Aims: The present review explores the existing evidence on pharmacogenomic tests for prediction of lithium response in the treatment of bipolar disorder. We focused our research article on reports describing findings from genome-wide association studies, polygenic risk scores, and gene expression analyses associated with lithium response. Methods: We conducted a non-systematic review of studies from PubMed/Medline by using terms such as “pharmacogenomics,” “GWAS,” “gene expression,” and “lithium response.” Inclusion criteria focused on original research involving human subjects and assessing lithium response outcomes as well as in vitro studies. An extensive pearl-growing strategy was employed to further enlarge the scope of the piece by capitalizing on the knowledge of study authors on the subject. Results: The observed results, albeit promising, remain preliminary in terms of clinical relevance. Machine learning combining genetic and clinical data appears associated with moderate success in predicting lithium responsiveness. Gene expression studies and genome-wide association studies have helped identify possible targets of lithium and have the potential to support target-specific drug research. Conclusions: Pharmacogenomics may support further discoveries in precision medicine further enlarging our understanding of the underlying mechanisms of lithium for its efficacy. However, clinical applications currently appear out of reach in the near future.

Pharmacogenomics and response to lithium in bipolar disorder

Paribello P.
Primo
Writing – Original Draft Preparation
;
Isayeva U.;Pisanu C.;Squassina A.;Manchia M.
Ultimo
Writing – Original Draft Preparation
2025-01-01

Abstract

Aims: The present review explores the existing evidence on pharmacogenomic tests for prediction of lithium response in the treatment of bipolar disorder. We focused our research article on reports describing findings from genome-wide association studies, polygenic risk scores, and gene expression analyses associated with lithium response. Methods: We conducted a non-systematic review of studies from PubMed/Medline by using terms such as “pharmacogenomics,” “GWAS,” “gene expression,” and “lithium response.” Inclusion criteria focused on original research involving human subjects and assessing lithium response outcomes as well as in vitro studies. An extensive pearl-growing strategy was employed to further enlarge the scope of the piece by capitalizing on the knowledge of study authors on the subject. Results: The observed results, albeit promising, remain preliminary in terms of clinical relevance. Machine learning combining genetic and clinical data appears associated with moderate success in predicting lithium responsiveness. Gene expression studies and genome-wide association studies have helped identify possible targets of lithium and have the potential to support target-specific drug research. Conclusions: Pharmacogenomics may support further discoveries in precision medicine further enlarging our understanding of the underlying mechanisms of lithium for its efficacy. However, clinical applications currently appear out of reach in the near future.
2025
GWAS; GWES; Lithium response; machine learning; pharmacogenomics; polygenic risk score; precision psychiatry; prediction
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/448124
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