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Objectives: The Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale) is the most widely used clinical measure of lithium response phenotypes. We assess its performance against recommended psychometric and clinimetric standards. Methods: We used data from the Consortium for Lithium Genetics and a French study of lithium response phenotypes (combined sample >2500) to assess reproducibility, responsiveness, validity, and interpretability of the A scale (assessing change in illness activity), the B scale, and its items (assessing confounders of response) and the previously established response categories derived from the Total Score for the Alda scale. Results: The key findings are that the B scale is vulnerable to error measurement. For example, some items contribute little to overall performance of the Alda scale (eg, B2) and that the B scale does not reliably assess a single construct (uncertainty in response). Machine learning models indicate that it may be more useful to employ an algorithm for combining the ratings of individual B items in a sequence that clarifies the noise to signal ratio instead of using a composite score. Conclusions: This study highlights three important topics. First, empirical approaches can help determine which aspects of the performance of any scale can be improved. Second, the B scale of the Alda is best applied as a multidimensional index (identifying several independent confounders of the assessment of response). Third, an integrated science approach to precision psychiatry is vital, otherwise phenotypic misclassifications will undermine the reliability and validity of findings from genetics and biomarker studies. [ABSTRACT FROM AUTHOR]

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 interview‐based 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 between‐site 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. [ABSTRACT FROM AUTHOR]

Objective To confirm prior findings that the larger the maximum monthly increase in solar insolation in springtime, the younger the age of onset of bipolar disorder. Method Data were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries. Variables included solar insolation, birth-cohort, family history, polarity of first episode and country physician density. Results There was a significant, inverse association between the maximum monthly increase in solar insolation at the onset location, and the age of onset. This effect was reduced in those without a family history of mood disorders and with a first episode of mania rather than depression. The maximum monthly increase occurred in springtime. The youngest birth-cohort had the youngest age of onset. All prior relationships were confirmed using both the entire sample, and only the youngest birth-cohort (all estimated coefficients P < 0.001). Conclusion A large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders. Recent societal changes that affect light exposure ( LED lighting, mobile devices backlit with LEDs) may influence adaptability to a springtime circadian challenge. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this study was to determine whether the clinical profiles of bipolar disorder (BD) patients could be differentiated more clearly using the existing classification by diagnostic subtype or by lithium treatment responsiveness., Methods: We included adult patients with BD-I or II (N = 477 across four sites) who were treated with lithium as their principal mood stabilizer for at least 1 year. Treatment responsiveness was defined using the dichotomized Alda score. We performed hierarchical clustering on phenotypes defined by 40 features, covering demographics, clinical course, family history, suicide behaviour, and comorbid conditions. We then measured the amount of information that inferred clusters carried about (A) BD subtype and (B) lithium responsiveness using adjusted mutual information (AMI) scores. Detailed phenotypic profiles across clusters were then evaluated with univariate comparisons., Results: Two clusters were identified (n = 56 and n = 421), which captured significantly more information about lithium responsiveness (AMI range: 0.033 to 0.133) than BD subtype (AMI: 0.004 to 0.011). The smaller cluster had disproportionately more lithium responders (n = 47 [83.8%]) when compared to the larger cluster (103 [24.4%]; p = 0.006)., Conclusions: Phenotypes derived from detailed clinical data may carry more information about lithium responsiveness than the current classification of diagnostic subtype. These findings support lithium responsiveness as a valid approach to stratification in clinical samples., (© 2024 The Authors. Acta Psychiatrica Scandinavica published by John Wiley & Sons Ltd.)

Lithium is the mainstay treatment in bipolar disorder (BD) for its effectiveness in the acute phases of illness and in prevention of recurrences. Lithium's mechanism of action is complex, and while it modulates the function of hundreds of molecular targets, most of these effects could be unspecific and not relevant for its clinical efficacy. In this study, we applied an integrated analytical approach using genome-wide expression and genotyping data from BD patients to identify lithium-responsive genes that may serve as biomarkers of its efficacy. To this purpose, we tested the effect of treatment with lithium chloride 1 mM on the transcriptome of lymphoblasts from 10 lithium responders (LR) and 10 nonresponders (NR) patients and identified genes significantly influenced by the treatment exclusively in LR. These findings were integrated with gene-based analysis on genome-wide genotyping data from an extended sample of 205 BD patients characterized for lithium response. The expression of 29 genes was significantly changed by lithium exclusively in LR. Gene-based analysis showed that two of these genes, zinc finger protein 429 (ZNF429) and zinc finger protein 493 (ZNF493), were also significantly associated with lithium response. Validation with quantitative real-time polymerase chain reaction confirmed the lithium-induced downregulation of ZNF493 in LR (p = .036). Using convergent analyses of genome-wide expression and genotyping data, we identified ZNF493 as a potential lithium-responsive target that may be involved in modulating lithium efficacy in BD. To our knowledge, this is the first evidence supporting the involvement of zinc finger proteins in lithium response., (© 2018 Wiley Periodicals, Inc.)

The discovery of the genetic factors implicated in the predisposition to complex diseases may greatly profit from genetic studies in isolated populations. In this perspective, we performed a genome-wide scan using 507 microsatellite markers, with an average interval size of 7.6 cM, on a sample of 88 nuclear families with at least two affected sibs with bipolar disorder recruited in the Sardinian population. An initial analysis yielded non-parametric linkage exceeding 3.4 with P-values <0.0003 at two adjacent markers, D1S206 and D1S435 in the 1p22-p21 chromosomal region. Moreover, positive linkage ranging between 2.0 and 3.0 was obtained for other loci in several cases in regions that have already been linked to predisposition to bipolar disorder, such as 5p15.33, 8q24.13, and 11q14.3. A subsequent analysis of the 1p22-p21 region using the same set of families and a dense panel of 20 new microsatellite markers, spaced at 1.2 cM on average, reinforced the finding of suggestive linkage for this region. Interestingly, NPL values above 2.1 and P-values <0.02 were obtained for a cluster of 10 markers comprising D1S435. Thus, this study suggests that the 1p22-p21 region may contain a new locus participating to the genetic susceptibility to bipolar disorder and reproduces positive linkage for several other loci already implicated in this pathology. Since the Sardinian population presents a peculiar genetic homogeneity, these results may pave the way to further studies for replication in this population contributing to the rapid discovery of the genetic factors predisposing to bipolar disorder., ((c) 2010 Wiley-Liss, Inc.)