Systematic genomic Mendelian randomization profiling of early molecular markers of optic atrophy.

Integrative genomic and proteomic analyses identify candidate genetic loci and genetically supported proteins in age-related macular degeneration

Age-related macular degeneration (AMD) is a leading cause of visual impairment; however, robust drug targets for primary prevention remain elusive. This study aimed to identify candidate genetic loci and putative genetically supported proteins for AMD through integrative genomics and proteomics. A genome-wide association study (GWAS) meta-analysis (28,543 cases and 1,072,092 controls) was performed to identify risk loci, followed by proteome-wide Mendelian randomization (MR), colocalization, and multi-omics summary-data-based MR with heterogeneity in dependent instruments (SMR-HEIDI) analyses to infer genetically supported proteins. Functional characterization included gene enrichment, single-cell RNA sequencing, mediation across 731 immunophenotypes, and a mouse knockout assessment. Druggability was evaluated using the Drug–Gene Interaction Database. The GWAS meta-analysis identified 10 candidate genetic loci for AMD (including three previously reported and seven newly identified loci). Proteome-wide MR and colocalization analyses uncovered 23 genetically supported plasma proteins (11 risk and 12 protective factors). Multi-omics SMR-HEIDI analysis prioritized LAMC2 and PLTP as first-tier risk genes, which was consistently supported across protein, expression, and methylation levels. Single-cell RNA sequencing revealed cell-type-specific enrichment of key genes in monocytes and stromal/progenitor-like cells within AMD retinas, and subsequent mediation analysis identified specific immune traits, most notably regulatory T-cell subsets, as potential partial mediators of AMD risk. Druggability assessment identified 15 target genes, and bioinformatic enrichment nominated cyclophosphamide. Given the toxicity profile of cyclophosphamide, this computational finding serves strictly as a pathway indicator, reinforcing the broader therapeutic relevance of modulating the identified immune-related targets. Our integrative analyses identified candidate genetic loci and genetically supported proteins for AMD, providing a foundation for translating genomic findings toward primary prevention. The exploratory nature of this study highlights the need to experimentally validate the proposed targets and underlying mechanisms.

Mendelian Randomization and Transcriptome Analysis Identify Ischemic Stroke Biomarkers With Putative Relevance to Cerebrospinal Fluid

Background Circulating proteins have been associated with the pathogenesis of ischemic stroke (IS), yet its biomarkers remain underutilized. Using plasma protein GWAS data with putative relevance to CSF, this study integrated mendelian randomization (MR) and transcriptomics to identify potential IS biomarkers. Methods A two‐sample MR analysis was undertaken to determine the genetic association between circulating protein levels and IS. The identification of differentially expressed genes (DEGs) in the GSE268634 and GSE262257 datasets was carried out via the transcriptomic analysis. Candidate biomarkers overlapping MR‐derived genes (MRGs) and DEGs underwent functional enrichment, protein‐protein interaction (PPI), and machine learning (LASSO/SVM‐RFE) screening. Biomarker mechanisms were assessed via gene set enrichment analysis (GSEA), immune infiltration, and hypothesis‐generating drug prediction. The validation included RT‐qPCR and immunohistochemistry in MCAO/R rats. Results The MR analysis identified 157 circulating protein‐related MRGs with suggestive genetic associations with IS. Transcriptomics identified 4144 DEGs, and 46 overlapping with MRGs. Functional enrichment highlighted their roles in cell adhesion and immune responses. Machine learning identified six candidate biomarkers, among which CDH7, MGAT4C, and ITPKC exhibited both high diagnostic accuracy (AUC > 0.7) and consistently differential expression, and were therefore prioritized as putative biomarkers. GSEA revealed that CDH7 and MGAT4C were positively correlated, whereas ITPKC was negatively correlated with the calcium signaling pathway. Immune infiltration analysis showed that CDH7 and MGAT4C were negative, whereas ITPKC was positively correlated with immune cells. Computationally predicted drugs including genistein and pioglitazone may alleviate IS damage, though this requires experimental confirmation. RT‐qPCR and immunohistochemistry indicated markedly high CDH7 and MGAT4C expression, whereas low ITPKC expression was in MCAO/R rats. Conclusion CDH7, MGAT4C, and ITPKC are genetically associated and transcriptionally altered candidates derived from circulating protein‐related analyses for IS, warranting further investigation.

