Drug-induced Changes Research Articles

Theta and gamma modulation in the nucleus accumbens as drivers of neurophysiological responses to acute methamphetamine sensitization in mice.

Methamphetamine (METH) has well-documented long-term effects on the brain, including increased psychomotor activity and behavioral sensitization. However, its immediate effects on the brain's reward system following acute exposure, which may contribute to the development of addiction, are less understood. This study aimed to investigate the effects of acute METH on brain oscillations in the nucleus accumbens of C57BL/6 mice. Mice in the METH group received 5mg/kg of METH for 5 days during the conditioning phase, followed by an 8-day abstinence period. Afterward, they underwent a 6-minute tail suspension test and were given a 1mg/kg METH challenge. Local field potential (LFP) data were analyzed for percent total power, mean frequency indices, and phase-amplitude coupling (PAC) to assess the neural effects of METH exposure across these phases. A reduction in theta power was observed across the conditioning, abstinence, and challenge phases of METH exposure. The subsequent METH challenge enhanced gamma oscillations, and PAC analysis revealed a consistent theta-gamma coupling index during both the METH administration and challenge phases. It highlights the sensitivity of the reward system to intense, short-term drug exposure, providing new insights into how acute neural stimulation may contribute to the development of addictive behaviors, reinforcing the brain's vulnerability to drug-induced changes in neural circuitry.

Biophysical and Morphological Cell Features Retrieved by Digital Holographic Microscopy Correlate with Drug-Induced Changes in Cell Migration Behavior.

Quantitative analysis of cancer cell migration is critical for developing effective therapies to curb cancer metastasis. However, traditional methods are time-consuming and labor-intensive and lack quantitative capabilities. Cell volume change, a key physiological indicator of cell migration, is directly linked to phase change. In this work, we have developed a model that connects phase features from digital holographic microscopy (DHM) with cell healrate values from the wound healing assay. This approach aims to provide a rapid and quantitative evaluation of the breast cancer cell migration capability. Using DHM, six phase features of 231 cells treated with varying drug concentrations were extracted. It was observed that the rate of change of these phase features, termed characteristic parameters, showed a high linear correlation with cell healrate values from wound healing assays. Based on these linear correlations, a composite coefficient was derived by linearly combining the characteristic parameters of the six phase features. This composite coefficient was then linearly correlated with the cell healrate values to create a correlation model. This model establishes a strong connection between DHM-extracted morphological/biophysical features and cell migration metrics from a complementary assay. It provides a new, rapid, and quantitative method for assessing cancer cell migration in vitro and delivering valuable insights for cancer research.

Danicamtiv reduces myosin's working stroke but enhances contraction by activating the thin filament.

Heart failure is a leading cause of death worldwide, and there is a need to develop new treatments that improve outcomes for patients. Recently, the myosin-binding small molecule danicamtiv entered clinical trials for heart failure; however, its mechanism at the level of single myosin crossbridges is not well understood. We determined the molecular mechanism of danicamtiv and showed how drug-induced molecular changes can mechanistically increase heart contraction. Moreover, we demonstrate fundamental differences between danicamtiv and the related myosin-binding small molecule omecamtiv mecarbil that explain the improved diastolic function seen with danicamtiv. Our results have important implications for the design of new therapeutics for heart failure.

Detection of carboxylesterases by an activatable NIR fluorescence probe with high selectivity in living systems

Carboxylesterases (CEs) have attracted increasingly attention in the physiological and pathological processes of many diseases such as diabetes, hepatocellular carcinoma (HCC) and drug metabolism. Selective detection of CEs activity is imperative to evaluate the pathophysiological process of CEs-related disease. Herein, a selective near-infrared (NIR) fluorescent probe (DCM-CE) with high selectivity is reported. DCM-CE was composed of dicyanoisophorone-based fluorophore and carbamate unit which is a highly selective identification group for CEs. DCM-CE exhibited good sensitivity for CEs detection at physiological pH and temperature. Furthermore, DCM-CE featured large Stokes shift (175 nm) and good at tracking the drug-induced trace change of CEs activity in HepG2 cells with little effect on cell viability. Moreover, DCM-CE was applied to monitor the activity of CEs in living mice. Taken all together, DCM-CE had extensive potential application value in detecting CEs for evaluating related diseases.

