Importance:Blood-based biomarkers for Alzheimer disease, particularly plasma phosphorylated tau 217 (p-tau217), accurately reflect early Alzheimer disease brain pathology in cognitively unimpaired individuals, but estimates of absolute risk of progression to cognitive impairment across multiple cohorts are needed. Objective:To estimate absolute risk of progression to cognitive impairment and rates of cognitive decline based on plasma p-tau217 across cognitively unimpaired older adults. Design, Setting, and Participants:Longitudinal cohort study using harmonized data from 2684 cognitively unimpaired older adults (defined within cohort) across 6 observational and clinical trial cohorts based in North America, Japan, and Australia. The earliest enrollment was in 2004, with most recent follow-up in 2025. Exposure:Baseline plasma p-tau217. Main Outcomes and Measures:The primary outcome was time to progression to cognitive impairment (mild cognitive impairment, dementia, or 2 consecutive global Clinical Dementia Rating scores ≥0.5). The secondary outcome was longitudinal change on the latent Preclinical Alzheimer Cognitive Composite (PACC; higher values indicate better performance). Results:Among the 2684 participants (median [IQR] age, 69.6 [66.2-74.2] years; 1697 [63%] female), there were 478 events of progression to cognitive impairment over a median follow-up of 5.4 years (maximum follow-up of 13.5 years). Each 1-SD increase in baseline p-tau217 level was associated with an increased risk of progression to cognitive impairment (hazard ratio, 1.38 [95% CI, 1.30-1.46]), and the association remained significant after adjustment, including β-amyloid positron emission tomography scan Centiloids (hazard ratio, 1.32 [95% CI, 1.24-1.41]). Participants with high (1.1-2.4 SD) and very high (>2.5 SD) baseline p-tau217 had 24% (95% CI, 20%-28%) and 38% (95% CI, 33%-43%) absolute risk of progression over 5 years, respectively, and risk was markedly higher over 10 years, although longer-term estimates were constrained by limited data. Elevated p-tau217 was also associated with faster cognitive decline based on change in latent PACC score. Among the overall sample, baseline latent PACC scores ranged from -0.8 to 2.7. The 5-year annualized decline for the very high p-tau217 group was -0.07 latent PACC units/y (95% CI, -0.10 to -0.05), relative to 0.03 units/y (95% CI, 0.02-0.04) in the low p-tau217 group. Conclusions and Relevance:In a pooled sample of multiple selected cohorts of cognitively unimpaired older adults, higher plasma p-tau217 levels were consistently associated with increased risk of clinical progression and accelerated cognitive decline. By providing time-specific absolute risk estimates, these findings support the potential of p-tau217 for prognostic model development, with direct implications for future trial design. Further validation in unselected populations is needed to inform individual prognosis and clinical decision-making in cognitively unimpaired individuals.

Plasma p-tau217 closely tracks amyloid-β (Aβ) pathology, yet its ability to predict long-term clinical progression in cognitively unimpaired (CU) adults remains uncertain. We analyzed harmonized data from 2,705 CU participants (Agemean=69.8±7years; Female=63%) across six longitudinal cohorts with up to 13.5 years of follow-up. Cox models evaluated associations between p-tau217 and progression to a clinical diagnosis of cognitive impairment, while natural cubic spline models assessed associations with longitudinal decline on a cognitive composite. Higher p-tau217 was associated with increased risk of progression (hazard-ratio[HR]=1.38; 95%CI:1.31-1.44), independent of demographics and APOEε4, and in models with Aβ-PET (HR=1.30; 95%CI:1.23-1.38). Very high p-tau217 levels (>2.5SD) were associated with 61%[95%CI:53-68%] absolute risk of progression over 10 years. Elevated p-tau217 associated with accelerated cognitive decline, both independent of, and synergistic with, greater Aβ-PET. These findings establish plasma p-tau217 as a robust prognostic marker in preclinical AD and support its value in future individualized risk prediction.

