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PubMed2026

Multi-omics identification of therapeutic targets of compound sappan decoction in hepatocellular carcinoma.

BACKGROUND: Compound sappan decoction (CSD) is a multi-herbal traditional Chinese medicine formulation with clinical relevance in hepatocellular carcinoma (HCC). However, its therapeutic mechanisms remain unclear. METHODS: Bioactive compounds of CSD were identified and standardized using pharmacological and chemical databases. Potential targets were predicted via multiple target inference platforms. HCC-related genes were curated from comprehensive disease databases. Summary-data-based Mendelian randomization (SMR) was conducted to infer causal relationships between compound targets and HCC risk using large-scale quantitative trait loci (QTL) datasets and HCC genome-wide association study data. Colocalization analysis, protein-protein interaction (PPI) network construction, and GO/KEGG enrichment were performed on SMR-identified targets. Molecular docking evaluated binding affinities of representative compounds to prioritized targets. RESULTS: A total of 784 overlapping genes between predicted CSD targets and HCC-related genes were subjected to SMR analysis. Among these, 22 targets were significantly associated with HCC risk based on transcriptomic or proteomic QTLs and showed colocalization evidence. Notably, four targets (ADRB2, APOE, SYK, and PGF) were supported by both replication in an independent cohort and strong colocalization. These 22 targets were enriched in apoptosis, PI3K-Akt signaling, redox metabolism, and detoxification pathways. PPI analysis revealed central hubs including MMP9, BCL2, CASP1, and MCL1. Molecular docking demonstrated strong binding of APOE to quercetin, PGF to luteolin-7-olate, and SYK to kaempferol. CONCLUSIONS: CSD may exert therapeutic effects on HCC through modulation of genetically validated targets involved in tumor progression, inflammation, and metabolic reprogramming, supporting its potential clinical utility as an adjunctive treatment strategy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s12672-026-04740-8.

Caesalpinia↗

PubMed2026

Large-Scale Proteomic Profiling of Incident Heart Failure and Its Subtypes in Older Adults.

BACKGROUND: Heart failure (HF) and its main subtypes, heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF), impose an enormous health burden on elders. Assessment of the circulating proteome to illuminate pathogenesis could open new opportunities for treatment. METHODS: We conducted a plasma proteomics screen of incident HF and its subtypes in 2 older population-based cohorts, the CHS (Cardiovascular Health Study) and the AGES-RS (Aging, Gene/Environment Susceptibility-Reykjavik Study). The 2 studies used SomaLogic platforms, with 4404 aptamers in common. Multivariable Cox models were fit to evaluate individual-protein associations with HF, HFpEF, and HFrEF separately in each cohort, and study-specific associations were combined by fixed-effects meta-analysis. Replication was performed in the ARIC (Atherosclerosis Risk in Communities) cohort. Two-sample Mendelian randomization of HF and its subtypes, along with colocalization analysis, was performed to support causal inference. RESULTS: Among 8599 participants, 1590 experienced incident HF (536 HFpEF, 471 HFrEF). There were 119 proteins associated with HF, 15 proteins with HFpEF, and 11 proteins with HFrEF, at Bonferroni-corrected significance. Among these, 9 have never previously been identified for cardiovascular diseases, and another 61 represent new associations with incident HF or its subtypes. Of these 70 proteins, 55 of the 66 available replicated externally. Mendelian randomization analysis revealed 7 proteins genetically associated with HF at nominal significance; 2 were separately associated with HFpEF, and another 2 with HFrEF. Seven of these 9 proteins (NPDC1 [neural proliferation differentiation and control protein 1], APOF [apolipoprotein F], LMAN2 [lectin, mannose-binding 2], ADIPOQ [adiponectin], CD14 [cluster of differentiation 14], ARHGAP1 [Rho GTPase-activating protein 1], C9 [complement 9]) showed new, possibly causal associations, although we did not detect evidence for colocalization. CONCLUSIONS: In this large-scale proteomic study involving 3 longitudinal cohorts of older adults, we identified and replicated 55 novel protein markers of HF or its subtypes, and 7 new, possibly causal proteins. These proteins may enhance risk prediction, improve understanding of pathobiology, and help prioritize targets for therapeutic development of these foremost disorders in elders.

