Biology subjects

Proctor, E. A.

Publications and source records attributed to Proctor, E. A..

15 recordsLinked to original sources

bioRxiv2025

Metabolites associated with type 2 diabetes and Alzheimer's disease trigger differential intracellular signaling responses in mouse primary neurons

Alzheimers disease (AD) is a progressive neurodegenerative disease that is accelerated by the pathological features of type 2 diabetes (T2D). Neuroinflammation is an extensively studied component shared by T2D and AD that remains poorly understood. In this work, we studied nine blood-brain barrier permeable metabolites associated with protective or harmful effects of AD and T2D in literature (aminoadipic acid, arachidonic acid, asparagine, D-sorbitol, fructose-6-phosphate, lauric acid, L-tryptophan, niacinamide, and retinol) and quantified intracellular signaling responses in primary cortical neuron monocultures. After stimulation of neuronal cultures with each metabolite, we quantified signaling analytes with a Luminex assay. Using univariate and multivariate analysis approaches, we identified potential intracellular signaling pathways linked to AD and T2D pathology. With partial least squares discriminant analysis, we identified the separation between the disease and protective-associated metabolites. We identified Akt and STAT5 up-regulation by AD- and T2D-associated metabolites, whereas c-Jun and MEK1 were up-regulated by disease-protective metabolites. Finally, we performed a canonical correlation analysis to link neuronal cytokine data we previously collected from these cultures to our new intracellular signaling data, to which we found intracellular proteins associated with detrimental and protective properties that correlated with IL-9 and MCP-1, respectively. Our experimental and computational approach identified potential associations between intracellular and cytokine signaling molecules in the context of AD and T2D pathology. Nevertheless, primary neuron responses to metabolites associated with T2D and AD may contribute to neuroinflammation and progressive cognitive decline.

systems biology↗

bioRxiv2024

Cross-disease modeling of peripheral blood identifies biomarkers of type 2 diabetes predictive of Alzheimer's disease

Type 2 diabetes (T2D) is a significant risk factor for Alzheimers disease (AD). Despite multiple studies reporting this connection, the mechanism by which T2D exacerbates AD is poorly understood. It is challenging to design studies that address co-occurring and comorbid diseases, limiting the number of existing evidence bases. To address this challenge, we expanded the applications of a computational framework called Translatable Components Regression (TransComp-R), initially designed for cross-species translation modeling, to perform cross-disease modeling to identify biological programs of T2D that may exacerbate AD pathology. Using TransComp-R, we combined peripheral blood-derived T2D and AD human transcriptomic data to identify T2D principal components predictive of AD status. Our model revealed genes enriched for biological pathways associated with inflammation, metabolism, and signaling pathways from T2D principal components predictive of AD. The same T2D PC predictive of AD outcomes unveiled sex-based differences across the AD datasets. We performed a gene expression correlational analysis to identify therapeutic hypotheses tailored to the T2D-AD axis. We identified six T2D and two dementia medications that induced gene expression profiles associated with a non-T2D or non-AD state. Finally, we assessed our blood-based T2DxAD biomarker signature in post-mortem human AD and control brain gene expression data from the hippocampus, entorhinal cortex, superior frontal gyrus, and postcentral gyrus. Using partial least squares discriminant analysis, we identified a subset of genes from our cross-disease blood-based biomarker panel that significantly separated AD and control brain samples. Our methodological advance in cross-disease modeling identified biological programs in T2D that may predict the future onset of AD in this population. This, paired with our therapeutic gene expression correlational analysis, also revealed alogliptin, a T2D medication that may help prevent the onset of AD in T2D patients.

systems biology↗

bioRxiv2024

Comprehensive mapping of the Interaction of levodopa and iron metabolism in Parkinson's disease

