Computational Analysis of Therapeutic Neuroadaptation to Chronic Antidepressant in a Model of the Monoaminergic Neurotransmitter, Stress Hormone, and Male Sex Hormone Systems (original) (raw)
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The clinical practice of selective serotonin reuptake inhibitor (SSRI) augmentation relies heavily on clinical judgment and trial-and-error. Unfortunately, the drug combinations prescribed today fail to provide relief for all treatment-resistant depressed patients. In order to identify potentially more effective treatments, we developed a computational model of the monoaminergic neurotransmitter and stress-steroid systems that neuroadapts to chronic administration of combinations of antidepressant drugs and hormones by adjusting the strengths of its transmitter-system components (TSCs). We used the model to screen 60 chronically administered drug/hormone pairs and triples, and identified as potentially therapeutic those combinations that raised the monoamines (serotonin, norepinephrine, and dopamine) but lowered cortisol following neuroadaptation in the model. We also evaluated the contributions of individual and pairs of TSCs to therapeutic neuroadaptation with chronic SSRI using s...
Computational Model of Antidepressant Response Heterogeneity as Multi-pathway Neuroadaptation
Frontiers in Pharmacology
Current hypotheses cannot fully explain the clinically observed heterogeneity in antidepressant response. The therapeutic latency of antidepressants suggests that therapeutic outcomes are achieved not by the acute effects of the drugs, but rather by the homeostatic changes that occur as the brain adapts to their chronic administration. We present a computational model that represents the known interactions between the monoaminergic neurotransmitter-producing brain regions and associated non-monoaminergic neurotransmitter systems, and use the model to explore the possible ways in which the brain can homeostatically adjust to chronic antidepressant administration. The model also represents the neuron-specific neurotransmitter receptors that are known to adjust their strengths (expressions or sensitivities) in response to chronic antidepressant administration, and neuroadaptation in the model occurs through sequential adjustments in these receptor strengths. The main result is that the model can reach similar levels of adaptation to chronic administration of the same antidepressant drug or combination along many different pathways, arriving correspondingly at many different receptor strength configurations, but not all of those adapted configurations are also associated with therapeutic elevations in monoamine levels. When expressed as the percentage of adapted configurations that are also associated with elevations in one or more of the monoamines, our modeling results largely agree with the percentage efficacy rates of antidepressants and antidepressant combinations observed in clinical trials. Our neuroadaptation model provides an explanation for the clinical reports of heterogeneous outcomes among patients chronically administered the same antidepressant drug regimen.
Journal of Affective Disorders, 2007
Artificial neural networks (ANN) represent a promising tool for combining multiple predictors in complex diseases. Antidepressant response in mood disorders is a typical complex phenomenon were a number of predictors influence outcome under non-linear interactions. In the present study we tested a neural network strategy for antidepressant outcome in subjects affected by major depression. One hundred and forty-five never reported depressed inpatients were included in this study (major depressives/ bipolars: 111/34). A multi layer perceptron network composed of 1 hidden layer with 13 nodes was chosen. The network was performed on the sample of 145 cases divided as follows: train 73 + verify 36 + test 36. Correlation of predicted versus observed response was 0.46 in the test (independent) sample that corresponds to 21% of variance explained. Number of episodes, side effects, delusional features, baseline HAM-D, length of current episode, lithium augmentation, current medical condition and personality disorders were the main factors identified by the model. Sex, age at onset, polarity, plasma level and baseline VAS score were part of the model but with a lower rank.
