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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]

The understanding of the genetic architecture of psychiatric disorders has made significant advances in the last decade and some scientific findings can now be translated into clinical practice. The rise of genetic testing and the awareness of patients and their families motivate psychiatrists to examine this approach. The COST Action EnGagE (CA17130) is promoting these developments in Europe. Whereas the findings of common variants are the domain of research, screening for rare variants at the genomewide level is already applicable in clinical practice. It is now possible to return meaningful results to the individual to help him/her understanding the disease and the comorbidities, to guide treatment and to perform genetic counseling. In this presentation, we will give meaningful examples for psychiatric practice. For instance, around one-third of the patients diagnosed with autism spectrum disorder can benefit from a molecular diagnosis (fragile X syndrome, SHANK3 deletion...). Microdeletion or microduplication may explain a fraction of schizophrenic cases (e.g. del22q11). Identification of rare variants causing the disease may decrease the stigma and feeling of guilt often reported by patients and families. This could also help to detect and manage other comorbidities. It is expected that treatment guidelines and clinical trials would be developed in the near future for patients carrying a rare variant, opening the way to personalized psychiatry. Finally, this effort has a huge impact on the family, by enhancing genetic counseling in psychiatry. The rise of psychiatric genetics might align our field more closely with the other medical specialties. [ABSTRACT FROM AUTHOR]

Introduction: Studies about mental health of medical students have highlighted higher rates of depression compared to the general population. However, comparisons to a general student population are rare. Objectives: The French Observatoire national de la Vie Etudiante (OVE) has conducted a national survey and has measured the 12-month prevalence of major depressive episode (MDE) with the CIDI-SF and suicidal thoughts in 18,875 students. Methods: This survey investigated 2,414 medical students including 975 in the 1st year, 607 in the preclinical phase, 342 clinical studentsand 485 residents. MDE was regressed on the sociodemographic data using univariate and multivariate logistic regression and a network analysis was performed to compare the symptoms between students. Results: There was no significant difference for MDE prevalence among medical students (15.4%) compared to other fields of studies (15.7%). There was also no difference comparing the networks of depressive symptoms. However, some categories were particularly at risk for MDE: 1st year of medical studies (OR=1.74, 95%CI=[1.41-2.13]); Letters, Humanities and Social Sciences (OR=1.39[1.23-1.58]) and Law or Economics (OR=1.20[1.04-1.39]). Other sociodemographic variables were also significant risk factors: having important financial difficulties (OR=2.93[2.61-3.29]), having a net parental income less than 1500€/month (OR=1.17[1.02-1.34]), receiving scholarships based on social criteria (OR=1.11[1.01-1.23]), being of a female gender (OR=1.45[1.32-1.60]), being single (OR=1.35[1.20-1.52]). Prevalence of suicidal ideation is no different betweenmedical students (8.53%) and other fields of studies (8.68%). Conclusions: This is the largest cross-sectional French study about student mental health. The prevalence of MDEremains higher than in the general population (9.8%). [ABSTRACT FROM AUTHOR]