Ketamine and Imipramine Reverse Transcriptional Signatures of Susceptibility and Induce Resilience-Specific Gene Expression Profiles.

BACKGROUND: Examining transcriptional regulation by antidepressants in key neural circuits implicated in depression and understanding the relation to transcriptional mechanisms of susceptibility and natural resilience may help in the search for new therapeutic agents. Given the heterogeneity of treatment response in human populations, examining both treatment response and nonresponse is critical. METHODS: We compared the effects of a conventional monoamine-based tricyclic antidepressant, imipramine, and a rapidly acting, non-monoamine-based antidepressant, ketamine, in mice subjected to chronic social defeat stress, a validated depression model, and used RNA sequencing to analyze transcriptional profiles associated with susceptibility, resilience, and antidepressant response and nonresponse in the prefrontal cortex (PFC), nucleus accumbens, hippocampus, and amygdala. RESULTS: We identified similar numbers of responders and nonresponders after ketamine or imipramine treatment. Ketamine induced more expression changes in the hippocampus; imipramine induced more expression changes in the nucleus accumbens and amygdala. Transcriptional profiles in treatment responders were most similar in the PFC. Nonresponse reflected both the lack of response-associated gene expression changes and unique gene regulation. In responders, both drugs reversed susceptibility-associated transcriptional changes and induced resilience-associated transcription in the PFC. CONCLUSIONS: We generated a uniquely large resource of gene expression data in four interconnected limbic brain regions implicated in depression and its treatment with imipramine or ketamine. Our analyses highlight the PFC as a key site of common transcriptional regulation by antidepressant drugs and in both reversing susceptibility- and inducing resilience-associated molecular adaptations. In addition, we found region-specific effects of each drug, suggesting both common and unique effects of imipramine versus ketamine.

Metabolomic biosignature differentiates melancholic depressive patients from healthy controls.

BACKGROUND: Major depressive disorder (MDD) is a heterogeneous disease at the level of clinical symptoms, and this heterogeneity is likely reflected at the level of biology. Two clinical subtypes within MDD that have garnered interest are "melancholic depression" and "anxious depression". Metabolomics enables us to characterize hundreds of small molecules that comprise the metabolome, and recent work suggests the blood metabolome may be able to inform treatment decisions for MDD, however work is at an early stage. Here we examine a metabolomics data set to (1) test whether clinically homogenous MDD subtypes are also more biologically homogeneous, and hence more predictiable, (2) devise a robust machine learning framework that preserves biological meaning, and (3) describe the metabolomic biosignature for melancholic depression. RESULTS: With the proposed computational system we achieves around 80 % classification accuracy, sensitivity and specificity for melancholic depression, but only ~72 % for anxious depression or MDD, suggesting the blood metabolome contains more information about melancholic depression.. We develop an ensemble feature selection framework (EFSF) in which features are first clustered, and learning then takes place on the cluster centroids, retaining information about correlated features during the feature selection process rather than discarding them as most machine learning methods will do. Analysis of the most discriminative feature clusters revealed differences in metabolic classes such as amino acids and lipids as well as pathways studied extensively in MDD such as the activation of cortisol in chronic stress. CONCLUSIONS: We find the greater clinical homogeneity does indeed lead to better prediction based on biological measurements in the case of melancholic depression. Melancholic depression is shown to be associated with changes in amino acids, catecholamines, lipids, stress hormones, and immune-related metabolites. The proposed computational framework can be adapted to analyze data from many other biomedical applications where the data has similar characteristics.

GPR139, an Orphan Receptor Highly Enriched in the Habenula and Septum, Is Activated by the Essential Amino Acids L-Tryptophan and L-Phenylalanine.