Hypoxic Effects of Heroin and Fentanyl and Their Basic Physiological Mechanisms.

Respiratory depression that diminishes oxygen delivery to the brain is the most dangerous effect of opioid drugs. While plethysmography is a valuable tool to examine drug-induced changes in respiration, the primary cause of brain abnormalities induced by opioids is the global decrease in brain oxygen levels. The primary goal of this review is to provide an overview and discussion on fluctuations in brain oxygen levels induced by opioids, with a focus on heroin and fentanyl. To evaluate fluctuations in brain oxygen levels we used oxygen sensors coupled with high-speed amperometry in awake, freely moving rats. First, we provide an overview of brain oxygen responses induced by natural physiological stimuli and discuss the mechanisms regulating oxygen entry into brain tissue. Then, we present data on brain oxygen responses induced by heroin and fentanyl and review their underlying mechanisms. These data allowed us to compare the effects of these drugs on brain oxygen regarding their latency, potency, time-dependency, and potential lethality at high doses as well as their relationships with peripheral oxygen responses. We also discuss data on the effects of naloxone on brain oxygen responses induced by heroin and fentanyl in the paradigms of both the pre-treatment and treatment, when naloxone is administered at different times after the primary opioid drug. Although most data discussed were obtained in rats, they may have clinical relevance for understanding the mechanisms underlying the physiological effects of opioids and developing rational treatment strategies to decrease acute lethality and long-term health complications of opioid misuse.

Cocaine taking and craving produce distinct transcriptional profiles in dopamine neurons.

Dopamine (DA) signaling plays an essential role in reward valence attribution and in encoding the reinforcing properties of natural and artificial rewards. The adaptive responses from midbrain dopamine neurons to artificial rewards such as drugs of abuse are therefore important for understanding the development of substance use disorders. Drug-induced changes in gene expression are one such adaptation that can determine the activity of dopamine signaling in projection regions of the brain reward system. One of the major challenges to obtaining this understanding involves the complex cellular makeup of the brain, where each neuron population can be defined by a distinct transcriptional profile. To bridge this gap, we have adapted a virus-based method for labeling and capture of dopamine nuclei, coupled with nuclear RNA-sequencing, to study the transcriptional adaptations, specifically, of dopamine neurons in the ventral tegmental area (VTA) during cocaine taking and cocaine craving, using a mouse model of cocaine intravenous self-administration (IVSA). Our results show significant changes in gene expression across non-drug operant training, cocaine taking, and cocaine craving, highlighted by an enrichment of repressive epigenetic modifying enzyme gene expression during cocaine craving. Immunohistochemical validation further revealed an increase of H3K9me3 deposition in DA neurons during cocaine craving. These results demonstrate that cocaine-induced transcriptional adaptations in dopamine neurons vary by phase of self-administration and underscore the utility of this approach for identifying relevant phase-specific molecular targets to study the behavioral course of substance use disorders.

Investigating the Interrelationship between the Desire for a Cohesive Community and Opioid Abuse: A Neuropsychological Study of Demon Copperhead

