BACKGROUND:Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive liver malignancy with limited therapeutic options and poor prognosis. Recent evidence indicates that lactate metabolism (LM) plays a pivotal role in tumor metabolic reprogramming, immune evasion, and disease progression; however, the heterogeneity and regulatory mechanisms of LM activity within ICC remain largely undefined. AIM:To systematically characterize LM-driven heterogeneity and its molecular and functional implications in ICC. METHODS:Single-cell RNA sequencing and bulk transcriptomic datasets were integrated to characterize LM heterogeneity in ICC. High-dimensional weighted gene co-expression network analysis and multiple machine-learning algorithms (least absolute shrinkage and selection operator, random forest, gradient boosting machine, adaptive best subset selection, and decision tree) were employed to identify LM-associated feature genes. CytoTRACE and CellChat analyses were used to assess differentiation potential and intercellular communication among malignant epithelial subpopulations. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses were performed to elucidate biological functions. A random forest model combined with SHapley Additive exPlanation (SHAP) interpretability analysis identified the most predictive LM-related gene. Functional assays, including quantitative polymerase chain reaction, cell counting kit-8, colony formation, wound-healing, and transwell experiments, were conducted to validate CYC1 in ICC cell lines. RESULTS:Malignant ICC cells were stratified into three LM-activity subtypes (high, intermediate, and low) exhibiting distinct transcriptional programs and differentiation trajectories. Twelve LM-associated feature genes GPX3, CYC1, NME1, GSTP1, MGST1, ALDH3A1, TALDO1, SNRPB, TKT, NAA20, G6PD, and RPL13A were identified as key molecular markers linked to aggressive phenotypes and poor prognosis. Among them, CYC1 showed the highest predictive accuracy (area under the curve = 0.844) and strongest model contribution (SHAP = 0.091), marking it as the principal LM-related driver gene. Functional experiments confirmed that CYC1 knockdown significantly suppressed ICC cell proliferation, migration, and invasion, validating its oncogenic role in promoting malignant progression. CONCLUSION:This integrative single-cell and machine-learning study delineates the molecular heterogeneity of LM in ICC and identifies twelve feature genes linking LM with tumor aggressiveness. These findings provide novel insight into LM-driven oncogenic mechanisms and propose CYC1 and other LM-associated genes as potential biomarkers and therapeutic targets for ICC.

Abstract Introduction Alzheimer’s disease (AD) is characterized by pathologies including amyloid, tau, neurodegeneration reflected in established blood biomarkers and track with clinical changes. However, the association between peripheral cell-specific signatures and AD-related phenotypes remain poorly characterized. Methods We analyzed bulk blood transcriptome data from the Mayo Clinic Study of Aging (MCSA) and Emory University Vascular study. We used BayesPrism, CIBERSORTx, and an in-house pipeline CNNreg to deconvolute these data and obtain peripheral cell proportions. Cell type specific transcripts were estimated with BayesPrism. We compared cell proportions between cases (AD/MCI) and controls. Association analysis was performed between cell type specific transcripts and AD-related phenotypes including diagnosis and cognition. Meta-analysis of transcripts associations and gene ontology analysis were conducted to assess the enriched pathways for significant genes. Results In MCSA, B and CD4+ T cells proportions are significantly lower while that of myeloid cells higher in cases. The Emory cohort had similar trends. We identified transcripts associated with AD-related phenotypes in CD4+ T and CD8+ T cells. In CD4+ T cells, transcripts downregulated in case are enriched in response to stimulus pathway, whereas those upregulated in negative regulation of immune response. Downregulation of CD4+ T genes enriched in extracellular matrix disassembly and epigenetic regulation and upregulation of those in protein localization associate with better cognition. In CD8+T cells, genes pertinent to vascular development were downregulated while those to metabolic processes were upregulated in cases. Downregulation of CD8+T genes involved in lipid transportation and upregulation of those in mitochondria associate with better cognition. Conclusion We identified peripheral cellular transcriptional changes associated with AD/MCI phenotypes and involved in important biological pathways, revealing potential disease mechanisms in AD. Funding Source RF1 AG051504 Topic Categories Neuroimmunology (NEUR)

