Although dietary cholesterol is known to exacerbate liver disease progression, whether and how it contributes to hepatic steatosis, the hallmark early pathological feature of both MASLD and ALD, remains poorly understood. Here, we investigated how cholesterol disrupts hepatic triacylglycerol metabolism using both dietary and cellular cholesterol-loading models. Integrated transcriptomic, metabolomic, and biochemical analyses were performed, and causality was examined through genetic and pharmacologic modulation in multiple hepatocyte systems and mice. Our results demonstrate that cholesterol overload induces hepatocellular fat accumulation in a dose-dependent, cell-autonomous manner, primarily by suppressing fatty acid β-oxidation. Mechanistically, we identified PPARα inhibition as a key event underlying this effect. Cholesterol overload suppressed PPARα transactivation, thereby impairing fatty acid β-oxidation and promoting hepatocellular fat accumulation. This inhibition was mechanistically linked to reduced O-GlcNAcylation. Specifically, cholesterol overload downregulated OGT, leading to reduced protein O-GlcNAcylation and consequent PPARα inhibition; similarly, liver-specific OGT knockout mice exhibited suppressed PPARα activity and increased hepatic fat accumulation. RNA-sequencing and co-immunoprecipitation analyses identified PPARα as an O-GlcNAc-modified protein, and loss of this modification impaired its transactivity. Functionally, restoration of O-GlcNAcylation via genetic OGA knockdown or pharmacological activation of PPARα with WY14643 alleviated cholesterol-induced hepatic steatosis in mice without altering hepatic cholesterol levels. Lastly, we identified SREBP2 as the upstream transcriptional regulator linking cholesterol overload to OGT suppression. In conclusion, our findings in this study uncover a previously unrecognized cholesterol-OGT-PPARα axis that suppresses hepatic fatty acid β-oxidation and drives steatosis. Targeting O-GlcNAc cycling or activating PPARα represents a promising therapeutic strategy for MASLD.

Alzheimer's Disease (AD) is a multifactorial neurodegenerative disorder marked by extensive biological and clinical heterogeneity, complicating prognosis and personalized treatment strategies. Because of this, data-driven methods that characterize patient similarity and subgroup-specific molecular signatures are essential for advancing precision medicine in AD. We applied manifold learning techniques to fuse proteomic, demographic, and clinical data from 438 AD patients, enabling the identification of "digital siblings"-patients with closely related molecular and clinical profiles within a learned latent space. This framework enabled robust clustering and stratification of patient subgroups, revealing distinct pathway enrichments associated with clinical traits such as age, alcohol use, and comorbidities. Moreover, structural and network analyses of key protein interactions within these subgroups provided insights into the molecular mechanisms potentially driving disease heterogeneity. While this approach primarily clustered patients based on comprehensive molecular patterns, it lays critical groundwork for developing predictive models that incorporate longitudinal progression and intervention outcomes. Overall, our results underscore the potential of "digital sibling"-based stratification to refine patient subgroup characterization and serve as a foundation for future dynamic modeling in AD.

O-GlcNAcylation is a dynamic and reversible post-translational modification contributing to various cellular processes and diseases. Despite its growing relevance, standardized methodologies and reproducibility remain challenges in the field. To address this, we conducted an international survey among researchers active in O-GlcNAc research to identify current practices, bottlenecks, and consensus recommendations. Here, we present the key findings of O-GlcNAc researchers worldwide. The data reveal variability in detection techniques, sample preparation, and data interpretation, underscoring the need for harmonized protocols. Based on these insights, we propose a set of best practices to improve rigor and reproducibility in O-GlcNAc research.

Patient iPSC-derived cerebral organoids are a leading human model of Alzheimers disease, yet their proteome has never been benchmarked against human disease. Clinical cohorts now nominate thousands of biomarkers and drug targets across three proteomic platforms, and whether patient organoids capture these candidates is unknown. Here, we profile AD and control cerebral organoids containing neurons, astrocytes, and microglia on the three platforms driving clinical discovery, mass spectrometry, SomaScan, and Olink, in both conditioned media and lysate. Benchmarked against 121 studies and clinical cohorts of over 17,000 plasma, CSF, and cortex samples, patient organoids detect almost every nominated candidate and reproduce the disease-associated change in roughly one in four of the most reproducible. This convergence spans plasma, CSF, and cortex, and extends to synaptic, mitochondrial, and proteostatic biology. We provide the first multi-platform reference proteome of a patient-derived AD model, establishing it as a translationally relevant system for studying AD.

