Literature DB >> 12562213

Predicting response to lithium in mood disorders: role of genetic polymorphisms.

Alessandro Serretti1, Paola Artioli.   

Abstract

Lithium is considered to be the first choice mood stabilizer in recurrent mood disorders. Its widespread and large-scale use is the result of its proven efficacy. In spite of this fact, patients have been observed to show a variable response to lithium treatment: in some cases it is completely effective in preventing manic or depressive relapses, while in other cases it appears to show no influence on the disease course. The possible definition of a genetic liability profile for adverse effects and efficacy will be of great help, as lithium therapy needs at least 6 months to be effective in stabilizing mood disorders. During the last few years, a number of groups have reported possible liability genes. Lithium long-term prophylactic efficacy has been associated with serotonin transporter protein, tryptophan hydroxylase and inositol polyphosphate 1-phosphatase variants. A number of other candidate genes and anonymous markers did not yield positive associations. Therefore, even if some positive results have been reported, no unequivocal susceptibility gene for lithium efficacy has been identified. Although the available data may not currently allow a meaningful prediction of lithium response, future research is aimed at the development of individualized treament of mood disorders, including the possibility of 'pharmacological genetic counseling'.

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Year:  2003        PMID: 12562213     DOI: 10.2165/00129785-200303010-00004

Source DB:  PubMed          Journal:  Am J Pharmacogenomics        ISSN: 1175-2203


  4 in total

Review 1.  Using pharmacogenetics and pharmacogenomics in the treatment of psychiatric disorders: some ethical and economic considerations.

Authors:  Katherine I Morley; Wayne D Hall
Journal:  J Mol Med (Berl)       Date:  2003-11-04       Impact factor: 4.599

Review 2.  Lithium: updated human knowledge using an evidence-based approach. Part II: Clinical pharmacology and therapeutic monitoring.

Authors:  Etienne Marc Grandjean; Jean-Michel Aubry
Journal:  CNS Drugs       Date:  2009       Impact factor: 5.749

Review 3.  Pharmacogenomics in depression and antidepressants.

Authors:  Brigitta Bondy
Journal:  Dialogues Clin Neurosci       Date:  2005       Impact factor: 5.986

4.  Neural network analysis in pharmacogenetics of mood disorders.

Authors:  Alessandro Serretti; Enrico Smeraldi
Journal:  BMC Med Genet       Date:  2004-12-09       Impact factor: 2.103

  4 in total

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