Starting from the important study by Stern et al. (2018), discuss and critically analyse in relation to the wider literature the evidence that bipolar patients could be categorized into two sub-populations based on the functional properties of their neurons. Importantly, consider and critically analyse evidence indicating that the bipolar disorder could be categorized into two different sub-disorders. In addition, using classic and more recent studies in the field debate the potential of using
Type of work:
Coursework
Level:
Master
Number of pages:
5 pages = 1375 words
Formatting style:
APA
Language Style:
English (U.K.)
Sources:
8
f
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Starting from the important study by Stern et al. (2018), discuss and critically analyse in relation to the wider literature the evidence that bipolar patients could be categorized into two sub-populations based on the functional properties of their neurons.
Importantly, consider and critically analyse evidence indicating that the bipolar disorder could be categorized into two different sub-disorders.
In addition, using classic and more recent studies in the field debate the potential of using patient-derived iPSCs as a model for personalised medicine.
Your essay should demonstrate a clear understanding of the selected mechanisms and the methodologies used, as well as a critical evaluation of the relevant literature and an ability to synthesize complex information from multiple sources.
Stern, S., Santos, R., Marchetto, M. C., Mendes, A. P. D., Rouleau, G. A., Biesmans, S., … Gage, F. H. (2018). Neurons derived from patients with bipolar disorder divide into intrinsically different sub-populations of neurons, predicting the patients’ responsiveness to lithium. Molecular Psychiatry, 23(6), 1453–1465. https://doi.org/10.1038/mp.2016.260‘ target=”_blank”>https://doi.org/10.1038/mp.2016.260
Summary of the main papers:
2) Stern, S., Santos, R., Marchetto, M. C., Mendes, A. P. D., Rouleau, G. A., Biesmans, S., … Gage, F. H. (2018). Neurons derived from patients with bipolar disorder divide into intrinsically different sub-populations of neurons, predicting the patients’ responsiveness to lithium. Molecular Psychiatry, 23(6), 1453–1465. https://doi.org/10.1038/mp.2016.260
Bipolar disorder (BD) is a debilitating psychiatric condition characterized by mood swings between depression and mania. Currently, lithium stands as the primary treatment option for managing mood episodes in individuals with bipolar disorder. But not all BD patients respond positively to lithium treatment. There are alternative treatment options, but these are typically only given once it is clear that the patient does not respond to lithium. Therefore, being able to predict whether a BD patient will respond positively to lithium treatment would greatly aid in selecting the most suitable treatment option. Taking this concept, the study by Stern et al., aimed to investigate the intrinsic neuronal differences in BD patients and their responsiveness to lithium treatment, by using an innovative approach using neurons derived from induced pluripotent stem cells (iPSCs) that have been generated from BD patients.
Previous to this study, work from the same group in 2015, demonstrated that neurons differentiated from iPSC-derived fibroblasts of BD patients exhibit hyperexcitability, particularly in hippocampal dentate gyrus (DG) neurons. Building on this, the study by Stern et al, set out to investigate how reproducible this hyperexcitability phenotype was in a new cohort of BD patients, and to further study how this could be related to lithium. To do this, the authors used Epstein–Barr virus-immortalized B-lymphocytes from 6 patients diagnosed with BD, to generate iPSCs from. Stern and colleagues then differentiated DG neurons from these iPSCs and used whole-cell patch-clamp electrophysiological recordings to analyze the intrinsic cell properties parameters of neurons derived from healthy individuals or BD patients. The cohort of BD neurons was further divided based on the patient’s responsiveness to lithium into lithium-responsive
Module: Biological Foundations of Mental Health Module Run: March 2024
(LR – 3 patients) and lithium-non-responsive (NR – 3 patients) groups. From this analysis, the key findings were:
1. That the study confirmed that DG-like neurons derived from both LR and NR BD patients showed hyperexcitability compared to those derived from healthy (control) individuals.
2. That LR and NR neurons displayed profoundly different intrinsic properties, indicating potential subtypes of BD.
3. Despite these differences, both LR and NR neurons exhibited a large, fast after-hyperpolarization (AHP), suggesting this feature might be a fundamental characteristic of BD neurons related to their spiking abilities.
4. That chronic lithium treatment reduced hyperexcitability in LR neurons but not in NR neurons.
The fact that Stern et al found substantial electrophysiological differences between LR and NR neurons, suggested that it was possible to distinguish neurons from either LR or NR based purely on their functional properties. To test if this was possible, the authors took the electrophysiological data obtained from 5 patient iPSCs with known responses to lithium and used it to train an effective naïve Bayes classifier. The aim was to develop a predictive machine learning approach that could then be used to predict (classify) if iPSC-neurons derived from a BD patient would respond to lithium or not. With an accuracy exceeding 92%, this classifier made it possible to determine if iPSC-neurons derived from a bipolar disorder patient with unknown responsiveness to lithium would exhibit positive treatment response.
Some take home thoughts from this study:
• The differential response to lithium treatment between LR and NR neurons suggests distinct underlying mechanisms in BD pathophysiology and supports the use of iPSC-derived neurons as a model for studying BD and other psychiatric disorders.
• The study supports the hyperexcitability phenotype in BD and introduces a potential model to distinguish BD subtypes based on neuron response to lithium. The results also suggest the large fast AHP as a key feature in BD neurons, contributing to their fast spiking capabilities, which could be a target for future therapeutic interventions.
• It is also important to recognize the potential for using patient-derived iPSCs to model psychiatric disorders, the significance of electrophysiological profiling in understanding and potentially predicting treatment responses, and the innovative use of machine learning in biomedical research. Additionally, it’s crucial to appreciate the complexity of BD as a disorder with potentially distinct subtypes that may require tailored therapeutic strategies.