Molecular markers of proliferation, DNA repair, and immune infiltration defines high-risk subset of resectable retroperitoneal sarcomas.

INTRODUCTION: For retroperitoneal sarcomas (RPS), aggressive surgical resection offers the only chance for a cure; however, 5-year survival remains below 65%. Therefore, there is a critical need to identify drivers of poor clinical outcomes. MATERIALS AND METHODS: To identify biomarkers of tumors likely to recur following curative intent resection, we performed genomic and transcriptomic sequencing for 47 and 34 patients, respectively, with non-metastatic RPS at a single, high-volume sarcoma center. RESULTS: At the DNA level, alterations in TERT were associated with poor disease-free survival (DFS) and overall survival (OS). Increased RNA expression of gene sets related to growth signaling and DNA repair were associated with poor DFS and OS. Infiltration of CD8+ T-Cells and activated dendritic cells were associated with poor DFS and OS. CONCLUSION: These findings may help to better identify and treat non-metastatic, high-risk RPS.

Cell-specific cross-talk proteomics reveals cathepsin B signaling as a driver of glioblastoma malignancy near the subventricular zone.

Glioblastoma (GBM) is the most prevalent and aggressive malignant primary brain tumor. GBM proximal to the lateral ventricles (LVs) is more aggressive, potentially because of subventricular zone contact. Despite this, cross-talk between GBM and neural stem/progenitor cells (NSC/NPCs) is not well understood. Using cell-specific proteomics, we show that LV-proximal GBM prevents neuronal maturation of NSCs through induction of senescence. In addition, GBM brain tumor-initiating cells (BTICs) increase expression of cathepsin B (CTSB) upon interaction with NPCs. Lentiviral knockdown and recombinant protein experiments reveal that both cell-intrinsic and soluble CTSB promote malignancy-associated phenotypes in BTICs. Soluble CTSB stalls neuronal maturation in NPCs while promoting senescence, providing a link between LV-tumor proximity and neurogenesis disruption. Last, we show LV-proximal CTSB up-regulation in patients, showing the relevance of this cross-talk in human GBM biology. These results demonstrate the value of proteomic analysis in tumor microenvironment research and provide direction for new therapeutic strategies in GBM.

Transcriptomic classification of diffuse large B-cell lymphoma identifies a high-risk activated B-cell-like subpopulation with targetable MYC dysregulation.

Immunochemotherapy has been the mainstay of treatment for newly diagnosed diffuse large B-cell lymphoma (ndDLBCL) yet is inadequate for many patients. In this work, we perform unsupervised clustering on transcriptomic features from a large cohort of ndDLBCL patients and identify seven clusters, one called A7 with poor prognosis, and develop a classifier to identify these clusters in independent ndDLBCL cohorts. This high-risk cluster is enriched for activated B-cell cell-of-origin, low immune infiltration, high MYC expression, and copy number aberrations. We compare and contrast our methodology with recent DLBCL classifiers to contextualize our clusters and show improved prognostic utility. Finally, using pre-clinical models, we demonstrate a mechanistic rationale for IKZF1/3 degraders such as lenalidomide to overcome the low immune infiltration phenotype of A7 by inducing T-cell trafficking into tumors and upregulating MHC I and II on tumor cells, and demonstrate that TCF4 is an important regulator of MYC-related biology in A7.

Effects of PreOperative radiotherapy in a preclinical glioblastoma model: a paradigm-shift approach.

PURPOSE: PreOperative radiotherapy (RT) is commonly used in the treatment of brain metastasis and different cancer types but has never been used in primary glioblastoma (GBM). Here, we aim to establish, describe, and validate the use of PreOperative RT for the treatment of GBM in a preclinical model. METHODS: Rat brains were locally irradiated with 30-Gy, hypofractionated in five doses 2 weeks before or after the resection of intracranial GBM. Kaplan-Meier analysis determined survival. Hematoxylin-eosin staining was performed, and nuclei size and p21 senescence marker were measured in both resected and recurrent rodent tumors. Immunohistochemistry assessed microglia/macrophage markers, and RNAseq analyzed gene expression changes in recurrent tumors. Akoya Multiplex Staining on two human patients from our ongoing Phase I/IIa trial served as proof of principle. RESULTS: PreOperative RT group median survival was significantly higher than PostOperative RT (p < 0.05). Radiation enlarged cytoplasm and nuclei in PreOperative RT resected tumors (p < 0.001) and induced senescence in PostOperative RT recurrent tumors (p < 0.05). Gene Set Enrichment Analysis (GSEA) suggested a more proliferative profile in PreOperative RT group. PreOperative RT showed lower macrophage/microglia recruitment in recurrent tumors (p < 0.01) compared to PostOperative RT. Akoya Multiplex results indicated TGF-ß accumulation in the cytoplasm of TAMs and CD4 + lymphocyte predominance in PostOperative group. CONCLUSIONS: This is the first preclinical study showing feasibility and longer overall survival using neoadjuvant radiotherapy before GBM resection in a mammalian model. This suggests strong superiority for new clinical radiation strategies. Further studies and trials are required to confirm our results.