BackgroundBladder cancer (BC) can be characterized clinically as either non-muscle-invasive (NMIBC) or muscle-invasive (MIBC). While NMIBC generally has a favorable prognosis, MIBC is characterized by high morbidity and mortality. Understanding the molecular determinants of tumor invasion is critical, yet research is hampered by the limitations of current experimental models. Standard assays such as the Boyden chamber lack physiological complexity, while porcine bladder models suffer from tissue contamination and genetic variability. There is an urgent need for reliable models that mimic the intact tissue architecture.MethodsWe established a unique ex vivo tissue invasion model (EXTIM) to evaluate the invasive capacity of BC cells within a largely intact tissue context, using freshly prepared bladders from mice. The invasiveness of human BC cells (RT4, T24, UMUC3) and the immortal urothelial cell strain (Y235T) was comparably evaluated using EXTIM, the Boyden chamber, and porcine models. Gene knockdown or ectopic expression of GJB3 or ORP3 indicated the suitability of EXTIM to investigate the impact of specific factors on tumor cell invasion. To identify novel genetic regulators of cell invasion, we combined EXTIM with a genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 knockout screen. Additionally, we utilized the EXTIM to perform a pharmacological screen of a small molecule library comprising 90 substances to identify compounds capable of suppressing BC cell dissemination.ResultsImportantly, by combining EXTIM with genomewide CRISPR-Cas9 screening, we identified several candidate genes involved in BC progression. Notably, discoidin domain receptor tyrosine kinase 1 (DDR1) was identified as a functional inhibitor of tumor cell invasion. Furthermore, the small-molecule screen revealed that PD-156707, a selective antagonist of the endothelin receptor A (ETA), significantly suppresses cancer cell invasion within the EXTIM environment.ConclusionsEXTIM serves as a robust and physiologically relevant tool for assessing tumor cell invasion and migration under ex vivo conditions. EXTIM can be used to identify factors involved in the progression of invasive BC by high-throughput genetic screenings in an ex vivo organ culture system, by culturing cells after transmigration through the bladder tissue. Moreover, the impact of specific genetic factors in the process of tumor cell dissemination can be assessed by placing bladders from genetically modified mice into the EXTIM.

We present the first results of the search for sub-MeV fermionic dark matter absorbed by electron targets of germanium using the 205.4 kg . day data collected by the CDEX-10 experiment, with the analysis threshold of 160 eVee. No significant dark matter (DM) signals over the background are observed. Results are presented as limits on the cross section of DM-electron interaction. We present new constraints of cross section in the DM range of 0.1-10 keV/c(2) for vector and axial-vector interaction. The upper limit on the cross section is set to be 6.8 x 10(-46) cm(2) for vector interaction, and 2.3 x 10(-46) cm(2) for axial-vector interaction at DM mass of 5 keV/c(2).

Alzheimer's disease (AD) brains have variable neuropathologic and biochemical changes. Capturing epigenetic factors associated with this variability can reveal novel biological insights into AD pathophysiology. Here, we conduct an epigenome-wide association study of DNA methylation in 472 AD brains with neuropathologic and biochemical brain protein levels core to AD pathogenesis. Using a novel regional methylation (rCpGm) approach, we identify 5478 significant associations, 99.7% of which associate with tau biochemical measures, and 93 concordant associations in external datasets. Transcriptome-methylome integration reveals enrichment in oligodendrocyte genes, including known AD risk gene BIN1, myelination genes MYRF, MBP and MAG previously implicated in AD, and novel genes like LDB3. Further characterization of these perturbations in independent AD and primary tauopathy datasets highlights consistent tau-related associations. In summary, we uncover the integrative epigenomic landscape of AD, demonstrate tau-related oligodendrocyte gene perturbations as a common potential pathomechanism across tauopathies and share findings via our Multiomic Atlas.