Importance:Among individuals with high levels of amyloid-β (Aβ), women exhibit higher insoluble tau burden and accumulation than age-matched men. It remains unclear whether this sex difference is influenced by soluble phosphorylated tau (p-tau), a biomarker that changes early in Alzheimer disease. Objective:To investigate whether sex and aggregated Aβ synergistically predict plasma phosphorylated tau 217 (p-tau217) levels and whether levels of p-tau217 predict cross-sectional and longitudinal tau aggregation in a sex-specific manner (as measured by positron emission tomography [PET]). Design, Setting, and Participants:This longitudinal study analyzed data between September 7, 2024, and October 29, 2025, from 1 clinical trial cohort and 4 observational study cohorts including men and women without cognitive impairment who had undergone multiple assessments via tau PET (18F-flortaucipir or 18F-MK-6240) and plasma p-tau217 assay at baseline. Cognitive performance was measured with the Preclinical Alzheimer Cognitive Composite. Data on cognitive performance were available from 3 of the 5 cohorts for a mean of 4.6 years (SD, 3.1 years). Across the 5 cohorts, the mean follow-up for tau PET was 3.6 years (SD, 1.7 years). Exposures:Self-reported sex (male or female), tau PET, and p-tau217 assay. Main Outcomes and Measures:The primary analyses used linear and mixed-effects models to assess baseline and longitudinal sex × p-tau217 interactions for 9 tau PET regions. The secondary analyses assessed sex × p-tau217 interactions for cognitive change using the Preclinical Alzheimer Cognitive Composite. Results:Across the 5 cohorts, there were a total of 1292 participants (63.6% women; mean age, 70.6 [SD, 6.4] years) with tau PET assessments. Compared with men, women had significantly higher baseline p-tau217 levels at higher aggregated Aβ Centiloid levels (β, -0.21 [95% CI, -0.37 to -0.05], P = .009; highest interaction was found in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease/Longitudinal Evaluation of Amyloid Risk and Neurodegeneration [A4/LEARN] cohort). The sex × p-tau217 interactions at baseline were significant for 1 tau PET region in the Harvard Aging Brain Study (HABS) cohort, for 2 tau PET regions in the A4/LEARN cohort, for 6 tau PET regions in the Wisconsin Registry of Alzheimer's Prevention (WRAP) cohort, and for 4 tau PET regions in the Presymptomatic Evaluation of Experimental or Novel Treatments for Alzheimer's Disease (PREVENT-AD) cohort. Longitudinal interactions were significant for 4 tau PET regions in the A4/LEARN cohort, for 5 tau PET regions in both the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort and the WRAP cohort, and for 2 PET regions in both the HABS cohort and the PREVENT-AD cohort. Compared with men, women displayed greater tau deposition and accumulation at higher p-tau217 levels. Use of a secondary model showed women with higher p-tau217 levels also exhibited faster rates of cognitive decline relative to men in the both the WRAP cohort and the ADNI cohort. Conclusion and Relevance:These findings add to growing evidence that women have a differential tau response to Aβ that may emerge at the point of p-tau secretion. These findings have implications for the therapeutics and diagnostics of preclinical Alzheimer disease.

Surface-based cortical analysis is valuable for a variety of neuroimaging tasks, such as spatial normalization, parcellation, and gray matter (GM) thickness estimation. However, most tools for estimating cortical surfaces work exclusively on scans with at least 1 mm isotropic resolution and are tuned to a specific magnetic resonance (MR) contrast, often T1-weighted (T1w). This precludes application using most clinical MR scans, which are very heterogeneous in terms of contrast and resolution. Here, we use synthetic domain-randomized data to train the first neural network for explicit estimation of cortical surfaces from scans of any contrast and resolution, without retraining. Our method deforms a template mesh to the white matter (WM) surface, which guarantees topological correctness. This mesh is further deformed to estimate the GM surface. We compare our method to recon-all-clinical (RAC), an implicit surface reconstruction method which is currently the only other tool capable of processing heterogeneous clinical MR scans, on ADNI and a large clinical dataset (n = 1,332). We show a ∼ 50 https://github.com/simnibs/brainnet .