Humans↗

PubMed2026

Integrative multi-omics quantitative trait loci prioritize CASP7 as a candidate protective gene for cataract.

Cataracts are the leading cause of vision loss worldwide. Despite surgery being the only effective treatment, its economic burden highlights the necessity of exploring the pathogenesis of cataracts. In this study, we analyzed 4 large-scale GWAS (genome-wide association study) datasets for cataracts and performed SMR analysis along with heterogeneity in dependent instruments (HEIDI) testing to explore the effects of methylation, expression, and protein QTLs on cataracts. We further validated shared genetic variants through COLOC analysis. Additionally, we searched datasets related to cataracts from the Gene Expression Omnibus (GEO) database for differentially expressed genes (DEGs) and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses. By integrating summary-based Mendelian randomization (SMR) results with bioinformatics findings, CASP7 showed a consistent protective-direction association with cataract risk (mQTL: OR [95% CI] = 0.959 [0.941-0.977], FDR-adjusted P = .039; eQTL: OR [95% CI] = 0.897 [0.860-0.937], FDR-adjusted P = .0046; pQTL: OR [95% CI] = 0.597 [0.483-0.738], FDR-adjusted P = .00083). GEO-based analyses provided transcriptomic support for CASP7 involvement in cataract-related lens biology. These findings prioritize CASP7 as a genetically supported candidate protective gene associated with cataract risk. Because this study is based on public summary-level and transcriptomic datasets, the results should be interpreted cautiously and require functional validation in human lens-relevant systems.

Quantitative Trait Loci↗

PubMed2025

Soluble Immune Checkpoint Protein and Lipid Network Associations with All-Cause Mortality Risk: Trans-Omics for Precision Medicine (TOPMed) Program.

Adverse cardiovascular events are emerging with the use of immune checkpoint therapies in oncology. Using datasets in the Trans-Omics for Precision Medicine program (Multi-Ethnic Study of Atherosclerosis, Jackson Heart Study [JHS], and Framingham Heart Study), we examined the association of immune checkpoint plasma proteins with each other, their associated protein network with high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C), and the association of HDL-C- and LDL-C-associated protein networks with all-cause mortality risk. Plasma levels of LAG3 and HAVCR2 showed statistically significant associations with mortality risk. Colocalization analysis using genome wide-association studies of HDL-C or LDL-C and protein quantitative trait loci from JHS and the Atherosclerosis Risk in Communities identified TFF3 rs60467699 and CD36 rs3211938 variants as significantly colocalized with HDL-C; in contrast, none colocalized with LDL-C. The measurement of plasma LAG3, HAVCR2, and associated proteins plus targeted genotyping may identify patients at increased mortality risk.

Journal Article↗

PubMed2026

Cell-type-specific genetic associations in Lewy body dementia identified using single-cell eQTL-based Mendelian randomization.

BACKGROUND: Lewy body dementia (LBD) is a complex neurodegenerative disorder marked by α-synuclein aggregation and dual impairment of cognitive and motor function.While genome-wide association studies have identified risk loci, the cellular mechanisms linking genetic variation to disease susceptibility remain largely unexplored. METHODS: We performed single-cell transcriptome-wide Mendelian randomization using brain cell-type-specific eQTLs across eight major cell types. Genetic associations were evaluated using inverse-variance weighted models, followed by Bayesian colocalization analysis. Replication was performed in independent stratified LBD cohorts based on APOE ε4 carrier status. Phenome-wide association analysis was included as a supplementary, descriptive assessment of cross-trait associations. RESULTS: Expression of ANKRD65 in excitatory neurons was significantly associated with reduced LBD risk (odds ratio = 0.65, 95 % CI: 0.52-0.81, p = 0.00013). This association passed a false discovery rate of 0.1 and showed strong evidence of colocalization (posterior probability = 0.93). Effect direction was consistent across APOE ε4+ and ε4- LBD subgroups in independent cohorts. No genome-wide significant associations were observed with non-neurological traits in the phenome-wide analysis. CONCLUSIONS: Our findings identify a genetically supported, cell-type-resolved association between ANKRD65 expression in excitatory neurons and LBD risk. This study demonstrates the value of integrating cell-resolved transcriptomic regulation with genetic inference to pinpoint functionally relevant targets in neurodegenerative diseases.

