Bipolar Disorder And The Impact Of Insulin Sensitivity
Overview
This study investigated the impact of insulin resistance (IR) and insulin sensitivity on various brain parameters in individuals with bipolar disorder (BD). Bipolar disorder is associated with structural and functional brain changes, and BD patients have an increased risk of developing insulin resistance, which can affect neurological functions and bipolar disorder outcomes. Researchers in this study examined white matter (WM) microstructure, resting-state functional connectivity (FC), and fractional amplitude of low-frequency fluctuation (fALFF) in bipolar disorder patients.
The study involved 92 BD patients who underwent diffusion tensor imaging (DTI), and a subgroup of 22 patients who underwent resting-state functional magnetic resonance imaging (rs-fMRI). Blood samples were collected to assess insulin and glucose levels, and insulin resistance and sensitivity were quantified using the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI). Data from DTI were analyzed using tract-based spatial statistics, and rs-fMRI data were used to extract ROI-to-ROI FC matrices and fALFF maps.
The findings of this study indicated that insulin levels were negatively associated with fractional anisotropy (FA) and positively correlated with radial diffusivity (RD) and mean diffusivity (MD) in various brain regions. HOMA-IR was linked to increased RD in the right superior longitudinal fasciculus, while QUICKI showed positive associations with FA and negative associations with RD and MD in specific WM tracts. Insulin and HOMA-IR had negative effects on fALFF, while QUICKI exhibited a positive association with fALFF in the precuneus region. However, no significant findings were observed in the ROI-to-ROI analysis.
Introduction
This study focused on the complex relationship between bipolar disorder, a severe mental illness characterized by fluctuating mood states, and metabolic alterations, particularly insulin resistance (IR) and related glucose metabolism issues. Bipolar disorder patients have a significantly increased risk of developing insulin resistance, obesity, metabolic syndrome, and type 2 diabetes (T2D), which, in turn, can worsen bipolar disorder outcomes, increase the risk of chronic illness, exacerbate symptoms, reduce treatment response, and elevate the risk of cardiovascular diseases and suicide.
The study aimed to explore the biological mechanisms underlying this comorbidity, including inflammation, oxidative stress, hypothalamic-pituitary-adrenal (HPA) axis hyperactivation, and altered insulin action. Insulin, in addition to its role in glucose regulation, functions as a neuropeptide with trophic and neuroprotective effects on the brain. It also acts as a neuromodulator, impacting brain reward, motivation mechanisms, and emotional behaviors. Dysregulation of insulin-dependent mechanisms may affect dopamine and serotonin signaling, potentially leading to depressive symptoms and compromised cognitive functions.
The study highlighted the potential role of insulin in regulating neurotransmitters like serotonin and dopamine, which are crucial for mood and cognitive functions. Insulin’s influence on these neurotransmitters involves mechanisms such as promoting the supply of tryptophan to the brain, enhancing serotonin synthesis, and modulating dopamine synthesis. Impaired insulin secretion and IR are associated with inflammatory responses, further complicating the relationship between metabolism and mood disorders.
Moreover, insulin action alteration can lead to changes in brain structures, including the hippocampus and cortical regions, and disrupt white matter (WM) microstructure. These WM abnormalities have been observed in both BD and T2D patients, suggesting a potential link between insulin-related metabolic changes and brain alterations in bipolar disorder.
The study also touched on resting-state functional connectivity (rs-FC) alterations in BD and T2D patients, particularly involving cortical, limbic, and insular regions, as well as midline regions like the medial prefrontal cortex and posterior cingulate cortex (PCC). However, the study emphasized that the fractional amplitude of low-frequency fluctuations (fALFF) could provide additional insights into spontaneous neural activity not captured by rs-FC.
Background
Insulin and Metabolic Regulation
Insulin, a peptide hormone produced by pancreatic beta cells, plays a pivotal role in regulating blood glucose levels. It also has important immuno-modulatory functions and interacts with other hormones such as glucagon and leptin. Insulin stimulates the production of glucagon and leptin when exposed to glucose. Conversely, glucagon and leptin reduce insulin secretion and enhance tissue sensitivity to insulin, facilitating glucose uptake. An elevated insulin-to-glucagon ratio inhibits glucose and free fatty acid production while promoting protein biosynthesis. Low levels of insulin-to-glucagon ratio promote the mobilization of stored nutrients and increase processes like glycogenolysis and gluconeogenesis. Disruptions in these feedback mechanisms, coupled with a low-grade inflammatory state, have been associated with metabolic syndrome.
Insulin in Bipolar Disorder
In recent years, studies have reported altered levels of insulin in individuals with bipolar disorder (BD), and these changes have been linked to the pathophysiology and progression of the disorder. Insulin resistance (IR) has been associated with more frequent mood episodes, cognitive decline, and poor responses to mood stabilizers. Notably, the medication metformin, which reduces hyperinsulinemia and, consequently, IGR, has shown benefits in patients with treatment-resistant bipolar disorder.
Neuroimaging Findings
In this study, the researchers found significant correlations between peripheral insulin levels and IGR with specific neuroimaging measures. These associations were characterized by:
– Negative associations between insulin levels and IGR with fractional anisotropy (FA), a measure reflecting white matter integrity, suggesting a potential relationship with dysmyelination or demyelination processes.
– Positive associations between insulin levels and IGR with radial diffusivity (RD) and mean diffusivity (MD), indicative of alterations in fiber diameter, fiber directionality, and increased spacing between fibers.