Apolipoprotein E (APOE) genetic variation is the strongest genetic risk factor for Alzheimer’s Disease (AD). Prior studies on APOE genotype-dependent changes have largely focused on amyloid beta (Aβ) aggregation and lipid metabolism. There is an increased interest in the relationship between metabolic function and APOE genetic variation. We examined how APOE genotype affects brain metabolism in young APOE3 and APOE4 targeted replacement (TR) mice. In addition, we examined cell type-specific differences using induced pluripotent stem cell (iPSC)-derived astrocytes and neurons. We found sex and APOE genotype dependent changes to brain metabolism where APOE4 mice show signs of metabolic stress. Using proteomics and stable isotope tracing, we found that APOE4 iAstrocytes and iNeurons exhibit mitochondrial dysfunction, altered citric acid cycle (TCA) cycle, and a metabolic shift from oxidative metabolism towards glycolysis. Taken together, this data indicates APOE4 causes early changes to metabolism within the central nervous system, and this has implications for early intervention to prevent AD. These metabolic alterations may contribute to the inflammatory changes observed in APOE4 cells, linking disrupted energy metabolism with immune activation in the brain. While this study establishes a relationship between APOE genotype and dysregulated bioenergetics, additional studies are needed to investigate underlying mechanisms.

Apolipoprotein E (APOE) genetic variation is the strongest genetic risk factor for late onset Alzheimer's disease (LOAD). Studies on APOE genotype dependent changes have largely focused on amyloid beta (Aβ) aggregation, disease pathology, and lipid metabolism. Recently, there has been increased interest in the relationship between metabolic function and APOE genetic variation. In this study, we examined how APOE genotype can alter metabolism in the brains of young male and female APOE3 and APOE4 targeted replacement (TR) mice. In combination with this, we also examined cell type-specific differences using induced pluripotent stem cell (iPSC) derived astrocytes and neurons. We found sex and genotype dependent changes to metabolism in the brains of young APOE TR mice. Specifically, APOE4 mice show signs of metabolic stress and compensatory mechanisms in the brain. Using proteomics and stable isotope tracing metabolomics, we found that APOE4 iAstrocytes and iNeurons exhibit signs of inflammation, mitochondrial dysfunction, altered TCA cycle and malate-aspartate shuttle activity, and a metabolic shift toward glycolysis. Taken together, this data indicates APOE4 causes early changes to metabolism within the central nervous system. While this study establishes a relationship between APOE genotype and alterations in bioenergetics, additional studies are needed to investigate underlying mechanisms.

The APOE ε4 genetic variant is the strongest genetic risk factor for late-onset Alzheimer's disease (AD) and is increasingly being implicated in other neurodegenerative diseases. Using the Global Neurodegeneration Proteomics Consortium SomaScan dataset covering 1,346 cerebrospinal fluid (CSF) and 9,924 plasma samples, we used machine learning-based proteome profiling to identify an APOE ε4 proteomic signature shared across individuals with AD, frontotemporal dementia (FTD), Parkinson's disease dementia (PDD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS) and nonimpaired controls. This signature was enriched in pro-inflammatory immune and infection pathways as well as immune cells, including monocytes, T cells and natural killer cells. Analysis of the dorsolateral prefrontal cortex proteome for 262 donors from the Accelerating Medicines Partnership for AD UPenn Proteomics Study revealed a consistent APOE ε4 phenotype, independent of neurodegenerative pathology, including amyloid-β tau and gliosis for all diseases, as well as TDP-43 in ALS and FTD cases, and α-synuclein in PD and PDD cases. While systemic proteomic changes were consistent across APOE ε4 carriers, their relationship with clinical and lifestyle factors, such as hypertension and smoking, varied by disease. These findings suggest APOE ε4 confers a systemic biological vulnerability that is necessary but not sufficient for neurodegeneration, emphasizing the need to consider gene-environment interactions. Overall, our study reveals a conserved APOE ε4-associated pro-inflammatory immune signature persistent across the brain, CSF and plasma irrespective of neurodegenerative disease, highlighting a fundamental, disease-independent biological vulnerability to neurodegeneration. This work reframes APOE ε4 as a pleiotropic immune modulator rather than an AD-specific risk gene, providing a foundation for precision biomarker development and early intervention strategies across neurodegenerative diseases.

