An atlas of brain IDPs associated with bipolar disorder is established, by integrating epidemiological and genetic evidence, and candidate IDPs that were consistently associated with BD are highlighted across complementary analyses.
Abstract
Despite many reported imaging markers for bipolar disorder (BD), systematic assessment across diverse brain imaging-derived phenotypes (IDPs) is lacking. We used epidemiological and genetic analyses to progress from association to causality and identify candidate biomarkers and potential pathways of BD.
We conducted an Exposome-Wide Association Study (ExWAS) in 35,680 UK Biobank participants to assess associations of 686 brain IDPs with BD. Genetic correlations were estimated via linkage disequilibrium score regression (LDSC). Bidirectional two-sample Mendelian randomization (MR) and meta-analysis were performed using large-scale GWAS data to infer causality. Additional analyses, including Functional Mapping and Annotation (FUMA), protein-protein interaction (PPI) network analysis, and spatiotemporal gene expression profiling during human brain development, were performed to investigate potential biological mechanisms of BD and IDPs.
In our ExWAS analyses, we identified 10 significant exposome-level IDPs, and LDSC further revealed 67 IDPs with significant genetic correlations with BD. The MR analyses provided robust causal evidence for 12 IDPs, 6 of which were further validated by meta-analysis. Integrative analyses identified two associations supported by both epidemiological and genetic evidence (IDP.1510: fractional anisotropy in the forceps major, and IDP.0387: volume of the right lateral orbital frontal cortex). Additionally, we identified pleiotropic genes between IDPs and BD. Gene enrichment analyses implicated shared biological pathways, such as nucleosome assembly and neutrophil extracellular trap formation . PPI network analysis suggested that histone family members occupied central hubs in the interaction network. Spatiotemporal expression profiling identified region-specific developmental trajectories of pleiotropic genes in brain regions, including the cerebellum and thalamus, with the late fetal to early postnatal period potentially representing a sensitive developmental period for neurodevelopmental effects of BD susceptibility genes.
This study establishes an atlas of brain IDPs associated with BD, by integrating epidemiological and genetic evidence. The findings highlight candidate IDPs, including right lateral orbital frontal cortex volume and fractional anisotropy in the forceps major, that were consistently associated with BD across complementary analyses. Our results provide genetically supported targets for early intervention and precision psychiatry.
Background Irritable bowel syndrome (IBS) is a complex disorder of gut-brain interaction, with heterogeneous symptoms, no available biomarkers and limited pathogenetic insight. Objective To identify genetic risk factors and actionable mechanisms for future clinical translation in IBS. Design We conducted a genome-wide association study (GWAS) meta-analysis of IBS in 2 775 539 individuals from 22 biobanks. IBS genetics was studied across multiple ancestries, different case definitions and symptom-related subtypes. Heritability and genetic correlations with other traits were estimated, and Mendelian randomisation was used to test causal relationships. GWAS data were functionally annotated and fine-mapped to prioritise tissues, cell types, pathways, candidate genes, specific mechanisms and druggable targets. Results Significant heritability was only detected in individuals of European ancestry, with near-identical genetic architecture across case definitions. Genetic correlations with GI, psychiatric and cardiometabolic traits were observed, including causal relationships with triglyceride (TG) levels. Functional annotation of IBS risk loci highlighted cell types and pathways relevant to brain, enteric neuro-glial and cardiometabolic domains, as well as actionable targets like GCKR, a regulator of TG metabolism. Druggability analyses converged on cardiometabolic mechanisms, including TG modulation. IBS polygenic risk scores were derived and showed a significant association with case status in an independent case-control dataset, supporting further evaluation in external population-based and clinically ascertained cohorts. Conclusions This study provides the most comprehensive assessment of IBS genetics to date, demonstrating reproducible polygenic inheritance. We link IBS risk to convergent neurogastrointestinal and novel cardiometabolic mechanisms, highlight specific biological pathways and actionable mechanisms and outline translational opportunities emerging from integrated computational analyses.
Biagio Di Lorenzo, L. Camargo Tavares, Cristian Díaz-Muñoz et al.· Gut· 0 citations
Aim: Bipolar disorder is a multifactorial psychiatric condition characterized by mood dysregulation. Although its heritability is established, the underlying genetic mechanism still remains incomplete. Herein, the aim of this study was to integrate genome-wide association study data with functional analyses in order to nominate key genetic loci, and pathways and regulatory mechanisms involved in bipolar disorder.
Methodology: Public datasets for GWAS-identified bipolar disorder variants were downloaded and subjected to functional enrichment, protein-protein interaction mapping, and miRNA target prediction. The analyses focused on GO, Reactome, and KEGG pathway enrichment, as well as metabolomic and transcription factor analyses, to assess molecular dysregulation in bipolar disorder.
Results: Mitochondrial function, PALB2, RHOU; immune response, HLA-B, DPY19L3; synaptic signaling, KCNU1, DPP10; and metabolic processes. PPI analysis highlighted hub proteins such as PTK2 and PAK1, which might be regulatory proteins, while miRNA analysis revealed hsa-miR-126-3p and hsa-miR-452-5p as post-transcriptional regulators. Metabolomic assessment showed perturbations in GTP-binding proteins and magnesium homeostasis.
Interpretation: This integrative analysis enhances knowledge on the genetic and molecular architecture of bipolar disorder, reinforcing its polygenic nature and implicating mitochondrial dysfunction, immune dysregulation, and neurotransmitter imbalances. The identified pathways provide potential targets for therapeutic intervention, emphasizing the role of precision medicine in the management of bipolar disorder.