Humans↗

PubMed2025

Exploring the shared genetic basis of attention-deficit/hyperactivity disorder and obstructive sleep apnea: A multi-omics analysis.

BACKGROUND: Observational studies have suggested an association between attention-deficit/hyperactivity disorder (ADHD) and obstructive sleep apnea (OSA), but these findings are often inconsistent due to potential biases from medication use, and varying diagnostic criteria. Genetic analyses can help mitigate these confounding factors, providing additional evidence. METHODS: This study evaluated the genetic correlations between ADHD and OSA using Genome-wide association study (GWAS) summary data, applying linkage disequilibrium score regression (LDSC) and SUPER GeNetic cOVariance Analyzer (SUPERGNOVA). Cross-trait association and colocalization analysis identify potential pleiotropic loci. Tissue enrichment analysis and gene-level analysis of shared genes between OSA and ADHD was conducted. Additionally, bidirectional Mendelian randomization was used to assess potential causal relationships. RESULTS: We found significant genetic correlations between ADHD and OSA (rg = 0.309, p = 3.252E-27), and identified 8 novel pleiotropic loci through cross-trait association analysis. Tissue enrichment analysis showed that these shared genes were primarily concentrated in brain tissues, particularly in deep gray matter regions, and were associated with immune and inflammatory pathways. Forward Mendelian Randomization analysis showed that ADHD was significantly associated with the risk of OSA (OR 1.070, 95 % CI 1.013-1.130, p = 0.016), and reverse analysis showed that OSA was significantly associated with the risk of ADHD (OR 1.240, 95 % CI 1.106-1.390, p = 2.213E-4). CONCLUSION: The findings of this study show a significant positive genetic correlation between ADHD and OSA and each is a risk factor for the other. Inflammation in specific brain regions may be the underlying mechanism for their comorbidity.

Humans↗

PubMed2026

Linking cortical structure and delirium in the elderly: insights from cohort study and shared genetic risk analysis.

BACKGROUND: This study aimed to assess the association between regional cortical changes measured via baseline magnetic resonance imaging (MRI) and the incidence of delirium. METHODS: Observational associations were assessed using a prospective cohort from the UK Biobank and an independent clinical cohort. The population-based study included participants aged 60 years or older who had undergone structural brain MRI since 2014. Regional cortical volume, mean thickness, and surface area were extracted based on the Desikan-Killiany cortical atlas. Delirium was defined using ICD-10 diagnostic codes. Additionally, preoperative brain MRI images from participants in another cohort were collected and automatically segmented using deep learning algorithms to obtain cortical measurements. Logistic analysis was performed to investigate the associations between cerebral cortical structure and delirium risk. Lastly, genome-wide association study data derived from the ENIGMA Consortium and FinnGen Biobank were utilized to conduct conditional/conjunctional false discovery rate (cond/conjFDR) analyses to identify shared genetic loci associated with cortical structures and delirium. RESULTS: This observational analysis included 31,890 participants from the UK Biobank and 152 participants from an independent cohort. In the UK Biobank cohort, decreased cortical thickness in the 17 regions was associated with a significantly increased risk of delirium. Similarly, a preoperative reduction in cortical volume in 7 regions was associated with an increased risk of delirium in the independent cohort. Besides, 100 single-nucleotide polymorphisms (SNPs) were identified as significantly associated with cortical structures when conditioned on delirium. Finally, colocalization analysis demonstrated that these pleiotropic risk loci modulated the expression of NT5C2, RGP1, CCDC25, TPM2, EEF1AKMT2, IQANK1 and LHPP in blood and brain tissues. CONCLUSION: Regional cortical atrophy is associated with an increased risk of delirium in the elderly. Brain MRI examinations may be beneficial for preoperative delirium risk assessment in elderly individuals undergoing elective surgery.