Abstract Foregrounding the increasing global crisis of opioids as the “leading cause of deaths in fatal overdoses,” the World Drug Report 2023, published by the United Nations Office on Drugs and Crime (UNODC), mentioned that in 2021 more than 80,000 people died due to opioid overdose in the United States of America. The Centers for Disease Control and Prevention (CDC), the national public health protection agency in the United States, has reported that “the predicted number of drug overdose deaths showed an increase of 0.5% from the 12 months ending in December 2021 to the 12 months ending in December 2022, from 109,179 to 179,680” (“Provisional Data”). Although the trajectory of opioid use disorders (OUDs) has affected different sociodemographic groups in the country since its first wave in the 1990s, teenagers in poverty-stricken rural areas are more vulnerable to such addiction (Keyes et al.). Poor parental guidance, impoverishment, troubled childhoods, detrimental familial structure, scarce opportunities, and accessibility to opioids are often considered to be the primary risk factors for unprivileged teenagers to develop a psychic reliance on opioids for engendering a perpetual sense of contentment. According to the incentive sensitization theory, the persistent desire to transcend physical and psychical limitations for a sense of relief, triggered by chronic drug misuse, often evokes a sense of “wanting” or incentive salience, a compulsive inclination towards drug-associated stimuli (Berridge and Robinson, “Drug Addiction” 22). This intense desire of “wanting” often generates a perpetual sensitization of the mesolimbic systems in the brain which is also activated by mental representations of drug-associated cues (Robinson and Berridge 3139). Focusing on drug-induced changes in the brain such as hypersensitization and neuroadaptation, this study analyzes Barbara Kingsolver’s Demon Copperhead, a modern reimagining of David Copperfield by Charles Dickens. The selected text addresses primarily some pertinent socio-political crises, such as the poor foster care system, poverty, and the engrossing opioid endemic in Southern Appalachia. However, this study attempts to analyze the precarious state of some characters, who become addicted to opioids seeking recognition from peer groups and perpetual psychic stability, in the selected text from a neuropsychological perspective.

12209 Validation Of A Novel Placenta Explant Protocol For Studying Circadian Rhythms In The Mouse Placenta In Early, Mid And Late Pregnancy

Abstract Disclosure: J.S. Lee: None. A.M. Yaw: None. H.M. Hoffmann: None. Introduction: The placenta serves as an interface facilitating the exchange of essential nutrients and oxygen between the mother and fetus. Preeclampsia, a complication of pregnancy driven by placental dysfunction, is one of the leading causes of maternal, fetal, and neonatal morbidity and mortality. While deregulation of the genes driving circadian rhythm has been associated with preeclampsia, the role of circadian rhythms in the placenta largely remains unknown. To address this gap of knowledge, our goal was to establish and validate an organotypic ex vivo preparation to study placenta circadian rhythms at gestation day (GD) 10, GD14, and GD18 in the mouse. Methods: To establish an organotypic placenta culture GD10, GD14, and GD18 placental explants, we sectioned the placenta into 350μm sections using a vibratome. The explants were prepared from the validated circadian Per2::Luciferase reporter mouse, allowing automated circadian rhythms recording of the explants in a LumiCycle. We compared explant success rate and rhythm quality in 2x2mm section vs whole slice explants at GD14. Using hematoxylin and eosin (H&E) staining we validated the explants to be decidua which is strictly of maternal origin, labyrinth which is strictly of fetal origin, and the junctional zone which consists of binucleated cells fused of maternal and fetal cells. Results: Through H&E staining, we confirmed the decidua is enriched with neutrophils, the junctional zone contains spongiotrophoblasts and glycogen trophoblasts, and the labyrinth has red blood cells. Both explant types were enriched with >80% of cells from the targeted region. We next established a protocol to record Per2::Luciferase rhythms for <6 days. The fragility of the GD10 placentas required the whole explant protocol, whereas the GD18 2x2mm sectioned explants produced strong rhythms with a high success rate. At GD14, the whole explants resulted in stronger rhythms with higher amplitude and higher goodness of fit compared to the 2x2mm explants. Conclusion: We found that depending on GD recording success differs. Specifically, the whole placental explant provides a more robust and reliable model for studying circadian rhythms in GD10 and GD14, whereas 2x2mm explants are successful at GD18. This novel placental preparation protocol will be valuable in studying disease- and drug-induced changes to circadian rhythms in a placenta layer-specific manner in the mouse. Presentation: 6/1/2024

Molecular and functional landscape of malignant serous effusions for precision oncology

Personalized treatment for patients with advanced solid tumors critically depends on the deep characterization of tumor cells from patient biopsies. Here, we comprehensively characterize a pan-cancer cohort of 150 malignant serous effusion (MSE) samples at the cellular, molecular, and functional level. We find that MSE-derived cancer cells retain the genomic and transcriptomic profiles of their corresponding primary tumors, validating their use as a patient-relevant model system for solid tumor biology. Integrative analyses reveal that baseline gene expression patterns relate to global ex vivo drug sensitivity, while high-throughput drug-induced transcriptional changes in MSE samples are indicative of drug mode of action and acquired treatment resistance. A case study exemplifies the added value of multi-modal MSE profiling for patients who lack genetically stratified treatment options. In summary, our study provides a functional multi-omics view on a pan-cancer solid tumor cohort and underlines the feasibility and utility of MSE-based precision oncology.