Deciphering Distinct Genetic Risk Factors for FTLD-TDP Pathological Subtypes via Whole-Genome Sequencing.

Frontotemporal lobar degeneration with neuronal inclusions of the TAR DNA-binding protein 43 (FTLD-TDP) is a fatal neurodegenerative disorder with only a limited number of risk loci identified. We report our comprehensive genome-wide association study as part of the International FTLD-TDP Whole-Genome Sequencing Consortium, including 985 cases and 3,153 controls, and meta-analysis with the Dementia-seq cohort, compiled from 26 institutions/brain banks in the United States, Europe and Australia. We confirm UNC13A as the strongest overall FTLD-TDP risk factor and identify TNIP1 as a novel FTLD-TDP risk factor. In subgroup analyses, we further identify for the first time genome-wide significant loci specific to each of the three main FTLD-TDP pathological subtypes (A, B and C), as well as enrichment of risk loci in distinct tissues, brain regions, and neuronal subtypes, suggesting distinct disease aetiologies in each of the subtypes. Rare variant analysis confirmed TBK1 and identified VIPR1 , RBPJL , and L3MBTL1 as novel subtype specific FTLD-TDP risk genes, further highlighting the role of innate and adaptive immunity and notch signalling pathway in FTLD-TDP, with potential diagnostic and novel therapeutic implications.

Multiomic analysis identifies a high-risk signature that predicts early clinical failure in DLBCL.

Recent genetic and molecular classification of DLBCL has advanced our knowledge of disease biology, yet were not designed to predict early events and guide anticipatory selection of novel therapies. To address this unmet need, we used an integrative multiomic approach to identify a signature at diagnosis that will identify DLBCL at high risk of early clinical failure. Tumor biopsies from 444 newly diagnosed DLBCL were analyzed by WES and RNAseq. A combination of weighted gene correlation network analysis and differential gene expression analysis was used to identify a signature associated with high risk of early clinical failure independent of IPI and COO. Further analysis revealed the signature was associated with metabolic reprogramming and identified cases with a depleted immune microenvironment. Finally, WES data was integrated into the signature and we found that inclusion of ARID1A mutations resulted in identification of 45% of cases with an early clinical failure which was validated in external DLBCL cohorts. This novel and integrative approach is the first to identify a signature at diagnosis, in a real-world cohort of DLBCL, that identifies patients at high risk for early clinical failure and may have significant implications for design of therapeutic options.

Comprehensive profiling of cancer neoantigens from aberrant RNA splicing.

BACKGROUND: Cancer neoantigens arise from protein-altering somatic mutations in tumor and rank among the most promising next-generation immuno-oncology agents when used in combination with immune checkpoint inhibitors. We previously developed a computational framework, REAL-neo, for identification, quality control, and prioritization of both class-I and class-II human leucocyte antigen (HLA)-presented neoantigens resulting from somatic single-nucleotide mutations, small insertions and deletions, and gene fusions. In this study, we developed a new module, SPLICE-neo, to identify neoantigens from aberrant RNA transcripts from two distinct sources: (1) DNA mutations within splice sites and (2) de novo RNA aberrant splicings. METHODS: First, SPLICE-neo was used to profile all DNA splice-site mutations in 11,892 tumors from The Cancer Genome Atlas (TCGA) and identified 11 profiles of splicing donor or acceptor site gains or losses. Transcript isoforms resulting from the top seven most frequent profiles were computed using novel logic models. Second, SPLICE-neo identified de novo RNA splicing events using RNA sequencing reads mapped to novel exon junctions from either single, double, or multiple exon-skipping events. The aberrant transcripts from both sources were then ranked based on isoform expression levels and z-scores assuming that individual aberrant splicing events are rare. Finally, top-ranked novel isoforms were translated into protein, and the resulting neoepitopes were evaluated for neoantigen potential using REAL-neo. The top splicing neoantigen candidates binding to HLA-A*02:01 were validated using in vitro T2 binding assays. RESULTS: We identified abundant splicing neoantigens in four representative TCGA cancers: BRCA, LUAD, LUSC, and LIHC. In addition to their substantial contribution to neoantigen load, several splicing neoantigens were potent tumor antigens with stronger bindings to HLA compared with the positive control of antigens from influenza virus. CONCLUSIONS: SPLICE-neo is the first tool to comprehensively identify and prioritize splicing neoantigens from both DNA splice-site mutations and de novo RNA aberrant splicings. There are two major advances of SPLICE-neo. First, we developed novel logic models that assemble and prioritize full-length aberrant transcripts from DNA splice-site mutations. Second, SPLICE-neo can identify exon-skipping events involving more than two exons, which account for a quarter to one-third of all skipping events.

