios showed minimal variation. M MDSC levels during relapse were associated with sustained regulatory features at 12 month follow up. Importantly, higher baseline M MDSC levels, but not Treg frequencies, were associated with complete relapse recovery at one year. Conclusion: These findings suggest that circulating M-MDSCs, but not Treg, reflect interindividual differences in immune regulation and clinical recovery after relapse in early RRMS.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease affecting more than 450,000 individuals worldwide and is frequently diagnosed more than 12 months after symptom onset, delaying intervention during a critical early window. Because up to 80% of patients develop dysarthria within two years, subtle changes in speech provide a signal of early bulbar motor neuron degeneration. However, existing speech-based systems rely on supervised classification trained on limited datasets, achieving moderate sensitivity and depending heavily on labeled disease examples, which restrict scalability and early detection. This study introduces SPEAK-NORM, the first-ever normative speech modeling framework for early ALS diagnosis, which learns age- and sex-conditioned motor-speech distributions exclusively from healthy individuals. A conditional variational autoencoder models coordination of hypoglossal, laryngeal, and respiratory motor pathways, and deviation from this healthy manifold is quantified through latent representations and reconstruction error to form a 354-dimensional profile. A calibrated linear Support Vector Machine performs subject-level classification under subject-disjoint validation. On the VOC-ALS database (n = 153), SPEAK-NORM achieves 98% accuracy with balanced sensitivity and specificity, significantly outperforming established clinical acoustic indices and prior systems. The framework maintains strong performance under cross-task generalization and when retrained on healthy controls in independent dementia and Parkinson disease cohorts, demonstrating disease-specific deviation patterns rather than generic neurodegenerative change. Spectral, temporal, and latent separations further support interpretability. By modeling healthy speech instead of memorizing disease examples, SPEAK-NORM enables scalable early neuromotor screening using recording devices, with potential to support earlier diagnosis, differential classification, and monitoring of ALS progression.

Blood biomarker models are increasingly used in Alzheimer's disease and related dementia translational research, but predictive performance can be inflated when the same dataset is used for both model development and evaluation. We assess the effect of data double dipping using simulations and NULISA proteomic data from the MYHAT-NI community-based cohort to predict brain amyloid-beta neuroimaging status. In both settings, training AUC increased as more biomarkers were added, while testing AUC peaked earlier and then declined. These findings show that data double dipping can inflate model performance and highlight the need for external validation or internal validation with data partitioning.

Background: Progressive multiple sclerosis (MS) is characterized by ongoing neurodegeneration and limited therapeutic options. Circulating metabolites provide insight into disease biology, yet biomarkers that predict disability progression and reflect treatment response are lacking. We aimed to identify metabolomic signatures associated with longitudinal MRI measures of brain atrophy and to evaluate whether ibudilast treatment was associated with metabolite trajectories over time. Methods: We repeatedly profiled 1,726 plasma metabolites using untargeted UPLC-MS/MS in 244 participants from the 96-week SPRINT-MS randomized trial of oral ibudilast, up to 100 mg daily, versus placebo. Weighted gene co-expression network analysis was used to derive groups of related metabolites. Associations between baseline metabolite groups and longitudinal MRI outcomes were evaluated using linear mixed-effects models adjusted for demographic, clinical, and treatment covariates. The primary outcome was the rate of whole-brain atrophy measured by brain parenchymal fraction (BPF), defined as the proportion of intracranial volume occupied by brain tissue. Secondary outcomes included white matter fraction (WMF), gray matter fraction (GMF), and cortical thickness (CTH). Metabolite groups nominally associated with MRI outcomes, defined as p < 0.05, were followed by individual metabolite analyses to identify potential drivers. Significant metabolites were tested for replication in a comparable real-world observational HEAL-MS cohort with longitudinal MRI data. Lastly, we tested whether ibudilast treatment was associated with metabolite trajectories and performed metabolite set enrichment analysis. Findings: Higher baseline levels of glycerophospholipids were associated with slower decline in both BPF and WMF, and sphingomyelins were similarly associated with slower BPF decline. For example, higher 1-palmityl-2-stearoyl-GPC (O-16:0/18:0) levels were associated with slower BPF decline in SPRINT-MS (beta = 0.016 [95% CI: 0.008, 0.024]; p = 4.35 x 10^-5) and replicated in HEAL-MS (beta = 0.108 [95% CI: 0.006, 0.211]; p = 3.90 x 10^-2). Metabolites associated with GMF preservation were enriched in androgenic steroids and steroid sulfates, with consistent positive associations observed in the replication cohort, whereas metabolites inversely associated with CTH were predominantly xenobiotic-related. Ibudilast treatment was associated with increased sphingomyelin species, such as palmitoyl sphingomyelin (d18:1/16:0; beta = 0.185 [95% CI: 0.085, 0.286]; FDR = 1.79 x 10^-2), and decreased levels of amino acid-related metabolites, such as anthranilate (beta = -0.270 [95% CI: -0.403, -0.137]; FDR = 3.87 x 10^-2). Pathway-based analyses corroborated these findings, highlighting glycerophospholipid and sphingolipid metabolism as key pathways implicated in brain atrophy in MS. Interpretation: Distinct lipid subsets were associated with slower brain atrophy in people with MS, and ibudilast treatment was associated with metabolite alterations in potentially neuroprotective directions. Metabolomics may provide prognostic and pharmacodynamic biomarkers for progressive MS.