Levodopa remains the primary treatment for Parkinsons disease (PD), yet its long-term use has been associated with iron accumulation in the brain, a phenomenon linked to neurodegeneration. We utilize deep machine learning to determine plausible molecular mechanisms that may underlie the effects of levodopa on iron metabolism. Using the DRIFT platform, we performed a proteome-wide target identification of levodopa and uncovered significant interactions potentially involved in cellular iron transport. Pathway analysis revealed that levodopa may influence critical iron-related pathways, including the response of EIF2AK1 to heme deficiency, heme signaling, and ABC-family protein-mediated transport. These findings suggest that levodopa may contribute to iron dysregulation in PD by interacting with iron transporters and modulating iron-related pathways. Because levodopa is used at relatively high doses in PD, our findings provide new insight into secondary effects unrelated to being a precursor of dopamine. This highlights the need for careful consideration of its effects on iron metabolism as a consequence of use in the long-term management of PD. Further experimental validation is required to confirm these interactions, and also to explore potential strategies to mitigate iron-related side effects while preserving therapeutic efficacy.

bioinformatics↗

bioRxiv2024

MODERATE ALCOHOL CONSUMPTION INDUCES LASTING IMPACTS ON PREFRONTAL CORTICAL SIGNALING IN MICE

Both alcohol use disorder (AUD) and Alzheimers Disease and Related Dementias (ADRD) appear to include disruption in the balance of excitation and inhibition in the cortex, but their potential interactions are unclear. We examined the effect of moderate voluntary binge alcohol consumption on the aged, pre-disease neuronal environment by measuring intrinsic excitability and spontaneous neurotransmission on prefrontal cortical pyramidal (excitatory, glutamatergic) and non-pyramidal (inhibitory, GABAergic) neurons following a prolonged period of abstinence from alcohol in mice. Results highlight that binge alcohol consumption has lasting impacts on the electrophysiological properties of prefrontal cortical neurons. A profound increase in excitatory events onto layer 2/3 non-pyramidal neurons following alcohol consumption was seen, along with altered intrinsic excitability of pyramidal neurons, which could have a range of effects on Alzheimers Disease progression in humans. These results indicate that moderate voluntary alcohol influences the pre-disease environment in aging and highlight the need for further mechanistic investigation into this risk factor. HIGHLIGHTSO_LIModerate voluntary alcohol consumption leads to disruption of prefrontal cortical signaling at protracted ages in both male and female mice C_LIO_LIExcitatory glutamatergic events onto prelimbic cortex GABAergic neurons, but not pyramidal neurons, are increased 6 months following alcohol exposure C_LIO_LIBoth pyramidal neurons and GABAergic neurons show altered intrinsic excitability 6 months following alcohol exposure C_LI

neuroscience↗

bioRxiv2024

Cytokine expression patterns predict suppression of vulnerable neural circuits in a mouse model of Alzheimer's disease

Alzheimers disease is a neurodegenerative disorder characterized by progressive amyloid plaque accumulation, tau tangle formation, neuroimmune dysregulation, synapse and neuron loss, and changes in neural circuit activation that lead to cognitive decline and dementia. Early molecular and cellular disease-instigating events occur 20 or more years prior to presentation of symptoms, making them difficult to study, and for many years amyloid-{beta}, the aggregating peptide seeding amyloid plaques, was thought to be the toxic factor responsible for cognitive deficit. However, strategies targeting amyloid-{beta} aggregation and deposition have largely failed to produce safe and effective therapies, and amyloid plaque levels poorly correlate with cognitive outcomes. However, a role still exists for amyloid-{beta} in the variation in an individuals immune response to early, soluble forms of aggregates, and the downstream consequences of this immune response for aberrant cellular behaviors and creation of a detrimental tissue environment that harms neuron health and causes changes in neural circuit activation. Here, we perform functional magnetic resonance imaging of awake, unanesthetized Alzheimers disease mice to map changes in functional connectivity over the course of disease progression, in comparison to wild-type littermates. In these same individual animals, we spatiotemporally profile the immune milieu by measuring cytokines, chemokines, and growth factors across various brain regions and over the course of disease progression from pre-pathology through established cognitive deficit. We identify specific signatures of immune activation predicting hyperactivity followed by suppression of intra- and then inter-regional functional connectivity in multiple disease-relevant brain regions, following the pattern of spread of amyloid pathology.