Longitudinal studies are required to measure individual differences in human brain aging, but are challenging over short intervals due to measurement error. Using cluster scanning, an approach that reduces error by densely repeating rapid structural scans, we assess brain aging in individuals across three timepoints in one year. Cluster scanning substantially improves the precision of individualized estimates, revealing previously undetectable individual differences in brain change. In just one year, we detect expected differences in the rates of brain aging between younger and older individuals, as well as differences between cognitively unimpaired and impaired individuals. Cognitively unimpaired older individuals variably reveal relative brain maintenance, unexpectedly rapid decline, and asymmetrical changes. We observe these atypical brain aging trajectories across structures and verify them in independent within-individual test-retest data. Cluster scanning promises to advance our understanding of the marked heterogeneity in brain aging by affording better short-term tracking of individual variability in structural change.

INTRODUCTION:Alzheimer's disease (AD) biomarkers are assessed on their ability to detect AD pathophysiology in vivo, with confirmation of AD neuropathology only at autopsy. METHODS:Positron emission tomography (PET), plasma, and cognitive AD biomarkers were compared to AD neuropathology in Harvard Aging Brain Study participants (10 cognitively unimpaired; 6 mild cognitive impairment). Different PET methods were evaluated, for example, standardized uptake volume ratio (SUVR), distribution volume ratio (DVR), spatial extent (EXT), and partial-volume correction (PVC). RESULTS:Amyloid beta (Aβ)-PET (11C-Pittsburgh compound B [PiB]), tau-PET (18F-flortaucipir [FTP]), and plasma tau phosphorylated at threonine 217 (p-tau217) correlate with Aβ plaques (A-score), Braak tau neurofibrillary tangle (NFT) stage (B-score), and neuritic plaques (C-score), whereas plasma glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and cognitive measures did not; although digital Clock Drawing Test (dCDT) latency features did, in an exploratory comparison. Correlations were stronger for Aβ-PET DVR and Aβ-PET EXT (than SUVR with/without PVC) and tau-PET SUVR (composite reference and PVC). DISCUSSION:These findings support the innovative use of imaging, plasma, and digital cognitive tools for detecting AD pathophysiology in a largely cognitively unimpaired population. HIGHLIGHTS:Amyloid beta-positron emission tomography (Aβ-PET), tau-PET imaging, and plasma tau phosphorylated at threonine 217 (p-tau217) correlate with ABC scores Correlations were larger for Aβ-PET distribution volume ratio (DVR) and tau-PET standardized uptake volume ratio (SUVR; composite reference, partial volume correction [PVC]) Digital Clock Drawing Test latency features correlate with A- and Cscores Standard cognitive measures mostly did not correlate with ABC scores Plasma glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) biomarkers did not correlate with ABC scores.

Tauopathies encompass diverse neurodegenerative diseases unified by aberrant patterns of tau deposition in brain. Although most appear sporadic, some are linked to genetic etiologies that offer unique mechanistic insights. Here we report that X-linked Dystonia-Parkinsonism (XDP), caused by a non-coding retrotransposon-associated repeat insertion in TAF1 , involves a significant imbalance of tau isoforms and the accumulation of hyperphosphorylated, four-repeat tau in the brain. In striatal tissue, both misfolded tau accumulation, predominantly in astrocytes, and MAPT exon 10 inclusion correlated with repeat length within the causal insertion. Transcriptomic profiling across brain regions revealed dysregulation of known tau-related pathways. Levels of phosphorylated tau181, glial fibrillary acidic protein, and neurofilament light chain were elevated in patient plasma and discriminated XDP from controls. These findings implicate defective tau proteostasis as a key pathogenic mechanism and position XDP as a genetic model for uncovering cellular drivers that may disrupt tau in other more common neurodegenerative diseases.

