Imaging the pathophysiology of major depressive disorder - from localist models to circuit-based analysis

The neuroimaging literature of Major Depressive Disorder (MDD) has grown substantially over the last several decades, facilitating great advances in the identification of specific brain regions, neurotransmitter systems and networks associated with depressive illness. Despite this progress, fundamental questions remain about the pathophysiology and etiology of MDD. More importantly, this body of work has yet to directly influence clinical practice. It has long been a goal for the fields of clinical psychology and psychiatry to have a means of making objective diagnoses of mental disorders. Frustratingly little movement has been achieved on this front, however, and the 'gold-standard’ of diagnostic validity and reliability remains expert consensus. In light of this challenge, the focus of the current review is to provide a critical summary of key findings from different neuroimaging approaches in MDD research, including structural, functional and neurochemical imaging studies. Following this summary, we discuss some of the current conceptual obstacles to better understanding the pathophysiology of depression, and conclude with recommendations for future neuroimaging research

Perceived Stress Predicts Altered Reward and Loss Feedback Processing in Medial Prefrontal Cortex

Stress is a significant risk factor for the development of psychopathology, particularly symptoms related to reward processing. Importantly, individuals display marked variation in how they perceive and cope with stressful events, and such differences are strongly linked to risk for developing psychiatric symptoms following stress exposure. However, many questions remain regarding the neural architecture that underlies inter-subject variability in perceptions of stressors. Using functional magnetic resonance imaging (fMRI) during a Monetary Incentive Delay (MID) paradigm, we examined the effects of self-reported perceived stress levels on neural activity during reward anticipation and feedback in a sample of healthy individuals. We found that subjects reporting more uncontrollable and overwhelming stressors displayed blunted neural responses in medial prefrontal cortex (mPFC) following feedback related to monetary gains as well monetary losses. This is consistent with preclinical models that implicate the mPFC as a key site of vulnerability to the noxious effects of uncontrollable stressors. Our data help translate these findings to humans, and elucidate some of the neural mechanisms that may underlie stress-linked risk for developing reward-related psychiatric symptoms.Psycholog

Does Professionalism Matter in the IT Workforce? An Empirical Examination of IT Professionals

This paper investigates the role of professionalism in the information technology (IT) workforce. We develop a model that describes how professionalism relates to attitudes, perceptions, and behaviors among IT professionals. Specifically, we hypothesize that dimensions of professionalism influence attitudes (including intrinsic motivation, job satisfaction, and organizational commitment), perceived job alternatives, job performance, and turnover. We test the research model with data, which includes supervisor evaluations and actual turnover data drawn from 214 IT professionals. Results show that some dimensions of professionalism demonstrate a positive relationship with intrinsic motivation, job satisfaction, and job performance. Other dimensions have no effect or positively influence awareness of job alternatives, driving turnover intention. As the IT workforce grows increasingly professional, managers may benefit from more satisfied, harder-working IT personnel at the cost of having a workforce more connected to the labor market

Adults with autism spectrum disorders exhibit decreased sensitivity to reward parameters when making effort-based decisions

Background: Efficient effort expenditure to obtain rewards is critical for optimal goal-directed behavior and learning. Clinical observation suggests that individuals with autism spectrum disorders (ASD) may show dysregulated reward-based effort expenditure, but no behavioral study to date has assessed effort-based decision-making in ASD. Methods: The current study compared a group of adults with ASD to a group of typically developing adults on the Effort Expenditure for Rewards Task (EEfRT), a behavioral measure of effort-based decision-making. In this task, participants were provided with the probability of receiving a monetary reward on a particular trial and asked to choose between either an “easy task” (less motoric effort) for a small, stable reward or a “hard task” (greater motoric effort) for a variable but consistently larger reward. Results: Participants with ASD chose the hard task more frequently than did the control group, yet were less influenced by differences in reward value and probability than the control group. Additionally, effort-based decision-making was related to repetitive behavior symptoms across both groups. Conclusions: These results suggest that individuals with ASD may be more willing to expend effort to obtain a monetary reward regardless of the reward contingencies. More broadly, results suggest that behavioral choices may be less influenced by information about reward contingencies in individuals with ASD. This atypical pattern of effort-based decision-making may be relevant for understanding the heightened reward motivation for circumscribed interests in ASD

Effect of Social Influence on Effort-Allocation for Monetary Rewards

Though decades of research have shown that people are highly influenced by peers, few studies have directly assessed how the value of social conformity is weighed against other types of costs and benefits. Using an effort-based decision-making paradigm with a novel social influence manipulation, we measured how social influence affected individuals’ decisions to allocate effort for monetary rewards during trials with either high or low probability of receiving a reward. We found that information about the effort-allocation of peers modulated participant choices, specifically during conditions of low probability of obtaining a reward. This suggests that peer influence affects effort-based choices to obtain rewards especially under conditions of risk. This study provides evidence that people value social conformity in addition to other costs and benefits when allocating effort, and suggests that neuroeconomic studies that assess trade-offs between effort and reward should consider social environment as a factor that can influence decision-making