Humans↗

PubMed2026

Genetic evidence that advanced COVID-19 accelerates longitudinal brain atrophy: A Mendelian randomization study.

Coronavirus disease 2019 (COVID-19) was reported to persist long-term in the brain and leave several long-term neurologic sequelae. However, the causal relationship between COVID-19 and brain aging is still unknown. The genome-wide association study (GWAS) data on COVID-19 phenotypes (susceptibility, hospitalization, and severity), involving a total of 5,779,391 participants, were collected from the COVID-19 Host Genetics Initiative. In addition, GWAS data on longitudinal changes in 15 brain structures, assessed via magnetic resonance imaging across the lifespan, were sourced from the ENIGMA Consortium and involved 15,640 participants. Two-sample Mendelian randomization was conducted to infer the causal relationship between COVID-19 and longitudinal brain changes. Multi-trait GWAS meta-analysis, colocalization, and fine-mapping analyses were performed to identify shared genetic etiologies. H3K27me3 ChIP-seq was used to evaluate the regulatory effect of colocalized loci. Two-step Mendelian randomization was applied to explore potential mediating mechanisms across multi-omics layers, including proteomics, metabolomics, and immunomics. Our results showed that COVID-19 hospitalization (β = -262.405, P = .041) and severity (β = -177.676, P = .049) were genetically associated with atrophied volume of total brain during longitudinal change. This suggests that individuals with advanced COVID-19 may be more susceptible to accelerated global brain aging. Caudate was genetically affected by all COVID-19 phenotypes. Seven variants were shared between advanced COVID-19 and global brain aging. rs117169628 was colocalized between advanced COVID-19 and global brain aging, and exerted an inhibitory effect on CDH15 expression, further strengthening the causality. Six metabolites, 1 protein, and 1 immune trait were identified as potential mediators. Our study indicates that advanced COVID-19 might be genetically associated with accelerated brain aging. Brain health should be paid more attention in long COVID-19.

Humans↗

PubMed2026

Colocalization and functional analyses identify GBE1 as a gene linking muscle strength and cardiometabolic fitness.

Handgrip strength is a proxy for muscular fitness, an indicator for general health status, and is associated with cardiometabolic health. The mechanisms connecting handgrip strength to skeletal muscle function are incompletely understood. We applied integrated linkage-disequilibrium-adjusted colocalization analysis of genome-wide association study summary statistics for handgrip strength, combined with expression and splicing quantitative trait loci from skeletal muscle, and identified glycogen branching enzyme 1 (GBE1) as a candidate gene for handgrip strength. CRISPR-interference knockdown of GBE1 in immortalized human skeletal muscle cells (HMCL-7304) demonstrated decreased glycogen content and accumulation of polyglucosan bodies. Knockdown of GBE1 led to increased oxygen consumption rate, oxidative stress, and changes in mitochondrial morphology. Transcriptomic profiling of GBE1 knockdown cells identified upregulation of the human superoxide dismutase 2 and enrichment of pathways related to muscle contraction and oxidative stress responses. These functional genomic analyses prioritize GBE1 as a muscle-relevant candidate gene for handgrip strength and provide mechanistic insights to muscle fitness.NEW & NOTEWORTHY Colocalization of genome-wide association study (GWAS) loci with quantitative trait loci (QTL) in skeletal muscle tissue identified GBE1 as a candidate for handgrip strength. Cellular phenotypes with GBE1 knockdown in immortalized human skeletal muscle cells include decreased glycogen content, accumulation of polyglucosan bodies, changes in mitochondrial function and morphology, and increased expression of reactive oxygen species (ROS) scavengers. Transcriptomic changes suggest a role for GBE1 in muscle contraction and oxidative stress-mediated responses.

