Bru Cormand

Cannabis use disorder (CUD) is a heterogeneous condition characterized by different patterns of comorbidity and clinical presentation, yet the genetic contributors to this heterogeneity remain poorly understood. CUD frequently co-occurs with attention-deficit/hyperactivity disorder (ADHD), reflecting, in part, their shared genetic liability. Distinguishing the genetic component of CUD that operates through ADHD from the component independent of ADHD may help clarify whether these two components differ in their association with substance-use phenotypes, psychiatric traits, and broader health outcomes. We applied genomic structural equation modeling–based GWAS-by-subtraction to large-scale ADHD and CUD genome-wide association studies to characterize these two CUD components and investigate their genetic and phenotypic association profiles. The ADHD-independent component accounted for approximately 35% of CUD SNP-based heritability and included three genome-wide significant loci. Although both components showed genetic correlations with substance dependence and risk-taking behaviors, they exhibited distinct patterns of genetic correlation with substance use phenotypes, other mental disorders, and health outcomes. In a phenome-wide association study of 114,410 Estonian Biobank participants, both genetic components were associated with multiple health conditions, but the ADHD-related genetic component generally showed larger effects. Across two clinical samples, polygenic score generated with both components further revealed distinct associations with the comorbidity between ADHD and substance use disorders (SUD). Both scores were associated with SUD among individuals without ADHD. In contrast, only the polygenic score for the ADHD-related component (PGSadhd) was associated with ADHD and comorbid ADHD and SUD, with the strongest association observed in the comorbid group. Mediation analysis further indicated that ADHD diagnosis accounted for approximately 20% of the association between PGSadhd and SUD. Together, these findings demonstrate that ADHD-related and ADHD-independent components of CUD have distinct genetic and phenotypic association profiles, suggesting that genetic heterogeneity may contribute to the clinical heterogeneity of SUD. This framework may help guide further research into the etiology and clinical presentation of the disorder.

Schizophrenia (SCZ) frequently co-occurs with substance use disorders (SUDs), yet the genetic basis of this comorbidity remains unclear. Using the latest European-ancestry genome-wide association studies (GWAS) for SCZ, cannabis use disorder (CanUD), opioid use disorder (OUD), problematic alcohol use (PAU), tobacco use disorder (TUD), and a general addiction factor (AF), together with two SCZ and one SUD case-control samples with individual-level genotype data, we applied multiple complementary genomic approaches to characterize their shared genetic architecture. Significant positive genome-wide genetic correlations were observed across all SCZ–SUD pairs. Local genetic correlation analyses identified multiple genomic regions contributing to this shared architecture, with both positive and negative correlations, and evidence of genomic regions shared across multiple SCZ–SUD pairs. Polygenic overlap analyses indicated substantial sharing (25–50%) of trait-associated variants between SCZ and SUDs. Genomic structural equation modelling supported a common latent factor underlying SCZ and all SUDs, accounting for approximately 23% of SCZ variance. Cross-trait polygenic risk score (PRS) analyses showed bidirectional associations between SCZ and SUD genetic liability. Mendelian randomization analyses provided evidence for a bidirectional causal relationship between SCZ and CanUD. Horizontal pleiotropy analyses identified numerous loci with concordant and discordant effects across traits, including loci shared among multiple SCZ–SUD pairs. Gene mapping and enrichment analyses indicated pathways related to neuroplasticity, synaptic transmission, immune system, metabolism and proteolysis, including both shared and SCZ–SUD-specific biological processes. Overall, these findings suggest that part of SCZ liability reflects genetic susceptibility to SUDs with potential implications for patient stratification and clinical management.

Schizophrenia (SCZ) frequently co-occurs with substance use disorders (SUDs), yet the genetic basis of this comorbidity remains unclear. Using the latest European-ancestry genome-wide association studies (GWAS) for SCZ, cannabis use disorder (CanUD), opioid use disorder (OUD), problematic alcohol use (PAU), tobacco use disorder (TUD), and a general addiction factor (AF), together with two SCZ and one SUD case-control samples with individual-level genotype data, we applied multiple complementary genomic approaches to characterize their shared genetic architecture. Significant positive genome-wide genetic correlations were observed across all SCZ–SUD pairs. Local genetic correlation analyses identified multiple genomic regions contributing to this shared architecture, with both positive and negative correlations, and evidence of genomic regions shared across multiple SCZ–SUD pairs. Polygenic overlap analyses indicated substantial sharing (25-50%) of trait-associated variants between SCZ and SUDs. Genomic structural equation modelling supported a common latent factor underlying SCZ and all SUDs, accounting for approximately 23% of SCZ variance. Cross-trait polygenic risk score (PRS) analyses showed bidirectional associations between SCZ and SUD genetic liability. Mendelian randomization analyses provided evidence for a bidirectional causal relationship between SCZ and CanUD. Horizontal pleiotropy analyses identified numerous loci with concordant and discordant effects across traits, including loci shared among multiple SCZ–SUD pairs. Gene mapping and enrichment analyses indicated pathways related to neuroplasticity, synaptic transmission, immune system, metabolism and proteolysis, including both shared and SCZ–SUD-specific biological processes. Overall, these findings suggest that part of SCZ liability reflects genetic susceptibility to SUDs with potential implications for patient stratification and clinical management.

