Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study

Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = −0.14; 95% confidence interval [CI]: −0.24 to −0.03; p value = 0.010) and MDD (β = −0.16; 95% CI: −0.27 to −0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34–1.93; p value = 2e−7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18–2.01) and European sample: OR = 1.75 (95% CI: 1.30–2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61–4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD

Phobie sociale et troubles sexuels (efficacité d'une thérapie cognitive et comportementale en groupe)

BORDEAUX2-BU Santé (330632101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

The Contribution of Multiplexing Single Cell RNA Sequencing in Acute Myeloid Leukemia

Decades ago, the treatment for acute myeloid leukemia relied on cytarabine and anthracycline. However, advancements in medical research have introduced targeted therapies, initially employing monoclonal antibodies such as ant-CD52 and anti-CD123, and subsequently utilizing specific inhibitors that target molecular mutations like anti-IDH1, IDH2, or FLT3. The challenge lies in determining the role of these therapeutic options, considering the inherent tumor heterogeneity associated with leukemia diagnosis and the clonal drift that this type of tumor can undergo. Targeted drugs necessitate an examination of various therapeutic targets at the individual cell level rather than assessing the entire population. It is crucial to differentiate between the prognostic value and therapeutic potential of a specific molecular target, depending on whether it is found in a terminally differentiated cell with limited proliferative potential or a stem cell with robust capabilities for both proliferation and self-renewal. However, this cell-by-cell analysis is accompanied by several challenges. Firstly, the scientific aspect poses difficulties in comparing different single cell analysis experiments despite efforts to standardize the results through various techniques. Secondly, there are practical obstacles as each individual cell experiment incurs significant financial costs and consumes a substantial amount of time. A viable solution lies in the ability to process multiple samples simultaneously, which is a distinctive feature of the cell hashing technique. In this study, we demonstrate the applicability of the cell hashing technique for analyzing acute myeloid leukemia cells. By comparing it to standard single cell analysis, we establish a strong correlation in various parameters such as quality control, gene expression, and the analysis of leukemic blast markers in patients. Consequently, this technique holds the potential to become an integral part of the biological assessment of acute myeloid leukemia, contributing to the personalized and optimized management of the disease, particularly in the context of employing targeted therapies

Bipolar disorder with seasonal pattern: clinical characteristics and gender influences.: Bipolar patients with seasonal pattern

International audienceBipolar disorder (BD) has a multifactorial etiology with heterogeneous clinical presentations. Around 25% of BD patients may present with a depressive seasonal pattern (SP). However, there are limited scientific data on the prevalence of SP, its clinical manifestations, and any gender influence. Four hundred and fifty-two BD I and II cases (62% female), recruited from three French university-affiliated psychiatric departments, were assessed for SP. Clinical, treatment, and sociodemographic variables were obtained from structured interviews. One hundred and two (23%) cases met DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) criteria for SP, with similar frequency according to gender. Multivariate analysis showed a significant association between SP and BD II (odds ratio [OR] = 1.99, p = 0.01), lifetime history of rapid cycling (OR = 2.05, p = 0.02), eating disorders (OR = 2.94, p = 0.003), and total number of depressive episodes (OR = 1.13, p = 0.002). Seventy-one percent of cases were correctly classified by this analysis. However, when stratifying the analyses by gender, SP was associated with BD II subtype (OR = 2.89, p = 0.017) and total number of depressive episodes (OR = 1.21, p = 0.0018) in males but with rapid cycling (OR = 3.02, p = 0.0027) and eating disorders (OR = 2.60, p = 0.016) in females. This is the first study to identify different associations between SP and clinical characteristics of BD according to gender. The authors suggest that SP represents a potentially important specifier of BD. These findings indicate that seasonality may reflect increased severity or complexity of disorder

Metabolic Syndrome in a French Cohort of Patients With Bipolar Disorder

International audienc

Genetic heterogeneity according to age at onset in bipolar disorder: A combined positional cloning and candidate gene approach

This study is the first that formally tests for genetic heterogeneity of bipolar disorder (BD) according to age at onset (AAO) subgroups by combining positional cloning and candidate gene approaches. Our previous genome-wide linkage-scan identified five genomic regions linked to early-onset form of BD. The present study uses association analysis to test genetic heterogeneity of candidate genes located in these five regions in a sample of 443 unrelated bipolar patients and 1,731 controls. The study involved the following steps: (1) test of heterogeneity by comparing early-onset BD patients versus later-onset BD patients; and (2) for significant results in step 1, comparison of early-onsetBDpatients and later-onsetBDpatients separately to controls. Two types of analyses were used: the single SNP test and the gene-based association test. We provide evidence for genetic heterogeneity within the ADRB2 (beta-2adrenoreceptor) gene region that is specifically associated with the early onset form of BD with an OR of 1.8. Unfortunately, the genotyping coverage of ADRB2 in the Wellcome Trust Case Control Consortium sample meant undermined our efforts to undertake a replication. However, as the ADRB2 gene product directly interacts with the CACNA1C gene product, and is known to be implicated in BD susceptibility, we conclude that further exploration of the relationships between ADRB2 and BD needs to be undertaken

Outcomes for bipolar patients assessed in the French expert center network: A 2-year follow-up observational study (FondaMental Advanced Centers of Expertise for Bipolar Disorder [FACE-BD])

International audienc