ABSTRACT INTRODUCTION: Microscopic fractional anisotropy ({micro}FA), an emerging diffusion MRI metric, may be more sensitive than conventional metrics to gray matter microstructural changes in neurodegeneration. This pilot study compared {micro}FA, mean diffusivity (MD), and volume between genetic frontotemporal dementia (FTD) variant carriers and non-carriers in the insula, frontal pole, and medial orbitofrontal cortex (mOFC). METHODS: Carriers and familial non-carriers of FTD variants in C9orf72, GRN, or MAPT were scanned between October 2024-December 2025. Non-parametric aligned rank transform ANCOVAs were computed to analyze between-group differences in {micro}FA, MD, and volume while controlling for age. RESULTS: Carriers (n=12) exhibited lower insula {micro}FA than non-carriers (n=8): F(1,19)=5.89, 95% CI [-10.7,-0.75], p=0.027, 2p=0.26. No group-differences were observed in other metrics, including MD and volume. DISCUSSION: Reduced {micro}FA in the insula, a region vulnerable to early atrophy in FTD, may be more sensitive to early microstructural changes in genetic FTD than traditional diffusivity measures.

The course of multiple sclerosis (MS) is highly heterogeneous, yet the biological mechanisms underlying this variability remain incompletely understood. Although metabolic alterations have increasingly been associated with disease progression, existing observational evidence is limited by confounding, reverse causation, and an inability to establish causal mechanisms. To bridge this gap, we used a metabolome-wide Mendelian Randomization (MR) framework, including thorough sensitivity analyses, to identify metabolites genetically linked to MS severity that can causally affect it. Bidirectional MR analyses revealed a subset of amino acid and lipid pathways with strong, consistent effects across different MR approaches, confirmed by tests for heterogeneity, horizontal pleiotropy, and LD confounding. For metabolites prioritized by metabolome-wide MR with evidence of causal effects, we conducted genetic colocalization at loci encompassing proximal enzyme-encoding genes, leveraging the corresponding instrumental variants to assess shared underlying genetic signals. This process revealed shared genetic signals between metabolite levels and MS severity, mapped to the FADS1/2 and CYP4F2 loci. A subsequent pathway-resolved set of cis-MR analyses across FADS1/2-derived polyunsaturated fatty acid (PUFA) metabolites, using a functional variant that proxies reduced {triangleup}5-desaturase activity, showed consistent effects indicating that FADS1 perturbation is associated with MS severity. Collectively, these results highlight FADS1 as a key driver of PUFA-related causal effects on MS severity in both systemic (circulating metabolites) and brain cell-specific contexts. Additional supportive cis-MR evidence implicates the disruption of CYP4F2 as another PUFA-metabolizing enzyme.

Objective Astrocyte activation is increasingly recognized as an important component of multiple sclerosis (MS) pathology. Natalizumab (NTZ), a highly effective therapy for relapsing-remitting MS (RRMS), primarily blocks leukocyte trafficking into the central nervous system. However, its effects on astrocytic metabolism remain unclear. We investigated astrocyte-associated metabolic changes after NTZ treatment using quantitative 1-11C-acetate positron emission tomography (PET). Methods Seven patients with RRMS underwent quantitative 1-11C-acetate PET before and after NTZ treatment. PET-derived k2, an index of oxidative acetate metabolism, was analyzed voxel-wise and within GM and white-matter volumes of interest. Clinical status and brain magnetic resonance imaging (MRI) findings were assessed, and cognitive performance was evaluated using Rao's Brief Repeatable Battery of Neuropsychological Tests. Results After NTZ treatment, k2 decreased in all patients compared with pretreatment levels. Both gray and white matter showed significant reductions, and voxel-based analysis demonstrated widespread decreases across cortical and subcortical regions of the cerebrum and cerebellum, with no regions showing significant posttreatment increases. MRI showed no worsening; Expanded Disability Status Scale scores were stable or improved, and cognitive performance was generally stable, with improvements in selected subtests. Interpretation Quantitative 1-11C-acetate PET demonstrated a whole-brain reduction in astrocyte-associated metabolism after NTZ treatment in RRMS, most prominently in gray matter. NTZ may modulate astrocyte activity, in addition to its established effects on peripheral immune cell trafficking.

