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Genetic Tool Predicts Lithium Responsiveness in Bipolar Disorder Patients

By LabMedica International staff writers
Posted on 17 Jul 2025

Bipolar disorder (BD) is characterized by cycles of extreme low and high moods. More...

Lithium has long been the gold standard in treating BD since its mood-stabilizing properties were discovered in 1949. However, its response varies significantly across patients. One-third of individuals respond optimally, another 30% experience partial responses, and over 25% gain little or no benefit at all. This variability, coupled with the absence of validated biomarkers to predict who will benefit from lithium, creates a trial-and-error approach to treatment. Recent research indicates that genetic factors account for approximately 25% of the variability in treatment responses. Now, a new solution to improve the treatment process uses pathway-specific polygenic scores (pPGS) to predict individual responses to lithium based on genetic predisposition.

This pPGS was developed as part of a collaboration between the Adelaide Medical School (Adelaide, Australia) and the International Consortium on Lithium Genetics (ConLi+Gen) using a set of genes involved in biological pathways implicated in BD or targeted by lithium. The researchers targeted genes in pathways such as dopamine, glutamate, calcium channel signaling, and circadian rhythm. These pPGSs were found to be associated with favorable lithium responses, particularly for individuals with higher genetic loading in acetylcholine, calcium channel, GABA, or circadian rhythm pathways. On the other hand, individuals with high genetic loading in the mitochondrial pathway showed poorer responses to lithium. This pathway-focused approach offers more biologically interpretable predictions, directly linked to lithium’s mechanism of action, and combines these genomic predictors with established clinical and demographic factors.

The study findings, published in Biological Psychiatry Global Open Science, showed that people with BD who had higher genetic loading for specific pathways were more likely to respond favorably to lithium. These findings may help create genetic tests for identifying lithium-responsive patients early and with more reliability. The implications of this research go beyond lithium treatment and could potentially inform the development of new treatment strategies for BD. The next steps will focus on the real-world implementation of these insights, including clinical trials to validate and refine the genetic predictors and their application in guiding lithium treatment.

“Our findings may lead to genetic tests that identify lithium-responsive patients earlier and more reliably and inform the discovery of new treatment strategies in BD,” said Associate Professor K. Oliver Schubert, who led the collaboration.


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