Large-scale plasma proteomics offers unprecedented opportunities to investigate the systemic biology of neurodegeneration, yet technical heterogeneity, site-specific artifacts, and clinical confounding remain major barriers to reproducible discovery. Leveraging data from 13,733 individuals with Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD), Parkinson's disease dementia (PDD), amyotrophic lateral sclerosis (ALS), and non-impaired controls in the Global Neurodegeneration Proteomics Consortium (GNPC), we present a scalable and generalizable analytical framework for harmonizing and interpreting consortium-scale proteomic datasets. Using a high-dimensional perturbation framework, we systematically benchmark five commonly used batch correction methods across a range of realistic confounding structures, including site-disease imbalance, nonlinear effects, and heteroskedasticity. Empirical Bayes modelling via limma consistently emerged as the most robust method, optimally balancing removal of site-related technical variance with retention of disease-relevant biological signal. On this harmonized foundation, we resolve neurodegenerative disease plasma signatures, including a shared immune-metabolic axis in AD and PD, neuromuscular disruption in ALS, and proteostatic imbalance in PD. Tissue and cell-type enrichment highlight widespread immune-endocrine involvement in AD and hematopoietic activation in PD. Demographically matched analyses nominate distinct, candidate biomarkers across diseases, including lipid, redox, and complement factors in AD, lysosomal and cytoskeletal proteins in PD, and muscle-derived markers in ALS. This study establishes a scalable analytical framework for integrating real-world proteomic data and provides a disease-resolved catalogue of circulating signatures to inform biomarker development and targeted intervention across neurodegenerative diseases.

Aberrant cell metabolism drives autosomal dominant polycystic kidney disease (ADPKD). O-GlcNAcylation, a metabolically regulated post-translational modification, is elevated in ADPKD kidneys. Using rapidly and slowly progressive ADPKD mouse models, we demonstrate that deleting O-GlcNAc transferase (Ogt) reduces renal cystogenesis and extends survival in a rapidly progressive model from postnatal day 21 to over a year. Pharmacological OGT inhibition similarly reduced cyst formation of patient-derived renal epithelial cells in vitro. In Pkd1 conditional knockout kidneys, Ogt deletion maintained phosphorylated AMPK and mitochondrial respiratory chain complex levels, preserving cellular energy sensing and production. Further, metabolomic analysis revealed normalization of glycolysis and of the hexosamine and hyaluronic acid biosynthesis pathways. In contrast, dysregulation of these pathways in Pkd1 conditional knockout kidneys culminated in increased tricarboxylic acid cycle entry, increased O-GlcNAc, and increased hyaluronic acid in the extracellular matrix, respectively. These findings identify Ogt as a central metabolic regulator and therapeutic target, linking metabolism to intracellular and extracellular mechanisms of cyst formation.

