57 research outputs found

    Foxa1 Reduces Lipid Accumulation in Human Hepatocytes and Is Down-Regulated in Nonalcoholic Fatty Liver

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    Triglyceride accumulation in nonalcoholic fatty liver (NAFL) results from unbalanced lipid metabolism which, in the liver, is controlled by several transcription factors. The Foxa subfamily of winged helix/forkhead box (Fox) transcription factors comprises three members which play important roles in controlling both metabolism and homeostasis through the regulation of multiple target genes in the liver, pancreas and adipose tissue. In the mouse liver, Foxa2 is repressed by insulin and mediates fasting responses. Unlike Foxa2 however, the role of Foxa1 in the liver has not yet been investigated in detail. In this study, we evaluate the role of Foxa1 in two human liver cell models, primary cultured hepatocytes and HepG2 cells, by adenoviral infection. Moreover, human and rat livers were analyzed to determine Foxa1 regulation in NAFL. Results demonstrate that Foxa1 is a potent inhibitor of hepatic triglyceride synthesis, accumulation and secretion by repressing the expression of multiple target genes of these pathways (e.g., GPAM, DGAT2, MTP, APOB). Moreover, Foxa1 represses the fatty acid transporter protein FATP2 and lowers fatty acid uptake. Foxa1 also increases the breakdown of fatty acids by inducing peroxisomal fatty acid β-oxidation and ketone body synthesis. Finally, Foxa1 is able to largely up-regulate UCP1, thereby dissipating energy and consistently decreasing the mitochondria membrane potential. We also report that human and rat NAFL have a reduced Foxa1 expression, possibly through a protein kinase C-dependent pathway. We conclude that Foxa1 is an antisteatotic factor that coordinately tunes several lipid metabolic pathways to block triglyceride accumulation in hepatocytes. However, Foxa1 is down-regulated in human and rat NAFL and, therefore, increasing Foxa1 levels could protect from steatosis. Altogether, we suggest that Foxa1 could be a novel therapeutic target for NAFL disease and insulin resistance

    Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants with Treatment Resistance in Schizophrenia

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    Importance: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10501) and individuals with non-TRS (n = 20325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures: GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results: The study included a total of 85490 participants (48635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P =.001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P =.04). Conclusions and Relevance: In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance

    Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

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    Schizophrenia and bipolar disorder are two distinct diagnoses that share symptomology. Understanding the genetic factors contributing to the shared and disorder-specific symptoms will be crucial for improving diagnosis and treatment. In genetic data consisting of 53,555 cases (20,129 bipolar disorder [BD], 33,426 schizophrenia [SCZ]) and 54,065 controls, we identified 114 genome-wide significant loci implicating synaptic and neuronal pathways shared between disorders. Comparing SCZ to BD (23,585 SCZ, 15,270 BD) identified four genomic regions including one with disorder-independent causal variants and potassium ion response genes as contributing to differences in biology between the disorders. Polygenic risk score (PRS) analyses identified several significant correlations within case-only phenotypes including SCZ PRS with psychotic features and age of onset in BD. For the first time, we discover specific loci that distinguish between BD and SCZ and identify polygenic components underlying multiple symptom dimensions. These results point to the utility of genetics to inform symptomology and potential treatment

    dCREB2-Mediated Enhancement of Memory Formation

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    CREB-responsive transcription has an important role in adaptive responses in all cells and tissue. In the nervous system, it has an essential and well established role in long-term memory formation throughout a diverse set of organisms. Activation of this transcription factor correlates with long-term memory formation and disruption of its activity interferes with this process. Most convincingly, augmenting CREB activity in a number of different systems enhances memory formation. In Drosophila , a sequence rearrangement in the original transgene used to enhance memory formation has been a source of confusion. This rearrangement prematurely terminates translation of the full-length protein, leaving the identity of the “enhancing molecule” unclear. In this report, we show that a naturally occurring, downstream, in-frame initiation codon is used to make a dCREB2 protein off of both transgenic and chromosomal substrates. This protein is a transcriptional activator and is responsible for memory enhancement. A number of parameters can affect enhancement, including the short-lived activity of the activator protein, and the time-of-day when induction and behavioral training occur. Our results reaffirm that overexpression of a dCREB2 activator can enhance memory formation and illustrate the complexity of this behavioral enhancement