Humans↗

PubMed2021

Genetic Relationship Between Endometriosis and Melanoma.

Epidemiological studies have observed that risk of endometriosis is associated with history of cutaneous melanoma and vice versa. Evidence for shared biological mechanisms between the two traits is limited. The aim of this study was to investigate the genetic correlation and causal relationship between endometriosis and melanoma. Summary statistics from genome-wide association meta-analyses (GWAS) for endometriosis and melanoma were used to estimate the genetic correlation between the traits and Mendelian randomization was used to test for a causal association. When using summary statistics from separate female and male melanoma cohorts we identified a significant positive genetic correlation between melanoma in females and endometriosis (r g = 0.144, se = 0.065, p = 0.025). However, we find no evidence of a correlation between endometriosis and melanoma in males or a combined melanoma dataset. Endometriosis was not genetically correlated with skin color, red hair, childhood sunburn occasions, ease of skin tanning, or nevus count suggesting that the correlation between endometriosis and melanoma in females is unlikely to be influenced by pigmentary traits. Mendelian Randomization analyses also provided evidence for a relationship between the genetic risk of melanoma in females and endometriosis. Colocalization analysis identified 27 genomic loci jointly associated with the two diseases regions that contain different causal variants influencing each trait independently. This study provides evidence of a small genetic correlation and relationship between the genetic risk of melanoma in females and endometriosis. Genetic risk does not equate to disease occurrence and differences in the pathogenesis and age of onset of both diseases means it is unlikely that occurrence of melanoma causes endometriosis. This study instead provides evidence that having an increased genetic risk for melanoma in females is related to increased risk of endometriosis. Larger GWAS studies with increased power will be required to further investigate these associations.

endometriosis↗

PubMed2025

Shared Genetic Architecture Between Atopic Dermatitis and Autoimmune Diseases.

Atopic dermatitis (AD) and autoimmune diseases exhibit epidemiological comorbidity, yet the shared genetic architecture remains incompletely understood. We investigated the genetic overlap between AD and three autoimmune disorders including inflammatory bowel disease (IBD), rheumatoid arthritis (RA), and vitiligo, leveraging genome-wide association data. Despite modest evidence for global genetic correlations, we found 113 independent pleiotropic loci shared among AD and autoimmune diseases, with 11 displaying a concordant effect across all 3 pairwise comparisons. Gene-set and tissue enrichment analyses evidenced the inflammatory background of pleiotropic associations. Multi-trait colocalization analysis prioritized 22 loci, linking the tissue-specific expression of DOK2, GPR132, RERE, RERE-AS1, SUOX, TNFRSF11A, and TRAF1 pleiotropic genes with AD risk. Mendelian randomization revealed no causal effect of genetic liability to AD on autoimmune diseases. Nevertheless, genetic liability to IBD increased AD risk, while vitiligo exhibited a protective effect post outlier correction. Our findings provide mechanistic insights into the multimorbidity of atopic dermatitis (AD) and autoimmune diseases, offering additional evidence for the pleiotropic genetic architecture of AD that contributes to systemic immune dysregulation across multiple organ systems.

Humans↗

PubMed2025

Genome-wide association study meta-analysis provides insights into the etiology of heart failure and its subtypes.

Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.9 million individuals. A total of 153,174 individuals had HF, of whom 44,012 had a nonischemic etiology (ni-HF). A subset of patients with ni-HF were stratified based on left ventricular systolic function, where data were available, identifying 5,406 individuals with reduced ejection fraction and 3,841 with preserved ejection fraction. We identify 66 genetic loci associated with HF and its subtypes, 37 of which have not previously been reported. Using functionally informed gene prioritization methods, we predict effector genes for each identified locus, and map these to etiologic disease clusters through phenome-wide association analysis, network analysis and colocalization. Through heritability enrichment analysis, we highlight the role of extracardiac tissues in disease etiology. We then examine the differential associations of upstream risk factors with HF subtypes using Mendelian randomization. These findings extend our understanding of the mechanisms underlying HF etiology and may inform future approaches to prevention and treatment.