Identification of gene expression changes in postmortem brain tissue of Alzheimer's disease donors compared to controls has implicated numerous biological pathways for Alzheimer's disease pathophysiology. Nonetheless, there is still limited understanding of how gene expression dysregulation underpins specific proteinopathies core to Alzheimer's disease. Here, we investigate brain transcriptomic changes in a well-characterized cohort of Alzheimer's disease donors to identify genes and networks that associate with Alzheimer's disease endophenotypes, including neuropathology measures (Braak stage, Thal phase and cerebral amyloid angiopathy score) and Alzheimer's disease-related brain protein levels (Apolipoprotein E, Amyloid-β 40, Amyloid-β 42, tau and phospho-Tau). Bulk transcriptome measures were collected from the temporal cortex tissue of 477 Alzheimer's disease donors. Following quality control, transcriptome-wide association studies were performed for each endophenotype. We used weighted gene co-expression network analysis to build co-expression networks and integrated transcriptome with epigenetic and genetic data from the same donors. We detected a total of 5740 Bonferroni-significant temporal cortex gene associations with Alzheimer's disease endophenotypes, most of which were with brain tau levels. We discovered tau-associated co-expression modules enriched in known and novel Alzheimer's disease pathways. We found that a beneficial (or neutral) brain biochemical state of higher total tau and lower phospho-Tau is associated with increased levels of synaptic, DNA damage/repair, nucleic acid metabolism and myelin processes. In contrast, in a detrimental state with lower total and higher phospho-Tau, there is upregulation of vascular and immune, and downregulation of mitochondrial and myelin pathways. There are brain gene expression perturbations that are associated with Alzheimer's disease endophenotypes. While some of these associations are common across multiple endophenotypes, many are distinct for different Alzheimer's disease-related proteins. Based on these findings, we propose a hypothetical model of dynamic brain gene expression changes that track with progressive Alzheimer's disease proteostasis. These expression changes hold potential to serve as dynamic, precision biomarkers of brain Alzheimer's disease progression. This study demonstrates the potential of integrative multi-omics and deep Alzheimer's disease endophenotypes in well-characterized brain tissues to precisely uncover the complex biology of Alzheimer's disease.

Alzheimer’s disease (AD) patients have decline in cognitive domains including memory, language, visuospatial, and/or executive function and brain pathology including amyloid-β and tau deposition, neurodegeneration, and frequent vascular co-pathologies detectable by neuroimaging and/or cerebrospinal fluid biomarkers. However, molecular disease mechanisms are complex and heterogeneous. It is necessary to develop cost-effective blood-based biomarkers reflecting brain molecular perturbations in AD. We identified blood-based gene and co-expression network level changes associated with AD/mild cognitive impairment (MCI) diagnosis and AD-related phenotypes. We performed differential gene expression and weighted gene co-expression network analysis, followed by meta-analysis, using blood transcriptome data of 391 participants from the Mayo Clinic Study of Aging and 654 participants from the Alzheimer's Disease Neuroimaging Initiative. The neuroimaging phenotypes include microhemorrhages, infarcts, amyloid burden, hippocampal volume, and white matter hyperintensities. The cognitive phenotypes include standardized cognitive subtest scores and composite scores for memory, language, visuospatial, and executive function. Five out of 18 modules(M) are significantly associated with diagnosis or cognition (FDR-adjusted p<0.05). M1 and M15 both positively associates with memory, M1 positively associated with language and M15 with visuospatial function. M1 and M15 are enriched in differentially expressed genes (DEGs) associated with language and executive function, respectively. M2 negatively associates with logical memory delayed recall scores(LMDR), memory, executive, and language functions and is enriched in DEGs for these phenotypes. M8 negatively associates with memory, language and executive functions and is enriched in DEGs for memory and language. M12 positively associates with LMDR. M1 and M15 are down-regulated while M2 and M8 are up-regulated in AD/MCI patients. Cell-type enrichment analysis showed M2 is enriched in monocytes and neutrophils; M8 in monocytes; M15 in B cells (FDR <0.05). Gene ontology terms enriched in these modules indicated broad consistency with their cell types. We identified five modules significantly associated with AD/MCI or cognitive phenotypes using blood transcriptome data. These findings nominate blood transcriptome changes and their enriched biological processes as potential pathomechanisms in cognitive decline and AD/MCI development. We aim to investigate these blood transcripts as potential biomarkers for AD or AD-related phenotypes and therapeutic targets through additional replication and experimental validation studies.

