Biology subjects

Young, M. E.

Publications and source records attributed to Young, M. E..

8 recordsLinked to original sources

bioRxiv2024

Long-Term Effects of Early Adolescent Second-Generation Antipsychotic Exposure on Body Weight, Caloric Intake, and Metabolism-Associated Gene Expression

The use of second-generation antipsychotic (SGA) medications in pediatric patients raises concerns about potential long-term adverse outcomes. The current study evaluated the long-term effects of treatment with risperidone or olanzapine on body weight, caloric intake, serum insulin, blood glucose, and metabolism-associated gene expression in C57Bl/6J female mice. Compared to mice treated with vehicle, female mice treated with risperidone or olanzapine gained weight at higher rates during treatment and maintained higher body weights for months following treatment cessation. During high-fat diet feeding, some groups of treated mice gained weight at higher rates than their respective control groups, but the finding was not consistent across experiments. Finally, female mice previously treated with olanzapine also exhibited increased expression of genes associated with inflammation and lipogenesis. These findings suggest that pediatric use of SGA medications that induce excess weight gain during treatment may exert persistent effects on body weight and gene expression and such outcomes may form an important aspect of assessing risk-to-benefit ratios in prescribing decisions.

pharmacology and toxicology↗

bioRxiv2024

Acute increase of protein O-GlcNAcylation in mice leads to transcriptome changes in the brain opposite to what is observed in Alzheimer Disease

Enhancing protein O-GlcNAcylation by pharmacological inhibition of the enzyme O-GlcNAcase (OGA) is explored as a strategy to decrease tau and amyloid-beta phosphorylation, aggregation, and pathology in Alzheimers disease (AD). There is still more to be learned about the impact of enhancing global protein O-GlcNAcylation, which is important for understanding the mechanistic path of using OGA inhibition to treat AD. In this study, we investigated the acute effect of pharmacologically increasing O-GlcNAc levels, using OGA inhibitor Thiamet G (TG), on normal mouse brains. We hypothesized that the transcritome signature in respones to TG treatment provides a comprehensive view of the effect of OGA inhibition. We sacrificed the mice and dissected their brains after 3 hours of saline or 50 mg/kg TG treatment, and then performed mRNA sequencing using NovaSeq PE 150 (n=5 each group). We identified 1,234 significant differentially expressed genes with TG versus saline treatment. Functional enrichment analysis of the upregulated genes identified several upregulated pathways, including genes normally down in AD. Among the downregulated pathways were the cell adhesion pathway as well as genes normally up in AD and aging. When comparing acute to chronic TG treatment, protein autophosphorylation and kinase activity pathways were upregulated, whereas cell adhesion and astrocyte markers were downregulated in both datasets. Interestingly, mitochondrial genes and genes normally down in AD were up in acute treatment and down in chronic treatment. Data from this analysis will enable the evaluation of the mechanisms underlying the potential benefits of OGA inhibition in the treatment of AD. In particular, although OGA inhibitors are promising to treat AD, their downstream chronic effects related to bioenergetics may be a limiting factor. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=185 SRC="FIGDIR/small/613769v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@178dcf6org.highwire.dtl.DTLVardef@1f2cc78org.highwire.dtl.DTLVardef@14dfe28org.highwire.dtl.DTLVardef@16918aa_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

Impact of O-GlcNAcylation elevation on mitophagy and glia in the dentate gyrus

O-GlcNAcylation is a dynamic and reversible protein post-translational modification of serine or threonine residues which modulates the activity of transcriptional and signaling pathways and controls cellular responses to metabolic and inflammatory stressors. We and others have shown that O-GlcNAcylation has the potential to regulate autophagy and mitophagy to play a critical role in mitochondrial quality control, but this has not been assessed in vivo in the brain. This is important since mitochondrial dysfunction contributes to the development of neurodegenerative disease. We used mito-QC reporter mice to assess mitophagy in diverse cells in the dentate gyrus in response to pharmacological inhibition of OGA with thiamet G which leads to elevation of protein O-GlcNAcylation. We demonstrate that mitophagy occurs predominantly in the GFAP positive astrocytes and is significantly decreased in response to elevated O-GlcNAcylation. Furthermore, with increased O-GlcNAcylation, the levels of astrocyte makers GFAP and S100B, and microglial cell marker IBA1 were decreased in the dentate gyrus, while the levels of microglial cell marker TMEM119 were increased, indicating significant changes in glia homeostasis. These results provide strong evidence of the regulation of mitophagy and glia signatures by the O-GlcNAc pathway.