neuroscience↗

bioRxiv2023

Differential responses of primary neuron-secreted MCP-1 and IL-9 to type 2 diabetes and Alzheimer's disease-associated metabolites

Type 2 diabetes (T2D) is implicated as a risk factor for Alzheimers disease (AD), the most common form of dementia. In this work, we investigated neuroinflammatory responses of primary neurons to potentially circulating, blood-brain barrier (BBB) permeable metabolites associated with AD, T2D, or both. We identified nine metabolites associated with protective or detrimental properties of AD and T2D in literature (lauric acid, asparagine, fructose, arachidonic acid, aminoadipic acid, sorbitol, retinol, tryptophan, niacinamide) and stimulated primary mouse neuron cultures with each metabolite before quantifying cytokine secretion via Luminex. We employed unsupervised clustering, inferential statistics, and partial least squares discriminant analysis to identify relationships between cytokine concentration and disease-associations of metabolites. We identified MCP-1, a cytokine associated with monocyte recruitment, as differentially abundant between neurons stimulated by metabolites associated with protective and detrimental properties of AD and T2D. We also identified IL-9, a cytokine that promotes mast cell growth, to be differentially associated with T2D. Indeed, cytokines, such as MCP-1 and IL-9, released from neurons in response to BBB-permeable metabolites associated with T2D may contribute to AD development by downstream effects of neuroinflammation.

systems biology↗

bioRxiv2023

Dynamic neuroinflammatory profiles predict Alzheimer's disease pathology in microglia-containing cerebral organoids

Neuroinflammation and the underlying dysregulated immune responses of microglia actively contribute to the progression and, likely, the initiation of Alzheimers disease (AD). Fine-tuned therapeutic modulation of immune dysfunction to ameliorate disease cannot be achieved without the characterization of diverse microglial states that initiate unique, and sometimes contradictory, immune responses that evolve over time in chronic inflammatory environments. Because of the functional differences between human and murine microglia, untangling distinct, disease-relevant reactive states and their corresponding effects on pathology or neuronal health may not be possible without the use of human cells. In order to profile shifting microglial states in early AD and identify microglia-specific drivers of disease, we differentiated human induced pluripotent stem cells (iPSCs) carrying a familial AD PSEN2 mutation or its isogenic control into cerebral organoids and quantified the changes in cytokine concentrations over time with Luminex XMAP technology. We used partial least squares (PLS) modeling to build cytokine signatures predictive of disease and age to identify key differential patterns of cytokine expression that inform the overall organoid immune milieu and quantified the corresponding changes in protein pathology. AD organoids exhibited an overall reduction in cytokine secretion after an initial amplified immune response. We demonstrate that reduced synapse density observed in the AD organoids is prevented with microglial depletion. Crucially, these differential effects of dysregulated immune signaling occurred without the accumulation of pathological proteins. In this study, we used microglia-containing AD organoids to quantitatively characterize an evolving immune milieu, made up of a diverse of collection of activation patterns and immune responses, to identify how a dynamic, overall neuroinflammatory state negatively impacts neuronal health and the cell-specific contribution of microglia.

neuroscience↗

bioRxiv2023

Alzheimer's disease-specific cytokine secretion suppresses neuronal mitochondrial metabolism

