Claudia Pisanu

Severe mental disorders such as bipolar disorder (BD), major depressive disorder (MDD) and schizophrenia (SZ) are characterized by reduced life expectancy, premature mortality and alterations of aging biomarkers, leading to hypothesize that they might be associated with accelerated cellular aging. We quantified the genetic overlap between severe mental disorders and a comprehensive set of aging biomarkers including multivariate longevity and healthy aging (mvAge), brain age gap (BAG), leucocyte telomere length (gLTL), mitochondrial DNA copy number and epigenetic age acceleration (gEAA) using cutting-edge methods, and evaluated their functional enrichment and suitability as drug targets. All disorders were negatively correlated with mvAge. Further, MDD correlated negatively with gLTL and positively with gEAA. We identified several pleiotropic variants, with nine genes (AC068490.2, ASIC2, CNNM2, FURIN, GPM6A, HS6ST3, RP5-1043L13.1, SORCS3 and SP4) containing variants shared between aging biomarkers and all disorders. Functional analyses with summary-data-based Mendelian randomization showed that increased expression of the druggable gene CRHR1 in the prefrontal cortex was associated with increased risk of MDD and BAG measures. Our findings suggest that shared heritability might contribute to reduced longevity and healthy aging in severe mental disorders and identify pleiotropic genes involved in synaptic function and metabolic processes related to micronutrients such as folate and magnesium.

Background and Objectives: Treatment-resistant depression (TRD) is a major clinical challenge in the management of major depressive disorder (MDD). While pharmacogenetics has been suggested to be clinically useful in guiding antidepressant treatment, few studies have explored if and how pharmacogenes can be involved in TRD pathophysiology and its clinical outcomes. Material amd Methods: We explored the role of differences in metabolizer phenotypes, gene expression levels, and microRNAs of three key pharmacogenes (CYP2D6, CYP2C19, CYP2B6) in TRD pathophysiology and antidepressant response in a cohort of 300 patients with MDD from the PROMPT consortium. Results: CYP2D6 phenotype distribution did not differ significantly between TRD and non-TRD groups, but mRNA expression was significantly upregulated in TRD. Hsa-miR-26b-5p, a microRNA predicted to regulate CYP2D6, was significantly downregulated in TRD. For CYP2C19, intermediate metabolizers (IMs) were underrepresented in TRD versus non-TRD (IMs vs. normal metabolizers (NMs): χ² = 6.07, p = 0.019). microRNA hsa-let-7d-5p and hsa-miR-27a-3p, predicted to regulate CYP2C19, were significantly downregulated in TRD. No significant differences were found for CYP2B6. Conclusions: This study contributes valuable insights to the PROMPT project on how pharmacokinetic gene variants and their expression and regulatory mechanisms may influence antidepressant response and resistance in MDD.

Identifying biological and clinical factors associated with response to mood-stabilizing medications is critical for improving bipolar disorder (BD) treatment. The Mood Stabilizer Genomics (MoStGen) Consortium was established to investigate pharmacogenomic and clinical predictors of response to treatment of BD with antiepileptic drug mood stabilizers (AMS). Here we present the first pharmacogenomic analyses of AMS treatment outcomes based on MoStGen Consortium data, including 917 individuals across contributing sites. We performed genome-wide association analyses in subcohorts followed by meta-analyses, with AMS treatment response measured quantitatively using the Alda scale. Medication-stratified analyses were performed for valproic acid (VPA) and lamotrigine (LTG) treatment response. Additionally, polygenic score (PGS) analyses were used to evaluate the overall genetic contribution to AMS response across cohorts and to test whether genetic liability for various neuropsychiatric illnesses impacts AMS response. We detected genome-wide significant associations with LTG treatment response for SNPs in the gene ROBO2 (top SNP: rs985123, p = 1.9E-10) and for POLR1E at the gene-level ( p = 2.53E-06). No significant associations were found for overall AMS or VPA treatment response. Leave-one-out PGS analyses provided significant evidence for a polygenic signal for AMS treatment response. Furthermore, the epilepsy PGS was nominally significantly associated with AMS response ( p = 0.024), suggesting higher genetic liability to epilepsy predicts a better response to treatment with AMS. These findings provide insights into the genetic contribution to AMS treatment outcomes, and in particular LTG response, and may contribute to the development of more precise treatments for BD.

