Ren, Yingxue

Abstract Glioblastoma (GBM) remains the most lethal primary brain cancer due to its remarkable metabolic plasticity and therapeutic resistance. Here, we identify cholesterol dependency as a therapeutically exploitable vulnerability in GBM using two FDA-approved drugs: the H1 histamine antagonist clemastine and the retinoid X receptor agonist bexarotene. Combined treatment induces potent synergistic anti-tumor activity across patient-derived glioma models, suppressing proliferation, stemness, and survival at sub-IC50 concentrations. Mechanistically, this therapy disrupts cholesterol biosynthesis, transport, and homeostasis, triggering endoplasmic reticulum stress and activation of the unfolded protein response, ultimately leading to autophagy and apoptotic cell death. Orthotopic patient-derived glioma models recapitulate these mechanisms in vivo, where local intracranial administration significantly reduces tumor progression and prolongs survival using fourfold lower doses than systemic intraperitoneal delivery. Single-cell RNA sequencing revealed activation of regeneration and plasticity programs, accompanied by immune microenvironment remodeling and enhanced inflammatory signaling. Importantly, syngeneic models preserved immune cell composition, supporting future integration with immunotherapeutic strategies. Together, these findings establish cholesterol dysregulation–induced metabolic collapse as a promising therapeutic approach for GBM.

Abstract Lewy pathology can form over decades in patients with Lewy body diseases, but the causal cellular mechanisms associated with this process remain unclear. This project aims to discover proteins that associate with monomeric and/or oligomeric alpha-synuclein during early stages of the aggregation process. To mimic the aggregation processes, cells expressing a synuclein-biotin ligase fusion protein were treated human recombinant pre-formed fibrils and subjected to BioSITe and mass spectrometry. Using a novel split biotin ligase fused to alpha-synuclein facilitated the identification of proteins specifically associated with multimeric alpha-synuclein. A total of 581 proteins were differentiated into potential interactors of monomeric versus multimeric alpha-synuclein in physiological versus aggregated conditions. The data reveal important phosphorylation mechanisms, connections to insulin processing, and a potential interaction with ALS-associated FUS. Interestingly, we identified that loss of specific interactions may contribute to pathology in patients with sporadic onset of Lewy body diseases. Future studies will validate both true interaction of highlighted proteins with alpha-synuclein, and the impact of such proteins on alpha-synuclein aggregation.

Abstract Smith-Lemli-Opitz syndrome (SLOS) is a rare, autosomal recessive disorder characterized by congenital malformations, intellectual disability, and behavioral abnormalities. SLOS results from mutations in the DHCR7 gene, leading to impaired cholesterol biosynthesis due to dysregulation of 7-dehydrocholesterol reductase. Cholesterol plays crucial roles in neurophysiology, including synaptic formation and neurotransmitter receptor regulation, which likely contribute to neurological manifestations in SLOS patients. While astrocytes are the main cholesterol producing cells in the brain, their specific role in SLOS pathogenesis remains unclear. In this study, we utilized induced pluripotent stem cell (iPSC)-derived astrocytes from a SLOS patient with DHCR7 c.C278T mutation and the isogenic control. We found decreased lipid droplet formation in SLOS iPSC astrocytes compared to controls, accompanied with diminished efflux of cholesterol and apolipoprotein E. Lipidomics revealed reduced cholesterol and cholesterol esters, as well as altered profiles of other lipids in SLOS iPSC astrocytes. While RNA-sequencing identified various genes and pathways affected by the disease status, those related to mitochondria functions were top-ranked. Mitochondrial electron transport chain oxidative phosphorylation gene expression decreased in SLOS iPSC astrocytes, alongside impaired mitochondrial respiration. Furthermore, SLOS iPSC astrocytes less effectively mediated neuroprotection on iPSC neurons than control astrocytes in serum-starvation conditions. SLOS iPSC astrocytes also poorly contributed to synaptic networks when co-cultured with iPSC neurons. Overall, our findings provide mechanistic insights into how DHCR7 disruption impacts astrocyte function, contributing to SLOS neuropathology by dysregulating lipid metabolism, mitochondrial respiration, and impaired neuroprotection.