IntroductionNeuroinflammation and metabolic dysfunction are early alterations in Alzheimers disease brain that are thought to contribute to disease onset and progression. Glial activation due to protein deposition results in cytokine secretion and shifts in brain metabolism, which have been observed in Alzheimers disease patients. However, the mechanism by which this immunometabolic feedback loop can injure neurons and cause neurodegeneration remains unclear. MethodsWe used Luminex XMAP technology to quantify hippocampal cytokine concentrations in the 5xFAD mouse model of Alzheimers disease at milestone timepoints in disease development. We used partial least squares regression to build cytokine signatures predictive of disease progression, as compared to healthy aging in wild-type littermates. We applied the disease-defining cytokine signature to wild-type primary neuron cultures and measured downstream changes in gene expression using the NanoString nCounter system and mitochondrial function using the Seahorse Extracellular Flux live-cell analyzer. ResultsWe identified a pattern of up-regulated IFN{gamma}, IP-10, and IL-9 as predictive of advanced disease. When healthy neurons were exposed to these cytokines in proportions found in diseased brain, gene expression of mitochondrial electron transport chain complexes, including ATP synthase, was suppressed. In live cells, basal and maximal mitochondrial respiration were impaired following cytokine stimulation. ConclusionsAn Alzheimers disease-specific pattern of cytokine secretion reduces expression of mitochondrial electron transport complexes and impairs mitochondrial respiration in healthy neurons. We establish a mechanistic link between disease-specific immune cues and impaired neuronal metabolism, potentially causing neuronal vulnerability and susceptibility to degeneration in Alzheimers disease.

neuroscience↗

bioRxiv2022

Apolipoprotein E4 modulates astrocyte neuronal support functions in the presence of amyloid-β

Apolipoprotein E (APOE) is a lipid transporter produced predominantly by astrocytes in the brain. The {varepsilon}4 variant of APOE (APOE4) is the strongest and most common genetic risk factor for Alzheimers disease (AD). Although the molecular mechanisms of this increased risk are unclear, APOE4 is known to alter immune signaling and lipid and glucose metabolism. Astrocytes provide various forms of support to neurons, including regulating neuron metabolism and immune responses through cytokine signaling. Changes in astrocyte function due to APOE4 may therefore decrease neuronal support, leaving neurons more vulnerable to stress and disease insults. To determine whether APOE4 alters astrocyte neuronal support functions, we measured glycolytic and oxidative metabolism of neurons treated with conditioned media from APOE4 or APOE3 (the common, risk-neutral variant) primary astrocyte cultures. We found that APOE4 neurons treated with conditioned media from resting APOE4 astrocytes had similar metabolism to APOE3 astrocytes, but treatment with ACM from astrocytes challenged with amyloid-{beta} (A{beta}), a key pathological protein in AD, caused APOE4 neurons to increase their basal mitochondrial and glycolytic metabolic rates more than APOE3 neurons. These changes were not due to differences in astrocytic lactate production or glucose utilization, but instead correlated with increased glycolytic ATP production and a lack of cytokine secretion response to A{beta}. Together, these findings suggest that in the presence of A{beta}, APOE4 astrocytes alter immune and metabolic functions that result in a compensatory increase in neuronal metabolic stress.

neuroscience↗

bioRxiv2022

Predictive link between systemic metabolism and immune signaling in the brain of APOE4 mice

The {varepsilon}4 variant of apolipoprotein E (APOE) is the strongest and most common genetic risk factor for Alzheimers disease (AD). While the mechanism of conveyed risk is incompletely understood, promotion of inflammation, dysregulated metabolism, and protein misfolding and aggregation are contributors to accelerating disease. Here we determined the concurrent effects of systemic metabolic changes and brain inflammation in young (3-month-old) and aged (18-month-old) male and female mice carrying the APOE4 gene. Using functional metabolic assays alongside multivariate modeling of hippocampal cytokine levels, we found that brain cytokine signatures are predictive of systemic metabolic outcomes, independent of AD proteinopathies. Male and female mice each produce different cytokine signatures as they age and as their systemic metabolic phenotype declines, and these signatures are APOE genotype dependent. Ours is the first study to identify a quantitative and predictive link between systemic metabolism and specific pathological cytokine signatures in the brain. Our results highlight the effects of APOE4 beyond the brain and suggest the potential for bi-directional influence of risk factors in the brain and periphery. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=123 SRC="FIGDIR/small/480074v2_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@5865d5org.highwire.dtl.DTLVardef@185a0e0org.highwire.dtl.DTLVardef@4d2e7org.highwire.dtl.DTLVardef@b27318_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2021