INTRODUCTION:Cerebrovascular lesions are associated with cognitive impairment. However, the impact of AD neuropathological changes (ADNC) on cerebral microvasculature is not completely understood. METHODS:Twelve decedents with ADNC and 15 matched controls were selected from the Brain Bank. The changes in the median tunica and basement membrane-related extracellular matrix (ECM) contents of the microvasculature were quantified and compared. Additionally, we explored the related mechanisms of agrin in pericytes. RESULTS:Venular collagenosis was significantly more severe in AD patients (p < 0.001), and ECM remolding was significantly correlated with ADNC. In the AD group, blood-brain barrier (BBB) disruption and decreased pericytes were observed. Finally, we confirmed that agrin induced ferroptosis in pericytes and BBB disruption in vitro. DISCUSSION:Our data indicate that venular collagenosis and significant ECM remolding are important contributors to ADNC. The mechanism by which agrin's role in disrupting the BBB by inducing ferroptosis presents a potential new target. HIGHLIGHTS:Changes in the median tunica and basement membrane-related ECM contents of the microvasculature were quantified in human brains. Venular collagenosis was significantly more severe in AD patients. In the AD group, BBB disruption and ECM remodeling were important contributors to AD neuropathological changes. Agrin disrupted the BBB by inducing ferroptosis in pericytes, which presents a potential new target.

Alzheimer's disease (AD) affects all brain cells and has complex genomic and immunological alterations. Previous research discovered missense AD risk or protective variants in microglial genes ABI3 and PLCG2, respectively. Expression levels of these genes are altered in AD and can influence microglial function. This study aims to uncover protective, and risk microglial molecular signatures associated with these variants to determine their role in microglial subtypes and states in AD by single cell expression and functional studies. We generated microglia-enriched snRNAseq data from donors harboring either AD protective PLCG2 or AD risk ABI3 missense mutations, or neither mutation. After standard snRNAseq QC, we performed differential expressed gene (DEG) analysis of all microglial cells between variant carriers and non-carriers using MAST. We defined protective signature as genes that are both down in ABI3 and up in PLCG2 mutation-carriers. In contrast, risk signature genes are up in ABI3 and down in PLCG2 mutation-carriers. We investigated the conservation of protective and risk signatures across multiple datasets, including scRNAseq data from iPSC-derived microglia cells carrying PLCG2 protective variant, snRNAseq data from AD-resilient donors, and data from AD and other diagnostic groups across multiple brain regions sourced from external datasets. We obtained snRNAseq profiles of 35,000 microglia from AD variant carriers. Our DEG analysis among all microglia cells provided 227 microglial protective and 293 risk signature genes defined by these variants. Using integrated analysis of multiple internal and external datasets, we further narrowed down these signatures. We determined that these high-confidence protective signature genes are downregulated in early AD, upregulated in late AD brains and positively-correlated with protective variant load in in vitro models. In contrast, risk signature genes are upregulated in early AD, downregulated in late AD and resilient donors. Risk signature expression is decreased with protective PLCG2 variant load, and altered with Aβ treatment in in vitro models. Our study uncovers microglia specific protective and risk signatures associated with AD using sn/scRNAseq datasets from multiple sources and models. These findings nominate novel immune targets and pathways with implications for microglial function in health and disease, and ultimately therapeutic potential.

Alzheimer’s disease (AD) is neuropathologically characterized by amyloid-β (Aβ) plaques and tau neurofibrillary tangles often quantified by Thal phase and Braak stage, respectively. Aβ also frequently deposits in the cerebrovasculature with severity categorized by a cerebral amyloid angiopathy (CAA) score. These and related measures often show high variability within AD suggesting distinct underlying mechanisms. We hypothesize that, within the AD brain, neuropathology and levels of core AD-related proteins are influenced by variations in DNA methylation (DNAm). To test this, we performed epigenome-wide association studies (EWAS) using DNAm measures from the temporal cortex (TCX) and cerebellum (CER) with AD-related neuropathologic measures (Braak, Thal, CAA) and brain biochemical levels of five proteins (apoE, Aβ40, Aβ42, tau, p-tau). DNAm from neuropathologically-confirmed AD cases was measured by reduced representation bisulfite sequencing (RRBS) from 471 TCX samples, 200 of which also had CER RRBS. TCX levels of five AD-related proteins from three tissue fractions (buffer-, detergent-, and in-soluble) were measured previously by ELISA (Liu 2020). CpG methylation (CpGm) was binned by a 15-state chromatin model (Kundaje 2015) and averaged into CpGm clusters (rCpGm). rCpGms were tested for association with each AD endophenotype and expression levels of nearby genes through multi-variable linear regression. Replication of significant rCpGms was performed in two independent datasets with AD-related endophenotypes (Shireby 2022, De Jager 2014). Our innovative binning method demonstrated biologically relevant CpGm patterns. We found epigenome-wide significant associations primarily with tau-related endophenotypes including 93 that had significant and concordant associations in the replication datasets. These rCpGms also significantly associated with expression of nearby genes showing enrichment in oligodendrocyte marker genes including those related to myelination. In vitro validation of tau effects on oligodendrocyte gene expression through DNAm is ongoing. Although all endophenotypes tested are core to AD pathophysiology, our results suggest each has a distinct epigenetic architecture underlying their variability in the AD brain. In particular, we found evidence of DNAm variability associating with brain oligodendrocyte gene expression and TCX tau levels. By discovering AD brain endophenotype-specific DNAm changes, we can identify core components of complex mechanisms revealing important biological insights into AD pathophysiology.