Key words: Bipolar disorder, GWAS, Bioinformatics, Genetic loci, Molecular mechanisms
J. Timmapuram, G. Baby Shalini, T. Poojasree et al.· Journal of environmental bio...· 0 citations
Adolescent externalizing behavior is a major risk factor for later substance use and other psychiatric outcomes. Understanding its genetic architecture and its relationship with brain imaging phenotypes requires scalable genome-wide methods applied to youth cohorts. Using data from the Adolescent Brain Cognitive Development (ABCD) Study, we implemented a pipeline for genome-wide association studies (GWAS) of longitudinally measured externalizing traits and multimodal neuroimaging-derived phenotypes (IDPs). We performed quality-controlled genotype processing and constructed harmonized phenotype and covariate datasets. GWAS analyses were conducted using REGENIE in a two-step framework, with Step 1 ridge regression models trained on LD-pruned variants and Step 2 association testing performed genome-wide. Externalizing traits measured at baseline and summarized as longitudinal means and slopes, together with approximately 200 IDPs measured at baseline and summarized as longitudinal means and slopes, were analyzed. We further constructed a custom linkage disequilibrium (LD) reference panel using unrelated individuals and computed LD scores using LDSC. Genetic correlations between externalizing traits and imaging phenotypes were estimated using LD Score Regression. This exploratory study systematically evaluated genome-wide genetic correlations between regional cortical morphology and externalizing phenotypes in adolescence. Although several associations reached nominal significance, none remained significant after correction for multiple comparisons. These findings should not be interpreted as demonstrating an absence of shared genetic architecture. Rather, the precision of the estimates was constrained by the available imaging GWAS sample size, uncertainty in SNP-heritability estimates, and the large number of regional comparisons. Larger imaging-genetics samples and independent replication will be required to determine whether modest or regionally specific genetic correlations exist.
Externalizing has been associated with differences in brain structure and function; however, it remains unclear whether these associations reflect shared common-variant genetic influences. Cross-trait linkage disequilibrium score regression was used to estimate genome-wide genetic correlations between externalizing GWAS results and 3,935 brain imaging-derived phenotypes from the UK Biobank BIG40 resource. Imaging phenotypes covered structural MRI, diffusion MRI, susceptibility-weighted imaging, resting-state functional MRI, and task functional MRI. Analyses were included in the primary dataset when the imaging phenotype had positive SNP heritability, a heritability Z statistic of at least 1.96, a mean GWAS chi-square statistic of at least 1.02, at least 200,000 regression SNPs, and a complete LDSC result without a fatal error. Technical imaging quality-control phenotypes were excluded from biological inference. Individual results were corrected using the Benjamini-Hochberg false discovery rate procedure. Aggregated Cauchy association tests were used to evaluate evidence across all imaging phenotypes and within predefined imaging categories. Power, simultaneous confidence bounds, and alternative quality-control definitions were examined in sensitivity analyses. Of 3,935 imaging phenotypes, 3,716 produced estimable genetic correlations, 2,980 met the primary LDSC quality-control criteria, and 2,967 were biological imaging phenotypes. No individual phenotype survived false discovery rate correction; the smallest unadjusted P value was 0.0005, and the minimum adjusted q value was 0.486. The distribution of genetic correlations was centered near zero, with a median genetic correlation of 0.0014 and a median absolute correlation of 0.0338. There was no aggregate evidence across all biological imaging phenotypes using ACAT (P = 0.302), and no predefined imaging category survived correction. The median minimum detectable genetic correlation at 80% power was 0.216. Bonferroni-adjusted simultaneous confidence intervals were contained within [-0.30, 0.30] for 80.0% of phenotypes in the primary analysis and 88.0% under stringent heritability quality control. Broad and stringent sensitivity analyses produced the same overall conclusions. In this study, no statistically robust evidence of global genetic correlations between externalizing and individual UK Biobank brain imaging phenotypes was found. Small, localized, mixed-direction, or developmentally specific genetic effects remain possible.
AIM
To identify early molecular diagnostic biomarkers for optic atrophy (OPA) and explore potential mechanisms mediated by proteins.
METHODS
Gene expression data was sourced from eQTLGen (31 684 samples; 19 960 genes). The OPA discovery cohort came from FinnGen (629 cases; 496 621 controls); the validation cohort came from the genome-wide association studies (GWAS) catalog (58 cases; 496 621 controls). Protein data for mediation analysis was obtained from the deCODE Genetics consortium (35 559 samples; 4907 proteins). Causal estimates were derived using two-sample Mendelian randomization (MR). Inverse-variance weighted (IVW) was the primary analysis method. Sensitivity analyses included MR-Egger intercept, Cochran's Q test for heterogeneity, and leave-one-out analysis. Colocalization analysis validated identified genes. Additionally, interaction analysis identified potential biomarkers. Finally, mediation analysis assessed potential mediating mechanisms.
RESULTS
Multi-cohort validation revealed that increased expression levels of the SEC61A2 and THNSL2 were causally associated with an elevated risk of OPA. Furthermore, we identified 386 genes potentially associated with OPA. Hormone secretion and immune-related pathways were found to play significant roles in OPA pathogenesis. Mediation analysis indicated that Upper zone of growth plate and cartilage matrix associated (UCMA) potentially mediates the effect of SEC61A2 in increasing OPA risk.
CONCLUSION
SEC61A2 and THNSL2 may serve as early diagnostic biomarkers for OPA. Additionally, SEC61A2 likely increases OPA risk through UCMA.
Jun-Zhao Yang, Yan-Ting Liu, Xinsen Liu et al.· International Journal of Oph...· 0 citations
Genetic evidence supporting a causal role for depression in the etiology of late-onset AD is provided, a link not observed for other major psychiatric disorders tested and highlighted the specific importance of managing depression as a potential strategy for mitigating AD risk.