Humans↗

PubMed2026

Identifying potential drug targets for physical and cognitive frailty: an integrative analysis of CHARLS cohort, mendelian randomization, and gene colocalization.

With the aging of the population, frailty has become a common syndrome that severely affects the quality of life of older adults. This study aims to analyze the correlation between cognition and frailty, physical activity and frailty, and elucidate the potential pharmacological targets of cognitive frailty and physical frailty.We conducted logistic regression analyses using data from the China Health and Retirement Longitudinal Study (CHARLS) to examine the associations between total cognition and frailty, physical activity and frailty. Furthermore, summary-data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (TSMR) were employed to explore potential pharmacological targets for frailty. Genes associated with physical frailty and cognitive frailty were identified, followed by analysis via colocalization analysis, phenome-wide association studies (PheWAS), and DsigDB drug prediction. Cross-sectional analysis of CHARLs revealed that total cognition(OR 0.93, 95% CI 0.92-0.95) and middle physical activity(OR 0.95, 95% CI 0.92-0.97) were negatively correlated with frailty. SMR identified 41 drug genes associated with frailty, and subsequent TSMR validation and co-localization analysis showed that 11 candidate genes exhibited strong colocalization (PP.H4 > 0.8). GRPEL 1, PABPC 4, and WBP 2NL were ultimately identified as potential drug targets associated with physical frailty, while LANCL1, LRPPRC, FADS1, and WBP2NL were identified as potential drug targets associated with cognitive frailty. Phenome-wide association analysis(PheWAS) did not reveal any significant associations between these genes and other phenotypes at the genome-wide significance threshold. Laudanosine, 25-hydroxycholesterol, and hexadecanal emerged as the top three candidate compounds for therapeutic intervention. We identified potential drug targets for physical frailty and cognitive frailty through comprehensive analysis and elucidated drugs associated with potentially relevant genetic markers, thereby laying the foundation for a deeper understanding of the mechanisms of frailty.

Humans↗

PubMed2025

Causal relationship between white matter structural connectivity and epilepsy.

White matter structural connectivity has recently been linked to epilepsy pathogenesis, yet its causal role remains unclear. This study used Mendelian randomization (MR) to investigate the causal relationship between white matter structural connectivity and epilepsy. GWAS summary statistics for white matter structural connectivity were sourced from the UK Biobank, while epilepsy data were obtained from FinnGen R10 and the International League Against Epilepsy (ILAE). Our MR analysis revealed significant causal links between white matter structural connectivity and epilepsy risk. Increased connectivity between the right hemisphere visual and salience/ventral attention networks (RH Vis to RH Sal/VentAttn WMSC) was associated with higher epilepsy risk in FinnGen_R10_FE_STRICT (OR = 2.25, 95 % CI = 1.43-3.56, p < 0.01, FDR P = 0.019). Conversely, increased connectivity between left and right hemisphere salience/ventral attention networks (LH Sal/VentAttn to RH Sal/VentAttn WMSC) was linked to reduced epilepsy risk in FinnGen_R10_GE_STRICT (OR = 0.17, 95 % CI = 0.07-0.46, p < 0.01, FDR P = 0.033). A total of 15 nominally significant associations were identified across datasets. These findings suggest a causal relationship between white matter structural connectivity and epilepsy, offering insights into disease mechanisms and potential therapeutic targets.

Humans↗

PubMed2026

Mitochondrial dysfunction in the pathogenesis of intervertebral disc herniation: a mitochondrial related genome-wide Mendelian randomization analysis.