African Americans (AA) are twice as likely to develop dementia than non-Hispanic Whites but remain underrepresented in Alzheimer's Disease (AD) research. Recent studies have identified AA specific risk factors for AD. Therefore, targeted biomarkers and/or therapies may be needed to effectively treat AD in AA. In this study, we aimed to determine if genetic variants that show association with AD-risk, plasma transcript or protein levels in AA, may serve as accurate and accessible AD biomarkers. In 189 clinically diagnosed AA AD cases and 183 AA cognitively unimpaired (CU) controls, we performed targeted DNA sequencing of 10 AD-associated loci. Genetic variants at these loci were tested for association with corresponding plasma transcripts and total tau protein levels previously measured in this cohort using a custom nanoString panel and Simoa assays, respectively. Utilizing phased haplotypes (SHAPEIT4) from target sequencing, we inferred local ancestry (RFMix v2) using five superpopulations from the 1000 Genomes Project as anchors. Subsequently, we tested the association of each ancestry specific allelic dosages with endophenotypes using Tractor. In receiver operating characteristic (ROC) analyses, the most significant e/pQTLs were added sequentially to a base model that included age and sex to identify e/pQTLs that improved the accuracy to correctly classify AD cases and CU controls. Of the 5,112 variants that were tested, 70 were nominally associated with AD-risk and with plasma transcript or protein levels. Seven of these 70 variants also showed nominally significant associations of AD-risk and transcript levels with either African or East Asian local ancestry. ROC analysis of age, sex, 33 e/pQTLs in APOE , SORL1 , TLR4 , EPHA1 , ABCA7 , CLU , and CR1 , and plasma levels of APP, ABCA7, AKAP9, CD14, CLU, and APOE -ɛ4 dosage achieved 88.2% area under the curve to discriminate AD vs. CU, a 30.4% improvement over the base model that only included age and sex. Plasma transcript levels and e/pQTLs are promising diagnostic biomarkers for AD that may improve accessibility and reduce costs for a more accurate diagnosis of AD.

Performing complete deconvolution analysis for bulk RNA-seq data to obtain both cell type specific gene expression profiles (GEP) and relative cell abundances is a challenging task. One of the fundamental models used, the nonnegative matrix factorization (NMF), is mathematically ill-posed. Although several complete deconvolution methods have been developed, and their estimates compared to ground truth for some datasets appear promising, a comprehensive understanding of how to circumvent the ill-posedness and improve solution accuracy is lacking. In this paper, we first investigated the necessary requirements for a given dataset to satisfy the solvability conditions in NMF theory. Even with solvability conditions, the 'unique' solutions of NMF are subject to a rescaling matrix. Therefore, we provide estimates of the converged local minima and the possible rescaling matrix, based on informative initial conditions. Using these strategies, we developed a new pipeline of pseudo-bulk tissue data augmented, geometric structure guided NMF model (GSNMF$ + $). In our approach, pseudo-bulk tissue data was generated, by statistical distribution simulated pseudo cellular compositions and single-cell RNA-seq (scRNA-seq) data, and then mixed with the original dataset. The constituent matrices of the hybrid dataset then satisfy the weak solvability conditions of NMF. Furthermore, an estimated rescaling matrix was used to adjust the minimizer of the NMF, which was expected to reduce mean square root errors of solutions. Our algorithms are tested on several realistic bulk-tissue datasets and showed significant improvements in scenarios with singular cellular compositions.