CSF biomarkers of immune activation and Alzheimer's disease for predicting cognitive impairment risk in the elderly.

The immune system substantially influences age-related cognitive decline and Alzheimer's disease (AD) progression, affected by genetic and environmental factors. In a Mayo Clinic Study of Aging cohort, we examined how risk factors like APOE genotype, age, and sex affect inflammatory molecules and AD biomarkers in cerebrospinal fluid (CSF). Among cognitively unimpaired individuals over 65 (N = 298), we measured 365 CSF inflammatory molecules, finding age, sex, and diabetes status predominantly influencing their levels. We observed age-related correlations with AD biomarkers such as total tau, phosphorylated tau-181, neurofilament light chain (NfL), and YKL40. APOE4 was associated with lower Aß42 and higher SNAP25 in CSF. We explored baseline variables predicting cognitive decline risk, finding age, CSF Aß42, NfL, and REG4 to be independently correlated. Subjects with older age, lower Aß42, higher NfL, and higher REG4 at baseline had increased cognitive impairment risk during follow-up. This suggests that assessing CSF inflammatory molecules and AD biomarkers could predict cognitive impairment risk in the elderly.

Deconvolution reveals cell-type-specific transcriptomic changes in the aging mouse brain.

Mounting evidence highlights the crucial role of aging in the pathogenesis of Alzheimer's disease (AD). We have previously explored human apoE-targeted replacement mice across different ages and identified distinct molecular pathways driven by aging. However, the specific contribution of different brain cell types to the gene modules underlying these pathways remained elusive. To bridge this knowledge gap, we employed a computational deconvolution approach to examine cell-type-specific gene expression profiles in major brain cell types, including astrocytes (AS), microglia (MG), oligodendroglia (OG), neurons (NEU), and vascular cells (VC). Our findings revealed that immune module genes were predominantly expressed in MG, OG, and VC. The lipid metabolism module genes were primarily expressed in AS, MG, and OG. The mitochondria module genes showed prominent expression in VC, and the synapse module genes were primarily expressed in NEU and VC. Furthermore, we identified intra- and inter-cell-type interactions among these module genes and validated their aging-associated expression changes using published single cell studies. Our study dissected bulk brain transcriptomics data at the cellular level, providing a closer examination of the cell-type contributions to the molecular pathways driven by aging.

Cell-specific crosstalk proteomics reveals cathepsin B signaling as a driver of glioblastoma malignancy near the subventricular zone.

Glioblastoma (GBM) is the most prevalent and aggressive malignant primary brain tumor. GBM proximal to the lateral ventricles (LVs) is more aggressive, potentially due to subventricular zone (SVZ) contact. Despite this, crosstalk between GBM and neural stem/progenitor cells (NSC/NPCs) is not well understood. Using cell-specific proteomics, we show that LV-proximal GBM prevents neuronal maturation of NSCs through induction of senescence. Additionally, GBM brain tumor initiating cells (BTICs) increase expression of CTSB upon interaction with NPCs. Lentiviral knockdown and recombinant protein experiments reveal both cell-intrinsic and soluble CTSB promote malignancy-associated phenotypes in BTICs. Soluble CTSB stalls neuronal maturation in NPCs while promoting senescence, providing a link between LV-tumor proximity and neurogenesis disruption. Finally, we show LV-proximal CTSB upregulation in patients, showing the relevance of this crosstalk in human GBM biology. These results demonstrate the value of proteomic analysis in tumor microenvironment research and provide direction for new therapeutic strategies in GBM. Highlights: Periventricular GBM is more malignant and disrupts neurogenesis in a rodent model.Cell-specific proteomics elucidates tumor-promoting crosstalk between GBM and NPCs.NPCs induce upregulated CTSB expression in GBM, promoting tumor progression.GBM stalls neurogenesis and promotes NPC senescence via CTSB.