Abstract Motivation Single-cell RNA sequencing (scRNA-seq) has become an important method for characterizing cellular heterogeneity, revealing more biological insights than the bulk RNA-seq. The surge in scRNA-seq data across multiple individuals calls for efficient and statistically powerful methods for differential expression (DE) analysis that addresses individual-level biological variability. Results We introduced DiSC, a method for conducting individual-level DE analysis by extracting multiple distributional characteristics, jointly testing their association with a variable of interest, and using a flexible permutation testing framework to control the false discovery rate (FDR). Our simulation studies demonstrated that DiSC effectively controlled the FDR across various settings and exhibited high statistical power in detecting different types of gene expression changes. Moreover, DiSC is computationally efficient and scalable to the rapidly increasing sample sizes in scRNA-seq studies. When applying DiSC to identify DE genes potentially associated with COVID-19 severity and Alzheimer’s disease across various types of peripheral blood mononuclear cells and neural cells, we found that our method was approximately 100 times faster than other state-of-the-art methods and the results were consistent and supported by existing literature. While DiSC was developed for scRNA-seq data, its robust testing framework can also be applied to other types of single-cell data. We applied DiSC to cytometry by time-of-flight data, DiSC identified significantly more DE markers than traditional methods. Availability and implementation The R software package “SingleCellStat” is freely available on CRAN (https://cran.r-project.org/web/packages/SingleCellStat/index.html) and GitHub (https://github.com/Lujun995/DiSC). The replication code for reproducing the analyses in this study is publicly accessible at https://github.com/Lujun995/DiSC_Replication_Code. The scRNA-seq expression matrix and metadata utilized in our simulations and analyses can be retrieved from https://cells.ucsc.edu/autism/rawMatrix.zip, https://cellxgene.cziscience.com/collections/1ca90a2d-2943-483d-b678-b809bf464c30, and https://covid19.cog.sanger.ac.uk/submissions/release1/haniffa21.processed.h5ad.

Pick’s disease (PiD) is a rare neurodegenerative disorder defined by dementia, frontotemporal lobe atrophy, and 3-repeat tau inclusions. To elucidate PiD pathobiology, we performed the first bulk transcriptomics study on PiD using short- and long-read sequencing on the parietal cortex of 28 PiD and 15 control samples. We identified several significantly differentially expressed genes, with CCL2 displaying the strongest association with 3-repeat tau pathology and increased burden in PiD compared to those in 4-repeat tau progressive supranuclear palsy (PSP) cases. Investigation of co-expressed genes and pathways suggested the involvement of mRNA processing, mitochondrial function, and immune processes in disease pathobiology. Long-read RNA sequencing on a subset of samples (eight PiD and four control) proposed novel, potentially disease-associated transcripts for AZGP1 , CD44 , HSD11B2 , and WIF1 , predicted to result in truncated proteins. In conclusion, we observed transcriptomic changes in the parietal cortex of patients with PiD that may inform into clinically relevant biomarkers and therapeutic strategies.

Abstract INTRODUCTION Loss‐of‐function variants of the ABCA7 gene are associated with an increased risk of Alzheimer's disease (AD). How neuronal ABCA7 contributes to AD pathogenesis is unknown. METHODS Using neuron‐specific Abca7 KO mice (n Abca7 −/− ) with or without 5×FAD amyloid model background and post mortem AD brains, we investigated AD‐related phenotypes through comprehensive approaches including transcriptomics and lipidomics. RESULTS Lipidomics analysis detected altered lipid profiles in the brains and synaptosomes of 5×FAD; n Abca7 −/− mice compared to controls. Transcriptomics profiling revealed that neuronal ABCA7 deficiency altered the expression of genes and pathways related to mitochondrial homeostasis and apoptosis, particularly in excitatory neurons. Consistently, synaptosomes isolated from 5×FAD; n Abca7 −/− mice showed diminished mitochondria respiration and reduced synaptic protein levels, which is further supported by results from human AD brains. DISCUSSION Our findings reveal that neuronal ABCA7 plays a critical role in mitochondrial homeostasis important for neuronal function and survival in the presence of AD pathology. Highlights Neuronal ABCA7 deficiency exacerbates Aβ pathology and neuronal damage in 5×FAD mice. Neuronal ABCA7 deficiency alters brain transcriptomes and lipidomes of 5×FAD mice. Neuronal ABCA7 deficiency disturbs mitochondria functions in synaptosomes from 5×FAD mice. Neuronal ABCA7 expression associates with genes and pathways related to mitochondrial homeostasis in AD brains.