Drug-induced change in transmitter identity is a shared mechanism generating cognitive deficits

Cognitive deficits are long-lasting consequences of drug use, yet the convergent mechanism by which classes of drugs with different pharmacological properties cause similar deficits is unclear. We find that both phencyclidine and methamphetamine, despite differing in their targets in the brain, cause the same glutamatergic neurons in the medial prefrontal cortex of male mice to gain a GABAergic phenotype and decrease expression of their glutamatergic phenotype. Suppressing drug-induced gain of GABA with RNA-interference prevents appearance of memory deficits. Stimulation of dopaminergic neurons in the ventral tegmental area is necessary and sufficient to produce this gain of GABA. Drug-induced prefrontal hyperactivity drives this change in transmitter identity. Returning prefrontal activity to baseline, chemogenetically or with clozapine, reverses the change in transmitter phenotype and rescues the associated memory deficits. This work reveals a shared and reversible mechanism that regulates the appearance of cognitive deficits upon exposure to different drugs.

Non-invasive acquisition of vital data in anesthetized rats using laser and radar application.

The aim of this study was to verify the possibility of obtaining vital sign information using a laser and radar sensor in a manner that is non-invasive and painless for test animals. A dataset was obtained from respiratory movement of anaesthetized male F344 rats, signals of laser and radar sensors were recorded simultaneously with vital data acquired with an integrated multiple-channel intraoperative monitor. In addition, respiratory movements were also video recorded, and used as reference data of respiration rate (RR; ref-RR). Reference data for heart rate (HR; ref-HR) were obtained from the R wave of electrocardiogram data for each epoch. Signals recorded from the radar sensor (I- and Q-signals) were input to a computer, and HR (radar-HR) and RR (radar-RR) were estimated using the frequency analysis method. Among the six positions where respiratory movements were measured by the laser sensor, the number of peak counts matched the visual counts of respiratory movements in the video records. The respiratory movements were significantly the greatest over the most caudal rib in the dorsal (p < 0.001). The average radar-RR and ref-RR values showed correspondence (ref-RR, 69 ± 6.2 breaths/min; radar-RR, 68 ± 5.7 breaths/min (p = 0.04-1.00); equivalence ratio, 86%). The radar-HR data showed slight variability; however, there was 80% homology compared with the ref-HR values (ref-HR, 336 ± 19.6 beats/min; radar-HR, 348 ± 34.1 (p = 0.10-0.95)). Although comparison of the data under noradrenaline administration failed to track drug-induced changes in some cases, the HR and RR data of anesthetized rats measured from the radar sensor system showed comparable accuracy to other conventional methods.

LSD Modulates Proteins Involved in Cell Proteostasis, Energy Metabolism and Neuroplasticity in Human Cerebral Organoids.

Proteomic analysis of human cerebral organoids may reveal how psychedelics regulate biological processes, shedding light on drug-induced changes in the brain. This study elucidates the proteomic alterations induced by lysergic acid diethylamide (LSD) in human cerebral organoids. By employing high-resolution mass spectrometry-based proteomics, we quantitatively analyzed the differential abundance of proteins in cerebral organoids exposed to LSD. Our findings indicate changes in proteostasis, energy metabolism, and neuroplasticity-related pathways. Specifically, LSD exposure led to alterations in protein synthesis, folding, autophagy, and proteasomal degradation, suggesting a complex interplay in the regulation of neural cell function. Additionally, we observed modulation in glycolysis and oxidative phosphorylation, crucial for cellular energy management and synaptic function. In support of the proteomic data, complementary experiments demonstrated LSD's potential to enhance neurite outgrowth in vitro, confirming its impact on neuroplasticity. Collectively, our results provide a comprehensive insight into the molecular mechanisms through which LSD may affect neuroplasticity and potentially contribute to therapeutic effects for neuropsychiatric disorders.