APOE deficiency impacts neural differentiation and cholesterol biosynthesis in human iPSC-derived cerebral organoids.

BACKGROUND: The apolipoprotein E (APOE) gene is the strongest genetic risk factor for Alzheimer's disease (AD); however, how it modulates brain homeostasis is not clear. The apoE protein is a major lipid carrier in the brain transporting lipids such as cholesterol among different brain cell types. METHODS: We generated three-dimensional (3-D) cerebral organoids from human parental iPSC lines and its isogenic APOE-deficient (APOE-/-) iPSC line. To elucidate the cell-type-specific effects of APOE deficiency in the cerebral organoids, we performed scRNA-seq in the parental and APOE-/- cerebral organoids at Day 90. RESULTS: We show that APOE deficiency in human iPSC-derived cerebral organoids impacts brain lipid homeostasis by modulating multiple cellular and molecular pathways. Molecular profiling through single-cell RNA sequencing revealed that APOE deficiency leads to changes in cellular composition of isogenic cerebral organoids likely by modulating the eukaryotic initiation factor 2 (EIF2) signaling pathway as these events were alleviated by the treatment of an integrated stress response inhibitor (ISRIB). APOE deletion also leads to activation of the Wnt/ß-catenin signaling pathway with concomitant decrease of secreted frizzled-related protein 1 (SFRP1) expression in glia cells. Importantly, the critical role of apoE in cell-type-specific lipid homeostasis was observed upon APOE deletion in cerebral organoids with a specific upregulation of cholesterol biosynthesis in excitatory neurons and excessive lipid accumulation in astrocytes. Relevant to human AD, APOE4 cerebral organoids show altered neurogenesis and cholesterol metabolism compared to those with APOE3. CONCLUSIONS: Our work demonstrates critical roles of apoE in brain homeostasis and offers critical insights into the APOE4-related pathogenic mechanisms.

Multiomic Analysis Identifies a High-Risk Metabolic and TME Depleted Signature that Predicts Early Clinical Failure in DLBCL.

PURPOSE: 60-70% of newly diagnosed diffuse large B-cell lymphoma (DLBCL) patients avoid events within 24 months of diagnosis (EFS24) and the remainder have poor outcomes. Recent genetic and molecular classification of DLBCL has advanced our knowledge of disease biology, yet were not designed to predict early events and guide anticipatory selection of novel therapies. To address this unmet need, we used an integrative multiomic approach to identify a signature at diagnosis that will identify DLBCL at high risk of early clinical failure. PATIENTS AND METHODS: Tumor biopsies from 444 newly diagnosed DLBCL were analyzed by WES and RNAseq. A combination of weighted gene correlation network analysis and differential gene expression analysis followed by integration with clinical and genomic data was used to identify a multiomic signature associated with high risk of early clinical failure. RESULTS: Current DLBCL classifiers are unable to discriminate cases who fail EFS24. We identified a high risk RNA signature that had a hazard ratio (HR, 18.46 [95% CI 6.51-52.31] P < .001) in a univariate model, which did not attenuate after adjustment for age, IPI and COO (HR, 20.8 [95% CI, 7.14-61.09] P < .001). Further analysis revealed the signature was associated with metabolic reprogramming and a depleted immune microenvironment. Finally, WES data was integrated into the signature and we found that inclusion of ARID1A mutations resulted in identification of 45% of cases with an early clinical failure which was validated in external DLBCL cohorts. CONCLUSION: This novel and integrative approach is the first to identify a signature at diagnosis that will identify DLBCL at high risk for early clinical failure and may have significant implications for design of therapeutic options.

LRP1 in vascular mural cells modulates cerebrovascular integrity and function in the presence of APOE4.