Role of Insulin in the Brain
Insulin receptors are widely distributed in the brain, including cortical areas like the hippocampus and cerebellum. Neuronal effects of insulin on myelination processes within fiber tracts may contribute to the observed global effects on white matter. In normal physiological homeostasis, insulin participates in synaptic plasticity, neurotransmitter regulation, glycogen synthesis, and the prevention of neuronal necrosis and apoptosis. Additionally, insulin and insulin-like growth factor (IGF)-1 have been implicated in promoting the development of myelin-producing oligodendrocytes during neural development.
Methods
Inclusion Criteria
The study included a total of 92 participants diagnosed with bipolar disorder based on DSM-5 criteria. Among these participants, 83 were experiencing depressive states, while 9 were in manic states. Inclusion criteria for these participants were as follows:
- Depressed Bipolar Patients: Participants diagnosed with bipolar disorder experiencing depressive episodes were required to have a baseline Hamilton Depression Rating Scale (HDRS) score of 18 or higher.
- Manic Bipolar Patients: Participants diagnosed with bipolar disorder in a manic state needed to have a baseline Young Mania Rating Scale (YMRS) score of 13 or higher.
- Absence of Other Diagnoses: Participants should not have any other psychiatric diagnoses on Axis I.
- Absence of Mental Retardation: Individuals with mental retardation on Axis II were excluded.
- Absence of Pregnancy: Pregnant individuals were not included in the study.
- No History of Epilepsy or Major Medical or Neurological Disorders: Participants should not have a history of epilepsy or significant medical or neurological conditions.
- No History of Drug or Alcohol Abuse or Dependency: Individuals with a history of drug or alcohol abuse or dependency were excluded.
- No Recent Electroconvulsive Therapy (ECT): Participants who had received electroconvulsive therapy within 6 months prior to study enrollment were not included.
Laboratory Tests:
Blood samples were collected from all participants in the morning for insulin, glucagon, and glucose analysis. The following metabolic markers were calculated based on the collected data:
- Insulin-Glucagon Ratio (IGR): This ratio was computed to assess the balance between insulin and glucagon.
- Homeostatic Model Assessment for Insulin Resistance (HOMA-IR): HOMA-IR was calculated using the formula (fasting glucose mg/dl × fasting insulin μU/ml)/405.
- Quantitative Insulin Sensitivity Check Index (QUICKI): QUICKI was derived using the inverse of the sum of the logarithms of fasting insulin and fasting glucose: 1/(log(fasting insulin μU/ml) + log(fasting glucose mg/dl)).
Exclusion Criteria:
The study had certain exclusion criteria to ensure the homogeneity and appropriateness of the participant sample:
- Physical Examination, Laboratory Tests, and Electrocardiograms: Participants who did not undergo these tests during admission were excluded.
- MRI Incompatibility: Individuals with MRI contraindications or incompatibility were not included in the study.
- Insufficient Data Quality: Participants with data quality issues, such as excessive motion artifacts or high framewise displacement, were considered outliers and excluded.
- Comorbid Conditions: Individuals with comorbid psychiatric or neurological conditions other than bipolar disorder (BD) were excluded.
These inclusion and exclusion criteria were designed to ensure that the study included a well-defined sample of individuals with bipolar disorder and that the data collected would be reliable and suitable for analysis.
Results
The study analyzed the clinical, demographic, and metabolic characteristics of the participant sample. Here are the key findings:
Sample Features
– The sample consisted of individuals with bipolar disorder.
– The demographic, clinical, and metabolic data of the participants were collected and analyzed.
Metabolic Profiles:
– Among the participants, 5 individuals (5.4% of the total sample) had serum glucose levels that indicated Impaired Fasting Glucose.
– In contrast, 18 patients (19.3% of the sample) had fasting insulin levels exceeding 25 mUI/L.
Insulin Resistance Classification:
– The study utilized the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) to classify insulin resistance.
– HOMA-IR cutoff values for metabolic consequences depended on obesity, with a commonly used cutoff of 2.5 and a proposed cutoff of 3.02 (75th percentile) in all participants.
– Based on these criteria, 29 patients were classified as insulin-resistant, indicating impaired insulin sensitivity.
Correlations with Insulin Levels:
– The analysis revealed a pattern of negative correlation between insulin levels and fractional anisotropy (FA), a measure reflecting the integrity of white matter (WM) tracts.
– Insulin levels showed a positive association with radial diffusivity (RD) and mean diffusivity (MD), indicating potential disruptions in WM microstructure.
Effect on White Matter Tracts:
– The effects of insulin resistance and insulin sensitivity were widespread, impacting various regions of the WM skeleton.
– Affected WM tracts included the superior longitudinal fasciculus, superior and inferior fronto-occipital fasciculus, corona radiata, corpus callosum, corticospinal tract, and uncinate fasciculus.
– Insulin resistance, as measured by HOMA-IR, showed a significant positive correlation with RD in the right superior longitudinal fasciculus.
– QUICKI, a measure of insulin sensitivity, exhibited a positive correlation with FA and negative correlations with RD and MD in specific WM tracts.
These findings indicate that insulin levels and insulin resistance are associated with alterations in white matter microstructure, affecting various regions of the brain’s WM skeleton. These correlations suggest a potential link between insulin metabolism and structural changes in the brain, particularly in individuals with bipolar disorder.
Conclusion
The study identified significant associations between various metabolic markers, including insulin, insulin-to-glucagon ratio (IGR), insulin resistance (HOMA-IR), insulin sensitivity (QUICKI), and neuroimaging indexes in a sample of individuals with bipolar disorder (BD).
In summary, the study highlights the intricate relationship between insulin metabolism, neuroimaging markers, and the potential impact on white matter integrity in individuals with bipolar disorder. It underscores the importance of further investigating these associations to better understand the underlying mechanisms of bipolar disorder and its metabolic implications in the brain.
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