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Several studies have indicated that patients with bipolar disorder (BD) who respond well to lithium prophylaxis constitute a biologically distinct subgroup. Lithium is thought to stablize mood by acting at the phosphoinositide cycle. We have investigated a polymorphism located in the gene (PLCG1) that codes for a ␥-1 isozyme of phospholipase (PLC), an enzyme that plays an important role in the phosphoinositide second messenger system. A population-based association study and a family-based linkage study were carried out on patients who were considered excellent responders to lithium prophylaxis. Response to lithium was evaluated prospectively with an average follow-up of 14.4 ± 6.8 years. The PLCG1 polymorphism was investigated in 136 excellent lithium responders and 163 controls. In addition, the segregation of this marker was studied in 32 families ascertained through lithium-responsive bipolar probands. The allele distributions between lithium-responsive bipolar patients and controls were different, with a higher frequency of one of the PLCG1 polymorphisms in patients ( 2 = 8.09; empirical P = 0.033). This polymorphism, however, confers only a small risk (OR = 1.88, CI 1.19-3.00). Linkage studies with the same marker yielded modest support for the involvement of this gene in the pathogenesis of BD when unilineal families were considered (Max LOD = 1.45; empirical P = 0.004), but not in the whole sample. Our results provide preliminary evidence that a PLC isozyme may confer susceptibility to bipolar disorder, probably accounting for a fraction of the total genetic variance. Whether this polymorphism is implicated in the pathogenesis of BD or in the mechanism of lithium response remains to be determined.

Genetic mapping studies in bipolar disorder (BD) have been hampered by the unclear boundaries of the phenotypic spectrum, and possibly, by the complexity of the underlying genetic mechanisms, and heterogeneity. Among the suggested approaches to circumvent these problems, a pharmacogenetic strategy has been increasingly proposed. Several studies have indicated that patients with BD who respond well to lithium prophylaxis constitute a biologically distinct subgroup. In this study we have conducted a complete genome scan using 378 markers spaced at an average distance of 10 cM in 31 families ascertained through excellent lithium responders. Response to lithium was evaluated prospectively with an average follow-up of 12 years. Evidence for linkage was found with a locus on chromosome 15q14 (ACTC, lod score = 3.46, locus-specific P-value = 0.000014) and suggestive results were observed for another marker on chromosome 7q11.2 (D7S1816, lod score = 2.68, locus-specific P-value = 0.00011). Other interesting findings were obtained with markers on chromosomes 6 and 22, namely D6S1050 (lod score = 2.0, locus-specific P-value = 0.00004) and D22S420 (lod score = 1.91). Nonparametric linkage analysis provided additional support for the role of these loci. Further analyses of these results suggested that the locus on chromosome 15q14 may be implicated in the etiology of BD, whereas the 7q11.2 locus may be relevant for lithium response. In conclusion, our results provide original evidence suggesting that loci on 15q14 and 7q11.2 may be implicated in the pathogenesis of BD responsive to lithium. Molecular Psychiatry (2001) 6, 570-578.

Prediction of lithium response using clinical data.Objective: Promptly establishing maintenance therapy could reduce morbidity and mortality in patients with bipolar disorder. Using a machine learning approach, we sought to evaluate whether lithium responsiveness (LR) is predictable using clinical markers. Method: Our data are the largest existing sample of direct interviewbased clinical data from lithium-treated patients (n = 1266, 34.7% responders), collected across seven sites, internationally. We trained a random forest model to classify LR-as defined by the previously validated Alda scale-against 180 clinical predictors. Results: Under appropriate cross-validation procedures, LR was predictable in the pooled sample with an area under the receiver operating characteristic curve of 0.80 (95% CI 0.78-0.82) and a Cohen kappa of 0.46 (0.4-0.51). The model demonstrated a particularly low false-positive rate (specificity 0.91 [0.88-0.92]). Features related to clinical course and the absence of rapid cycling appeared consistently informative. Conclusion: Clinical data can inform out-of-sample LR prediction to a potentially clinically relevant degree. Despite the relevance of clinical course and the absence of rapid cycling, there was substantial betweensite heterogeneity with respect to feature importance. Future work must focus on improving classification of true positives, better characterizing between-and within-site heterogeneity, and further testing such models on new external datasets.• Lithium response can be predicted accurately (area under the receiver operating characteristic curve of 0.80) in previously unobserved subjects based on data collected by careful clinical interview.• Variables related to clinical course of illness and absence of rapid cycling are particularly informative. Limitations• Our data were retrospective in nature, although data of such as scope would be difficult to collect prospectively.

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