GM1 mediates the formation and maintenance of cytotoxic Aβ oligomers

The aggregation of amyloid beta (A{beta}) peptide is associated with Alzheimers disease (AD) pathogenesis. Cell membrane composition, especially monosialotetrahexosylganglioside (GM1), is known to promote the formation of A{beta} fibrils, yet little is known about the roles of GM1 in the early steps of A{beta} oligomer formation. Here, by using GM1-contained liposomes as a mimic of neuronal cell membrane, we demonstrate that GM1 is a critical trigger of A{beta} oligomerization and aggregation. We find that GM1 not only promotes the formation of A{beta} fibrils, but also facilitates the maintenance of A{beta} oligomers on liposome membranes. We structurally characterize the A{beta} oligomers formed on the membrane and find that GM1 captures A{beta} by binding to its arginine-5 residue. To interrogate the mechanism of A{beta} oligomer toxicity, we design a new liposome-based Ca2+-encapsulation assay and provide new evidence for the A{beta} ion channel hypothesis. Finally, we conduct cell viability assay to determine the toxicity of A{beta} oligomers formed on membranes. Overall, by uncovering the roles of GM1 in mediating early A{beta} oligomer formation and maintenance, our work provides a novel direction for pharmaceutical research for AD.

biophysics↗

bioRxiv2020

Neurovascular coupling and bilateral connectivity during NREM and REM sleep

Hemodynamic signals in the brain are used as surrogates of neural activity, but how these hemodynamic signals depend on arousal state is poorly understood. Here, we monitored neural activity and hemodynamic signals in un-anesthetized, head-fixed mice to understand how sleep and awake states impact cerebral hemodynamics. In parallel with electrophysiological recordings, we used intrinsic optical signal imaging to measure bilateral changes in cerebral hemoglobin ([HbT]), and two-photon laser scanning microscopy (2PLSM) to measure dilations of individual arterioles. We concurrently monitored body motion, whisker movement, muscle EMG, cortical LFP, and hippocampal LFP to classify the arousal state of the mouse into awake, NREM sleep, or REM sleep. We found that mice invariably fell asleep during imaging, and these sleep states were interspersed with periods of awake. During both NREM and REM sleep, mice showed large increases in [HbT] relative to the awake state, showing increase in hemoglobin and arteriole diameter two to five times larger than those seen in response to sensory stimulation. During NREM sleep, the amplitude of bilateral low-frequency oscillations in [HbT] increased markedly, and coherency between neural activity and hemodynamic signals was higher than the awake resting and REM states. Bilateral correlations in neural activity and [HbT] were highest during NREM sleep, and lowest in the awake state. Our results show that hemodynamic signals in the cortex are strongly modulated by arousal state, with hemodynamic changes during sleep being substantially larger than sensory-evoked responses. These results underscore the critical importance of behavioral monitoring during studies of spontaneous activity, as sleep-related hemodynamics dominate measures of neurovascular coupling and functional connectivity.

neuroscience↗

bioRxiv2020

Novel microRNA multivariate biomarkers of response to immunotherapy against HPV E6 oncogene

Cervical cancer is caused by the persistent infection high-risk types of human papillomavirus (HPV) in over 99.9% of cases. To favor malignant transformation, HPV E6 and E7 oncogenes disrupt both p53 and retinoblastoma (Rb) respectively and control microRNA (miR) networks. We have previously demonstrated the therapeutic potential of anti-HPV E6 monoclonal antibodies (mAbs) in experimental models of human cervical cancer; yet the underlying mechanism remains unclear. Here, we sought to determine if anti-HPV E6 mAbs modulate the miR signatures of HPV E6 oncogenes. To this end, we performed qRT-PCR to measure the expression of thirty-four miRs and found that univariate analysis is not able to identify novel interactions characteristic of complex biological systems. Thus, we utilized partial least squares discriminant analysis (PLSDA) to identify signatures of co-varying miRs specific to mAb treatment. These miR signatures predictively discriminate between anti-HPV E6 mAb response and control mAb treatment, which may provide mechanistic insight into the action of anti-HPV E6 mAbs.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

bioRxiv2019

Coagulopathy signature precedes and predicts severity of end-organ heat stroke pathology in a mouse model