Analysis of genetic insights and molecular pathways in age-related macular degeneration: A functional enrichment

Aim: Age-related macular degeneration (AMD) is a leading cause of vision loss in older adults, with genetic factors strongly influencing onset and progression. This study aimed to analyse GWAS data to identify AMD-associated genetic variants and explore their biological and regulatory significance. Methodology: Publicly available GWAS datasets were analysed using Gene Ontology (GO), KEGG, and Reactome databases to identify functional pathways. MicroRNA enrichment analysis assessed regulatory control, whilst MetaboAnalyst linked genetic variation to metabolic alterations. Unsupervised machine learning approaches, including principal component analysis (PCA), K-means, and hierarchical clustering, identified biological patterns among single nucleotide polymorphisms (SNPs). Results: Strong associations were observed at known susceptibility loci, particularly CFH, with additional genes including INHBB, GLI2, and TYR implicated in immune regulation and retinal development. Enrichment analyses highlighted complement activation, lipid metabolism, and oxidative stress as key biological processes. MicroRNA analysis revealed regulators influencing inflammatory and immune pathways, whilst clustering identified three distinct SNP groups supported by hierarchical patterns. Interpretation: By integrating genetic, functional and regulatory data, this study advances molecular understanding of AMD, identifying complement dysregulation, immune dysfunction, and metabolic imbalance as central contributors, alongside novel candidate biomarkers and therapeutic targets with potential implications for precision medicine in AMD management. Key words: Age-related macular degeneration, Functional enrichment, Genome wide association study, Genetic variants, Molecular pathways

Brain imaging-derived phenotypes influence risk of bipolar disorder: comprehensive exposome-wide association and wide-angled genetic analyses

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.

Immune-Related Mendelian Randomization Signals for Anxiety Disorders Highlight the CD40 Locus on Chromosome 20 (chr20:46118–46130 Mb, GRCh38)

Background/Objectives: Although genetic studies have linked immune phenotypes with anxiety, broad Mendelian randomization (MR) screens require explicit multiple-testing control. We reappraised 1753 reported immune-cell-trait-to-anxiety inverse-variance-weighted (IVW) association records available in the analysis tables and assessed the chromosome 20 signal that includes CD40. Methods: The reported records were derived from the 731-trait Sardinian flow-cytometry GWAS of Orrù et al. and were evaluated across one UK Biobank and three FinnGen anxiety phenotypes; outcome-specific Benjamini–Hochberg false-discovery-rate (FDR) correction was applied to the available analysis table. The leading locus was examined using bulk and single-cell expression quantitative trait locus annotations, two-sample MR, summary-data-based MR (SMR), HEIDI tests, and regional colocalization results. Results: Of 1753 tests, 120 were nominally significant, and 21 were retained after outcome-specific FDR correction (14 for UK Biobank anxiety and 7 for FinnGen all anxiety; none for generalized or phobic anxiety). B-cell and regulatory/CD4 T-cell traits were common among retained associations, and several B-cell traits mapped to variants at the CD40 locus. For FinnGen all anxiety disorders, monocyte instruments gave a positive estimate (beta = 0.00418, p = 9.25 × 10−4), whereas three naïve B-cell instruments gave a negative estimate (beta = −0.0520, p = 2.64 × 10−4). Monocyte SMR was null (p = 0.542). Naïve B-cell SMR was nominally significant (p = 0.00537), but HEIDI could not be calculated. Regional colocalization was weak in both cell contexts (PP.H4 = 0.0205 and 0.00272). Conclusions: The post-selection locus follow-up prioritizes a chromosome 20 immune locus but does not establish CD40-mediated regulation of anxiety. Because the upstream screen was not regenerated from source GWAS files and complete per-instrument F-statistics were unavailable, all findings are exploratory. CD40 remains a testable candidate for ancestry-matched fine-mapping and cell-state-specific validation.

Using human proteomic and lipidomic to exploration drug target of bladder cancer