Alzheimer’s disease (AD) is characterized by amyloid-beta plaques and tau tangles in the brain, but these markers alone do not predict disease progression. The intersection of these pathologies with other processes including metabolic changes may contribute to disease progression. Brain glucose metabolism changes are among the earliest detectable events in AD. Pyruvate kinase (PKM) has been implicated as a potential biomarker to track these metabolic changes. We have developed an enzyme-linked immunosorbent assay (ELISA) to assess PKM levels in cerebrospinal fluid (CSF). First, we verified the relationship of CSF PKM levels with cognitive decline, revealing a correlation between elevated CSF PKM levels and accelerated cognitive decline in preclinical AD patients in a tau-dependent manner. We developed the ELISA using two PKM-specific antibodies and validated it through quality control steps, indicating robust quantification of PKM. We showed that ELISA measurements of PKM correlate with mass spectrometry values in matching samples. When tested on an independent cohort, the assay confirmed elevation of PKM in AD. These findings support the use of PKM as a potential biomarker for tracking early metabolic changes in AD, offering a novel tool for investigating metabolic alterations and their intersection with other underlying pathologies in AD progression.

Over 65 million COVID-19 survivors grapple with lasting neurological and cognitive symptoms that persist for months or years after infection, known as neuro-Post-acute Sequelae of COVID-19 (neuro-PASC). These symptoms are amongst the most common and incapacitating and are hypothesized to represent a heighted risk for neurological disease. Yet, little is known about the pathophysiological mechanisms underlying neuro-PASC. Here, we examined whether worse neuro-cognitive functioning was associated with markers of immune and neural dysfunction. We report data for 55 people with PASC (average age = 46.09) and 37 healthy controls (HC; average age = 42.84). PASC participants were never in the ICU, 68% female sex, and infected an average of 471.27 days pre-enrollment. HCs were 57% female sex and 15 were infected an average of 647.73 days pre-enrollment but fully recovered. We assessed subjective cognitive decline using the Measurement of Everyday Cognition (ECog), memory with the RBANS list learning, and executive functioning with the Trail-Making Test B (TMT-B). PASC participants completed a self-report questionnaire of PASC symptom severity. We measured plasma levels of CX3CL1/Fractalkine, a marker of immune function, and Ubiquitin C-terminal hydrolase-L1 (UCH-L1), a marker of neural function. We conducted t-tests and linear regressions adjusting for age. Neurological symptoms were amongst the most severe. Headaches, insomnia, and brain fog were rated as the ones that interfered the most with daily activities. Compared to HCs, PASC participants reported worse subjective memory, language, planning, organization, and attention decline. There were no significant group differences on cognitive test scores. PASC participants exhibited significantly higher CX3CL1/Fractalkine and UCH-L1, although the latter was not significant when controlling for age. Those with higher levels of CX3CL1 exhibited higher levels of UCH-L1, indicating a relationship between immune and neural dysfunction. Elevated UCH-L1 levels were associated with worse TMT-B performance, but not CX3CL1. Findings show that neurological symptoms, including subjective cognitive decline, are highly prevalent and severe in PASC. There was clear evidence of heightened inflammation potentially from endothelial cells, and of neural injury, which was associated with worse executive functioning. Therefore, immune dysregulation and neural injury may be underlying neuro-PASC, and potentially contributing to greater risk for brain disease.

INTRODUCTION:With the advent of Alzheimer's disease (AD)-modifying and symptomatic treatments of demonstrated efficacy, enrolling participants as concurrent placebo controls in trials can become increasingly difficult. Synthetic controls have been proposed as a viable alternative to concurrent control groups, but their feasibility and reliability remain untested in AD studies. METHODS:I-CONECT trial, which evaluates conversational interactions on cognition, was used to test synthetic control methods. Data from the National Alzheimer's Coordinating Center-Uniform Data Set was used to create synthetic-controls for I-CONECT participants using two methods: 1) case mapping and 2) case modeling. Efficacy estimates were compared between original versus synthetic-controlled trials. RESULTS:In parallel-group designs, treatment effect sizes for the primary outcome were closely aligned between the original trial (β = 1.67) and synthetic control analyses (β = 1.40-1.65). For n-of-1 designs, the two methods showed high agreement in identifying treatment responders (Kappa = 0.75-0.82). DISCUSSION:Synthetic control methods are feasible and reliable to create alternative controls in AD studies. CLINICAL TRIAL REGISTRATION:NCT02871921. HIGHLIGHTS:Synthetic control methods are feasible and suitable for evaluating treatment effects in various trial designs such as n-of-1, single-arm, and parallel groups. Synthetic control methods can help replicate early-phase Alzheimer's trials, informing go/no-go decisions for larger-scale studies. The choice of similarity algorithms is critical as it affects the quality of historical case mapping. The National Alzheimer's Coordinating Center-Uniform Data Set (NACC-UDS) provided an ideal pool for identifying historical cases with similar demographic, biological, and social characteristics to participants in trials, enabling the creation of synthetic control groups for Alzheimer's clinical research.

