Citations

Abstract Background Brain cells secrete extracellular vesicles (EVs) containing signaling and pathological proteins related to Alzheimer's disease (AD) and related disorders. Recent studies demonstrate brain‐derived EVs (BDEVs) contain misfolded tau and are transmissible of tau pathology in the brain. However, the underlying mechanism regarding EV‐mediated tau pathology is still largely uncharacterized. Method We conducted the immuno‐affinity purification of tau in human brain‐derived EVs (BDEVs) isolated from age and sex‐matched 14 AD and 14 CTRL cases and performed tandem mass‐tag mass spectrometry to profile unbiased tau interactome in BDEVs. We used Nanotemper Monolith to validate the interaction of EV‐tau interactors with tau, and super‐resolution microscopy (Nanoimager) to detect their colocalization in a single‐EV level. We next designed siRNAs to silence EV‐tau interactors in SH‐SY5Y cells overexpressing human P301L tau (SH‐SY5Y‐P301Ltau) and assessed tau loading to EVs by Flow Nanoanalyzer. These EVs were tested for their uptake and tau seeding by human iPSC‐derived neurons (iNeurons). We finally tested the inhibitors of identified molecules on BDEV‐mediated tau propagation in vivo . Result A total of 764 proteins were identified in BDEV‐associated tau interactome from CTRL and AD patients. Sixty‐five proteins were significantly downregulated in AD BDEVs; whereas 5 proteins were significantly upregulated in AD BDEVs compared to CTRL BDEVs. The most enriched tau‐interacting proteins were significantly positively correlated with Braak stage. We confirmed the direct binding of candidate proteins to tau with micromolar binding affinities by Monolith, and their colocalization with tau in human BDEVs using Nanoimager. Silencing of candidate molecules in human SH‐SY5Y‐P301Ltau cells showed reduced loading of tau in EVs, their reduced uptake by iNeurons, and tau seeding activities. Finally, intracerebroventricular injection of neutralizing antibody against the most promising target results in reduction of tau pathology in PS19 mice expressing P301S human tau mutant. Conclusion Our study identified tau‐interacting molecules highly enriched in AD BDEVs compared to CTRL BDVs. Silencing of candidate molecule reduced tau loading to the EVs and their uptake by iNeurons and neutralizing antibody suppressed tau dissemination, highlighting them as promising therapeutic targets to halt tau pathology in AD and related tauopathy.

Abstract Background Dynamically predicting patients at risk of Alzheimer's disease (AD) is crucial for timely treatment and care in precision medicine. Method We present a novel architecture, a Kolmogorov‐Arnold networks (KANs)‐based joint prediction model of longitudinal and survival data (JM‐KAN). Real‐life data of patients with Mild Cognitive Impairment (MCI) with no prior AD diagnosis from National Alzheimer's Coordinating Center (NACC) dataset was utilized for individualized predictions. We built joint models with landmark times every 1 year up to 4 years after the MCI diagnosis, and predicted survival outcomes one year after each landmark (i.e. 1, 2, 3, and 4 years). Integrated AUC (iAUC), and integrated Brier score (iBS) were measured for existing prediction models and our novel architecture. Result Out of 2711 unique patients with MCI, 821 patients progressed to develop AD. Mean time‐to‐event in years was 3.19 (standard deviation (SD): 2.29). The number of visits prior to AD diagnosis was 4.03 (SD: 2.41). With iAUC of 0.789, iBS of 0.118, JM‐KAN has both the highest iAUC and lowest iBS among joint models, which indicates superiority in discrimination and overall performance. For individualized predictions, the model successfully predicted both longitudinal risk factors and survival probability, as new information came in every year. Conclusion Using neural network‐based Artificial Intelligence (AI) model, we demonstrated that this architecture improves upon prior methods in dynamically updating predictions of AD as new longitudinal data becomes available.

