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Development of antipsychotic medications with novel mechanisms of action based on computational modeling of hippocampal neuropathology.

ABSTRACT: A large number of cellular level abnormalities have been identified in the hippocampus of schizophrenic subjects. Nonetheless, it remains uncertain how these pathologies interact at a system level to create clinical symptoms, and this has hindered the development of more effective antipsychotic medications. Using a 72-processor supercomputer, we created a tissue level hippocampal simulation, featuring multicompartmental neuron models with multiple ion channel subtypes and synaptic channels with realistic temporal dynamics. As an index of the schizophrenic phenotype, we used the specific inability of the model to attune to 40 Hz (gamma band) stimulation, a well-characterized abnormality in schizophrenia. We examined several possible combinations of putatively schizophrenogenic cellular lesions by systematically varying model parameters representing NMDA channel function, dendritic spine density, and GABA system integrity, conducting 910 trials in total. Two discrete "clusters" of neuropathological changes were identified. The most robust was characterized by co-occurring modest reductions in NMDA system function (-30%) and dendritic spine density (-30%). Another set of lesions had greater NMDA hypofunction along with low level GABA system dysregulation. To the schizophrenic model, we applied the effects of 1,500 virtual medications, which were implemented by varying five model parameters, independently, in a graded manner; the effects of known drugs were also applied. The simulation accurately distinguished agents that are known to lack clinical efficacy, and identified novel mechanisms (e.g., decrease in AMPA conductance decay time constant, increase in projection strength of calretinin-positive interneurons) and combinations of mechanisms that could re-equilibrate model behavior. These findings shed light on the mechanistic links between schizophrenic neuropathology and the gamma band oscillatory abnormalities observed in the illness. As such, they generate specific falsifiable hypotheses, which can guide postmortem and other laboratory research. Significantly, this work also suggests specific non-obvious targets for potential pharmacologic agents.

SUBMITTER: Siekmeier PJ

PROVIDER: S-EPMC3602393 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Development of antipsychotic medications with novel mechanisms of action based on computational modeling of hippocampal neuropathology.

Siekmeier Peter J PJ vanMaanen David P DP

PloS one 20130319 3

A large number of cellular level abnormalities have been identified in the hippocampus of schizophrenic subjects. Nonetheless, it remains uncertain how these pathologies interact at a system level to create clinical symptoms, and this has hindered the development of more effective antipsychotic medications. Using a 72-processor supercomputer, we created a tissue level hippocampal simulation, featuring multicompartmental neuron models with multiple ion channel subtypes and synaptic channels with ...[more]

PMID: 23526999

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Project description:BackgroundColorectal cancer is one of the most prevalent causes of cancer death. It has been studied extensively for a long time, and numerous genetic and epigenetic events have been associated with the disease. However, its molecular mechanisms are still unclear. High-throughput metabolomics data, combined with customized computational systems modeling, can assist our understanding of some of these mechanisms by revealing connections between alterations in enzymatic activities and their consequences for a person's metabolic profile. Of particular importance in this context is purine metabolism, as it provides the nucleotides needed for cell proliferation.Methods and findingsWe employ a computational systems approach to infer molecular mechanisms associated with purine metabolism in colorectal carcinoma. The approach uses a dynamic model of purine metabolism as the simulation system and metabolomics data as input. The execution of large-scale Monte Carlo simulations and optimization with the model permits a step-wise reduction in possibly affected enzyme mechanisms, from which likely targets emerge.ConclusionsAccording to our results, some enzymes in the purine pathway system are very unlikely the targets of colorectal carcinoma. In fact, only three enzymatic steps emerge with statistical confidence as most likely being affected, namely: amidophosphoribosyltransferase (ATASE), 5'-nucleotidase (5NUC), and the xanthine oxidase/dehydrogenase (XD) reactions. The first of these enzymes catalyzes the first committed step of de novo purine biosynthesis, while the other two enzymes are associated with critical purine salvage pathways. The identification of these enzymes is statistically significant and robust. In addition, the results suggest potential secondary targets. The computational method cannot discern whether the inferred mechanisms constitute symptoms of colorectal carcinoma, or whether they might be causative and critical components of the uncontrolled cellular growth in cancer. The inferred molecular mechanisms present testable hypotheses that suggest targeted experiments for future studies of colorectal carcinoma and might eventually lead to improved diagnosis and treatment.

Project description:OBJECTIVES:To compare the risk of major medical events in nursing home residents newly initiated on conventional or atypical antipsychotic medications (APMs). DESIGN:Cohort study, using linked Medicaid, Medicare, Minimum Data Set, and Online Survey Certification and Reporting data. Propensity score-adjusted proportional hazards models were used to compare risks for medical events at a class and individual drug level. SETTING:Nursing homes in 45 U.S. states. PARTICIPANTS:Eighty-three thousand nine hundred fifty-nine Medicaid-eligible residents aged 65 and older who initiated APM treatment after nursing home admission in 2001 to 2005. MEASUREMENTS:Hospitalization for myocardial infarction, cerebrovascular events, serious bacterial infections, and hip fracture within 180 days of treatment initiation. RESULTS:Risks of bacterial infections (hazard ratio (HR) = 1.25, 95% confidence interval (CI) = 1.05-1.49) and possibly myocardial infarction (HR = 1.23, 95% CI = 0.81-1.86) and hip fracture (HR = 1.29, 95% CI = 0.95-1.76) were higher, and risks of cerebrovascular events (HR = 0.82, 95% CI = 0.65-1.02) were lower in participants initiating conventional APMs than in those initiating atypical APMs. Little variation existed between individual atypical APMs, except for a somewhat lower risk of cerebrovascular events with olanzapine (HR = 0.91, 95% CI = 0.81-1.02) and quetiapine (HR = 0.89, 95% CI = 0.79-1.02) and a lower risk of bacterial infections (HR = 0.83, 95% CI = 0.73-0.94) and possibly a higher risk of hip fracture (HR = 1.17, 95% CI = 0.96-1.43) with quetiapine than with risperidone. Dose-response relationships were observed for all events (HR = 1.12, 95% CI = 1.05-1.19 for high vs low dose for all events combined). CONCLUSION:These associations underscore the importance of carefully selecting the specific APM and dose and monitoring their safety, especially in nursing home residents who have an array of medical illnesses and are undergoing complex medication regimens.

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Development of antipsychotic medications with novel mechanisms of action based on computational modeling of hippocampal neuropathology.

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Development of antipsychotic medications with novel mechanisms of action based on computational modeling of hippocampal neuropathology.

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