Lithium enhances exercise-induced glycogen breakdown and insulin-induced AKT activation to facilitate glucose uptake in rodent skeletal muscle

Effects of moderate intensity training and lithium on spatial learning and memory in a rat model: The role of SIRT3 and PGC1-α expression levels and brain-derived neurotropic factor

In this study we investigated the potential synergistic effects of moderate interval training (MIT) and lithium on spatial learning and memory. Forty-two male Wistar males were classified into six groups including I: Control, II: 10 mg/kg/day IP lithium (Li10), III: MIT, IV: Li10 + MIT, V: 40 mg/kg/day IP lithium (Li40), and VI: Li40 + MIT. Then, the rats underwent Morris Water Maze (MWM) test to assess their spatial memory and learning ability. Brain-derived neurotrophic factor (BDNF) density was measured by enzyme-linked immunosorbent assay (ELISA), and the expression of PGC1 and SIRT3 were assessed via qRT-PCR. The results show that MIT improves both memory and spatial learning; but lithium alone, does not cause this. Additionally, those exposed to a combination of exercise and lithium also had improved spatial learning and memory. Finally, we observed a positive role of BDNF protein, and PGC1 gene on the effects of exercise and lithium.

New Advances in the Pharmacology and Toxicology of Lithium: A Neurobiologically Oriented Overview

Over the last six decades, lithium has been considered the gold standard treatment for the long-term management of bipolar disorder due to its efficacy in preventing both manic and depressive episodes as well as suicidal behaviors. Nevertheless, despite numerous observed effects on various cellular pathways and biologic systems, the precise mechanism through which lithium stabilizes mood remains elusive. Furthermore, there is recent support for the therapeutic potential of lithium in other brain diseases. This review offers a comprehensive examination of contemporary understanding and predominant theories concerning the diverse mechanisms underlying lithium's effects. These findings are based on investigations utilizing cellular and animal models of neurodegenerative and psychiatric disorders. Recent studies have provided additional support for the significance of glycogen synthase kinase-3 (GSK3) inhibition as a crucial mechanism. Furthermore, research has shed more light on the interconnections between GSK3-mediated neuroprotective, antioxidant, and neuroplasticity processes. Moreover, recent advancements in animal and human models have provided valuable insights into how lithium-induced modifications at the homeostatic synaptic plasticity level may play a pivotal role in its clinical effectiveness. We focused on findings from translational studies suggesting that lithium may interface with microRNA expression. Finally, we are exploring the repurposing potential of lithium beyond bipolar disorder. These recent findings on the therapeutic mechanisms of lithium have provided important clues toward developing predictive models of response to lithium treatment and identifying new biologic targets. SIGNIFICANCE STATEMENT: Lithium is the drug of choice for the treatment of bipolar disorder, but its mechanism of action in stabilizing mood remains elusive. This review presents the latest evidence on lithium's various mechanisms of action. Recent evidence has strengthened glycogen synthase kinase-3 (GSK3) inhibition, changes at the level of homeostatic synaptic plasticity, and regulation of microRNA expression as key mechanisms, providing an intriguing perspective that may help bridge the mechanistic gap between molecular functions and its clinical efficacy as a mood stabilizer.

Lithium and exercise ameliorate insulin-deficient hyperglycemia by independently attenuating pancreatic α-cell mass and hepatic gluconeogenesis

As in type 1 diabetes, the loss of pancreatic β-cells leads to insulin deficiency and the subsequent development of hyperglycemia. Exercise has been proposed as a viable remedy for hyperglycemia. Lithium, which has been used as a treatment for bipolar disorder, has also been shown to improve glucose homeostasis under the conditions of obesity and type 2 diabetes by enhancing the effects of exercise on the skeletal muscles. In this study, we demonstrated that unlike in obesity and type 2 diabetic conditions, under the condition of insulin-deficient type 1 diabetes, lithium administration attenuated pancreatic a-cell mass without altering insulin-secreting β-cell mass, implying a selective impact on glucagon production. Additionally, we also documented that lithium downregulated the hepatic gluconeogenic program by decreasing G6Pase protein levels and upregulating AMPK activity. These findings suggest that lithium's effect on glucose metabolism in type 1 diabetes is mediated through a different mechanism than those associated with exerciseinduced metabolic changes in the muscle. Therefore, our research presents the novel therapeutic potential of lithium in the treatment of type 1 diabetes, which can be utilized along with insulin and independently of exercise.

Pharmacological treatment of bipolar disorder and risk of diabetes mellitus: A nationwide study of 30,451 patients

OBJECTIVE

While treatment with antipsychotics and antiepileptics have been associated with an increased risk of diabetes mellitus (DM), lithium may have the opposite effect via inhibition of glycogen synthase kinase-3. The aim of this study was to investigate whether treatment of bipolar disorder with lithium, antipsychotics, or antiepileptics is associated with the risk of DM in a real-world clinical setting.

METHODS

Using nationwide registers, we identified all patients diagnosed with bipolar disorder in Danish Psychiatric Services from January 1, 1996, to January 1, 2019 (N = 30,451). The risk of developing DM was operationalized via hospital diagnoses and redeemed prescriptions for glucose-lowering drugs. For lithium, antipsychotics, valproate, and lamotrigine, we calculated hazard rate ratios (HRR) for developing DM via adjusted Cox proportional hazards models. Potential cumulative dose-response-like associations were examined using the log-rank test.