GPR139 is an orphan G-protein-coupled receptor expressed in the central nervous system. To identify its physiologic ligand, we measured GPR139 receptor activity from recombinant cells after treatment with amino acids, orphan ligands, serum, and tissue extracts. GPR139 activity was measured using guanosine 5'-O-(3-[(35)S]thio)-triphosphate binding, calcium mobilization, and extracellular signal-regulated kinases phosphorylation assays. Amino acids L-tryptophan (L-Trp) and L-phenylalanine (L-Phe) activated GPR139, with EC50 values in the 30- to 300-µM range, consistent with the physiologic concentrations of L-Trp and L-Phe in tissues. Chromatography of rat brain, rat serum, and human serum extracts revealed two peaks of GPR139 activity, which corresponded to the elution peaks of L-Trp and L-Phe. With the purpose of identifying novel tools to study GPR139 function, a high-throughput screening campaign led to the identification of a selective small-molecule agonist [JNJ-63533054, (S)-3-chloro-N-(2-oxo-2-((1-phenylethyl)amino)ethyl) benzamide]. The tritium-labeled JNJ-63533054 bound to cell membranes expressing GPR139 and could be specifically displaced by L-Trp and L-Phe. Sequence alignment revealed that GPR139 is highly conserved across species, and RNA sequencing studies of rat and human tissues indicated its exclusive expression in the brain and pituitary gland. Immunohistochemical analysis showed specific expression of the receptor in circumventricular regions of the habenula and septum in mice. Together, these findings suggest that L-Trp and L-Phe are candidate physiologic ligands for GPR139, and we hypothesize that this receptor may act as a sensor to detect dynamic changes of L-Trp and L-Phe in the brain.

Effects of meal size on the release of GLP-1 and PYY after Roux-en-Y gastric bypass surgery in obese subjects with or without type 2 diabetes.

Changes in gastrointestinal peptide release may play an important role in improving glucose control and reducing body weight following Roux-en-Y gastric bypass (RYGB), but the impact of low caloric intake on gut peptide release post-surgery has not been well characterized. The purpose of this study was to assess the relationships between low caloric intake and gut peptide release and how they were altered by RYGB. Obese females including ten normoglycemic (ON) and ten with type 2 diabetes mellitus (T2DM) (OD) were studied before, 1 week, and 3 months after RYGB. Nine lean, normoglycemic women were studied for comparison. Subjects were given three separate mixed meal challenges (MMCs; 75, 150, and 300 kcal). Plasma glucagon-like peptide 1 (GLP-1) and peptide YY (PYY) were analyzed. Prior to surgery, only minimal increases in GLP-1 and PYY were observed in response to the MMCs. After surgery, the peak GLP-1 concentration was progressively elevated in response to increasing meal sizes. The meal sizes had a statistically significant impact on elevation of GLP-1 incremental areas under the curve (ΔAUC) in both ON and OD at 1 week and 3 months post-surgery visits (p < 0.05 for all comparisons). The PYY ∆AUC was also significantly increased in a meal size-dependent manner in both ON and OD at both post-surgery visits (p < 0.05 for all comparisons). Meal sizes as small as 75-300 kcal, which cause minimal stimulation in GLP-1 or PYY release in the subjects before RYGB, are sufficient to provide statistically significant, meal size-dependent increases in the peptides post-RYGB both acutely and after meaningful weight loss occurred.

Roux-en-Y gastric bypass corrects hyperinsulinemia implications for the remission of type 2 diabetes.

CONTEXT: Roux-en-Y gastric bypass (RYGB) has been shown to induce rapid and durable reversal of type 2 diabetes. OBJECTIVE: The aim of the study was to investigate a possible mechanism for the remission of type 2 diabetes after RYGB. DESIGN: A cross-sectional, nonrandomized, controlled study was conducted. Surgery patients were studied before RYGB and 1 wk and 3 months after surgery. SETTING: This study was conducted at East Carolina University. SUBJECTS: Subjects were recruited into three groups: 1) lean controls with no surgery [body mass index (BMI) < 25 kg/m²; n = 9], 2) severely obese type 2 diabetic patients (BMI > 35 kg/m²; n = 9), and 3) severely obese nondiabetic patients (BMI > 35 kg/m²; n = 9). INTERVENTION: Intervention was RYGB. RESULTS: One week after RYGB, diabetes was resolved despite continued insulin resistance (insulin sensitivity index was approximately 50% of lean controls) and reduced insulin secretion during an iv glucose tolerance test (acute insulin response to glucose was approximately 50% of lean controls). Fasting insulin decreased and was no different from lean control despite continued elevated glucose in the type 2 diabetic patients compared with lean. CONCLUSIONS: After RYGB, fasting insulin decreases to levels like those of lean control subjects and diabetes is reversed (fasting blood glucose < 125 mg/dl). This leads us to propose that 1) exclusion of food from the foregut corrects hyperinsulinemia and 2) fasting insulin is dissociated from the influence of fasting glucose, insulin resistance, and BMI. The mechanisms for reversal of diabetes in the face of reduced insulin remain a paradox.