Rapid Identification of Drug Mechanisms with Deep Learning-Based Multichannel Surface-Enhanced Raman Spectroscopy.

Rapid identification of drug mechanisms is vital to the development and effective use of chemotherapeutics. Herein, we develop a multichannel surface-enhanced Raman scattering (SERS) sensor array and apply deep learning approaches to realize the rapid identification of the mechanisms of various chemotherapeutic drugs. By implementing a series of self-assembled monolayers (SAMs) with varied molecular characteristics to promote heterogeneous physicochemical interactions at the interfaces, the sensor can generate diversified SERS signatures for directly high-dimensionality fingerprinting drug-induced molecular changes in cells. We further train the convolutional neural network model on the multidimensional SAM-modulated SERS data set and achieve a discriminatory accuracy toward 99%. We expect that such a platform will contribute to expanding the toolbox for drug screening and characterization and facilitate the drug development process.

Novel mimetic tissue standards for precise quantitative mass spectrometry imaging of drug and neurotransmitter concentrations in rat brain tissues.

Understanding the relationship between the concentration of a drug and its therapeutic efficacy or side effects is crucial in drug development, especially to understand therapeutic efficacy in central nervous system drug, quantifying drug-induced site-specific changes in the levels of endogenous metabolites, such as neurotransmitters. In recent times, evaluation of quantitative distribution of drugs and endogenous metabolites using matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) has attracted much attention in drug discovery research. However, MALDI-MSI quantification (quantitative mass spectrometry imaging, QMSI) is an emerging technique, and needs to be further developed for practicable and convenient use in drug discovery research. In this study, we developed a reliable QMSI method for quantification of clozapine (antipsychotic drug) and dopamine and its metabolites in the rat brain using MALDI-MSI. An improved mimetic tissue model using powdered frozen tissue for QMSI was established as an alternative method, enabling the accurate quantification of clozapine levels in the rat brain. Furthermore, we used the improved method to evaluate drug-induced fluctuations in the concentrations of dopamine and its metabolites. This method can quantitatively evaluate drug localization in the brain and drug-induced changes in the concentration of endogenous metabolites, demonstrating the usefulness of QMSI.

Kinetic Trajectories of Glucose Uptake in Single Cancer Cells Reveal a Drug-Induced Cell-State Change Within Hours of Drug Treatment.

The development of drug resistance is a nearly universal phenomenon in patients with glioblastoma multiforme (GBM) brain tumors. Upon treatment, GBM cancer cells may initially undergo a drug-induced cell-state change to a drug-tolerant, slow-cycling state. The kinetics of that process are not well understood, in part due to the heterogeneity of GBM tumors and tumor models, which can confound the interpretation of kinetic data. Here, we resolve drug-adaptation kinetics in a patient-derived in vitro GBM tumor model characterized by the epithelial growth factor receptor (EGFR) variant(v)III oncogene treated with an EGFR inhibitor. We use radiolabeled 18F-fluorodeoxyglucose (FDG) to monitor the glucose uptake trajectories of single GBM cancer cells over a 12 h period of drug treatment. Autocorrelation analysis of the single-cell glucose uptake trajectories reveals evidence of a drug-induced cell-state change from a high- to low-glycolytic phenotype after 5-7 h of drug treatment. Information theoretic analysis of a bulk transcriptome kinetic series of the GBM tumor model delineated the underlying molecular mechanisms driving the cellular state change, including a shift from a stem-like mesenchymal state to a more differentiated, slow-cycling astrocyte-like state. Our results demonstrate that complex drug-induced cancer cell-state changes of cancer cells can be captured via measurements of single cell metabolic trajectories and reveal the extremely facile nature of drug adaptation.

