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PubMed2025

Causal association between different types of ametropia and risk of diabetic retinopathy: a two-sample Mendelian randomization study.

OBJECTIVE: To investigate the causal link between ametropia and diabetic retinopathy, as well as to offer genetic support for the association between these two conditions. METHODS: This study employed a methodology involving the utilisation of genome-wide association studies data that are publicly accessible. Specifically, single nucleotide polymorphisms (SNPs) that exhibit a strong association with ametropia were employed as instrumental variables, and a two-sample Mendelian randomization (MR) approach was employed to examine the causal relationship between different types of ametropia and diabetic retinopathy. The main findings were derived from the utilisation of inverse variance weighted (IVW), while supplementary results were obtained through the utilisation of MR Egger, weighted median, simple mode and weighted mode. Additionally, a sensitivity analysis was conducted using the 'leave-one-out' method. Cochran's Q statistics were also used to quantify the heterogeneity of SNPs. RESULTS: 38 SNPs were finally included. The results of the IVW analysis indicate that myopia may exert an inhibitory effect on the development of diabetic retinopathy (OR=0.596, 95% CI (0.371, 0.957), p<0.05). Conversely, hypermetropia (OR=8.882, 95% CI (0.389×10-3, 2.06×105), p>0.05) and astigmatism (OR=1.004, 95% CI (0.888, 1.135), p>0.05) do not exhibit a causal relationship with the risk of diabetic retinopathy. CONCLUSION: This two-sample Mendelian randomization study provides evidence that myopia may impede diabetic retinopathy occurrence, while hypermetropia and astigmatism show no significant causal effects. However, our analysis treats refractive errors as independent entities, which may not reflect their clinical interdependence. Further investigations are warranted to elucidate myopia's protective mechanisms.

Humans↗

PubMed2026

GWAS Meta-analysis Identifies Novel Associated Loci and Points to Causal Tissues in Central Serous Chorioretinopathy.

OBJECTIVE: To define CSC genetic architecture and identify implicated ocular tissues, cell types, genes, and circulating proteins. DATA SOURCES: Genome-wide data were assembled from FinnGen, All of Us, Mass General Brigham Biobank, Million Veteran Program, and a Dutch chronic CSC cohort. Serum protein quantitative trait loci, human single-cell ocular atlases, and UK Biobank macular optical coherence tomography (OCT) imaging were used for downstream analyses. STUDY SELECTION: Five European-ancestry cohorts with genome-wide data and cohort-specific CSC case-control definitions were included, comprising 2,584 cases and 1,044,455 controls. Variants present in at least 2 cohorts were meta-analyzed. DATA EXTRACTION AND SYNTHESIS: Cohort-level GWASs were adjusted for age, age squared, sex, genotyping array or batch, and 10 genetic principal components, then combined using fixed-effects inverse-variance meta-analysis. Post-GWAS analyses included gene prioritization, colocalization, Mendelian randomization, single-cell disease-relevance scoring, and testing of a CSC genetic risk score in UK Biobank OCT images. MAIN OUTCOMES AND MEASURES: Genome-wide significant CSC loci, effector genes and proteins, tissue and cell-type enrichment, and CSC-relevant OCT abnormalities. RESULTS: Across 11,068,938 variants, 10 loci reached genome-wide significance (P < 5 × 10-8), including 3 novel loci near TGFB1, LINC00551, and LOC105375630 and 7 replicated loci near CFH, CD46, NOTCH4, PREX1, PTPRB, GATA5, and TNFRSF10A. Integrative analyses prioritized 10 candidate effector genes. Colocalization and Mendelian randomization implicated circulating TNFRSF10A, TGFB1, and CASP10 levels. Single-cell analyses localized genetic risk to sclera (P = 2.0 × 10-4) and vascular endothelial cells (P = 4.0 × 10-4), with fibroblast enrichment. In UK Biobank, OCT abnormalities were more frequent in the top vs bottom 1% of CSC genetic risk (18 of 109 [16.5%] vs 8 of 134 [6.0%]; odds ratio, 4.05; 95% CI, 1.65-10.87; P = .002). CONCLUSIONS AND RELEVANCE: In this GWAS meta-analysis, CSC susceptibility localized predominantly to scleral and vascular biology rather than primary retinal pigment epithelial dysfunction. These findings support CSC as a sclerovascular disorder and nominate complement regulation, endothelial signaling, and extracellular matrix pathways for future study.