Objectives: X-linked dystonia-parkinsonism is a neurodegenerative movement disorder with predominant striatal pathology in affected males, who frequently show hyperechogenicity of the lentiform nucleus on transcranial sonography. We aim to investigate female mutation carriers and female healthy controls using transcranial sonography to identify potential abnormalities in the striatum, substantia nigra, and ventricular system. Methods: We examined 81 participants (35 female mutation carriers and 46 female controls) using transcranial sonography to assess the presence of hyperechogenicity of the lentiform nucleus, the area of substantia nigra hyperechogenicity, and the widths of the lateral and third ventricles. Clinical evaluation focused on dystonic and parkinsonian symptoms, and we determined genotypes relevant for four X-linked dystonia-parkinsonism genetic modifiers. Results: Female mutation carriers showed more subtle parkinsonian signs compared with controls. The prevalence of hyperechogenicity of the lentiform nucleus was higher in female mutation carriers and was associated with a more unfavorable genetic modifier profile. No relevant abnormalities were observed in the substantia nigra or the ventricular system. Imbalanced X-chromosome inactivation in favor of the wildtype allele expression was not significantly associated with clinical severity or hyperechogenicity of the lentiform nucleus frequency, although female mutation carriers with such an imbalance showed no parkinsonian signs and only rarely hyperechogenicity of the lentiform nucleus (1/8, 13%). Conclusions: Women carrying the X-linked dystonia-parkinsonism-causing variant display subtle parkinsonian signs and frequently exhibit hyperechogenicity of the lentiform nucleus, supporting hyperechogenicity of the lentiform nucleus as a sensitive imaging marker of early neurodegenerative change, especially in those with higher genetic risk.

Objective Memory impairment is a frequent comorbidity of focal epilepsy, incompletely explained by seizure frequency or structural pathology. Ictal and postictal hippocampal dysfunction disrupt memory processes, but their cumulative impact remains poorly quantified. This study introduces cumulative hippocampal seizure-related burden metrics and examines their association with long-term memory consolidation. Methods Twenty consecutive patients undergoing stereo-EEG in Marseille (2016-2018) were prospectively included. Continuous stereo-EEG recordings between two memory assessments (30 minutes and one week post-encoding) were analysed. Hippocampal ictal involvement and durations were assessed using epileptogenicity markers and visual stereo-EEG analysis. The postictal period was quantified using permutation entropy. Cumulative hippocampal seizure-related burden metrics (ictal, postictal and combined: c-HipSZB) were computed across hippocampus-involving ictal events. Verbal and visual memory were assessed using standardized recall and recognition tasks. Associations were examined using univariate and multivariate analyses. Results Higher dominant-hemisphere hippocampal burden was associated with poorer one-week verbal memory (performance and retention), independently of most covariates. Higher c-HipSZB was associated with lower total recall performance (RT; free + cued) and RT retention ({beta} = -25.04 and -23.88; R2 = 0.57 and 0.53; p < 0.05) and accounted for the greatest variance in both outcomes (adjusted R2= 0.59 and 0.53; {beta} = -25.45 and -24.27; p < 0.01), particularly when adjusting for epilepsy duration. No robust associations were observed between non-dominant-hemisphere hippocampal seizure-related burden metrics and visual memory. Effects predominantly involved recall. Interpretation Cumulative ictal-postictal hippocampal dysfunction is a major determinant of impaired long-term verbal memory consolidation in focal epilepsy.