    dCREB2-Mediated Enhancement of Memory Formation

    No full text
    CREB-responsive transcription has an important role in adaptive responses in all cells and tissue. In the nervous system, it has an essential and well established role in long-term memory formation throughout a diverse set of organisms. Activation of this transcription factor correlates with long-term memory formation and disruption of its activity interferes with this process. Most convincingly, aug-menting CREB activity in a number of different systems enhances memory formation. In Drosophila, a sequence rearrangement in the original transgene used to enhance memory formation has been a source of confusion. This rearrangement prematurely terminates translation of the full-length protein, leaving the identity of the “enhancing molecule” unclear. In this report, we show that a naturally occurring, downstream, in-frame initiation codon is used to make a dCREB2 protein off of both transgenic and chromosomal substrates. This protein is a transcriptional activator and is responsible for memory enhancement. A number of parameters can affect enhancement, including the short-lived activity of the activator protein, and the time-of-day when induction and behavioral training occur. Our results reaffirm that overexpression of a dCREB2 activator can enhance memory formation and illustrate the complexity of this behavioral enhancement

    No One Leaves Unchanged: Insights for Civilian Mental Health Care Professionals Into the Military Experience and Culture

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    This article aims to elucidate an understanding of military culture and experience, so as to better frame the services offered by civilian clinicians. Service members indoctrinated into such an influential culture can experience adjustment problems upon reentry into the larger society, and thus professional counselors and social workers must be ready to address the reintegration process with veteran clients. Furthermore, this article highlights a few of the major mental health concerns that are prevalent in combat veterans, especially for those returning from Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF), and presents a brief overview of treatment modalities implemented both within and outside of the military. Practical therapeutic suggestions for clinicians with little or no knowledge of the military are discussed. The objective is to educate and prepare civilian mental health practitioners to administer culturally sensitive prevention and intervention services to meet the unique needs of this population

    ZIP in BLA Disrupts Inhibitory Avoidance Memory

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    <p>Latency to enter the dark compartment during the acquisition and retention phases of inhibitory avoidance. Retention was tested 24 h after acquisition, 2 h after the bilateral BLA injections (sal, <i>n</i> = 7; scr-ZIP, <i>n</i> = 15; and ZIP, <i>n</i> = 16). The latency to enter the dark compartment was similar across groups during acquisition, but not during retention. The interaction between group and phase of the inhibitory avoidance task was significant (<i>F</i><sub>2,35</sub> = 4.28; <i>p</i> = 0.02). ZIP impaired retention of inhibitory avoidance compared to the animals treated with saline and scr-ZIP, which were indistinguishable. The asterisk (*) indicates <i>p</i> < 0.01, ZIP relative to saline and scr-ZIP. All data are presented as averages, with error bars indicating standard errors of the mean.</p

    ZIP in BLA Disrupts Classically Conditioned Fear Memory

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    <div><p>(A) Retention of context-conditioned fear 26 h after bilateral DH injection of saline (sal, <i>n</i> = 4), inactive (scr-ZIP, <i>n</i> = 7), or active ZIP (<i>n</i> = 6). ZIP did not impair retention of contextual fear (<i>F</i><sub>2,14</sub> = 0.15; <i>p</i> = 0.86).</p> <p>(B) Retention of tone-conditioned fear after 22-h posttraining bilateral BLA injections. Retention was tested 2 h (sal, <i>n</i> = 6; scr-ZIP <i>n</i> = 3; ZIP <i>n</i> = 10) or 24 h (sal, <i>n</i> = 5; scr-ZIP <i>n</i> = 4; ZIP <i>n</i> = 8) after the injection. ZIP impaired retention of tone-conditioned fear (<i>F</i><sub>2,33</sub> = 4.93; <i>p</i> = 0.01).</p> <p>(C) Immediate postshock freezing after bilateral BLA injections. Fear was tested 5 min (sal, <i>n</i> = 4; ZIP, <i>n</i> = 4) or 120 min (sal, <i>n</i> = 5; ZIP, <i>n</i> = 5) after the injections. ZIP did not affect immediate postshock freezing, indicating the expression of fear was intact (<i>F</i><sub>1,16</sub> = 0.58; <i>p</i> = 0.46). All data are presented as averages, with error bars indicating standard errors of the mean.</p></div
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