Journal Article↗

PubMed1988

Individual specific DNA fingerprints from a hypervariable region probe: alpha-globin 3'HVR.

A probe detecting a hypervariable region (HVR) 3' to the alpha globin locus on chromosome 16 has been used to produce DNA fingerprints. Segregation analysis has revealed multiple, randomly dispersed DNA fragments inherited in a Mendelian fashion with minimal allelism and linkage. The fingerprints are highly polymorphic (probability of chance association between random individuals much less than 10(-14]. The probe is, therefore, a powerful discriminating tool: it is envisaged that this probe will have forensic applications, including paternity cases, and will be informative in linkage analysis.

Alleles↗

PubMed2026

Integrated multi-omics strategies for identifying novel therapies in psoriasis.

MOTIVATION: Psoriasis is a chronic, immune-mediated disorder with an unmet need for effective treatments. To systematically prioritize therapeutic targets, we integrated proteome-wide Mendelian randomization (MR) with expression validation in blood/skin, genetic susceptibility analysis, differential gene expression (DGE) from bulk and single-cell RNA sequencing (scRNA-seq), colocalization, pathway enrichment, and protein-protein interaction analyses. RESULTS: Proteome-wide MR identified 29 candidate protein targets (Bonferroni-corrected), all replicated in independent datasets. Fifteen targets showed significant expression associations in blood or skin. Eleven proteins-UBLCP1, IL23A, ASF1A, RARRES2, ICAM1, PRSS53, ICAM5, GCA, IL2RA, DBI, and NFKB1-exhibited consistent directional effects with their genes. Genetic susceptibility analysis confirmed 20 target-specific polygenic scores for psoriasis and five for psoriatic arthritis. DGE analysis identified 13 targets in bulk and 13 in scRNA-seq-primarily in keratinocytes and immune cells-with IL2RA, COMP, and A2ML1 dysregulated across both. Colocalization analysis implicated shared causal variants for psoriasis in ASF1A, CD8A, CTF1, IL7R, MMP12, RARRES2, XCL2, DBI, IL23A, IL2RA, SGSH, and TIMD4. Enrichment analyses highlighted involvement in cytotoxicity, immune regulation, and JAK-STAT signaling. Eighteen targets interacted with approved anti-psoriasis drugs. Notably, drugs targeting IL2RA, IL7R, CTF1, ICAM1, MMP12, NFKB1, CD8A, DDX58, IL12A, SGSH, and FAP are approved or in trials for other diseases, suggesting repurposing potential. Our integrative multi-omics approach prioritized 29 high-confidence targets, including 13 novel candidates (RARRES2, ASF1A, CTF1, DBI, B3GNT2, CD8A, TIMD4, CRTAM, SGSH, XCL2, DAPK2, A2ML1, and FAP). Several high-priority targets-such as IL2RA, IL23, MMP12, RARRES2, IL7R, and ICAM1-were supported across analytical layers. These findings provide a robust foundation for psoriasis drug development. AVAILABILITY AND IMPLEMENTATION: The code used for the analyses in this manuscript has been archived in Zenodo at [DOI: 10.5281/zenodo.19692128].

Psoriasis↗

PubMed2026

Integrative multi-omics analyses suggest a candidate microbial metabolite-associated host gene network in ulcerative colitis.