BACKGROUND:Multi-omic studies provide comprehensive insight into biological systems by evaluating cellular changes between normal and pathological conditions at multiple levels of measurement. Biological networks, which represent interactions or associations between biomolecules, have been highly effective in facilitating omic analysis. However, current network-based methods lack generalizability to accommodate multiple data types across a range of diverse experiments. RESULTS:We present AMEND 2.0, an updated active module identification method which can analyze multiplex and/or heterogeneous networks integrated with multi-omic data in a highly generalizable framework, in contrast to existing methods, which are mostly appropriate for at most two specific omic types. It is powered by Random Walk with Restart for multiplex-heterogeneous networks, with additional capabilities including degree bias adjustment and biased random walk for multi-objective module identification. AMEND was applied to two real-world multi-omic datasets: renal cell carcinoma data from The cancer genome atlas and an O-GlcNAc Transferase knockout study. Additional analyses investigate the performance of various subroutines of AMEND on tasks of node ranking and degree bias adjustment. CONCLUSIONS:While the analysis of multi-omic datasets in a network context is poised to provide deeper understanding of health and disease, new methods are required to fully take advantage of this increasingly complex data. The current study combines several network analysis techniques into a single versatile method for analyzing biological networks with multi-omic data that can be applied in many diverse scenarios. Software is freely available in the R programming language at https://github.com/samboyd0/AMEND .

APOE ε4 is the strongest genetic risk factor for late-onset Alzheimer’s disease (AD), but its contribution to disease pathogenesis remains incompletely understood. Here, we integrate proteomic profiling of plasma, cerebrospinal fluid (CSF), and brain tissue from over 10,000 individuals to define the immune phenotype associated with APOE ε4. We identify a conserved, allele dose-dependent pro-inflammatory immune signature across peripheral and central tissues independent of AD diagnosis. This signature is enriched in adaptive immune cells and white matter-resident glial and vascular cells. It also emerges in patient-derived cortical organoids prior to amyloid-β and tau pathology, supporting a causal, genotype-driven mechanism. Cross-tissue comparisons reveal shared innate and antiviral responses alongside tissue-specific immune signaling. Notably, a 12-week medical ketogenic diet partially reversed the APOE ε4 immune signature. These findings position immune dysregulation as an early and tractable driver of AD risk in APOE ε4 carriers with direct implications for targeted prevention strategies.

Abstract The role of hormone receptors in breast cancer has been well established as a key contributor to breast cancer tumorigenesis. Estrogen receptor and progesterone receptors are present in nearly 70% of breast cancers. Estrogen receptor and estrogens in breast cancer has been extensively studied and targeted effectively through endocrine therapy, however the impact of progesterone and the progesterone receptor (PR) independent of estrogen is not well understood. We have previously demonstrated that PR promotes tumor growth and drives an immune suppressive environment, therefore understanding the biology of PR in breast cancer is critical. We demonstrated that PR attenuates type 1 interferon signaling via inhibition of STAT1 phosphorylation and increased degradation of STAT2. In this study we investigated the mechanism of PR regulation of IFN signaling. Post-translational modifications such as phosphorylation and SUMOylation can influence PR target gene promoter selectivity thereby altering its function. We have identified that PR is modified by O-GlcNAc, a single N-acetyl-glucosamine sugar that cycles on and off and serine or threonine amino acids in nuclear, cytoplasmic and mitochondrial proteins. Levels of total O-GlcNAc staining are higher in breast cancer tissue compared to adjacent normal tissue. Active O-GlcNAcylation, as evidenced by immunohistochemistry staining of O-GlcNAc-transferase (OGT), is elevated in patients with PR+ tumors compared to PR-. Using T47D breast cancer cells (an ER/PR-positive tumor line), mass spectrometry analysis revealed an O-GlcNAc site at S499, S733 and S735 on PR. Using a naturally occurring PR-negative variant of T47D cells, we introduced stable expression of a mutant PR with serine to alanine substitution at the O-GlcNAc sites (S499A, S733A, S75A), thereby blocking O-GlcNAc flux, in addition to wt PR as a control. RNA-Seq analysis of these cells following treatment with progesterone revealed ligand dependent PR gene regulation, however major differences were observed in gene expression of the two cell lines independent of ligand. These results indicate ligand independent PR suppression of IFN signaling requires O-GlcNAc at these three sites. Additionally, T47D-mutant PR cell lines implanted into immune deficient mice had significantly decreased growth compared to WT-PR control tumors. Together these findings indicate O-GlcNAcylation of PR contributes to PR driven breast cancer tumor growth and immune evasion via modulation of IFN signaling. Citation Format: Harmony Ivanna Saunders, Sean Holloran, Eilidh Chowanec, Julio Tinoco, Chad Slawson, Christy Hagan. O-GlcNAc sites on progesterone receptor are critical for its ligand independent repression of interferon signaling in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6571.