INTRODUCTION:Neuroinflammation, a key player in Alzheimer's disease (AD) pathogenesis, may be differentially involved in young-onset (YOAD) compared to late-onset (LOAD) AD. METHODS:Using proximity extension assay technology, we examined 737 inflammatory markers in the CSF of 26 healthy controls (63.9 ± 8.7; 12♀), 57 patients with YOAD (60.8 ± 4.9 y/o; 40♀), and 33 with LOAD (76.6 ± 4.5 y/o; 18♀). We also assessed biomarkers of AD pathology (Aβ42, p-tau181, t-tau) and neurodegeneration (neurofilament light-chain [NfL]). RESULTS:Compared to controls, SCRN1 and MMP10 were increased in LOAD and YOAD, but 16 markers showed YOAD-specific increases. Forty-six markers were significantly associated with NfL. P-tau181 and t-tau mediated the association between inflammatory markers and NfL in YOAD. In LOAD we could not identify a direct or indirect relationship between neuroinflammation and neurodegeneration. DISCUSSION:Using a proteomics approach, we observed an exacerbation of neuroinflammatory changes and a differential contribution of neuroinflammation to AD pathology and neurodegeneration in YOAD compared to LOAD. HIGHLIGHTS:Olink's Proximity Extension Assay was used to compare the inflammatory profile of 26 healthy controls and 90 Alzheimer's disease (AD) patients. AD patients were further stratified into young-onset (YOAD, n = 57) and late-onset (LOAD, n = 33) AD. Cerebrospinal fluid (CSF) levels of MMP10 and SCRN1 were increased in both YOAD and LOAD, but 16 proteins were only increased in YOAD. Tau mediated the association between inflammatory markers and neurodegeneration in YOAD. Neuroinflammation may be differentially involved in the pathogenesis of YOAD compared to LOAD.

BACKGROUND:This study explores the potential of developing digital biomarkers from wearables for monitoring individuals with Alzheimer's Disease and Related Dementias, focusing on the feasibility of using Apple Watches for tracking health and behaviors in older adults with cognitive impairment. METHODS:Data collection used the Amissa Health technology stack, which passively collects time-series data from smartwatches and provides a high-frequency cloud database for secure data storage, query, and visualization by clinicians and researchers. The platform consists of (i) AmissaWear, a software app that runs on smartwatches and sends information to a cloud database using a secure API; and (ii) AmissaOrbis, a centralized cloud portal for the collected data. Each participant was provided an Apple Watch configured to collect steps, calories burned, accelerometer and gyroscope readings, heart rate, and sleep information. RESULTS:Seven participants, with cognitive impairment diagnosed by a neurologist, were enrolled in the study from December 2023 through June 2024. The watches successfully collected more than 700 000 observations during the study. Each observation contains data recorded from over a dozen sensors (eg, heart rate, pedometer, gyroscope, and accelerometer). The participants wore Apple Watches for an average of 11.48 hours/day for 84.91% of days during a 6-month period without a decrease in usage over time. Overall, the technology yielded high wear adherence and participation within this pilot. CONCLUSIONS:This study demonstrates the feasibility of using widely available Apple Watches for continuous monitoring of individuals with cognitive impairment and provides insights into their daily health and activity patterns, which could aid in future development of digital biomarkers.