BACKGROUND: As a degenerative disease, the pathophysiology of intervertebral disc herniation (IDH) closely related to mitochondrial dysfunction. However, the specific molecular mechanisms involved have yet to be precisely established. METHODS: Here, we employed a two-sample, two-step Mendelian Randomization (MR) approach, along with summary-Data-Based MR, genetic colocalization, full phenomenon association analysis, and GO and KEGG enrichment analysis to investigate the genetical effects of mitochondrial dysfunction on IDH. RESULTS: From the intercross between mitochondrial-related genes and eQTLGen genes, we obtained seven genes (DMPK, EHHADH, SLC25A16, ME3, METTL17, TUFM, NDUFA13) with strong causal association with disc herniation. By SMR and genetic colocalization analysis, we further identify five key genes (EHHADH, METTL17, TUFM, NDUFA13, DMPK) as the direct causal tartgeted genes with no heterogeneity and pleiotropy in the SNPs of the genes. Full phenomenon Mendelian randomization was performed to determine possible side effects of the 5 targeting genes. Finally, we validated the expressions of key genes in the degenerative intervertebral discs tissues by qRT-PCR and double-immunofluorescence examinations, and the results were consistent with the MR analysis. CONCLUSIONS: Our study provided genetic support for the relationship between mitochondrial related genes and IDH, implicating potential therapeutic targets for future development. However, more basic experiments need to be finished to validate the role of key genes in the development of IDH.

Intervertebral Disc Displacement↗

PubMed2025

The role of the brain-bone axis in skeletal degenerative diseases and psychiatric disorders, A genome-wide pleiotropic analysis.

INTRODUCTION: Skeletal degenerative diseases and psychiatric disorders often coexist clinically. However, the genetic correlations and underlying biological mechanisms between these two types of diseases remain unclear. OBJECTIVES: To investigate the genetic correlations between skeletal degenerative diseases and psychiatric disorders and to identify shared genomic loci, genes, and pathways. METHODS: This comprehensive genome-wide pleiotropic association study utilized summary statistics from publicly available genome-wide association data. Various statistical genetic correlation methods were employed, including LDSC, HDL, PLACO, Coloc, Hyprcoloc, and Mendelian randomization (MR) analysis, along with immune cell colocalization analysis. The study aimed to identify potential shared genetic factors among three skeletal degenerative diseases (osteoarthritis, intervertebral disc degeneration, and osteoporosis) and three psychiatric disorders (schizophrenia, anxiety disorder, and major depressive disorder). RESULTS: Analyses using LDSC, HDL, and Bonferroni corrections revealed significant genetic correlations between intervertebral disc degeneration (IVDD) and anxiety disorder (ANX); fractures, IVDD, and arthritis with major depressive disorder (MDD); and arthritis with schizophrenia (SCZ). Significant genetic correlations were also observed between VDD and ANX, fractures, IVDD, hip osteoarthritis (HipOA), knee osteoarthritis (KneeOA) and MDD, and KneeOA and SCZ. Pleiotropy analysis using PLACO, MAGMA, and multitrait colocalization Hyprcoloc identified 65 pleiotropic loci, 27 shared causal loci, and 9 shared risk loci involving immune cells related to both psychiatric and bone-related diseases. Additionally, tissue-specific enrichment analysis showed that genes mapped to these loci were enriched in brain, cardiovascular, pancreatic, and other tissues. The IVW method demonstrated that MDD increased the risk of IVDD and KneeOA, while IVDD increased the risk of ANX and MDD. Conversely, SCZ was associated with a reduced risk of KneeOA. Multiple sensitivity analyses further supported a positive causal effect of IVDD on MDD. CONCLUSION: These findings suggest significant genetic correlations between skeletal degenerative diseases and psychiatric disorders, highlighting multiple shared comorbid genes and key immune cell types. Importantly, the study supports the role of the brain-bone axis in the regulation of skeletal degenerative diseases and psychiatric disorders, which could provide valuable insights for potential therapeutic targets and interventions for these conditions.

Humans↗

PubMed2026

Shared genetic architecture between major depression and intrinsic brain functional connectome organization.