1. Severe mental disorders such as major depressive disorder (MDD), schizophrenia, and bipolar disorder (BD) are leading contributors to the global health burden [1]. Pharmacological treatment with...

Purpose: We conducted a comprehensive analysis of esketamine-related adverse events (AE) on the FDA Adverse Event Reporting System (FAERS) database, taking into account for the first time drug-drug interaction signals. Methods: We conducted a retrospective case/non-case study of esketamine-related AEs reported in the FAERS database up to the last quarter (Q4) of 2024. Potential signals were detected using the reporting odds ratio (ROR) and confidence intervals (CI), while drug-drug interactions were studied using different metrics such as lift, conviction and the combination risk ratio detection algorithm. An analysis of sex differences was also performed using the relative ROR and CI. Results: The analysis of 7,790 reports in which esketamine was a primary or secondary suspect identified potential safety signals for 173 AEs. Novel signals include homicidal ideation (ROR = 5.30, 95% CI: 2.38-11.82) and substance use disorder (ROR = 6.12, 95% CI: 2.54-14.73). Women showed a longer time to onset than men (p = 0.003). In addition, we detected sex differences in 23 AEs, seven of which were more likely to be reported in women, while 16 in men. Among these, four were significant exclusively in women (oxygen saturation decreased, abnormal behaviour, unresponsive to stimuli and aggression) and two in men (vision blurred and bradycardia). Potential signals of additive and multiplicative drug-drug interactions were detected for antidepressants (venlafaxine for“dizziness” and bupropion for “agitation”) and antipsychotics (risperidone for “vertigo”). Conclusions: Our results increase knowledge on potential risks related to esketamine AEs and potential drug-drug interaction signals in a real-world setting.

Background: Epigenetic mechanisms might play a role in modulating susceptibility to bipolar disorder (BD) and response to lithium, the mainstay treatment for BD. Additionally, individuals with BD experience accelerated biological aging. Methods: We compared blood DNA methylation profiles measured with EPIC v.2.0 arrays between patients with BD (33 lithium responders and 31 nonresponders) and nonpsychiatric controls (n = 32), as well as based on long-term lithium response. In addition, we compared cellular aging between these groups using epigenetic age, pace of aging, and, for the first time, transcriptional age acceleration based on bulk RNA sequencing in 93 patients and 56 controls. Results: We identified 191 differentially methylated positions (DMPs) and 8 differentially methylated regions between patients with BD and controls, located in genes enriched for “Postsynaptic Density” (odds ratio = 6.81, p = 0.001). No DMP was significantly associated with lithium response after multiple testing correction. Patients showed a significantly higher biological age acceleration than controls based on two epigenetic clocks (GrimAge, Mann–Whitney U = 551, p = 0.0009; GrimAge2: U = 477, p = 9.0E-05) and pace of aging (DunedinPACE, t = 3.01, p = 0.003), but not on transcriptional age. While we observed no significant difference in epigenetic aging based on lithium response, lithium responders showed lower epigenetic acceleration using all clocks, with a trend observed using the PhenoAge clock (t = 1.97, p = 0.053). Conclusions: Our findings point to methylation patterns characterizing BD and support the hypothesis of accelerated cellular aging in BD.

We examined the association of selected candidate pharmacodynamic (PD) genes in MDD with treatment outcomes, defined according to remission thresholds for Hamilton Depression Rating Scale (HDRS) with 6- and 17- items. To this end, we recruited 158 individuals living with MDD followed in an academic community mental health center. We reconstructed their clinical history and tested the association of a selected panel of pharmacodynamic genes with clinical remission. Our multivariate models were corrected for illness duration, substance use, lifetime stressful events, and sex. We found partially concordant associations for candidate biomarkers and clinical remission defined with HDRS-6 and HDRS-17. In the logistic regression model, two polymorphisms were statistically significantly associated with HDRS-17 remission: namely rs10975641 and rs11628713. Our results suggest that polymorphisms in PD genes might influence clinical response in MDD. Interestingly, we showed some degree of concordance of the association depending on the definition of the response.