There is an unmet need for reliable biomarkers for amyotrophic lateral sclerosis (ALS). Recent studies have demonstrated that the levels of the microtubule-associated protein tau, are altered in plasma and cerebrospinal fluid (CSF) from people with ALS. Our previous findings demonstrated that while the ratio between tau and phosphorylated tau at T181 (pTau-T181) is decreased, increases in CSF tau correlated with faster disease progression in people with ALS. Here, we measured tau and pTau-T181 in plasma samples from participants with ALS and healthy controls (HC) using two methods (Quanterix Simoa and Meso Scale Discovery, MSD). Using both assays, there was an increase in pTau-T181 levels and in the pTau-T181:tau ratio in ALS compared to HC andlarger increases in pTau-T181 and pTau-T181:tau ratio at baseline correlated with faster ALS progression. Plasma total tau levels were increased in ALS compared to HC on the MSD assay and decreased on Quanterix Simoa assay. Collectively, our results suggest that plasma pTau-T181 levels are increased in ALS. Future studies should aim to clarify its role as a diagnostic or prognostic biomarker for ALS.

The relationship between cerebrospinal fluid (CSF) biomarkers of Alzheimer’s disease and neurodegenerative effects is not fully understood. This study investigates neurodegeneration patterns across CSF Alzheimer’s disease biomarker groups, the association of brain volumes with CSF amyloid and tau status and sex differences in these relationships in a clinical neurology sample. MRI and CSF Alzheimer’s disease biomarkers data were analysed in 306 patients of the Mass General Brigham healthcare system aged 50+ (mean age = 68.4 ± 8.8 years; 43.1% female), who had lumbar punctures within 1 year of clinical MRI scans. We first analysed neurodegeneration patterns across four biomarker groups: 60 controls (A−T−&CU; amyloid negative, tau negative, cognitively unimpaired), 25 A+T− (amyloid positive, tau negative), 121 A+T+ (amyloid positive, tau positive) and 100 other dementia (A−T−&CI; amyloid negative, tau negative, cognitively impaired). Second, we examined volumetric associations with amyloid (amyloid positive, tau negative versus control) and tau in the presence of amyloid (amyloid positive, tau positive versus amyloid positive, tau negative) across 52 brain areas. Third, we examined sex differences in these relationships. Finally, we validated core analyses across three independent datasets—NACC (National Alzheimer’s Coordinating Center), ADNI (Alzheimer’s Disease Neuroimaging Initiative) and EPAD (European Prevention of Alzheimer’s Dementia)—totalling 3137 participants, and performed meta-analyses to obtain more robust estimates. We observed distinct neurodegeneration patterns across biomarker groups, with disrupted connectivity (brain volume covariance networks) in amyloid positive and other dementia groups, while amyloid and tau negative, cognitively unimpaired controls exhibited the most connected network. Amyloid was associated with subcortical, cerebellar and brainstem atrophy, with consistent association observations in the thalamus and amygdala across all four datasets. Tau in the presence of amyloid demonstrated general brain shrinkage through enlargement of extracerebral CSF, alongside unexpected ventricle shrinkages. Sex-based analyses revealed that A+T+ (amyloid positive, tau positive) had lower sex differences in connectivity patterns compared with other groups. Sex differences were also noted in amyloid-related ventricular volume changes. This study reveals how amyloid and tau affect brain connectivity and volume across sex and CSF biomarker groups, emphasizing global brain changes and sex differences. By leveraging automated pipelines and advanced MRI and biomarker analyses, we extracted meaningful and replicable findings from heterogeneous clinical samples from real-world data. The meta-analyses across four datasets enhance the generalizability of our results.