Predictive toxicogenomics approaches reveal underlying molecular mechanisms of nongenotoxic carcinogenicity.

Toxicogenomics technology defines toxicity gene expression signatures for early predictions and hypotheses generation for mechanistic studies, which are important approaches for evaluating toxicity of drug candidate compounds. A large gene expression database built using cDNA microarrays and liver samples treated with over one hundred paradigm compounds was mined to determine gene expression signatures for nongenotoxic carcinogens (NGTCs). Data were obtained from male rats treated for 24 h. Training/testing sets of 24 NGTCs and 28 noncarcinogens were used to select genes. A semiexhaustive, nonredundant gene selection algorithm yielded six genes (nuclear transport factor 2, NUTF2; progesterone receptor membrane component 1, Pgrmc1; liver uridine diphosphate glucuronyltransferase, phenobarbital-inducible form, UDPGTr2; metallothionein 1A, MT1A; suppressor of lin-12 homolog, Sel1h; and methionine adenosyltransferase 1, alpha, Mat1a), which identified NGTCs with 88.5% prediction accuracy estimated by cross-validation. This six genes signature set also predicted NGTCs with 84% accuracy when samples were hybridized to commercially available CodeLink oligo-based microarrays. To unveil molecular mechanisms of nongenotoxic carcinogenesis, 125 differentially expressed genes (P<0.01) were selected by Student's t-test. These genes appear biologically relevant, of 71 well-annotated genes from these 125 genes, 62 were overrepresented in five biochemical pathway networks (most linked to cancer), and all of these networks were linked by one gene, c-myc. Gene expression profiling at early time points accurately predicts NGTC potential of compounds, and the same data can be mined effectively for other toxicity signatures. Predictive genes confirm prior work and suggest pathways critical for early stages of carcinogenesis.

Drug-induced oxidative stress in rat liver from a toxicogenomics perspective.

Macrophage activators (MA), peroxisome proliferators (PP), and oxidative stressors/reactive metabolites (OS/RM) all produce oxidative stress and hepatotoxicity in rats. However, these three classes of hepatotoxicants give three distinct gene transcriptional profiles on cDNA microarrays, an indication that rat hepatocytes respond/adapt quite differently to these three classes of oxidative stressors. The differential gene responses largely reflect differential activation of transcription factors: MA activate Stat-3 and NFkB, PP activate PPARa, and OS/RM activate Nrf2. We have used gene signature profiles for each of these three classes of hepatotoxicants to categorize over 100 paradigm (and 50+ in-house proprietary) compounds as to their oxidative stress potential in rat liver. In addition to a role for microarrays in predictive toxicology, analyses of small subsets of these signature profiles, genes within a specific pathway, or even single genes often provide important insights into possible mechanisms involved in the toxicities of these compounds.

A gene expression signature for oxidant stress/reactive metabolites in rat liver.

Formation of free radicals and other reactive molecules is responsible for the adverse effects produced by a number of hepatotoxic compounds. cDNA microarray technology was used to compare transcriptional profiles elicited by training and testing sets of 15 oxidant stressors/reactive metabolite treatments to those produced by approximately 85 other paradigm compounds (mostly hepatotoxicants) to determine a shared signature profile for oxidant stress-associated hepatotoxicity. Initially, 100 genes were chosen that responded significantly different to oxidant stressors/reactive metabolites (OS/RM) compared to other samples in the database, then a 25-gene subset was selected by multivariate analysis. Many of the selected genes (e.g., aflatoxin aldehyde reductase, diaphorase, epoxide hydrolase, heme oxgenase and several glutathione transferases) are well-characterized oxidant stress/Nrf-2-responsive genes. Less than 10 other compounds co-cluster with our training and testing set compounds and these are known to generate OS/RMs as part of their mechanisms of toxicity. Using OS/RM signature gene sets, compounds previously associated with macrophage activation formed a distinct cluster separate from OS/RM and other compounds. A 69-gene set was chosen to maximally separate compounds in control, macrophage activator, peroxisome proliferator and OS/RM classes. The ease with which these 'oxidative stressor' classes can be separated indicates a role for microarray technology in early prediction and classification of hepatotoxicants. The ability to rapidly screen the oxidant stress potential of compounds may aid in avoidance of some idiosyncratic drug reactions as well as overtly toxic compounds.