Insights into gemcitabine resistance in pancreatic cancer: association with metabolic reprogramming and TP53 pathogenicity in patient derived xenografts

BackgroundWith poor prognosis and high mortality, pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. Standard of care therapies for PDAC have included gemcitabine for the past three decades, although resistance often develops within weeks of chemotherapy initiation through an array of possible mechanisms.MethodsWe reanalyzed publicly available RNA-seq gene expression profiles of 28 PDAC patient-derived xenograft (PDX) models before and after a 21-day gemcitabine treatment using our validated analysis pipeline to identify molecular markers of intrinsic and acquired resistance.ResultsUsing normalized RNA-seq quantification measurements, we first identified oxidative phosphorylation and interferon alpha pathways as the two most enriched cancer hallmark gene sets in the baseline gene expression profile associated with intrinsic gemcitabine resistance and sensitivity, respectively. Furthermore, we discovered strong correlations between drug-induced expression changes in glycolysis and oxidative phosphorylation genes and response to gemcitabine, which suggests that these pathways may be associated with acquired gemcitabine resistance mechanisms. Thus, we developed prediction models using baseline gene expression profiles in those pathways and validated them in another dataset of 12 PDAC models from Novartis. We also developed prediction models based on drug-induced expression changes in genes from the Molecular Signatures Database (MSigDB)’s curated 50 cancer hallmark gene sets. Finally, pathogenic TP53 mutations correlated with treatment resistance.ConclusionOur results demonstrate that concurrent upregulation of both glycolysis and oxidative phosphorylation pathways occurs in vivo in PDAC PDXs following gemcitabine treatment and that pathogenic TP53 status had association with gemcitabine resistance in these models. Our findings may elucidate the molecular basis for gemcitabine resistance and provide insights for effective drug combination in PDAC chemotherapy.

Evaluation of antihypertensive drug-induced changes in mandibular bone using fractal analysis

ObjectivesThe aim was to evaluate changes in trabecular and cortical mandibular bone caused by antihypertensive (AHT) drugs through fractal analysis. MethodsThis retrospective study included 230 patients who were taking AHT medication and had no conditions affecting bone metabolism other than hypertension. A control group of 230 healthy, sex-matched individuals was also included. Patients were divided into subgroups according to AHT drugs: thiazide diuretics (TDs), beta-blockers (BBs), angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), calcium channel blockers (CCBs), and a combination of drugs. The fractal dimension (FD) was calculated bilaterally in 5 regions of interest (ROI 1 – ROI 5) including 4 trabecular regions and 1 cortical region using Image J software. ResultsMean FD values were significantly higher in all ROIs for the study group compared to the control group (P<0.001). FDs were significantlty higher for BB, ACEI, ARB, CCB, and combined subgroups compared to controls in ROIs 1, 2, and 4; for ACEI and CCB subgroups compared to controls in ROI 3; and for TD, BB, ACEI, ARB, CCB, and combined subgroups compared to controls in ROI 5 (P<0.001). ConclusionAHTs may increase FD values of the trabecular and cortical structures. Assessment of the effects of AHT drugs is essential for predicting the prognosis for bone healing after tooth extraction, osseointegration after implant surgery or other surgical procedures.

GSFM: A genome-scale functional module transformation to represent drug efficacy for in silico drug discovery

Pharmacotranscriptomic profiles, which capture drug-induced changes in gene expression, offer vast potential for computational drug discovery and are widely used in modern medicine. However, current computational approaches neglected the associations within gene‒gene functional networks and unrevealed the systematic relationship between drug efficacy and the reversal effect. Here, we developed a new genome-scale functional module (GSFM) transformation framework to quantitatively evaluate drug efficacy for in silico drug discovery. GSFM employs four biologically interpretable quantifiers: GSFM_Up, GSFM_Down, GSFM_ssGSEA, and GSFM_TF to comprehensively evaluate the multi-dimension activities of each functional module (FM) at gene-level, pathway-level, and transcriptional regulatory network-level. Through a data transformation strategy, GSFM effectively converts noisy and potentially unreliable gene expression data into a more dependable FM active matrix, significantly outperforming other methods in terms of both robustness and accuracy. Besides, we found a positive correlation between RSGSFM and drug efficacy, suggesting that RSGSFM could serve as representative measure of drug efficacy. Furthermore, we identified WYE-354, perhexiline, and NTNCB as candidate therapeutic agents for the treatment of breast-invasive carcinoma, lung adenocarcinoma, and castration-resistant prostate cancer, respectively. The results from in vitro and in vivo experiments have validated that all identified compounds exhibit potent anti-tumor effects, providing proof-of-concept for our computational approach.