RESULTS

During follow-up (245,181 person-years), 2107 (6.9%) patients developed DM. Compared with non-users of the respective drugs, we found no clinically or statistically significant difference in the risk of developing DM among patients receiving lithium (n = 11,690; incidence rate of DM/1000 person-years (IR) = 8.87, 95% CI: 8.02-9.90; HRR = 0.94, 95% CI: 0.84-1.06) or lamotrigine (n = 11,785; IR = 7.58, 95% CI: 6.69-8.59; HRR = 0.89, 95% CI: 0.77-1.02), respectively. Conversely, for patients receiving valproate (n = 5171; IR = 12.68, 95% CI: 10.87-14.80; HRR = 1.34, 95% CI: 1.14-1.58) and antipsychotics (n = 22,719; IR = 12.00, 95% CI: 11.14-12.94; HRR = 1.65, 95% CI: 1.45-1.88), respectively, there was increased risk of developing DM. For antipsychotics, we observed a clear cumulative dose-response-like association with the risk of DM.

CONCLUSIONS

Treatment with valproate and antipsychotics-but not with lithium and lamotrigine-was associated with increased risk of DM in a real-world cohort of patients with bipolar disorder.

Association Between Essential and Non-essential Metals, Body Composition, and Metabolic Syndrome in Adults

Growing evidence indicates that metal exposure is associated with metabolic syndrome (MetS); however, mixed results have been reported. The aim of this study was to clarify associations of exposure to essential and non-essential metals with body composition and risks of obesity and MetS. Anthropometry and blood biochemistry of metabolic parameters were obtained from 150 middle-aged Taiwanese adults. Plasma metals were assessed using inductively coupled plasma mass spectrometry, and body compositions were measured by a bioelectrical impedance analysis (BIA). The essential metals of copper (Cu), manganese (Mn), and chromium (Cr) were positively correlated with the body fat mass but inversely correlated with the skeletal muscle mass (all p < 0.05). An adjusted logistic regression showed that Mn [odds ratio (OR) = 1.624 (95% confidence interval 1.072, 2.462), p = 0.02] and, to a lesser extent, Cu [OR = 1.501 (0.985, 2.292), p = 0.059] predicted abdominal obesity, while plasma Cu [OR = 2.211 (1.146, 4.266), p = 0.02] and zinc (Zn) [OR = 2.228 (1.048, 4.736) p = 0.04] predicted MetS. Significant correlations between dyslipidemia and lithium [OR = 1.716 (1.080, 2.726)], Cu [OR = 2.210 (1.415, 3.454)], Mn [OR = 2.200 (1.320, 3.666)], molybdenum [OR = 1.853 (1.160, 2.958)], and Zn [OR = 1.993 (1.186, 3.349)], and between boron [OR = 2.583 (1.137, 5.868)] and hyperglycemia were observed (all p < 0.05). Exposure to essential metals may affect the body composition and metabolic profiles, exacerbating the risk of MetS.

Associations between whole blood trace elements concentrations and HbA1c levels in patients with type 2 diabetes

Previous researches have been conducted to study the associations of trace elements on Type 2 diabetes (T2D) risk. The present study focuses on the evaluation of potential associations between trace elements and Hemoglobin A1c (HbA1c) in patients with T2D, via the determination of their levels in human whole blood. 100 diabetes without complications, 75 prediabetes and 40 apparently healthy subjects were studied. The levels of eleven trace elements including lithium (Li), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), copper (Cu), zinc (Zn), selenium (Se), strontium (Sr) and molybdenum (Mo) were measured using inductively coupled plasma mass spectrometry (ICP-MS). The levels of fasting glucose, HbA1c, Hemoglobin, lipid, liver function, kidney function, thyroid function and demographic data were obtained from the Laboratory Information System. Nonparametric correlation (Spearman) was used to analyze the relationship between trace elements and HbA1c. The contents of V, Cr, Mn, Fe, Co, Cu, Zn and Mo in diabetes increased comparing with the healthy subject while Li decreased. But the levels of Li, V, Cr, Mn, Co, Se and Mo negatively correlated with HbA1c in the diabetes subjects (r value: - 0.2189, - 0.2421, - 0.3260, - 0.2744, - 0.2812, - 0.2456, - 0.2240; 95% confidence interval - 0.4032 to - 0.0176, - 0.4235 to - 0.0420, - 0.4955 to - 0.1326, - 0.4515 to - 0.0765, - 0.4573 to - 0.0838, - 0.4266 to - 0.0458, - 0.4076 to - 0.0229; p < 0.05, p < 0.05, p < 0.001, p < 0.01, p < 0.01, p < 0.05, p < 0.05). Accordingly, the contents of V, Cr, Mn and Se showed lower in HbA1c ≥ 7.0% group in contrast to HbA1c < 7.0% group. No correlation of HbA1c (or FBG) and trace elements was found in the healthy subjects. Trace element levels and metabolic abnormalities of blood glucose may be mutually affected. The extra supplement of trace elements needs to be cautious.