Background: Suicide is a major public health concern and a highly complex, heterogeneous phenotype. Increasing evidence implicates epigenetic mechanisms, particularly DNA methylation (DNAm), in suicidal behavior. Methods: Building on previous epigenome-wide association studies (EWASs), we conducted the largest EWAS to date in postmortem dorsolateral prefrontal cortex (Brodmann area 9), analyzing DNAm and epigenetic aging (EA) in 199 suicide decedents (SD) and 190 age- and sex-matched non-psychiatric controls (NPC) using the Infinium MethylationEPIC BeadChip Array v2.0. Results: Bulk tissue analysis identified no significant differentially methylated positions or regions. In contrast, cell type-specific analysis using DNAm-deconvoluted cell proportions identified 605 differentially methylated cytosines in individual cell types (DMCTs) in excitatory neurons, 10 in inhibitory neurons, and 28 in oligodendrocyte precursor cells. Sex-stratified analyses identified mainly male-specific DMCTs, most of which were found in excitatory neurons, while comparison of violent and non-violent suicide identified additional DMCTs in glial cell types. Excitatory neuron DMCTs were enriched for synaptic, small GTPase signaling, and neurodevelopmental pathways, and overlapped genes previously associated with suicidal behavior, including MAD1L1 . No significant differences in EA acceleration were observed overall or by sex or suicide mechanism. Conclusions: These findings indicate that suicide-associated DNAm patterns are primarily neuron-specific and may remain undetectable in bulk tissue, highlighting the importance of cell type-specific approaches to elucidate biological mechanisms underlying suicide.

Cannabis is one of the most widely used psychoactive substances worldwide, and cannabis use disorder (CUD) is increasingly recognized as a major public health concern. Clinical evidence indicates that women may be particularly vulnerable to developing addiction, exhibiting a faster transition from initial drug use to loss of control and increased relapse vulnerability. However, females remain underrepresented in both preclinical and clinical research, limiting our understanding of the neurobiological mechanisms underlying this susceptibility. Here, we investigated sex differences in behavioral and epigenetic susceptibility to cannabinoid addiction using a mouse operant self-administration model with the synthetic cannabinoid agonist WIN 55,212-2. Female mice displayed increased addiction-like behavior, characterized by greater persistence of responding during drug-free periods and enhanced compulsive-like drug seeking compared to males. miRNA profiling in the medial prefrontal cortex (mPFC) identified a female-specific epigenetic signature associated with the addiction-like phenotype, including downregulation of mmu-miR-669j, mmu-miR-7036b-5p, mmu-miR-878-3p, and mmu-miR-7017-3p, together with upregulation of mmu-miR-3092-5p in addicted females. Functional enrichment analyses of predicted target genes revealed pathways related to synaptic organization, axon guidance, neurotransmission, and structural plasticity. Together, these findings demonstrate sex-dependent differences in vulnerability to cannabinoid addiction-like behavior and identify a specific miRNA signature in the mPFC associated with this phenotype, highlighting potential targets for the development of sex-specific therapeutic strategies.

Endometriosis is a chronic systemic disease affecting ~10% of women, yet its genetic basis and molecular mechanisms remain poorly understood. Hence, here we conducted a genome-wide association study of endometriosis and adenomyosis in ~1.4 million women, including 105,869 cases, aiming to expand loci discovery across ancestries, dissect symptom-specific effects and integrate multi-omic data. We identified 80 genomic regions associated with endometriosis risk, including 37 new loci, of which 5 are also associated with adenomyosis. We identified putative causal variants underlying over 50 of these associations. Transcriptomic, epigenetic and proteomic analyses across tissues linked endometriosis risk to pathways involved in cell differentiation, immune and hormonal regulation, tissue remodeling and inflammation. Drug-repurposing analyses highlighted potential treatments currently used for breast cancer, contraception and preterm birth prevention. Endometriosis polygenic risk interacted with abdominal pain, anxiety, migraine and nausea. This study advances understanding of genetic risk factors for endometriosis and provides molecular support for several hypotheses on its pathogenesis.