Applying Spatial Metabolomics To Investigate Age- and Drug-Induced Neurochemical Changes.

In an era when population aging is increasing the burden of neurodegenerative conditions, deciphering the mechanisms underlying brain senescence is more important than ever. Here, we present a spatial metabolomics analysis of age-induced neurochemical alterations in the mouse brain using negative ionization mode mass spectrometry imaging. The age-dependent effects of the acetylcholinesterase inhibitor tacrine were simultaneously examined. For ultrahigh mass resolution analysis, we utilized a Fourier-transform ion cyclotron resonance spectrometer. To complement this, a trapped ion mobility spectrometry time-of-flight analyzer provided high speed and lateral resolution. The chosen approach facilitated the detection and identification of a wide range of metabolites, from amino acids to sphingolipids. We reported significant, age-dependent alterations in brain lipids which were most evident for sulfatides and lysophosphatidic acids. Sulfatide species, which are mainly localized to white matter, either increased or decreased with age, depending on the carbon chain length and hydroxylation stage. Lysophosphatidic acids were found to decrease with age in the detailed cortical and hippocampal subregions. An age-dependent increase in the glutamine/glutamate ratio, an indicator of glia-neuron interconnection and neurotoxicity, was detected after tacrine administration. The presented metabolic mapping approach was able to provide visualizations of the lipid signaling and neurotransmission alterations induced by early aging and can thus be beneficial to further elucidating age-related neurochemical pathways.

SomaLogic proteomics reveals new biomarkers and provides mechanistic, clinical insights into Acetyl coA Carboxylase (ACC) inhibition in Non-alcoholic Steatohepatitis (NASH)

Non-alcoholic Fatty Liver Disease (NAFLD) and Non-alcoholic Steatohepatitis (NASH) are major metabolic diseases with increasing global prevalence and no approved therapies. There is a mounting need to develop biomarkers of diagnosis, prognosis and treatment response that can effectively replace current requirements for liver biopsies, which are invasive, error-prone and expensive. We performed SomaLogic serum proteome profiling with baseline (n = 231) and on-treatment (n = 72, Weeks 12 and 16, Placebo and 25 mg PF-05221304) samples from a Phase 2a trial (NCT03248882) with Clesacostat (PF-05221304), an acetyl coA carboxylase inhibitor (ACCi) in patients with NAFLD/NASH. SomaSignal NASH probability scores and expression data for 7000+ analytes were analyzed to identify potential biomarkers associated with baseline clinical measures of NAFLD/NASH [Magnetic Resonance Imaging-Proton Density Fat Fraction (MRI-PDFF), alanine aminotransferase (ALT) and aspartate aminotransferase (AST)] as well as biomarkers of treatment response to ACCi. SomaSignal NASH probability scores identified biopsy-proven/clinically defined NIT-based (Presumed) NASH classification of the cohort with > 70% agreement. Clesacostat-induced reduction in steatosis probability scores aligned with observed clinical reduction in hepatic steatosis based on MRI-PDFF. We identify a set of 69 analytes that robustly correlate with clinical measures of hepatic inflammation and steatosis (MRI-PDFF, ALT and AST), 27 of which were significantly reversed with ACC inhibition. Clesacostat treatment dramatically upregulated Wnt5a protein and Apolipoproteins C3 and E, with drug-induced changes significantly correlating to changes on MRI-PDFF. Our data demonstrate the utility of SomaLogic- analyte panel for diagnosis and treatment response in NAFLD/NASH and provide potential new mechanistic insights into liver steatosis reduction, inflammation and serum triglyceride elevation with ACC inhibition. (Clinical Trial Identifier: NCT03248882).