Pharmacopsychiatry, 2011
the orbitofrontal cortex that exhibits reduced behavioral inhibition, and the amygdala that is related to elevated impulsive behavior (• ▶ Fig. 1a). In addition, pharmacological studies have shown that several transmitter systems are involved in the symptomatology of depressive disorders. Defi cits in norepinephrinergic, serotonergic and dopaminergic neurotransmission are well known [65] , a hyperfunction of the cholinergic system was proposed [24] , and lately also a GABA hypofunction hypothesis and a glutamate hyperfunction hypothesis were discussed [30, 32, 60]. Although the etiology of MDD is not well understood, it has been suggested from a biochemical point of view that monoamines and the hypothalamic-pituitary-adrenal (HPA) axis in human brain are important contributors [33, 53]. Briefl y, the HPA axis responds to stress with the release
Serotonergic and Noradrenergic Modulation of Emotion Processing by Single Dose Antidepressants
2010
Serotonergic and noradrenergic pathways are the main targets of antidepressants. Their differential effects on emotion processing-related brain activation are, however, to be further characterized. We aimed at elucidating the neural sites of action of an acute differential serotonergic and noradrenergic influence on an emotion-processing task, which was earlier shown to be associated with depressiveness. In a single-blind pseudo-randomized crossover study, 21 healthy subjects (16 subjects finally included in the analysis) participated to ingest a single dose at three time points of either 40 mg citalopram, a selective serotonin-reuptake inhibitor, 8 mg reboxetine, a selective noradrenaline-reuptake inhibitor, or placebo 2-3 h before functional magnetic resonance imaging (fMRI). During fMRI, subjects performed a task comprising the anticipation and perception of pictures of either 'known' (positive, negative, neutral) or 'unknown' valence (randomly 50% positive or negative). In direct comparison with citalopram and with placebo, reboxetine increased brain activity in the medial thalamus. Citalopram modulated certain prefrontal and insular areas more prominently. Other frontal and parieto-occipital areas were modulated by both drugs. In conclusion, the functional network involved in emotional information processing could be modulated by the acute application of selective noradrenergic and serotonergic drugs revealing a noradrenergic effect in thalamic and frontal areas, and a prefrontal and insular focus of serotonergic modulation. These findings could have implications for future selection criteria concerning personalized antidepressant medication in depression.
The neurobiology of treatment response to antidepressants and mood stabilizing medications
Journal of psychiatry & neuroscience : JPN, 2002
As the neurobiology of mood disorders and the mechanisms of action of antidepressant drugs continue to be elucidated, there has been a shift in emphasis from changes in neurotransmitter release and metabolism to regulation of gene expression and neuroprotection. Evidence from animal studies suggests that drug therapy may act on specific transcription factors and target genes that regulate processes such as neuroprotection and neuronal survival. Clinical studies consistently identify changes in prefrontal cortex, hippocampus and amygdala that may be related to the course of illness and may be prevented with successful treatment. Together, these findings suggest that clinically relevant neurobiological correlations may ultimately be identified in patients who respond and remit to treatment. With these and future advances in the neuroscience of psychiatry, it may be possible to identify biological markers that will help in decisions about specific treatments for an individual patient.
The international journal of neuropsychopharmacology / official scientific journal of the Collegium Internationale Neuropsychopharmacologicum (CINP), 2004
There is extensive comorbidity between depression and anxiety disorders. Dimensional psychiatric and psychometric approaches have suggested that dysregulation of a limited number of behavioural dimensions that cut across diagnostic categories can account for both the shared and unique symptoms of depression and anxiety disorders. Such an approach recognizes that anxiety, the emotional response to stress, is a key element of depression as well as the defining feature of anxiety disorders, and many antidepressants appear to be effective in the treatment of anxiety disorders as well as depression. Therefore, the pharmacological actions of these drugs must account for their efficacy in both. Brain noradrenergic and serotonergic systems, and perhaps to a more limited extent the dopaminergic system, regulate or modulate many of the same behavioural dimensions (e.g. negative or positive affect) that are affected in depression and anxiety disorders, and that are ameliorated by drug treatmen...
Mathematical Models of Serotonin, Histamine, and Depression
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The coauthors have been working together for ten years on serotonin, dopamine, and histamine and their connection to neuropsychiatric illnesses. Hashemi has pioneered many new experimental techniques for measuring serotonin and histamine in real time in the extracellular space in the brain. Best, Reed, and Nijhout have been making mathematical models of brain metabolism to help them interpret Hashemi’s data. Hashemi demonstrated that brain histamine inhibits serotonin release, giving a direct mechanism by which inflammation can cause a decrease in brain serotonin and therefore depression. Many new biological phenomena have come out of their joint research including 1) there are two different reuptake mechanisms for serotonin; 2) the effect of the serotonin autoreceptors is not instantaneous and is long-lasting even when the extracellular concentrations have returned to normal; 3) that mathematical models of serotonin metabolism and histamine metabolism can explain Hashemi’s experime...