Perinatal depression (PD) is common and disabling, yet its longitudinal comorbidity patterns and predictability remain poorly understood. This study leveraged 8,804 women with delivery records in the All of Us cohort, including 438 with clinically diagnosed postpartum depression (PPD), to characterize multimorbidity trajectories and develop integrated prediction models. Comorbidities were grouped into 38 conditions across psychiatric, autoimmune, metabolic, neurological/pain, and reproductive/gynecological categories and examined both cross-sectionally and in monthly time bins from 250 months before to 500 months after delivery. Latent class analysis identified three pre- and post-delivery multimorbidity profiles and transitions between classes, while polygenic risk scores for depression and obstetric, clinical and socioeconomic variables were combined in machine learning models to predict PPD, post-delivery class membership, and symptom worsening among initially low-burden women. PPD cases showed higher odds of several psychiatric, autoimmune, and metabolic conditions and a tendency toward greater post-delivery comorbidity accumulation, particularly among women who were healthy pre-pregnancy. Multimorbidity profiles based on latent classes captured clinically meaningful risk gradients, and transition analyses revealed that incident PPD in previously healthy women marked a shift toward more symptomatic post-delivery profiles. Machine learning models achieved moderate discrimination for PPD and comorbidity outcomes and highlighted the importance of genetic liability, obstetric complications, and socioeconomic disadvantage, but low positive predictive values limit clinical implementation. These findings position PPD as a critical event in women’s psychiatric, cardiometabolic, and pain-related health trajectories and support life-course, multimorbidity-informed screening and prevention strategies that extend beyond the traditional postpartum period.

Mutations in the RBFOX1 gene are associated with psychiatric disorders but how RBFOX1 influences psychiatric disorder vulnerability remains unclear. Recent studies showed that RBFOX proteins mediate the alternative splicing of PAC1, a critical HPA axis activator. Further, RBFOX1 dysfunction is linked to dysregulation of BDNF/TRKB, a pathway promoting neuroplasticity, neuronal survival and stress resilience. Hence, RBFOX1 dysfunction may increase psychiatric disorder vulnerability via HPA axis dysregulation, leading to disrupted development and allostatic overload. To test this hypothesis, we generated a zebrafish rbfox1 loss of function (LoF) line and examined behavioural and molecular effects during development. We found that rbfox1 LoF mutants exhibited hyperactivity, impulsivity and heightened arousal, alongside alterations in proliferation – traits associated with neurodevelopmental and stress-related disorders. In adults, loss of rbfox1 function led to decreased fertility and survival, consistent with allostatic overload. At the molecular level, at larval stages rbfox1 mutants showed increased cortisol levels and disrupted expression of key stress-related genes (bdnf, trkb2, pac1a-hop, crhb, nr3c2). Pharmacological intervention targeting TRKB restored crhb and nr3c2 gene expression and hyperactive and hyperarousal behaviours. In adults, dysregulation of crhb, nr3c2 and bdnf/trkb2 genes was only seen following acute stress exposure. Our findings reveal a fundamental role for RBFOX1 in integrating stress responses through its regulation of BDNF/TRKB and neuroendocrine signalling.

Synaptic Ras GTPase-Activating Protein 1 (SynGAP) is a key regulator of synaptic plasticity, neurodevelopment, and neuronal circuit function. It is encoded by the SYNGAP1 gene, in which de novo dominant pathogenic variants are a major cause of SYNGAP1 Encephalopathy, a rare neurodevelopmental disorder characterized by intellectual disability, epilepsy, autistic traits, and other clinical manifestations. While some genetic studies have reported genotype-phenotype correlations in this condition, our understanding of how specific genetic variants contribute to the heterogeneous clinical symptoms remain limited. Here, we analysed a cohort of 44 cases extensively characterised at the phenotypic level to investigate the impact of genetic variants in SYNGAP1 and in potentially modulatory genes on the clinical features of SYNGAP1 Encephalopathy. Our results indicate that patients with variants in the PH domain of SynGAP exhibited milder phenotypes than other individuals. Moreover, missense variants were associated with a higher prevalence of autistic traits compared to loss-of-function variants. Autistic traits also showed a suggestive positive correlation with the predicted length of the encoded protein. Finally, patients harbouring rare or low-frequency variants in SYNGAP1 - related genes tended to present with higher global severity. Taken together, these findings suggest that both the location and nature of SYNGAP1 variants, along with additional genetic modifiers, may contribute to the variability in clinical presentation and severity. Further studies involving larger cohorts and functional validation are needed to refine genotype-phenotype correlations and support the development of personalized management strategies.