BACKGROUND AND OBJECTIVES:Plasma neurofilament light chain (NfL) is a marker of neuroaxonal injury associated with cognitive decline. High-density lipoprotein (HDL) cholesterol has neuroprotective properties, but its interaction with neurodegeneration remains unclear. This study examined whether HDL moderates the association between NfL and cognitive performance. METHODS:Baseline data from 417 participants in the Aging Adult Brain Connectome study were analyzed. Plasma NfL and HDL were measured via Simoa and enzymatic assays; cognition was assessed using Montreal Cognitive Assessment (MoCA) and Preclinical Alzheimer Cognitive Composite (PACC). Generalized linear models were used to evaluate NfL and HDL interactions, adjusting for demographics. Sensitivity analyses included apolipoprotein E ε4, body mass index, total cholesterol, LDL, and triglycerides. RESULTS:Significant interaction effects were observed: MoCA (β = -1.86×10-4, P = 0.006) and PACC (β = -4.0×10-5, P = 0.004), indicating HDL moderates the negative association between NfL and cognition. DISCUSSION:These findings suggest that HDL modifies the cognitive impact of neurodegeneration, highlighting the importance of metabolic-neurological interactions. Highlights:High-density lipoprotein (HDL) cholesterol moderates the negative association between plasma neurofilament light chain (NfL) and cognition.Higher HDL levels intensify the negative effect of NfL on cognitive performance.Findings challenge the assumption of HDL's uniformly protective role.Results support the integrated use of metabolic and neurodegenerative biomarkers.

Surface-based analysis of the cerebral cortex is ubiquitous in human neuroimaging with MRI. It is crucial for tasks like cortical registration, parcellation, and thickness estimation. Traditionally, such analyses require high-resolution, isotropic scans with good gray-white matter contrast, typically a T1-weighted scan with 1 mm resolution. This requirement precludes application of these techniques to most MRI scans acquired for clinical purposes, since they are often anisotropic and lack the required T1-weighted contrast. To overcome this limitation and enable large-scale neuroimaging studies using vast amounts of existing clinical data, we introduce recon-all-clinical, a novel methodology for cortical reconstruction, registration, parcellation, and thickness estimation for clinical brain MRI scans of any resolution and contrast. Our approach employs a hybrid analysis method that combines a convolutional neural network (CNN) trained with domain randomization to predict signed distance functions (SDFs), and classical geometry processing for accurate surface placement while maintaining topological and geometric constraints. The method does not require retraining for different acquisitions, thus simplifying the analysis of heterogeneous clinical datasets. We evaluated recon-all-clinical on multiple public datasets like ADNI, HCP, AIBL, OASIS and including a large clinical dataset of over 9,500 scans. The results indicate that our method produces geometrically precise cortical reconstructions across different MRI contrasts and resolutions, consistently achieving high accuracy in parcellation. Cortical thickness estimates are precise enough to capture aging effects, independently of MRI contrast, even though accuracy varies with slice thickness. Our method is publicly available at https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all-clinical, enabling researchers to perform detailed cortical analysis on the huge amounts of already existing clinical MRI scans. This advancement may be particularly valuable for studying rare diseases and underrepresented populations where research-grade MRI data is scarce.

The differential diagnosis of Alzheimer’s disease (AD) and normal pressure hydrocephalus (NPH) is complicated by overlapping clinical manifestations. This challenges accurate clinical diagnosis and highlights the need for molecular level investigations to understand underlying pathologies. There have been few proteomic investigations into NPH, which were limited by low sample sizes and limited analytical depth. Here we applied machine learning to investigate the distinct and overlapping proteomic signatures associated with AD and NPH, compared to that of cognitively unimpaired controls (CU). Banked cerebrospinal fluid (CSF) samples were obtained from diagnostic lumbar punctures at an outpatient neurology clinic. Participants were classified based on clinical presentation, improvement after a high-volume LP, and CSF amyloid-b status as CU (N = 53), AD (N = 158), or NPH (N = 56). Proteomic quantification was done using data-independent acquisition mass spectrometry. Defining molecular signatures between classes was investigated with random forest models in two-way fashion and top features were assessed using Gini importance. Additionally, to determine functional changes, we examined enriched and depleted pathways with gene-set enrichment analysis (GSEA) using fold-change data between classes. Random forest models obtained high classification accuracy (>75%). Comparison of the top 30 proteins of each model indicated four proteins, MASP1, NRXN2, VCAN and LTBP2 as defining features in NPH compared to both CU and AD. Six proteins, SMOC1, PTPRN2, NPTX2, LUM, APLP1 and GFRA2 were defining features for both AD and NPH compared to CU. One protein, TTR, was a defining feature comparing AD to both CU and NPH. GSEA indicated 91 pathways to be differentially regulated in NPH compared to both CU and AD. Further analysis indicated specific enrichment of complement activation and immune response pathways in NPH. Pathways differentially regulated in AD compared to both CU and NPH included pathways related to glycolysis and metabolic processes. Our analyses validate previously suggested mechanisms and provide novel insights into the differential pathologies of AD and NPH. Hereby, we aim to contribute to the development of more refined and early diagnostic tools, facilitating targeted therapeutic approaches for these neurologically challenging disorders.