neuroscience↗

bioRxiv2023

Statistical power and false positive rates for interdependent outcomes are strongly influenced by test type: Implications for behavioral neuroscience

Statistical errors in preclinical science are a barrier to reproducibility and translation. For instance, linear models (e.g., ANOVA, linear regression) may be misapplied to data that violate assumptions. In behavioral neuroscience and psychopharmacology, linear models are frequently applied to interdependent or compositional data, which includes behavioral assessments where animals concurrently choose between chambers, objects, outcomes, or types of behavior (e.g., forced swim, novel object, place/social preference). The current study simulated behavioral data for a task with four interdependent choices (i.e., increased choice of a given outcome decreases others) using Monte Carlo methods. 16,000 datasets were simulated (1,000 each of 4 effect sizes by 4 sample sizes) and statistical approaches evaluated for accuracy. Linear regression and linear mixed effects regression (LMER) with a single random intercept resulted in high false positives (>60%). Elevated false positives were attenuated in an LMER with random effects for all choice-levels and a binomial logistic mixed effects regression. However, these models were underpowered to reliably detect effects at common preclinical sample sizes. A Bayesian method using prior knowledge for control subjects increased power by up to 30%. These results were confirmed in a second simulation (8,000 datasets). These data suggest that statistical analyses may often be misapplied in preclinical paradigms, with common linear methods increasing false positives, but potential alternatives lacking power. Ultimately, using informed priors may balance statistical requirements with ethical imperatives to minimize the number of animals used. These findings highlight the importance of considering statistical assumptions and limitations when designing research studies.

neuroscience↗

bioRxiv2021

Corticostriatal dynamics underlying components of binge-like eating in mice

Binge eating (BE) is a maladaptive repetitive feeding behavior present across nearly all eating disorder diagnoses. Despite the substantial negative impact of BE on psychological and physiological health, its underlying neural mechanisms are largely unknown. Other repetitive behavior disorders (e.g., obsessive compulsive disorder) show dysfunction within corticostriatal circuitry. Additionally, previous pre-clinical and clinical work has highlighted an imbalance between goal-directed and habitual responding in BE. The aim of the current study was to longitudinally examine in vivo neural activity within corticostriatal regions associated with habitual behavior- the infralimbic cortex (IL) and dorsolateral striatum (DLS)- in a robust pre-clinical model for BE. Female C57BL/6 mice (N=32) were randomized to receive: 1) intermittent (daily, 2-hour) binge-like access to palatable food (BE mice), or 2) continuous, non-intermittent (24-hour) access to palatable food (non-BE mice). In vivo calcium imaging was performed via fiber photometry at baseline and after chronic (4 weeks) engagement in the model for BE. Feeding behaviors (feeding bout onset/offset) during the recordings were captured using lickometers which generated TTL outputs for precise alignment of behavior to neural data. IL showed no specific changes in neural activity related to BE. However, BE animals showed decreased DLS activity at feeding onset and offset at the chronic timepoint when compared to baseline. Additionally, BE mice had significantly lower DLS activity at feeding onset and offset at the chronic timepoint compared to non-BE mice. These results point to a role for DLS hypofunction in chronic BE, highlighting a potential target for future treatment intervention. Significance StatementBinge eating is a chronic and repetitive eating behavior that is associated with poor physiological and psychosocial outcomes. Despite the negative impact of binge eating, little is known about the neurobiological mechanisms contributing to the chronic course and persistence of the behavior. To investigate potential neural mechanisms underlying binge eating, we are using approaches developed to monitor neural activity in rodents. This study is the first to identify longitudinal changes in neural activity within regions of the prefrontal cortex and dorsal striatum during binge-like eating behavior in mice. Findings from this work could inform targeted biological treatments for binge eating.

