ArticleEuropean archives of psychiatry and clinical neuroscience2026
Mechanisms of weight gain associated with valproic acid: a scoping review.
Article in European archives of psychiatry and clinical neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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Authors and funding
11 authors.
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Abstract
introductionValproic acid (VPA), a widely prescribed mood stabilizer and antiepileptic drug, is frequently associated with metabolic side effects, particularly weight gain. Despite its clinical relevance, the range and diversity of mechanisms underlying VPA-associated weight gain remain incompletely mapped.
objectivesTo map the breadth of evidence on mechanisms of VPA-associated weight gain, characterize the types of studies and populations investigated, and identify knowledge gaps to inform future research.
methodsThis PRISMA-ScR-guided scoping review searched PubMed, Cochrane Library, Scopus, and Google Scholar for studies on VPA-weight gain mechanisms in adults. One reviewer charted data using a piloted form; two independently assessed quality (Newcastle-Ottawa Scale). Sources were grouped by mechanistic pathway with descriptive summaries and vote-counting.
resultsFifteen studies (n = 1,339 participants) were included, representing diverse designs: cross-sectional (n = 4), prospective observational (n = 3), genetic association (n = 2), and others. Evidence mapped to three primary mechanistic domains: hormonal dysregulation (like elevated insulin, leptin, insulin resistance, and other findings); genetic predispositions, including CYP2C19 polymorphisms, CRTC1 methylation, and other genetic variants; and lipid metabolism alterations (increased TC, LDL-C, TG, FFAs; decreased Apo A1; mixed HDL-C findings). Hormonal and lipid pathways are well-documented, while genetic mechanisms require validation in larger, standardized cohorts.
conclusionsThis scoping review identifies a heterogeneous evidence base with well-established hormonal and lipid mechanisms and emerging genetic pathways. Key gaps include underrepresentation of bipolar disorder populations, limited longitudinal genetic studies, and lack of integrated frameworks combining hormonal, genetic, and metabolic data. Findings inform future research priorities and highlight the need for personalized monitoring strategies.
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Registered trials
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