INTRODUCTION:We evaluated the long-term effects of daily 40 Hz (gamma frequency) audiovisual stimulation on cognition and biomarkers in five patients with mild Alzheimer's disease (AD). METHODS:Over 2 years, patients received 1-h daily stimulation. Electroencephalography (EEG) was used to assess neural entrainment; magnetic resonance imaging (MRI) measured brain volumes; actigraphy monitored activity patterns; neuropsychological tests evaluated cognition; and S-PLEX assay measured plasma pTau217. RESULTS:No adverse events occurred over the study period. Three female patients with late-onset AD (LOAD) retained strong EEG entrainment and showed less decline in Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR), and Functional Assessment Scale (FAS) scores compared to matched controls from National Alzheimer's Coordinating Center (NACC), Alzheimer's Disease Neuroimaging Initiative (ADNI), and Longitudinal Early-Onset Alzheimer's Disease Study (LEADS). Plasma samples were available for only two of five participants - both with LOAD - and both showed pTau217 reductions of 47% and 19%. DISCUSSION:These findings suggest that long-term 40 Hz audiovisual stimulation is safe, feasible, and may offer cognitive and biomarker benefits in some individuals with mild AD, supporting further investigation. CLINICAL TRIAL REGISTRATION INFORMATION:ClinicalTrials.gov (NCT04055376). HIGHLIGHTS:Five mild Alzheimer's disease (AD) patients safely used daily 40 Hz audiovisual stimulation for 2 years. Late-onset AD (LOAD) patients showed increased 40 Hz electroencephalography (EEG) power and improved cognitive scores. National Alzheimer's Coordinating Center (NACC) data enhanced early-phase analysis and support precision medicine in AD studies. Plasma pTau217 declined in 2 LOAD patients after 2 years of daily use. This small pilot is the first to link long-term 40 Hz therapy to AD biomarker change.

Clinical trials are increasingly focused on pre-manifest and early Alzheimer’s disease. Accurately predicting clinical progression is important to avoid unnecessary treatment and improve trial efficiency. Plasma p-tau217, an indicator of tau pathology with strong associations to amyloid-beta pathology, NfL, a marker of axonal damage and neurodegeneration and GFAP, a marker of inflammation, are promising diagnostic and prognostic tools. Their combined use could offer more accurate prognostic insights than either biomarker alone. We examined the trajectories of domain-specific cognitive functions by stratifying participants based on plasma p-tau217, NfL and GFAP levels (high/low). Participants were from the Massachusetts Alzheimer’s Disease Research Center cohort (n = 523). Cognitive functions were assessed using the National Alzheimer’s Coordinating Center Uniform Data Set v1-3: global cognition (CDR sum of box; MMSE, MoCA converted in v3), memory (Logical Memory), executive functions (Trail Making Test B), language (Boston Naming), and language-based executive function (Category Fluency Animals). We used linear mixed-effects models with 8 groups combining 3 plasma biomarkers to predict cognitive trajectories over 7 years, controlling for age, sex, and education. High p-tau217 alone was significantly associated with declines in Logical Memory (coefficient=-0.12; p = 0.03) and Boston Naming (coefficient=-0.16; p < 0.01), but not associated with decline in CDR sum of box and MMSE unless combined with a high burden of NfL and/or GFAP (CDR group*time coefficients=0.17-0.34, p < 0.01; MMSE group*time coefficients=-0.39 to -0.69, p < 0.01). Neither high GFAP alone nor high NfL alone was associated with significant cognitive declines. The combined use of plasma biomarkers provides a promising approach for predicting domain-specific cognitive decline.