A Physiological Instability Displayed in Hippocampal Neurons Derived From Lithium-Nonresponsive Bipolar Disorder Patients

Published:February 04, 2020DOI:



      We recently reported a hyperexcitability phenotype displayed in dentate gyrus granule neurons derived from patients with bipolar disorder (BD) as well as a hyperexcitability that appeared only in CA3 pyramidal hippocampal neurons that were derived from patients with BD who responded to lithium treatment (lithium responders) and not in CA3 pyramidal hippocampal neurons that were derived from patients with BD who did not respond to lithium (nonresponders).


      Here we used our measurements of currents in neurons derived from 4 control subjects, 3 patients with BD who were lithium responders, and 3 patients with BD who were nonresponders. We changed the conductances of simulated dentate gyrus and CA3 hippocampal neurons according to our measurements to derive a numerical simulation for BD neurons.


      The computationally simulated BD dentate gyrus neurons had a hyperexcitability phenotype similar to the experimental results. Only the simulated BD CA3 neurons derived from lithium responder patients were hyperexcitable. Interestingly, our computational model captured a physiological instability intrinsic to hippocampal neurons that were derived from nonresponder patients that we also observed when re-examining our experimental results. This instability was caused by a drastic reduction in the sodium current, accompanied by an increase in the amplitude of several potassium currents. These baseline alterations caused nonresponder BD hippocampal neurons to drastically shift their excitability with small changes to their sodium currents, alternating between hyperexcitable and hypoexcitable states.


      Our computational model of BD hippocampal neurons that was based on our measurements reproduced the experimental phenotypes of hyperexcitability and physiological instability. We hypothesize that the physiological instability phenotype strongly contributes to affective lability in patients with BD.


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      Linked Article

      • Can Computational Modeling Predict Disease Phenotype?
        Biological PsychiatryVol. 88Issue 2
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          To understand the cellular and molecular pathophysiology of mood disorders, including bipolar disorder (BD), has been an inherently challenging task. One of the primary barriers is the infeasibility of accessing live neuronal cells and tissue from patients to undertake experiments in the laboratory. Even though postmortem studies provide a great depth of knowledge, they cannot demonstrate precisely when during the neurodevelopmental trajectory the disease develops.
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