Pharmacologic or genetic manipulation of O-GlcNAcylation, an intracellular, single sugar post-translational modification, are difficult to interpret due to the pleotropic nature of O-GlcNAc and the vast signaling pathways it regulates. To address this issue, we employed either OGT (O-GlcNAc transferase), OGA (O-GlcNAcase) liver knockouts, or pharmacological inhibition of OGA coupled with multi-Omics analysis and bioinformatics. We identified numerous genes, proteins, phospho-proteins, or metabolites that were either inversely or equivalently changed between conditions. Moreover, we identified pathways in OGT knockout samples associated with increased aneuploidy. To test and validate these pathways, we induced liver growth in OGT knockouts by partial hepatectomy. OGT knockout livers showed a robust aneuploidy phenotype with disruptions in mitosis, nutrient sensing, protein metabolism/amino acid metabolism, stress response, and HIPPO signaling demonstrating how OGT is essential in controlling aneuploidy pathways. Moreover, these data show how a multi-Omics platform can discern how OGT can synergistically fine-tune multiple cellular pathways.

BackgroundThe accumulation of dysfunctional mitochondria is an early feature of Alzheimer’s disease (AD). The impaired turnover of damaged mitochondria increases reactive oxygen species production and lowers ATP generation, leading to cellular toxicity and neurodegeneration. Interestingly, AD exhibits a disruption in the global post-translational modification β-N-acetylglucosamine (O-GlcNAc). O-GlcNAc is a ubiquitous single sugar modification found in the nuclear, cytoplasmic, and mitochondrial proteins. Cells maintain a homeostatic level of O-GlcNAc by cycling the addition and removal of the sugar by O-GlcNAc transferase (OGT) or O-GlcNAcase (OGA), respectively.MethodsWe used patient-derived induced pluripotent stem cells, a transgenic mouse model of AD, SH-SY5Y neuroblastoma cell lines to examine the effect of sustained O-GlcNAcase inhibition by Thiamet-G (TMG) or OGT deficiency on mitophagy using biochemical analyses.ResultsHere, we established an essential role for O-GlcNAc in regulating mitophagy (mitochondria-selective autophagy). Stimulating mitophagy using urolithin A (UA) decreases cellular O-GlcNAc and elevates mitochondrial O-GlcNAc. Sustained elevation in O-GlcNAcylation via pharmacologically inhibiting OGA using Thiamet-G (TMG) increases the mitochondrial level of mitophagy protein PTEN-induced kinase 1 (PINK1) and autophagy-related protein light chain 3 (LC3). Moreover, we detected O-GlcNAc on PINK1 and TMG increases its O-GlcNAcylation level. Conversely, decreasing cellular O-GlcNAcylation by knocking down OGT decreases both PINK1 protein expression and LC3 protein expression. Mitochondria isolated from CAMKII-OGT-KO mice also had decreased PINK1 and LC3. Moreover, human brain organoids treated with TMG showed significant elevation in LC3 compared to control. However, TMG-treated AD organoids showed no changes in LC3 expression.ConclusionCollectively, these data demonstrate that O-GlcNAc plays a crucial role in the activation and progression of mitophagy, and this activation is disrupted in AD.