Abstract Background Our group recently performed the largest‐to‐date X‐chromosome wide association study (XWAS) of Alzheimer's disease (AD). Here, we expand on this with additional samples, novel sex‐ and APOE *4‐stratified analyses, and evaluate escape from random X chromosome inactivation (eXCI) to better capture female‐biased risk genes. We then integrate these results with XWASs of various AD‐relevant traits to elucidate shared genetic signals and ultimately uncover novel AD risk genes and mechanisms. Method The AD XWAS design is shown in Figure 1A and includes random X chromosome inactivation (rXCI) and eXCI models. We further assessed suggestive AD signals ( p <1x10 ‐3 ) for pleiotropy using genetic colocalization with 2852 AD‐relevant traits (Figure 2A). Loci exhibiting X chromosome‐wide significance ( p <1x10 ‐5 ) or apparent trait colocalization underwent quantitative trait locus (QTL) colocalization analyses across 62 tissues and cell types to functionally prioritize AD risk genes. Result Full sample analyses reproduced Belloy et al. 2024 findings and identified 3 additional loci, including a male‐specific signal near GLUD2 that impacts glutamate/glutamine metabolism (Figure 1B). APOE *4‐stratified analyses revealed 9 additional loci, including 3 eXCI hits in APOE *4 carriers (Figure 1C‐D). Pleiotropy colocalization identified 38 loci, most being novel and many driven by eXCI and/or female‐specific AD XWAS, including MOSPD2, PNMA3 and GABRE loci that showed extensive colocalization with brain imaging traits (Figure 2B). The most significant XWAS locus, SLC9A7 , colocalized with total testosterone, HDL‐C, and various brain imaging traits. Only the NLGN4X locus colocalized with amyloid positivity, linking its proposed role in synaptic dysfunction to amyloid pathology. The locus at KDM6A , previously implicated as an AD resilience gene, colocalized with a functional MRI (fMRI) phenotype. QTL colocalization analyses confirmed gene prioritizations in Belloy et al. 2024, and additionally provided support for PNMA3 , an antigen highly expressed in the brain, and 3 APOE ‐stratified loci, including ACLS4 , which impacts lipid metabolism. Conclusion This study provides novel insights into biological mechanisms that contribute to X‐linked genetic risk for AD in an APOE *4 and sex‐specific manner, identifying various novel risk loci. Notably, 29 female‐biased risk loci were uncovered, which may shed light on sex disparities in AD. Overall, our findings will aid in elucidating AD pathways and drug targets relevant to personalized medicine.

Abstract Background Mitophagy constitutes a crucial cellular pathway in mitochondrial quality control, in which the enzymatic pair PINK1 and PRKN selectively decorates damaged mitochondria with phosphorylated‐ubiquitin (pS65‐Ub), facilitating their autophagic‐lysosomal removal. We previously demonstrated significant accumulation of pS65‐Ub labeled damaged mitochondria in Lewy body and Alzheimer’s disease autopsy brain. This mitophagy alteration was strongly associated with pre‐tangle tau pathology in neurons. The effects of distinct tau species on mitophagy across different cell types however remain largely unknown. We therefore expanded our analyses to primary tauopathies, exploring how specific tau forms and their aggregation influence mitophagy in selectively vulnerable brain regions and cell types. Method This study included 92 control and tauopathy cases with primary age‐related tauopathy (PART), Pick’s disease (PiD), progressive supranuclear palsy (PSP), or corticobasal degeneration (CBD). Immunohistochemistry for the mitophagy marker pS65‐Ub and phospho‐tau was performed in vulnerable brain regions (hippocampus for PART and PiD, primary motor cortex for PSP and CBD). A deep learning‐based image identification model was used to identify and quantify distinct tau inclusions. pS65‐Ub‐positive cells were manually counted and grouped based on signal intensity and morphology. Immunofluorescence co‐staining of pS65‐Ub and phospho‐tau was conducted to study their spatial relationship at single‐cell level. Result We observed marked increases in pS65‐Ub‐positive cells in the hippocampus of PART and PiD cases compared to controls. Although less prominent, significant increases were also found in the primary motor cortex of PSP, whereas only minor changes were observed in CBD. Single‐cell analyses revealed that the accumulation of pS65‐Ub was most abundant in hippocampal neurons from PART. Cells with lower signal intensity contained mostly granular pS65‐Ub deposits, while those with higher intensity harbored rather vacuolar inclusions. Across tau aggregate subtypes, pS65‐Ub levels were strongly correlated and often co‐resided with neurofibrillary tangles and Pick bodies. Such correlations were weaker for coiled bodies and tufted astrocytes, and absent for astrocytic plaques. Conclusion Our study highlights distinct mitophagy alterations in primary tauopathies that are associated with specific tau inclusions in neurons, oligodendrocytes, and astrocytes. The observed pathological heterogeneity and complex mitophagy disruption underscores the need for future studies to elucidate pathogenic mechanisms and advance targeted therapeutics for each tauopathy.