Systemic inflammation plays a pivotal role in many chronic diseases including Alzheimer’s disease (AD). Assessing the composition of immune pathways in neurodegenerative diseases can contribute to precision medicine. Using publicly available transcriptomic data, we sought to elucidate transcriptional networks pertinent to inflammatory pathways across brain regions and peripheral blood in AD/mild cognitive impairment (MCI) and peripheral blood in Parkinson’s disease (PD). For the AD/MCI vs. control dataset, we analyzed bulk-RNAseq collected from 6 brain regions of donors from ROSMAP, Mayo Clinic, and Mount Sinai School of Medicine (MSSM) brain banks available from the AMP-AD consortium. Ante-mortem, blood RNAseq expression data was retrieved from the AMP-AD Emory Vascular cohort and Mayo Clinic Study of Aging (MCSA). We also collected blood-derived microarray expression data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). For the PD vs Control dataset, blood-derived bulk-RNAseq from the PDBP and PPMI cohorts were available through the AMP-PD consortium. Following quality control, normalization, and residual generation to account for biological and technical variables, co-expression network modules and their enriched pathways were identified using WGCNA within each dataset. Module/trait correlation tests for aging and diagnosis (cases [AD/MCI or PD] vs control) phenotypes were evaluated. Gene Ontology enrichment analyses were executed to identify enriched pathways and brain or blood cell types within the modules. Modules were tested for preservation across cohorts. We identified conserved immune signatures across brain regions and cohorts. Modules involved in immune response were preserved across all cohorts. Blood consensus modules involved in immune response were preserved in the brain and vice versa. Some immune modules were associated with AD/MCI, PD, and/or aging. Brain immune modules are significantly associated with aging and/or AD. Significant correlations (q<0.05) with PD diagnosis were present. In the MCSA and Emory vascular cohorts, there were no significant (q<0.05) associations between modules and diagnosis, while in ADNI there were nominal (p<0.05) associations. Preserved transcriptional immune networks were identified across blood and brain and across two neurodegenerative diseases. Expanding gene co-expression network analyses to other diseases and integrating additional omics measures and phenotypes can further strengthen these findings to unravel the immune signatures across complex diseases.

Blood-brain barrier (BBB) dysfunction is a key feature of Alzheimer's disease (AD), particularly in individuals carrying the APOE-ε4 allele. This dysfunction worsens neuroinflammation and hinders the removal of toxic proteins, such as amyloid-beta (Aβ42), from the brain. In post-mortem brain tissues and in animal models, we previously reported that fibronectin accumulates at the BBB predominantly in APOE-ε4 carriers. Furthermore, we found a loss-of-function variant in the fibronectin 1 ( FN1 ) gene significantly reduces aggregated fibronectin levels and decreases AD risk among APOE-ε4 carriers. Yet, the molecular mechanisms downstream of fibronectin at the BBB remain unclear. The extracellular matrix (ECM) plays a crucial role in maintaining BBB homeostasis and orchestrating the interactions between BBB cell types, including endothelia and astrocytes. Understanding the mechanisms affecting the ECM and BBB cell types will be critical for developing effective therapies against AD, especially among APOE-ε4 carriers. Here, we demonstrate that APOE-ε4 , Aβ42, and inflammation drive the induction of FN1 expression in several models including zebrafish, mice, iPSC-derived human 3D astrocyte and 3D cerebrovascular cell cultures, and in human brains. Fibronectin accumulation disrupts astroglial-endothelial interactions and the signalling cascade between vascular endothelial growth factor (VEGF), heparin-binding epidermal growth factor (HBEGF) and Insulin-like growth factor 1 (IGF1). This accumulation of fibronectin in APOE-ε4- associated AD potentiates BBB dysfunction, which strongly implicates reducing fibronectin deposition as a potential therapeutic target for AD. Graphical abstract: Accessibility text:This image illustrates the effects of different APOE isoforms (ApoE-ε3 and ApoE-ε4) on blood-brain barrier (BBB) integrity, focusing on the molecular interactions between astrocytes and endothelial cells. This figure emphasizes the detrimental effects of ApoE-ε4 on BBB integrity via fibronectin accumulation and altered signaling pathways. The top section provides a schematic overview of the blood-brain barrier, highlighting astrocytes, endothelial cells, and their interface. The left panel represents the ApoE-ε3 condition: Normal fibronectin (FN1) levels support healthy interactions between astrocytes and endothelial cells. Growth factors, including VEGFA, HBEGF, and IGF1, maintain BBB integrity through their respective receptors (VEGFR and EGFR). Green arrows indicate activation of these signaling pathways. The right panel depicts the ApoE-ε4 condition: Elevated fibronectin (FN1) disrupts astrocyte-endothelium interactions. FN1 binds integrins and activates focal adhesion kinase (FAK), inhibiting VEGFA, which is required for endothelial HBEGF that in turn activates IGF1 signaling. Red symbols indicate inhibition of HBEGF, VEGFA, and IGF1 pathways, leading to BBB dysfunction. Highlights:APOE-ε4 drives fibronectin deposition in Alzheimer's, disrupting astrocyte-endothelia interactions. APOE-ε4 and fibronectin co-localize, forming aggregates at blood-brain barrier (BBB). Fibronectin alters the signaling between VEGF, IGF1, and HBEGF impairing BBB function. Reducing fibronectin restores BBB integrity and offsets APOE-ε4 pathology.