Cerebrovasculature is critical in maintaining brain homeostasis; its dysregulation often leads to vascular cognitive impairment and dementia (VCID) during aging. VCID is the second most prevalent cause of dementia in the elderly, after Alzheimer's disease (AD), with frequent cooccurrence of VCID and AD. While multiple factors are involved in the pathogenesis of AD and VCID, APOE4 increases the risk for both diseases. A major apolipoprotein E (apoE) receptor, the low-density lipoprotein receptor-related protein 1 (LRP1), is abundantly expressed in vascular mural cells (pericytes and smooth muscle cells). Here, we investigated how deficiency of vascular mural cell LRP1 affects the cerebrovascular system and cognitive performance using vascular mural cell-specific Lrp1-KO mice (smLrp1-/-) in a human APOE3 or APOE4 background. We found that spatial memory was impaired in the 13- to 16-month-old APOE4 smLrp1-/- mice but not in the APOE3 smLrp1-/- mice, compared with their respective littermate control mice. These disruptions in the APOE4 smLrp1-/- mice were accompanied with excess paravascular glial activation and reduced cerebrovascular collagen IV. In addition, blood-brain barrier (BBB) integrity was disrupted in the APOE4 smLrp1-/- mice. Together, our results suggest that vascular mural cell LRP1 modulates cerebrovasculature integrity and function in an APOE genotype-dependent manner.

AT-101 Enhances the Antitumor Activity of Lenalidomide in Patients with Multiple Myeloma.

Bcl-2 and Mcl-1 proteins play a role in multiple myeloma (MM) cell survival, for which targeted inhibitors are being developed. AT-101 is an oral drug, which disrupts Bcl-2 and Mcl-1 function, impedes mitochondrial bioenergetic processes and induces apoptosis in MM cells. When combined with lenalidomide and dexamethasone (Rd), AT-101 significantly reduced tumor burden in an in vivo xenograft model of MM. These data provided rationale for a phase I/II study to establish the effective dose of AT-101 in combination with Rd (ARd regimen) in relapsed/refractory MM. A total of 10 patients were enrolled, most with high-risk cytogenetics (80%) and prior stem cell transplant (70%). Three patients were lenalidomide-refractory, 2 were bortezomib-refractory and 3 were daratumumab-refractory. The ARd combination was well tolerated with most common grade 3/4 adverse events being cytopenia's. The overall response rate was 40% and clinical benefit rate was 90%. The median progression free survival was 14.9 months (95% CI 7.1-NE). Patients responsive to ARd showed a decrease in Bcl-2:Bim or Mcl-1:Noxa protein complexes, increased CD8+ T and NK cells and depletion of T and B-regulatory cells. The ARd regimen demonstrated an acceptable safety profile and promising efficacy in patients with relapsed/refractory MM prompting further investigation in additional patients.

Opposing effects of apoE2 and apoE4 on microglial activation and lipid metabolism in response to demyelination.

BACKGROUND: Abnormal lipid accumulation has been recognized as a key element of immune dysregulation in microglia whose dysfunction contributes to neurodegenerative diseases. Microglia play essential roles in the clearance of lipid-rich cellular debris upon myelin damage or demyelination, a common pathogenic event in neuronal disorders. Apolipoprotein E (apoE) plays a pivotal role in brain lipid homeostasis; however, the apoE isoform-dependent mechanisms regulating microglial response upon demyelination remain unclear. METHODS: To determine how apoE isoforms impact microglial response to myelin damage, 2-month-old apoE2-, apoE3-, and apoE4-targeted replacement (TR) mice were fed with normal diet (CTL) or 0.2% cuprizone (CPZ) diet for four weeks to induce demyelination in the brain. To examine the effects on subsequent remyelination, the cuprizone diet was switched back to regular chow for an additional two weeks. After treatment, brains were collected and subjected to immunohistochemical and biochemical analyses to assess the myelination status, microglial responses, and their capacity for myelin debris clearance. Bulk RNA sequencing was performed on the corpus callosum (CC) to address the molecular mechanisms underpinning apoE-mediated microglial activation upon demyelination. RESULTS: We demonstrate dramatic isoform-dependent differences in the activation and function of microglia upon cuprizone-induced demyelination. ApoE2 microglia were hyperactive and more efficient in clearing lipid-rich myelin debris, whereas apoE4 microglia displayed a less activated phenotype with reduced clearance efficiency, compared with apoE3 microglia. Transcriptomic profiling revealed that key molecules known to modulate microglial functions had differential expression patterns in an apoE isoform-dependent manner. Importantly, apoE4 microglia had excessive buildup of lipid droplets, consistent with an impairment in lipid metabolism, whereas apoE2 microglia displayed a superior ability to metabolize myelin enriched lipids. Further, apoE2-TR mice had a greater extent of remyelination; whereas remyelination was compromised in apoE4-TR mice. CONCLUSIONS: Our findings provide critical mechanistic insights into how apoE isoforms differentially regulate microglial function and the maintenance of myelin dynamics, which may inform novel therapeutic avenues for targeting microglial dysfunctions in neurodegenerative diseases.