Inverse gene expression patterns for macrophage activating hepatotoxicants and peroxisome proliferators in rat liver.

Macrophage activation contributes to adverse effects produced by a number of hepatotoxic compounds. Transcriptional profiles elicited by two macrophage activators, LPS and zymosan A, were compared to those produced by 100 paradigm compounds (mostly hepatotoxicants) using cDNA microarrays. Several hepatotoxicants previously reported to activate liver macrophages produced transcriptional responses similar to LPS and zymosan, and these were used to construct a gene signature profile for macrophage activators in the liver. Measurement of cytokine mRNAs in the same liver samples by RT-PCR independently confirmed that these compounds are associated with macrophage activation. In addition to expected effects on acute phase proteins and metabolic pathways that are regulated by LPS and inflammation, a strong induction was observed for many endoplasmic reticulum-associated stress/chaperone proteins. Additionally, many genes in our macrophage activator signature profile were well-characterized PPARalpha-induced genes which were repressed by macrophage activators. A shared gene signature profile for peroxisome proliferators was determined using a training set of clofibrate, WY 14643, diethylhexylphthalate, diisononylphthalate, perfluorodecanoic acid, perfluoroheptanoic acid, and perfluorooctanoic acid. The signature profile included macrophage activator-induced genes that were repressed by peroxisome proliferators. NSAIDs comprised an interesting pharmacological class in that some compounds, notably diflunisal, co-clustered with peroxisome proliferators whereas several others co-clustered with macrophage activators, possibly due to endotoxin exposure secondary to their adverse effects on the gastrointestinal system. While much of these data confirmed findings from the literature, the transcriptional patterns detected using this toxicogenomics approach showed relationships between genes and biological pathways requiring complex analysis to be discerned.

Mutational analysis of the transcription factor IIIB-DNA target of Ty3 retroelement integration.

The Ty3 retrovirus-like element inserts preferentially at the transcription initiation sites of genes transcribed by RNA polymerase III. The requirements for transcription factor (TF) IIIC and TFIIIB in Ty3 integration into the two initiation sites of the U6 gene carried on pU6LboxB were previously examined. Ty3 integrates at low but detectable frequencies in the presence of TFIIIB subunits Brf1 and TATA-binding protein. Integration increases in the presence of the third subunit, Bdp1. TFIIIC is not essential, but the presence of TFIIIC specifies an orientation of TFIIIB for transcriptional initiation and directs integration to the U6 gene-proximal initiation site. In the current study, recombinant wild type TATA-binding protein, wild type and mutant Brf1, and Bdp1 proteins and highly purified TFIIIC were used to investigate the roles of specific protein domains in Ty3 integration. The amino-terminal half of Brf1, which contains a TFIIB-like repeat, contributed more strongly than the carboxyl-terminal half of Brf1 to Ty3 targeting. Each half of Bdp1 split at amino acid 352 enhanced integration. In the presence of TFIIIB and TFIIIC, the pattern of integration extended downstream by several base pairs compared with the pattern observed in vitro in the absence of TFIIIC and in vivo, suggesting that TFIIIC may not be present on genes targeted by Ty3 in vivo. Mutations in Bdp1 that affect its interaction with TFIIIC resulted in TFIIIC-independent patterns of Ty3 integration. Brf1 zinc ribbon and Bdp1 internal deletion mutants that are competent for polymerase III recruitment but defective in promoter opening were competent for Ty3 integration irrespective of the state of DNA supercoiling. These results extend the similarities between the TFIIIB domains required for transcription and Ty3 integration and also reveal requirements that are specific to transcription.