Dopaminergic contributions to hippocampal pathophysiology in schizophrenia: a computational study

Psychopathological characteristics in patients with arginine vasopressin deficiency (central diabetes insipidus) and primary polydipsia compared to healthy controls

OBJECTIVE

Distinguishing arginine vasopressin deficiency (AVP-D; central diabetes insipidus) from primary polydipsia (PP), commonly referred to as psychogenic polydipsia, is challenging. Psychopathologic findings, commonly used for PP diagnosis in clinical practice, are rarely evaluated in AVP-D patients, and no comparative data between the two conditions currently exist.

DESIGN

Data from two studies involving 82 participants [39 AVP-D, 28 PP, and 15 healthy controls (HC)].

METHODS

Psychological evaluations were conducted using standardized questionnaires measuring anxiety [State-Trait Anxiety Inventory (STAI)], alexithymia [Toronto Alexithymia Scale (TAS-20)], depressive symptoms (Beck's Depression Inventory-II (BDI-II), and overall mental health [Short Form-36 Health Survey (SF-36)]. Higher STAI, TAS-20, and BDI-II scores suggest elevated anxiety, alexithymia, and depression, while higher SF-36 scores signify better overall mental health.

RESULTS

Compared to HC, patients with AVP-D and PP showed higher levels of anxiety (HC 28 points [24-31] vs AVP-D 36 points [31-45]; vs PP 38 points [33-46], P < .01), alexithymia (HC 30 points [29-37] vs AVP-D 43 points [35-54]; vs PP 46 points [37-55], P < .01), and depression (HC 1 point [0-2] vs AVP-D 7 points [4-14]; vs PP 7 points [3-13], P < .01). Levels of anxiety, alexithymia, and depression showed no difference between both patient groups (P = .58, P = .90, P = .50, respectively). Compared to HC, patients with AVP-D and PP reported similarly reduced self-reported overall mental health scores (HC 84 [68-88] vs AVP-D 60 [52-80], P = .05; vs PP 60 [47-74], P < .01).

CONCLUSION

This study reveals heightened anxiety, alexithymia, depression, and diminished overall mental health in patients with AVP-D and PP. The results emphasize the need for careful interpretation of psychopathological characteristics to differentiate between AVP-D and PP.

Electroencephalographic study of chlorpromazine alone or combined with alpha-lipoic acid in a model of schizophrenia induced by ketamine in rats

Schizophrenia is characterized by behavioral symptoms, brain function impairments and electroencephalographic (EEG) changes. Dysregulation of immune responses and oxidative imbalance underpins this mental disorder. The present study aimed to investigate the effects of the typical antipsychotic chlorpromazine (CP) alone or combined with the natural antioxidant alpha-lipoic acid (ALA) on changes in the hippocampal average spectral power induced by ketamine (KET). Three days after stereotactic implantation of electrodes, male Wistar rats were divided into groups treated for 10 days with saline (control) or KET (10 mg/kg, IP). CP (1 or 5 mg/kg, IP) alone or combined with ALA (100 mg/kg, P.O.) was administered 30 min before KET or saline. Hippocampal EEG recordings were taken on the 1st, 5th and 10th days of treatment immediately after the last drug administration. KET significantly increased average spectral power of delta and gamma-high bands on the 5th and 10th days of treatment when compared to control. Gamma low-band significantly increased on the 1st, 5th and 10th days when compared to control group. This effect of KET was prevented by CP alone or combined with ALA. Indeed, the combination of ALA 100 + CP1 potentiated the inhibitory effects of CP1 on gamma low-band oscillations. In conclusion, our results showed that KET presents excitatory and time-dependent effects on hippocampal EEG bands activity. KET excitatory effects on EEG were prevented by CP alone and in some situations potentiated by its combination with ALA.

An in Silico, Biomarker-Based Method for the Evaluation of Virtual Neuropsychiatric Drug Effects

The recent explosion in neuroscience research has markedly increased our understanding of the neurobiological correlates of many psychiatric illnesses, but this has unfortunately not translated into more effective pharmacologic treatments for these conditions. At the same time, researchers have increasingly sought out biological markers, or biomarkers, as a way to categorize psychiatric illness, as these are felt to be closer to underlying genetic and neurobiological vulnerabilities. While biomarker-based drug discovery approaches have tended to employ in vivo (e.g., rodent) or in vitro test systems, relatively little attention has been paid to the potential of computational, or in silico, methodologies. Here we describe such a methodology, using as an example a biophysically detailed computational model of hippocampus that is made to generate putative schizophrenia biomarkers by the inclusion of a number of neuropathological changes that have been associated with the illness (NMDA system deficit, decreased neural connectivity, hyperdopaminergia). We use the specific inability to attune to gamma band (40 Hz) auditory stimulus as our illness biomarker. We expose this system to a large number of virtual medications, defined by systematic variation of model parameters corresponding to five cellular-level effects. The potential efficacy of virtual medications is determined by a wellness metric (WM) that we have developed. We identify a number of virtual agents that consist of combinations of mechanisms, which are not simply reversals of the causative lesions. The manner in which this methodology could be extended to other neuropsychiatric conditions, such as Alzheimer's disease, autism, and fragile X syndrome, is discussed.

Methamphetamine compromises gap junctional communication in astrocytes and neurons

Methamphetamine (meth) is a central nervous system (CNS) stimulant that results in psychological and physical dependency. The long-term effects of meth within the CNS include neuronal plasticity changes, blood-brain barrier compromise, inflammation, electrical dysfunction, neuronal/glial toxicity, and an increased risk to infectious diseases including HIV. Most of the reported meth effects in the CNS are related to dysregulation of chemical synapses by altering the release and uptake of neurotransmitters, especially dopamine, norepinephrine, and epinephrine. However, little is known about the effects of meth on connexin (Cx) containing channels, such as gap junctions (GJ) and hemichannels (HC). We examined the effects of meth on Cx expression, function, and its role in NeuroAIDS. We found that meth altered Cx expression and localization, decreased GJ communication between neurons and astrocytes, and induced the opening of Cx43/Cx36 HC. Furthermore, we found that these changes in GJ and HC induced by meth treatment were mediated by activation of dopamine receptors, suggesting that dysregulation of dopamine signaling induced by meth is essential for GJ and HC compromise. Meth-induced changes in GJ and HC contributed to amplified CNS toxicity by dysregulating glutamate metabolism and increasing the susceptibility of neurons and astrocytes to bystander apoptosis induced by HIV. Together, our results indicate that connexin containing channels, GJ and HC, are essential in the pathogenesis of meth and increase the sensitivity of the CNS to HIV CNS disease. Methamphetamine (meth) is an extremely addictive central nervous system stimulant. Meth reduced gap junctional (GJ) communication by inducing internalization of connexin-43 (Cx43) in astrocytes and reducing expression of Cx36 in neurons by a mechanism involving activation of dopamine receptors (see cartoon). Meth-induced changes in Cx containing channels increased extracellular levels of glutamate and resulted in higher sensitivity of neurons and astrocytes to apoptosis in response to HIV infection.