Predicting Metabolic Adverse Effects of Lithium in Bipolar Disorder
AI Summary
Three-month lithium therapy raised triglycerides, lowered HDL cholesterol, and increased Castelli Risk Index, indicating early atherogenic metabolic worsening.
Lower baseline Prognostic Nutritional Index independently predicted higher post-treatment CRI, while baseline CRI remained the strongest predictor.
Routine PNI measurement may enable pretreatment risk stratification and closer lipid monitoring, but findings require confirmation in broader, longer studies.
PURPOSE: Patients with bipolar disorder (BD) are at an increased metabolic risk due to chronic inflammation, metabolic vulnerability, and psychotropic medication exposure. Although lithium is a cornerstone of BD treatment, its metabolic safety profiles are heterogeneous. The reason why some patients tolerate lithium metabolically while others develop early metabolic adverse effects remains unclear. The Prognostic Nutritional Index (PNI), which reflects the inflammatory-nutritional reserve, may identify individuals vulnerable to lithium-related metabolic stress.
METHODS: Euthymic patients with BD (n=152) were evaluated at baseline and after 3 months of lithium therapy. Changes in lipid parameters and the Castelli Risk Index (CRI) were assessed. Multiple regression analysis was used to identify the predictors of post-treatment CRI. Albumin values reported in g/L were converted to g/dL for the PNI calculation.
RESULTS: Triglyceride levels increased (P<0.001), HDL cholesterol levels decreased (P=0.001), and CRI increased (P=0.001) after lithium therapy. A lower baseline PNI independently predicted a higher post-treatment CRI (P=0.023), although the baseline CRI remained the strongest predictor (P<0.001). Age, sex, smoking status, atypical antipsychotic use, illness duration, and serum lithium levels were not significant predictors.
CONCLUSIONS: A reduced baseline inflammatory-nutritional reserve predicts early atherogenic worsening during lithium treatment. Early metabolic worsening during lithium treatment may be associated with individual biological vulnerability rather than occurring uniformly across patients. Incorporating a simple, routinely available biomarker into pretreatment evaluations may support early risk stratification and closer lipid monitoring, although these findings require confirmation in studies with broader metabolic assessment and longer follow-up.
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