Abstract Background Amyloid related imaging abnormality edema (ARIA‐E) occurs in about 19% of individuals with autosomal dominant Alzheimer disease (ADAD) treated with an anti‐amyloid‐b monoclonal antibody (Salloway et al., 2021). In a previously reported case, ARIA‐E appeared to colocalize with decreases in PiB‐PET uptake (Joseph‐Mathurin, Llibre‐Guerra, et al, 2022), suggesting an association between amyloid‐b (Aβ) removal and ARIA‐E. Here, we compare longitudinal neuroimaging and corresponding neuropathology in an ADAD individual treated with gantenerumab, who experienced multiple ARIA‐E episodes as sulcal effusions that resolved by the end of the four‐year trial. Methods PiB‐PET and MRI were collected pre‐ and post‐randomization (2 and 4 years). The participant consented to brain donation, which was received a year after trial completion. Four tissue samples were taken from the location of the ARIA‐E in the parieto‐occipital left hemibrain as identified by MRI (one block contained the sulcus affected by ARIA‐E; the rest of the coronal section was captured in the remaining three blocks). Area fractions (AFs) of Aβ (10D5 immunohistochemistry (IHC)), tauopathy (PHF1), microglia (Iba1), and astrocytes (GFAP) in one sulcal region of interest (ROI) from each block and PiB‐PET SUVRs of corresponding ROIs were extracted ( n = 4, Figure 1). Additionally, we included PiB‐PET SUVRs corresponding to ARIA‐E findings observed in the right hemisphere at baseline, two‐year, and four‐year visits ( n = 6). Results Overall PiB‐PET uptake increased during the first two years (before ARIA‐E) and decreased during the last two years (including ARIA‐E episodes) (0.03±0.05 vs. ‐0.04±0.04 SUVR/year, p ‐value=0.01, Figure 2). The decrease seemed more pronounced in ARIA‐E ROIs versus normal‐appearing sulcus ROIs (‐0.05±0.04 vs. ‐0.02±0.03 SUVR/year). Lower PiB uptake at last visit appeared associated with lower Aβ AF (estimates=0.03±0.01, p ‐value=0.07). The ARIA‐E ROI had an Aβ AF of 0.009 while normal‐appearing sulcus ROIs had a mean of 0.02+0.003 (Figure 3). AFs for tauopathy, microglia, and astrocytes were within the range of those of normal‐appearing sulcus ROIs, suggesting an Aβ‐specific effect, although unexamined markers may play a role. Conclusions Our preliminary findings indicated that ARIA‐E is associated with longitudinal PiB‐PET decrease and Aβ AF, supporting the link between ARIA‐E, changes in PiB‐PET, and local Aβ removal observed at autopsy. Funding : K01AG080123; U01AG042791; R01AG046179; R01AG053267

Abstract Background Most existing biomarkers for Alzheimer’s disease (AD) inform on core AD pathologies in the central nervous system, namely amyloid, tau and neurodegeneration (ATN). However, molecular disease mechanisms underlying AD are complex and heterogeneous, highlighting the need for cost‐effective blood‐based biomarkers that reflect brain molecular changes in AD beyond ATN. Method Using peripheral blood transcriptome data from the Mayo Clinic Study of Aging(MCSA) and the Alzheimer's Disease Neuroimaging Initiative, we identified genes associated with AD or mild cognitive impairment (MCI) diagnosis, cognitive, and harmonized neuroimaging measures in two cohorts, followed by meta‐analysis. We identified consensus gene co‐expression modules in MCSA and ADNI using WGCNA and assessed the association between module eigengenes and aforementioned measures. Using seven bulk brain RNAseq cohorts, we confirmed the preservation of coexpression modules across blood and brain. Enrichment analyses of Gene Ontology (GO) terms and cell‐types were performed using significant and/or hub genes. The MCSA transcriptome was further deconvoluted to obtain cell‐type proportions and cell‐type specific expression. Result Blood transcriptome modules M5 and M8 are upregulated in AD/MCI and associate with worse cognition, whereas M1, M10, M13, M16, and M21 are downregulated in AD/MCI and associate with better cognition. M17 associates with more microhemorrhages. Cell‐type enrichment analysis revealed that M5 is enriched in basophils, monocytes, and neutrophils; M8 in monocytes and neutrophils; M13 in natural kills cells; M17 in megakaryocytes; M21 in B cells. GO analysis shows broad consistency with the cell‐type enrichment analysis. M1, 5, and 8 are preserved in the brain network modules. From these modules, we prioritized transcripts significantly associated with at least one AD‐related phenotype in both blood and brain. Cell‐type deconvolution analysis shows that prioritized transcripts in M1 associate with better cognition and higher metabolic activity in B cells. Conclusion We identified blood transcripts and modules associated with AD/MCI, cognition, or neuroimaging, with three preserved in brain networks. These three modules represent centrally linked peripheral molecular signatures that can reveal perturbed brain pathways and cell level transcriptional changes in AD/MCI. We aim to further investigate the prioritized transcripts in additional datasets to establish them as potential novel biomarkers and therapeutic targets.