ABSTRACT Recent development of single-cell technology across multiple omics platforms has provided new ways to obtain holistic views of cells to study disease pathobiology. Alzheimer’s disease (AD) is the most common form of dementia worldwide, yet the detailed understanding of its cellular and molecular mechanisms remains limited. In this study, we analyzed paired single-cell transcriptomic (scRNA-seq) and chromatin accessibility (scATAC-seq) data from the Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD) Consortium to investigate the molecular mechanisms of AD at a cell-subpopulation-specific resolution focusing on glial cells. We benchmarked various multi-omics integration methods using diverse metrics and built an analytic workflow that enabled effective batch correction and cross-modality alignment, creating a unified cell state space. Through integrative analysis of 26 human brain samples, we uncovered AD-associated gene expression and pathway changes in glial subpopulations and highlighted important transcriptomic and epigenomic signatures via functional inference and interpretable machine learning paradigms, discovering the profound involvement of the Solute Carrier proteins (SLC) family genes in multiple glial cell types. We also identified glial cell-specific regulatory programs mediated by key transcription factors such as JUN and FOSL2 in astrocytes, the Zinc Finger (ZNF) family genes in microglia, and the SOX family of transcription factors in oligodendrocytes. Our study provides a comprehensive workflow and a high-resolution view of how glial regulatory programs are disrupted in AD. Our findings offer novel insights into disease-related changes in gene regulation and suggest potential targets for further research and therapy.

AbstractBackgroundThe immune system is substantially involved in the development and progression of age‐related cognitive decline and Alzheimer’s disease (AD).MethodAs genetic and environmental factors interactively impact these conditions, we investigated how risk factors such as APOE genotype, age, and sex influence immune activation markers and AD biomarkers in cerebrospinal fluid (CSF) in elderly individuals enrolled in the Mayo Clinic Study of Aging cohort. Among cognitively unimpaired individuals aged over 65 at the baseline visit (N=298), we measured 365 CSF immune activation markers using the proximity extension assay.ResultWe found that age, sex, and diabetes status are associated with altered CSF levels of immune activation markers independently of other factors. For CSF AD biomarkers, we observed significant positive correlations between age and total tau, phosphorylated tau‐181 (p‐tau181), neurofilament light (NfL), and YKL40. APOE4 was also associated with lower Aβ42 and higher SNAP25 in CSF. We further examined whether baseline visit variables can predict cognitive decline, represented by the conversion from CDR=0 to CDR>0. We found that age, Aβ42, NfL, and REG4 were independently correlated with CDR conversion risk. When the cohort was dichotomized by their median values, older participants with lower Aβ42, higher NfL, and higher REG4 at baseline developed cognitive impairment during the follow up with a c‐index of 0.762 while age alone had a c‐index of 0.699.ConclusionTogether, our results suggest that assessing CSF immune activation markers and AD biomarkers can improve the prediction of cognitive impairment risk in the elderly.

AbstractBackgroundTwo 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.MethodWe 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.ResultFour 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.ConclusionOur 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.

AbstractBackgroundThe immune system is substantially involved in the development and progression of age‐related cognitive decline and Alzheimer’s disease (AD).MethodAs genetic and environmental factors interactively impact these conditions, we investigated how risk factors such as APOE genotype, age, and sex influence immune activation markers and AD biomarkers in cerebrospinal fluid (CSF) in elderly individuals enrolled in the Mayo Clinic Study of Aging cohort. Among cognitively unimpaired individuals aged over 65 at the baseline visit (N=298), we measured 365 CSF immune activation markers using the proximity extension assay.ResultWe found that age, sex, and diabetes status are associated with altered CSF levels of immune activation markers independently of other factors. For CSF AD biomarkers, we observed significant positive correlations between age and total tau, phosphorylated tau‐181 (p‐tau181), neurofilament light (NfL), and YKL40. APOE4 was also associated with lower Aß42 and higher SNAP25 in CSF. We further examined whether baseline visit variables can predict cognitive decline, represented by the conversion from CDR=0 to CDR>0. We found that age, Aß42, NfL, and REG4 were independently correlated with CDR conversion risk. When the cohort was dichotomized by their median values, older participants with lower Aß42, higher NfL, and higher REG4 at baseline developed cognitive impairment during the follow up with a c‐index of 0.762 while age alone had a c‐index of 0.699.ConclusionTogether, our results suggest that assessing CSF immune activation markers and AD biomarkers can improve the prediction of cognitive impairment risk in the elderly.