Network approaches for omics studies of neurodegenerative diseases.

The recent methodological advances in multi-omics approaches, including genomic, transcriptomic, metabolomic, lipidomic, and proteomic, have revolutionized the research field by generating "big data" which greatly enhanced our understanding of the molecular complexity of the brain and disease states. Network approaches have been routinely applied to single-omics data to provide critical insight into disease biology. Furthermore, multi-omics integration has emerged as both a vital need and a new direction to connect the different layers of information underlying disease mechanisms. In this review article, we summarize popular network analytic approaches for single-omics data and multi-omics integration and discuss how these approaches have been utilized in studying neurodegenerative diseases.

Elevating microglia TREM2 reduces amyloid seeding and suppresses disease-associated microglia.

TREM2 is exclusively expressed by microglia in the brain and is strongly linked to the risk for Alzheimer's disease (AD). As microglial responses modulated by TREM2 are central to AD pathogenesis, enhancing TREM2 signaling has been explored as an AD therapeutic strategy. However, the effective therapeutic window targeting TREM2 is unclear. Here, by using microglia-specific inducible mouse models overexpressing human wild-type TREM2 (TREM2-WT) or R47H risk variant (TREM2-R47H), we show that TREM2-WT expression reduces amyloid deposition and neuritic dystrophy only during the early amyloid seeding stage, whereas TREM2-R47H exacerbates amyloid burden during the middle amyloid rapid growth stage. Single-cell RNA sequencing reveals suppressed disease-associated microglia (DAM) signature and reduced DAM population upon TREM2-WT expression in the early stage, whereas upregulated antigen presentation pathway is detected with TREM2-R47H expression in the middle stage. Together, our findings highlight the dynamic effects of TREM2 in modulating AD pathogenesis and emphasize the beneficial effect of enhancing TREM2 function in the early stage of AD development.

Assessment and Optimization of Explainable Machine Learning Models Applied to Transcriptomic Data.

Explainable artificial intelligence aims to interpret how machine learning models make decisions, and many model explainers have been developed in the computer vision field. However, understanding of the applicability of these model explainers to biological data is still lacking. In this study, we comprehensively evaluated multiple explainers by interpreting pre-trained models for predicting tissue types from transcriptomic data and by identifying the top contributing genes from each sample with the greatest impacts on model prediction. To improve the reproducibility and interpretability of results generated by model explainers, we proposed a series of optimization strategies for each explainer on two different model architectures of multilayer perceptron (MLP) and convolutional neural network (CNN). We observed three groups of explainer and model architecture combinations with high reproducibility. Group II, which contains three model explainers on aggregated MLP models, identified top contributing genes in different tissues that exhibited tissue-specific manifestation and were potential cancer biomarkers. In summary, our work provides novel insights and guidance for exploring biological mechanisms using explainable machine learning models.

Peripheral apoE4 enhances Alzheimer's pathology and impairs cognition by compromising cerebrovascular function.

The ε4 allele of the apolipoprotein E (APOE) gene, a genetic risk factor for Alzheimer's disease, is abundantly expressed in both the brain and periphery. Here, we present evidence that peripheral apoE isoforms, separated from those in the brain by the blood-brain barrier, differentially impact Alzheimer's disease pathogenesis and cognition. To evaluate the function of peripheral apoE, we developed conditional mouse models expressing human APOE3 or APOE4 in the liver with no detectable apoE in the brain. Liver-expressed apoE4 compromised synaptic plasticity and cognition by impairing cerebrovascular functions. Plasma proteome profiling revealed apoE isoform-dependent functional pathways highlighting cell adhesion, lipoprotein metabolism and complement activation. ApoE3 plasma from young mice improved cognition and reduced vessel-associated gliosis when transfused into aged mice, whereas apoE4 compromised the beneficial effects of young plasma. A human induced pluripotent stem cell-derived endothelial cell model recapitulated the plasma apoE isoform-specific effect on endothelial integrity, further supporting a vascular-related mechanism. Upon breeding with amyloid model mice, liver-expressed apoE4 exacerbated brain amyloid pathology, whereas apoE3 reduced it. Our findings demonstrate pathogenic effects of peripheral apoE4, providing a strong rationale for targeting peripheral apoE to treat Alzheimer's disease.