Glioblastoma (GBM) remains one of the most lethal brain tumors, characterized by extensive immune evasion and a macrophage-dominated tumor microenvironment (TME). However, the molecular determinants governing tumor-associated macrophage (TAM) states and their immunoregulatory functions remain poorly understood. We integrated bulk- and single-cell transcriptomic datasets (TCGA, CGGA, Ivy GAP, and Brain Immune Atlas) to systematically characterize the expression, prognostic relevance, and immune contexture of the myeloid biomarker membrane-spanning 4-domain A6A, MS4A6A, in GBM. Differential expression, survival, and pathway enrichment analyses were performed. Single-cell mapping and CellChat modeling delineated MS4A6A-associated TAM subpopulations, intercellular communication networks, and ligand–receptor signaling dynamics. Spatial transcriptomic validation and pharmacogenomic modeling were conducted to assess anatomic enrichment and therapeutic vulnerabilities. High MS4A6A expression predicted unfavorable survival and correlated with increased stromal and immune infiltration. Single-cell analyses localized MS4A6A predominantly to TAMs, especially Regulatory- and Ribo-TAM states enriched for antigen presentation, T-cell regulation, and ribosomal biogenesis pathways. CellChat analysis revealed that MS4A6A-high TAMs exhibited markedly enhanced communication with CD4+ T cells and Tregs through upregulated PGE2–PTGER2/PTGER4, PECAM1–CD38, and THBS1–CD36 signaling axes, implicating MS4A6A in prostaglandin-driven immune suppression. Spatial profiling confirmed preferential localization of MS4A6A within perivascular and angiogenic niches. Pharmacogenomic prediction indicated that MS4A6A-high tumors were more sensitive to ERK, mTOR, and CDK4/6 inhibition. MS4A6A defines a macrophage-centered, immunosuppressive ecosystem in GBM, mediated by the activation of the PGE2 signaling axis. These findings position MS4A6A both as a prognostic biomarker and as a potential therapeutic node linking myeloid reprogramming to actionable pathway vulnerabilities in glioblastoma.

Neuromyelitis optica spectrum disorder (NMOSD) is a severe autoimmune disease that predominantly affects the optic nerves and spinal cord, which is a distinct disease process from multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease. The most common neuro-ophthalmologic manifestation of NMOSD is atypical optic neuritis (ON), characterized by severe vision loss with a higher propensity toward bilateral involvement, longitudinal enhancement of the optic nerve, and chiasmal involvement than MS-related optic neuritis. Due to the severity of disease, high recurrence rate, and significant risk of permanent deficits, early recognition of neuro-ophthalmologic signs and short- and long-term management with immunosuppressive therapies is critical. In this article, we will review the characteristic neuro-ophthalmologic findings in NMOSD, serologic markers, neuroimaging findings, and current approaches to both acute and long-term treatment.

Multiplex immunofluorescence and immunohistochemistry (mIF/IHC) are increasingly employed antibody-based technologies that use tissue sparingly and facilitate the detection of co-localized or neighboring biomarkers. Specifically, these platforms enable spatial analyses of the tumor microenvironment as well as extended applications, for example, describing normal tissue anatomy, autoimmunity, infectious diseases, etc. mIF/IHC has greatly enhanced biomarker discovery efforts, and a growing number of studies suggest superiority to traditional IHC. Standardization of staining approaches, reporting of image analysis strategies and resultant data is critical for facilitating cross-study comparisons, validation, deployment, and generalization of findings. To address this challenge, The Society for Immunotherapy of Cancer (SITC) previously published two articles providing best practice guidelines for mIF/IHC staining, image analysis, and data sharing. Here, SITC convened stakeholders to develop the third article in the series, a consensus checklist for scientific reporting of mIF/IHC data to support and complement the best practice guidelines. The checklist includes critical components of mIF/IHC applications to be defined within publications such as detailed descriptions of analytical validation; image acquisition, selection, and registration methods; and cell clustering and spatial analysis strategies, amongst others. Such information will help with data reproducibility and comparison across studies towards future drug and assay development.