Genetically informed dissection of multimodal brain aging and ten major psychiatric disorders.

Mapping genetic convergence across brain structure, mental health, and cardiometabolic disease

It is found that schizophrenia and ADHD show distinct genetic patterns: schizophrenia shares more genetic factors with brain structure and diabetes, while ADHD is more strongly linked to metabolic pathways.

Developmental and cellular vulnerabilities underlie genetic architecture of schizophrenia.

Joint analysis of GWAS and blood and brain QTL summary statistics reveals potential therapeutic targets for neuropsychiatric disorders

Neurological and psychiatric disorders (NPDs) impose a substantial global burden. Many genetic associations have been reported for a range of NPDs, but the specific genes and proteins underlying susceptibility and their tissue- and cell type-specific manifestations remain poorly understood, hindering the development of targeted therapies. We integrated large-scale genome-wide association study (GWAS) summary statistics for 11 common NPDs with tissue- and cell type-specific multi-omics data from blood and brain using a Bayesian-based multi-omics Mendelian randomisation (MR) framework. We further performed pathway enrichment analyses to delineate functional pathways underlying these candidate signatures and used Connectivity Map (CMap) and ExPheWAS to prioritise therapeutic compounds mapping to NPD‑specific gene–protein signatures while systematically screening for potential off‑target side effects. We identified 26 and 60 significant gene–protein associations (posterior probability ≥ 0.7) across nine NPDs in blood and brain, respectively. Among these, 11 associations were resolved to specific brain-based cell types. Notably, we identified three previously unreported brain-specific gene–protein signatures, which to the best of our knowledge, with no prior evidence from GWAS, gene-based association studies or MR findings for the respective disorders: TRMT61B (associated with major depressive disorder [MDD] and Parkinson’s disease [PD] in bulk brain), EEFSEC (associated with schizophrenia [SCZ] in bulk brain and excitatory neurons), and SLC25A24 (associated with SCZ in bulk brain and at single-cell resolution across astrocytes, excitatory neurons, oligodendrocytes and oligodendrocyte progenitor cells). The association with TRMT61B implicates mitoribosome remodelling and mitochondrial translation in susceptibility to MDD and PD, whereas findings for EEFSEC and SLC25A24 suggest roles for serotonergic signalling dysregulation and disrupted mitochondrial homeostasis/calcium-sensitive signalling, respectively, in the pathophysiology of SCZ. We additionally delineated novel cell type-specific signals for established NPD-related signatures, including TRAF3 (associated with Alzheimer’s disease and multiple sclerosis in excitatory neurons) and SCFD1 (associated with amyotrophic lateral sclerosis in excitatory and inhibitory neurons). Our analyses also identified bortezomib as a potential candidate for drug re-purposing in SCZ. By resolving gene–protein associations at tissue and cell‑type resolution, our study provides new insights into the biological basis of risk for multiple NPDs. These insights provide a framework for advancing mechanistic understanding and therapeutic development, including opportunities for drug re-purposing for NPDs.

A genome-wide cross-trait analysis characterises the shared genetic architecture between rheumatoid arthritis and psychiatric disorders.

OBJECTIVES Patients with rheumatoid arthritis (RA) have a 2- to 3-fold elevated risk of psychiatric disorders, suggesting an underlying genetic link between these phenotypes. However, the shared genetic architectures and pathological mechanisms driving RA-psychiatric disorder comorbidity remain to be fully elucidated. Herein, we performed cross-trait analysis to investigate the shared genetic architecture between RA and psychiatric disorders. METHODS Leveraging European-ancestry genome-wide association studies (GWASs) datasets of RA (N = 1,026,690) and ten major psychiatric disorders (N = 14,307 to 1,222,882), we performed cross-trait pleiotropic analysis to identify the shared pleiotropic loci and genes between RA and psychiatric disorders, followed by functional annotation and Mendelian randomization analysis to explore the pathological mechanisms underlying RA-psychiatric disorder comorbidity. RESULTS Our analysis revealed significant positive genetic correlations between RA and seven psychiatric disorders, such as major depressive disorder. From these correlations, we identified 61 pleiotropic loci jointly influencing RA and psychiatric disorder risk, along with 208 pleiotropic genes predominantly involved in immune and inflammatory response biological processes. Druggable target exploration identified 21 drug-gene interactions involving pleiotropic genes, with two genes (RHOA and TRAF3) classified as clinically actionable category, representing potential therapeutic target for both RA and psychiatric disorders. Mendelian randomization further demonstrated a bidirectional causal relationship between RA and SCZ, while supporting the causal roles of ADHD, MDD, and PTSD in increasing RA risk. CONCLUSIONS Our findings elucidate the shared genetic architecture between RA and psychiatric disorders, providing novel insights into the pathological mechanisms underlying their comorbidity and laying groundwork for improved comorbidity management.

Distributed Genetic Effects on Human Brain Structure Emerge Across Multiple Spatial Scales

The findings suggest that genetic influences on brain morphology are expressed across multiple spatial scales, with consequences that may help to guide the design of deep learning methods to discover genomic loci associated with brain structure and brain diseases.

Shared genetic architecture between brain iron deposition and Alzheimer's disease

Brain iron accumulation is well established in Alzheimer's disease (AD), but whether the two share a genetic basis remains unclear. Here, we performed genome-wide association analyses of brain iron across six iron-rich brain regions, quantified via quantitative susceptibility mapping (QSM) in 38,142 UK Biobank participants. Genetic pleiotropic overlap, genetic correlation and genomic structural equation modelling were used to identify shared genetic architecture between brain iron and risk of AD, and bidirectional Mendelian randomisation was used to test for causal relationships. We identified 116 independent genome-wide significant loci associated with brain iron (r2<0.1; p <5 x 10-8) and validated these signals in an independent cohort using polygenic scores, which explained between 8.9% and 25.4% of variance in regional iron. Genetic pleiotropy and correlation analyses revealed that brain iron and AD share a polygenic basis extending well beyond the canonical APOE locus. This shared liability is specific to basal ganglia structures relevant to cognition, specifically, iron deposition across the caudate nucleus, putamen, and globus pallidus loaded onto a single latent factor that correlated significantly with AD (rg = 0.13, P = 0.019). Multivariate genome-wide association analysis of the shared liability factor between AD and brain iron revealed 27 independent genome-wide significant loci implicating genes that modulate neuroimmune function. Mendelian randomisation provided no evidence of a causal effect in either direction. In summary, we identified region-specific shared genetic liability between brain iron and AD, and a putative neuroimmune mechanism underlying it.