Genetic variations have emerged as crucial players in the etiology of Alzheimer’s disease (AD), and they serve for a better understanding of the disease mechanisms; yet the specific roles of these genetic variants remain uncertain. Animal models with reminiscent disease pathology could uncover previously uncharacterized roles of these genes. Therefore, we generated zebrafish models for AD variants to analyze the in depth molecular and biological functions of these variants. Using CRISPR/Cas9, we generated a knockout model for abca7 , orthologous to human ABCA7 . We performed single cell transcriptomics and analyzed the altered genes and molecular pathways in zebrafish. We leveraged data from multiethnic AD cohorts at Mayo Clinic and Columbia University, to perform genetic association studies, co-expression analyses, in silico interaction mapping, family based variant segregation analyses and epigenetic association studies, and the functional and histological studies in zebrafish. The abca7 ± zebrafish reduced astroglial proliferation, synaptic integrity, and microglial response after Aβ42 toxicity. We found that the abca7 loss-of-function (LOF) reduced neuropeptide Y ( npy ) expression as well as Brain-derived neurotrophic factor ( bdnf) and Nerve growth factor receptor (ngfr) . Human brain analysis showed reduced NPY in AD, regulatory interaction between NPY and BDNF , genetic variants in NPY associated with AD, and segregation of variants in ABCA7 , BDNF and NGFR in families. ABCA7 variants altered the epigenetic codes in NPY , BDNF , and NGFR promoter regions. Human results paralleled with zebrafish findings to indicate an evolutionarily conserved disease mechanism through ABCA7-NPY signalling axis. NPY administration to zebrafish rescued the phenotypes in abca7 knockout, suggesting a true biological relevance. Our results demonstrate a previously unknown link between ABCA7 and NPY in regulation of synaptic integrity and neurogenesis in AD. We propose that ABCA7-dependent NPY is a resilience factor in vertebrate brains, and this reserve mechanism is impaired in AD.

The microenvironment of the central nervous system is highly complex and plays a crucial role in maintaining the function of neurons, which influences Alzheimer’s disease (AD) progression. The pH value of the brain is a critical aspect of the brain microenvironment in regulating various physiological processes. However, the specific mechanisms and role of this mechanism are not yet fully understood. To better understand the relationship between brain pH and AD, we analyzed the brain pH of the frontal lobe and AD pathology scores in postmortem brain samples from 368 donors from the National Human Brain Bank for Development and Function, 96 of whom were diagnosed with AD pathology. Analysis revealed a significant decrease in brain pH in AD patients, which was strongly correlated with β-amyloid plaques and phosphorylated tau proteins. Here, we elucidated the differential protein expression level of CD68-positive microglia between control and AD groups (t = 3.198, df = 20, P = 0.0045), and its protein expression level was correlated negatively with the brain pH value (F = 26.93, p = 0.0006). Our findings revealed that increased activation of CD68-positive microglia and disrupted lysosomal homeostasis in the pathological brain tissue of individuals with AD may lead to a decrease in brain pH.

[This corrects the article PMC11643596.].