Heat stroke is a life-threatening condition characterized by loss of thermoregulation and severe elevation of core body temperature, which can cause organ failure and damage to the central nervous system. While no definitive test exists to measure heat stroke severity, immune challenge is known to increase heat stroke risk, although the mechanism of this increased risk is unclear. In this study, we used a mouse model of classic heat stroke to test the effect of immune challenge on pathology. Employing multivariate supervised machine learning to identify patterns of molecular and cellular markers associated with heat stroke, we found that prior viral infection simulated with poly I:C injection resulted in heat stroke presenting with high levels of factors indicating coagulopathy. Despite a decreased number of platelets in the blood, platelets are large and non-uniform in size, suggesting younger, more active platelets. Levels of D-dimer and soluble thrombomodulin were increased in more severe heat stroke, and in cases presenting with the highest level of organ damage markers D-dimer levels dropped, indicating potential fibrinolysis-resistant thrombosis. Genes corresponding to immune response, coagulation, hypoxia, and vessel repair were up-regulated in kidneys of heat-challenged animals, and these increases correlated with both viral treatment and distal organ damage while appearing before discernible tissue damage to the kidney itself. We conclude that heat stroke-induced coagulopathy may be a driving mechanistic force in heat stroke pathology, especially when exacerbated by prior infection, and that coagulation markers may serve as an accessible biomarker for heat stroke severity and therapeutic strategies.\n\nKey pointsO_LIA signature of pro-coagulation markers predicts circadian core body temperature and levels of organ damage in heat stroke\nC_LIO_LIChanges in coagulopathy-related gene expression are evidenced before histopathological organ damage\nC_LI

physiology↗

bioRxiv2018

A framework for translation of genomic responses from mouse models to human inflammatory disease contexts

The high failure rate of therapeutics showing promise in mouse disease models to translate to patients is a pressing challenge in biomedical science. However, mouse models are a useful tool for evaluating mechanisms of disease and prioritizing novel therapeutic agents for clinical trials. Though retrospective studies have examined the fidelity of mouse models of inflammatory disease to their respective human in vivo conditions, approaches for prospective translation of insights from mouse models to patients remain relatively unexplored. Here, we develop a semi-supervised learning approach for prospective inference of disease-associated human in vivo differentially expressed genes and pathways from mouse model experiments. We examined 36 transcriptomic case studies where comparable phenotypes were available for mouse and human inflammatory diseases and assessed multiple computational approaches for inferring human in vivo biology from mouse model datasets. We found that a semi-supervised artificial neural network identified significantly more true human in vivo associations than interpreting mouse experiments directly (95% CI on F-score for mouse experiments [0.090, 0.175], neural network [0.278, 0.375], p = 0.00013). Our study shows that when prospectively evaluating biological associations in mouse studies, semi-supervised learning approaches combining mouse and human data for biological inference provides the most accurate assessment of human in vivo disease and therapeutic mechanisms. The task of translating insights from model systems to human disease contexts may therefore be better accomplished by the use of systems modeling driven approaches.\n\nAuthor SummaryComparison of genomic responses in mouse models and human disease contexts is not sufficient for addressing the challenge of prospective translation from mouse models to human disease contexts. Here, we address this challenge by developing a semi-supervised machine learning approach that combines supervised modeling of mouse experiment datasets with unsupervised modeling of human disease-context datasets to predict human in vivo differentially expressed genes and pathways as if the model system experiment had been run in the human cohort. A semi-supervised version of a feed forward artificial neural network was the most efficacious model for translating experimentally derived mouse molecule-phenotype associations to the human in vivo disease context. We find that computational generalization of signaling insights from mouse to human contexts substantially improves upon direct generalization of mouse experimental insights and argue that such approaches can facilitate more clinically impactful translation of insights from preclinical studies in model systems to patients.

systems biology↗