neuroscience↗

bioRxiv2021

BSCL2/Seipin Deficiency in Heart Causes Energy Deficit and Heart Failure via Inducing Excessive Lipid Catabolism

Heart failure (HF) is one of the leading causes of death world-wide and is associated with cardiac metabolic perturbations. Human Type 2 Berardinelli-Seip Congenital Lipodystrophy (BSCL2) disease is caused by mutations in the BSCL2 gene. Global lipodystrophic Bscl2-/- mice exhibit hypertrophic cardiomyopathy. Whether BSCL2 plays a direct role in regulating cardiac substrate metabolism and/or contractile function remains unknown. Here we show that mice with cardiac-specific deletion of Bscl2 (Bscl2cKO) developed dilated HF. Myocardial BSCL2 deletion led to elevated ATGL expression and FA oxidation (FAO) along with reduced cardiac lipid contents. Cardiac dysfunction in Bscl2cKO mice was independent of mitochondrial dysfunction and oxidative stress, but associated with decreased metabolic reserve and ATP levels. Importantly, heart failure in Bscl2cKO mice could be partially reversed by pharmacological inhibition of FAO, or prevented by high fat diet (HFD) feeding. Lipidomic analysis further identified markedly reduced glycerolipids, glycerophospholipids, NEFA and acylcarnitines in Bscl2cKO hearts, which were partially normalized by FAO inhibition or HFD. Our study reveals a new form of HF with excessive lipid catabolism, and identifies a crucial cardiomyocyte-specific role of BSCL2 in controlling cardiac lipid catabolism, energy state and contractile function. It also provides novel insights into metabolically treating energy-starved HF using FAO inhibitor or HFD.

physiology↗

bioRxiv2020

Inferring brain-wide interactions using data-constrained recurrent neural network models

Behavior arises from the coordinated activity of numerous anatomically and functionally distinct brain regions. Modern experimental tools allow unprecedented access to large neural populations spanning many interacting regions brain-wide. Yet, understanding such large-scale datasets necessitates both scalable computational models to extract meaningful features of inter-region communication and principled theories to interpret those features. Here, we introduce Current-Based Decomposition (CURBD), an approach for inferring brain-wide interactions using data-constrained recurrent neural network models that directly reproduce experimentally-obtained neural data. CURBD leverages the functional interactions inferred by such models to reveal directional currents between multiple brain regions. We first show that CURBD accurately isolates inter-region currents in simulated networks with known dynamics. We then apply CURBD to multi-region neural recordings obtained from mice during running, macaques during Pavlovian conditioning, and humans during memory retrieval to demonstrate the widespread applicability of CURBD to untangle brain-wide interactions underlying behavior from a variety of neural datasets.

neuroscience↗

bioRxiv2020

Temporally-specific sequences of neural activity across interconnected corticolimbic structures during reward anticipation

Functional neuroimaging studies indicate that interconnected parts of the subcallosal anterior cingulate cortex (ACC), striatum, and amygdala play a fundamental role in affect in health and disease. Yet, while the patterns of neural activity engaged in striatum and amygdala during affective processing are well established, especially during reward anticipation, little is known about subcallosal ACC. Here we recorded neural activity in non-human primate subcallosal ACC and compared this to interconnected parts of basolateral amygdala and rostromedial striatum while macaque monkeys performed reward-based tasks. Applying multiple analysis approaches, we found that neurons in subcallosal ACC and rostromedial striatum preferentially signal anticipated reward using short bursts of activity that form temporally specific patterns. By contrast, basolateral amygdala uses a mixture of both temporally specific and more sustained patterns of activity to signal anticipated reward. Thus, dynamic patterns of neural activity across populations of neurons are engaged in affect, especially in subcallosal ACC. HIGHLIGHTSO_LISustained changes in neural activity signal anticipated reward in basolateral amygdala C_LIO_LITemporally specific patterns signal anticipated reward in all areas recorded C_LIO_LINeurons exhibit more punctate encoding when tasks become more complex C_LIO_LITemporally specific patterns of neural activity signal different anticipated rewards in BLA C_LI

neuroscience↗