Two main risk factors of Alzheimer’s disease (AD) are aging and APOE-ε4. However, some individuals remain cognitively normal despite having these risk factors. They are considered “cognitively resilient”. This study aimed to identify molecular factors that confer cognitive resilience in APOE-ε4 carriers ≥ 80 years of age and may serve as biomarkers. We applied weighted gene co-expression network analysis (WGCNA) to generate consensus co-expression networks from blood of participants in two antemortem cohorts, the Mayo Clinic Study of Aging (MCSA, n=105), and the Alzheimer’s Disease Neuroimaging Initiative (ADNI, n=91), using RNA-sequencing and microarray data, respectively. We associated these networks with resilience (resilient vs non-resilient), cognitive endophenotypes and hippocampal volume. Preservation between consensus networks from blood and those derived from postmortem brain tissues of AD and control donors from AMP-AD (n=1174) was evaluated. We validated the human findings in four AD mouse models. Finally, machine learning models were utilized to discriminate cases (AD+mild cognitive impairment (MCI)) from controls in MCSA, ADNI and ANMerge antemortem cohorts. Four consensus networks were significantly correlated with a memory phenotype (logical memory delayed recall=LMDR) and hippocampal volume in both MCSA and ADNI. Among these, blood expression module M3 was most preserved with the brain transcriptome. M3 was enriched with NDUF hub genes that are involved in the mitochondrial respiratory chain. Expression levels of M3 and many blood NDUFs had significant associations with better LMDR and hippocampal volume. In brain, NDUFs were upregulated in controls compared to AD, and their expression levels were associated with better global cognition and decreased AD neuropathology. Many NDUFs were significantly downregulated in the hippocampus or cortex of AD mice compared to wild-types. Lastly, models that included blood NDUFs improved diagnostic accuracy of AD+MCI compared to models that only included demographic and risk variables (age, sex, APOE-ε4) in MCSA, ADNI and ANMerge. In MCSA and ADNI, adding NDUFs’ expression to models that included established blood biomarkers (Aβ42/40, ptau181, NFL) further improved diagnostic accuracy. Our results suggest that mitochondrial NDUFs are centrally-linked peripheral molecular signatures that may be resilience factors against AD and serve as both therapeutic targets and novel diagnostic biomarkers.

Our Alzheimer Disease Metabolomics Consortium (ADMC), part of the Accelerating Medicines Partnership for AD (AMP-AD) and in partnership with AD Neuroimaging Initiative (ADNI), applied state-of-the-art metabolomics and lipidomics technologies combined with genomic and imaging data to map metabolic failures across the trajectory of the disease. Our studies confirmed that peripheral metabolic changes influenced by the exposome inform about cognitive changes, brain imaging changes, and ATN markers for disease confirming that peripheral and central changes are connected, in part through the metabolome. To map the biochemical changes in AD, we used various targeted and untargeted metabolic platforms to profile ∼800 postmortem brain tissue, and ∼ 5000 blood samples. Recently, we built a comprehensive reference map of extensive AD-related metabolic changes in brain, spanning multiple AD-related traits, including neuropathological b-amyloid and tau tangle burden, as well as late-life cognitive performance. Using this resource, we extracted novel metabolic including bioenergetic pathways, cholesterol metabolism, neuroinflammation, broad impairment of osmoregulation, an imbalance between excitatory/inhibitory neurotransmitter ratios and identification of tau load as a potential driver of metabolic dysfunction in the AD brain, with minimal contributions from b-amyloid load. As AD and progressive supranuclear palsy (PSP) share the pathological feature of tauopathy and metabolic alterations, we compared their metabolomic profiles to identify shared biological pathways that could be targeted for therapeutic interventions. Our findings indicate that both diseases display oxidative stress, mitochondrial dysfunction, and tau-induced polyamine stress response. Overall, through our studies, (1) We identified biochemical processes altered in AD, with findings supported across both metabolomic and proteomic data, indicating multimodal deregulation. (2) Our research pinpointed widespread AD-related biochemical changes across various brain regions with differing levels of neuropathology. While there are many overlapping changes across the brain regions, each region also has its distinct metabolic alterations. (3) We identified biochemical processes disrupted by AD, with parallel findings in other neurodegenerative diseases, hinting at broader implications in neurodegenerative research. Currently, we are working on mapping widespread connections of the brain metabolome with various determinants of AD namely genome, gut microbiome, exposome, and linking with peripheral metabolic alterations in AD.