CHD4 (Chromodomain Helicase DNA Binding Protein 4) is a DNA helicase and an essential component of the NuRD (Nucleosome Remodeling and Deacetylase) complex. CHD4 can interact with numerous proteins to form unique repressor or activator complexes to control gene expression. The control of CHD4 protein interactions is not well understood. We hypothesized that CHD4 O-GlcNAcylation allows CHD4 to interact with and form multi-protein complexes with numerous proteins. O-GlcNAc is a single N-accetylglucosamine sugar (O-GlcNAc) modification found on intracellular proteins. To identify novel O-GlcNAcylated CHD4 interacting proteins, we treated a gene-edited erythroleukemia cell line (UAP1:F383G K-562) with a sugar analogue containing a photo-crosslinkable diazirine group (GlcNDAz). O-GlcNAc transferase (OGT) adds the sugar analogue to proteins. Thus, after crosslinking we used CHD4 immunoprecipitation (IP) coupled with mass spectrometry to identify CHD4 interacting proteins. Interestingly, in the control IP, OGT was associated with unmodified CHD4; while, O-GlcNDAzylated CHD4 was associated as expected with proteins involved in gene regulation. Next, we induced gene expression and terminal differentiation in the UAP1:F383G K-562 cells and identified GlcNDAz CHD4 interacting proteins. We found greater than 150 novel interacting proteins. GlcNDAz CHD4 interacted preferentially with proteins in the mini-chromosome complex (MCM), mitotic spindle, and with specific NuRD complex members. Using cell cycle synchronized HeLa cells, we validated an S phase interaction of CHD4 with MCM7 and a M phase interaction with the mitotic spindle. Together, these data show robust and novel functions for CHD4 and suggest these functions are preferentially generated by O-GlcNAcylation of CHD4.

Hormone receptor positive (HR+) breast cancer, defined by expression of estrogen receptor (ER) and/or progesterone receptor (PR), is the most commonly diagnosed type of breast cancer. PR alters the transcriptional landscape to support tumor growth in concert with, or independent of, ER. Understanding the mechanisms regulating PR function is critical to developing new strategies to treat HR+ breast cancer. O-linked β-N-acetylglucosamine (O-GlcNAc) is a posttranslational modification responsible for nutrient sensing that modulates protein function. Although PR is heavily posttranslationally modified, through both phosphorylation and O-GlcNAcylation, specific sites of O-GlcNAcylation on PR and how they regulate PR action have not been investigated. Using established PR-expressing breast cancer cell lines, we mapped several sites of O-GlcNAcylation on PR. RNA-sequencing after PR O-GlcNAc site mutagenesis revealed site-specific O-GlcNAcylation of PR is critical for ligand-independent suppression of interferon signaling, a regulatory function of PR in breast cancer. Furthermore, O-GlcNAcylation of PR enhances PR-driven tumor growth in vivo. Herein, we have delineated one contributing mechanism to PR function in breast cancer that impacts tumor growth and provided additional insight into the mechanism through which PR attenuates interferon signaling.

O-GlcNAcylation was identified in the 1980s by Torres and Hart and modifies thousands of cellular proteins, yet the regulatory role of O-GlcNAc is still poorly understood compared to the abundance of mechanistic information known for other cycling post-translational modifications like phosphorylation. Many challenges are associated with studying O-GlcNAcylation and are tied to the technical hurdles with analysis by mass spectrometry. Over the years, many research groups have developed important methods to study O-GlcNAcylation revealing its role in the cell, and this perspective aims to review the challenges and innovations around O-GlcNAc research and chronicle the work by Donald F. Hunt and his laboratory, particularly in development of ETD and its application to this field of research.

OBJECTIVE:Pharmacologic or genetic manipulation of O-GlcNAcylation, an intracellular, single sugar post-translational modification, are difficult to interpret due to the pleotropic nature of O-GlcNAc and the vast signaling pathways it regulates. METHOD:To address the pleotropic nature of O-GlcNAc, we employed either OGT (O-GlcNAc transferase), OGA (O-GlcNAcase) liver knockouts, or pharmacological inhibition of OGA coupled with multi-Omics analysis and bioinformatics. RESULTS:We identified numerous genes, proteins, phospho-proteins, or metabolites that were either inversely or equivalently changed between conditions. Moreover, we identified pathways in OGT knockout samples associated with increased aneuploidy. To test and validate these pathways, we induced liver growth in OGT knockouts by partial hepatectomy. OGT knockout livers showed a robust aneuploidy phenotype with disruptions in mitosis, nutrient sensing, protein metabolism/amino acid metabolism, stress response, and HIPPO signaling demonstrating how OGT is essential in controlling aneuploidy pathways. CONCLUSION:These data show how a multi-Omics platform can disentangle the pleotropic nature of O-GlcNAc to discern how OGT fine-tunes multiple cellular pathways involved in aneuploidy.