BACKGROUND: Major depression (MD) is increasingly understood as a disorder characterized by widespread abnormalities in intrinsic brain functional network organization. Although both MD and brain functional connectome architecture are highly heritable, the genetic architecture underlying their relationship remains poorly characterized. METHODS: We integrated genome-wide association studies of MD with 191 ICA-based resting-state functional connectome traits to investigate their shared genetic architecture. These traits captured intrinsic connectome organization across amplitude, functional connectivity, and global connectivity domains. Cross-trait genetic analyses were used to assess pleiotropic overlap between traits. Locus-level and gene-based analyses integrating multi-omics evidence were performed to characterize the biological relevance of shared genetic signals. RESULTS: We identified significant genetic overlap between MD and 148 of 191 brain functional connectome traits. Cross-trait analyses revealed widespread shared genetic signals organized into 627 genomic loci across amplitude, functional connectivity, and global connectivity measures. Among these, 193 loci showed evidence consistent with shared causal variants based on colocalization analyses. Gene-level integration mapped these loci to 1459 protein-coding genes (390 unique genes). Multi-layer prioritization identified 17 high-confidence genes supported by convergent genomic, transcriptomic, and proteomic evidence, with enrichment in neurodevelopmental and lipid-related metabolism pathways. CONCLUSIONS: This study provides a multi-scale characterization of the shared genetic architecture between MD and intrinsic brain functional connectome organization, revealing that shared genetic signals between MD and brain functional systems are distributed across multiple functional levels and converge at the molecular level.

Connectome↗

PubMed2026

Dissecting the shared genetic architecture between migraine subtypes and cardiovascular diseases: a multi-layered genomic analysis.

BACKGROUND: Epidemiological studies have linked migraine to an increased risk of cardiovascular disease (CVD); however, the shared genetic basis and putative causal relationships between migraine subtypes and cardiovascular traits remain poorly understood. METHODS: Leveraging large-scale GWAS summary statistics for migraine phenotypes (overall migraine, migraine with aura [MA], and migraine without aura [MO]) from FinnGen R12, along with seven cardiovascular diseases from publicly available consortia, we conducted a multi-layered genetic analysis. This integrative framework encompassed genetic correlation [linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL)], cross-trait meta-analysis (CPASSOC and PLACO), Bayesian colocalization, summary-data-based Mendelian randomization (SMR) using GTEx v8 eQTL data, and bidirectional two-sample Mendelian randomization (MR). RESULTS: Significant genetic correlations were identified between migraine and multiple cardiovascular traits, with hypertension and coronary artery disease (CAD) showing the most robust associations. MA exhibited broader genetic overlap with cardiovascular diseases than MO, including a notably stronger correlation with ischemic stroke, whereas MO demonstrated a stronger correlation with hypertension. Cross-trait meta-analysis identified 160 pleiotropic loci across 17 of 21 trait pairs. Colocalization analysis confirmed 32 loci harboring shared causal variants, mapped to 13 candidate genes, of which 7 (PHACTR1, LRP1, SOX7, ABO, FHOD3, MEI1, XKR6) were further validated by SMR as exhibiting tissue-specific regulatory effects. Among these, PHACTR1 displayed the broadest pleiotropic profile across migraine phenotypes and vascular diseases. After MR-PRESSO outlier removal, bidirectional MR identified 10 MR-supported associations, two of which (genetic liability to hypertension on overall migraine, and CAD on MA) survived Bonferroni correction, all free of detectable horizontal pleiotropy. Genetic liability to hypertension was associated with increased migraine risk (OR = 1.90, 95% CI 1.25-2.90, P = 2.64 × 10⁻³), atherosclerotic diseases showed subtype-specific effects (inverse for MO, positive for MA), and, in the reverse direction, migraine was associated with increased ischemic stroke risk. CONCLUSIONS: This study provides a comprehensive and systematic characterization of the shared genetic architecture between migraine subtypes and cardiovascular diseases. By identifying pleiotropic genes and bidirectional putative causal relationships with subtype-specific patterns, our findings carry implications for the development of targeted therapeutics and subtype-specific cardiovascular risk stratification.

Humans↗