Modeling the Mechanism of Action of a DGAT1 Inhibitor Using a Causal Reasoning Platform

Triglyceride accumulation is associated with obesity and type 2 diabetes. Genetic disruption of diacylglycerol acyltransferase 1 (DGAT1), which catalyzes the final reaction of triglyceride synthesis, confers dramatic resistance to high-fat diet induced obesity. Hence, DGAT1 is considered a potential therapeutic target for treating obesity and related metabolic disorders. However, the molecular events shaping the mechanism of action of DGAT1 pharmacological inhibition have not been fully explored yet. Here, we investigate the metabolic molecular mechanisms induced in response to pharmacological inhibition of DGAT1 using a recently developed computational systems biology approach, the Causal Reasoning Engine (CRE). The CRE algorithm utilizes microarray transcriptomic data and causal statements derived from the biomedical literature to infer upstream molecular events driving these transcriptional changes. The inferred upstream events (also called hypotheses) are aggregated into biological models using a set of analytical tools that allow for evaluation and integration of the hypotheses in context of their supporting evidence. In comparison to gene ontology enrichment analysis which pointed to high-level changes in metabolic processes, the CRE results provide detailed molecular hypotheses to explain the measured transcriptional changes. CRE analysis of gene expression changes in high fat habituated rats treated with a potent and selective DGAT1 inhibitor demonstrate that the majority of transcriptomic changes support a metabolic network indicative of reversal of high fat diet effects that includes a number of molecular hypotheses such as PPARG, HNF4A and SREBPs. Finally, the CRE-generated molecular hypotheses from DGAT1 inhibitor treated rats were found to capture the major molecular characteristics of DGAT1 deficient mice, supporting a phenotype of decreased lipid and increased insulin sensitivity

Human liver glycogen phosphorylase inhibitors bind at a new allosteric site

AbstractBackground: Glycogen phosphorylases catalyze the breakdown of glycogen to glucose-1-phosphate for glycolysis. Maintaining control of blood glucose levels is critical in minimizing the debilitating effects of diabetes, making liver glycogen phosphorylase a potential therapeutic target.Results: The binding site in human liver glycogen phosphorylase (HLGP) for a class of promising antidiabetic agents was identified crystallographically. The site is novel and functions allosterically by stabilizing the inactive conformation of HLGP. The initial view of the complex revealed key structural information and inspired the design of a new class of inhibitors which bind with nanomolar affinity and whose crystal structure is also described.Conclusions: We have identified the binding site of a new class of allosteric HLGP inhibitors. The crystal structure revealed the details of inhibitor binding, led to the design of a new class of compounds, and should accelerate efforts to develop therapeutically relevant molecules for the treatment of diabetes

Polyomic profiling reveals significant hepatic metabolic alterations in glucagon-receptor (GCGR) knockout mice: implications on anti-glucagon therapies for diabetes

<p>Abstract</p> <p>Background</p> <p>Glucagon is an important hormone in the regulation of glucose homeostasis, particularly in the maintenance of euglycemia and prevention of hypoglycemia. In type 2 Diabetes Mellitus (T2DM), glucagon levels are elevated in both the fasted and postprandial states, which contributes to inappropriate hyperglycemia through excessive hepatic glucose production. Efforts to discover and evaluate glucagon receptor antagonists for the treatment of T2DM have been ongoing for approximately two decades, with the challenge being to identify an agent with appropriate pharmaceutical properties and efficacy relative to potential side effects. We sought to determine the hepatic & systemic consequence of full glucagon receptor antagonism through the study of the glucagon receptor knock-out mouse (Gcgr^-/-) compared to wild-type littermates.</p> <p>Results</p> <p>Liver transcriptomics was performed using Affymetric expression array profiling, and liver proteomics was performed by iTRAQ global protein analysis. To complement the transcriptomic and proteomic analyses, we also conducted metabolite profiling (~200 analytes) using mass spectrometry in plasma. Overall, there was excellent concordance (R = 0.88) for changes associated with receptor knock-out between the transcript and protein analysis. Pathway analysis tools were used to map the metabolic processes in liver altered by glucagon receptor ablation, the most notable being significant down-regulation of gluconeogenesis, amino acid catabolism, and fatty acid oxidation processes, with significant up-regulation of glycolysis, fatty acid synthesis, and cholesterol biosynthetic processes. These changes at the level of the liver were manifested through an altered plasma metabolite profile in the receptor knock-out mice, e.g. decreased glucose and glucose-derived metabolites, and increased amino acids, cholesterol, and bile acid levels.</p> <p>Conclusions</p> <p>In sum, the results of this study suggest that the complete ablation of hepatic glucagon receptor function results in major metabolic alterations in the liver, which, while promoting improved glycemic control, may be associated with adverse lipid changes.</p