Objectives. Despite the body of literature on genetic risk factors for dementia, little is known on protective genetic factors associated with favourable cognitive ageing in the oldest population. In Europe, Italy has a leading position with a swelling population of centenarians, and the urban area of Genoa in the Liguria region has one of the highest prevalence of centenarians. The COOL study is a not-for-profit, multicentric study involving a cohort of centenarians (aged >99) living in the Genoa area. The ultimate aim is the identification of genomic biomarkers associated with cognition in the oldest old population. Results. Participants underwent a semi-structured interview on personal, disease and family history, and a neuropsychological assessment of the main cognitive domains. As of July 2025, we enrolled 88 centenarians (age range: 99-108, median 100.56) with and without cognitive impairment; 32 subjects were followed up. All participants were of Italian ancestry, 81% were female. The cognitive profile in assessed subjects showed a wide range of cognitive health measures (CDR 0-5; MMSE 3-30, median 24). Whole peripheral blood and DNA samples from 67 participants were stored. Conclusions. We demonstrated that the protocol is feasible, and acceptable by participants and their families. A comprehensive phenotype dataset was established, and DNA samples were stored. Centenarians exhibited a broad spectrum of cognitive profiles, from preserved cognition to severe dementia. These findings will eventually allow to interpret the profiles of genomic variants as associated with variability of cognitive performance in centenarians. The molecular underpinnings of healthy cognitive ageing could inform health policy strategies in the general population.

Although the associations between cerebrovascular dysfunctions and Alzheimer's disease are increasingly appreciated, the relationship of cerebral blood flow and white matter hyperintensities with tau and amyloid-{beta} pathology remains unclear, particularly in the longitudinal context. This study investigated cross-sectional and longitudinal associations of cerebral blood flow and white matter hyperintensities with tau and amyloid-{beta} pathology using multimodal imaging and blood biomarkers in 179 participants from the ADNI3 cohort. Participants underwent structural (T1-weighted, T2-weighted FLAIR) and arterial spin labelling perfusion MRI, tau and amyloid-{beta} PET, and plasma assay tests for amyloid-{beta} 42, amyloid-{beta} 40, and phosphorylated tau-217. Tau from PET was negatively associated with cerebral blood flow both cross-sectionally and longitudinally in the posterior brain, independent of amyloid-{beta} quantified from PET. Higher white matter hyperintensities volumes were associated with higher levels of tau and amyloid-{beta} at baseline, but the associations were significantly attenuated after further adjusting for amyloid-{beta} and tau, respectively. Plasma amyloid-{beta} 42/40 ratio was negatively associated with white matter hyperintensity volumes both cross-sectionally and longitudinally. In conclusion, tau pathology showed spatially specific associations with cerebral hypoperfusion, independent of amyloid-{beta}, particularly in posterior regions. The attenuation of associations of white matter hyperintensities with amyloid-{beta} and tau after adjustment may reflect shared disease-related variance rather than distinct independent effects. Keywords: Alzheimer's disease, Cerebral blood flow, White matter hyperintensities, Tau pathology, Amyloid-{beta}.

Background Neuropsychiatric fluctuations in Parkinson's disease (PD) often accompany motor fluctuations, but their temporal relationship during the acute levodopa response remains unclear. Objectives To determine whether motor and neuropsychiatric responses occur synchronously during the OFF-to-ON transition. Methods Nineteen fluctuating PD patients underwent a high-resolution levodopa challenge with repeated assessments every 10 minutes for 60 minutes after levodopa administration. Motor symptoms (akinesia, rigidity) and neuropsychiatric fluctuations were quantified. Transition times (t25%-t50%-t75%-t100%) and response profiles were analyzed using correlation and clustering approaches. Results Motor and neuropsychiatric transition times were not correlated at any threshold (all FDR-corrected p>0.05; Bayes factors <1), supporting temporal dissociation. Among 18 patients with complete data, clustering revealed synchronous (6/18), neuropsychiatric-preceding (7/18), and motor-preceding (3/18) profiles. Conclusion Motor and neuropsychiatric responses to levodopa during PD fluctuations are partly independent and follow heterogeneous, patient-specific temporal profiles, supporting the search for distinct biomarkers and future individualized adaptative therapies

Wolfram syndrome (WFS) is characterized by youth-onset insulin-dependent diabetes and neurological deficits. Brain white matter deficiency has been reported, but its trajectory remains unclear. Applying diffusion basis spectrum imaging models longitudinally in 29 individuals with WFS (baseline ages, 5.2 to 25.8 years; maximum 7 visits) and 52 matched controls, we found that WFS is associated with microstructural alterations suggesting diminished axonal integrity, myelin content, and cellularity. These changes were present and stable early in the disease progression in visual and auditory-related regions, whereas abnormalities in the corpus callosum appeared later in adolescence and adulthood. Our results support developmental hypomyelination as a neurophenotype of WFS.