Ulcerative colitis (UC) is associated with gut microbial dysbiosis, but the host molecular alterations potentially linked to microbially derived metabolites remain incompletely understood. We integrated Mendelian randomization (MR), microbial metabolite annotation, computational target prediction, colonic transcriptomics, network analysis, and machine learning. MiBioGen microbiome GWAS data were used as exposures and FinnGen Release 12 ULCERENTER as the outcome. Metabolites linked to MR-prioritized taxa were retrieved from GutMGene, and human targets were predicted using SwissTargetPrediction and SEA. UC-related genes were defined by integrating differential expression analysis and WGCNA and then intersected with predicted metabolite targets. MR prioritized one family and eight genera showing nominal genetically supported associations with UC, but none remained significant after Benjamini-Hochberg FDR correction. Three prioritized genera were linked to 15 microbe-metabolite records, corresponding to 13 unique metabolites; nine were retained for target prediction, yielding 277 unique predicted human targets. Transcriptomic analysis identified 1,530 DEGs and a 312-gene MEgrey60 module, with 273 overlapping genes, producing 1,569 unique UC-related genes. Their intersection with the 277 predicted targets yielded 47 candidate genes. Enrichment analyses highlighted mainly metabolic and lipid-related processes. Random Forest showed the highest mean AUC across the two independent external benchmarking cohorts, and SHAP prioritized EPHX1, HSD17B2, IGFBP5, and MMP10. IBDome analysis showed inflammation-associated expression differences in these genes. This study provides a genomics-informed, hypothesis-generating framework that prioritizes candidate microbe-metabolite-host relationships in UC for future experimental validation.

Humans↗

PubMed2025

Inflammatory pathways and immune dysregulation in pediatric postoperative septic shock: A study integrating transcriptomics, machine learning and molecular docking.

This study elucidates the molecular and immune regulatory mechanisms of pediatric postoperative septic shock. Transcriptomic data were obtained from the Gene Expression Omnibus database. Differentially expressed genes were identified using the limma package, and gene co-expression modules were constructed using Weighted Gene Co-expression Network Analysis. Functional enrichment was performed via gene set enrichment analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses. Immune cell infiltration was assessed using ESTIMATE and CIBERSORT. Mendelian randomization was applied to explore causal relationships between gene expression and septic shock. Feature genes were selected using machine learning algorithms, and a diagnostic nomogram model was constructed. Finally, molecular docking analysis was performed to screen and evaluate the binding affinity of traditional Chinese medicine monomers to core target proteins. A total of 1331 differentially expressed genes were identified, and the turquoise module was strongly correlated with septic shock. Enrichment analysis revealed significant activation of IL-6/JAK/STAT3, TNF-α/NF-κB, and PI3K/Akt/mTOR pathways. Immune infiltration analysis indicated suppressed immune scores and imbalances in neutrophils, macrophages, T cells, and B cells. Mendelian randomization confirmed causal associations for 6 genes, including PIM3. The predictive model based on feature genes demonstrated high diagnostic performance. Molecular docking suggested that quercetin and astramembrannin I could stably bind PIM3. This study systematically identified core genes, dysregulated immune pathways, and candidate small-molecule interventions in pediatric septic shock, providing novel insights for early diagnosis and targeted therapy.

Humans↗

PubMed2026

Genetic interconnections between personality-related phenotypes and psychiatric disorders.

BACKGROUND: Personality-related phenotypes are genetically correlated with psychiatric disorders, but whether these relationships reflect shared genetic loci and differ across individual phenotypes remains unclear. We investigated their shared genetic architecture at the level of specific phenotype-disorder pairs. METHODS: We analyzed genome-wide association study summary statistics for 13 personality-related phenotypes and eight psychiatric disorders in populations of European ancestry. Genetic correlations were evaluated separately for 104 phenotype-disorder pairs using linkage disequilibrium score regression and high-definition likelihood. For pairs supported by both methods, MTAG and CPASSOC were applied separately to identify pleiotropic signals, followed by linkage disequilibrium clumping, Bayesian colocalization, gene prioritization, functional enrichment and bidirectional two-sample Mendelian randomization analyses. No composite personality or psychiatric-disorder phenotype was constructed. RESULTS: Among the 104 evaluated pairs, 77 showed significant positive genetic correlations in both analyses. Joint screening of MTAG and CPASSOC results identified pleiotropic signals in 61 pairs, comprising 1088 independent lead SNV-pair associations and 776 unique SNVs. Bayesian colocalization supported 351 signals across 42 pairs and 284 unique lead SNVs. MAGMA identified 1293 unique genes, of which 379 were prioritized by PoPS and 151 were further supported by SMR. These genes were enriched in brain tissues and biological processes involving nervous system development, synaptic organization and intercellular connectivity. Inverse-variance weighted Mendelian randomization identified 41 forward and 32 reverse associations after false-discovery-rate correction, including 21 pairs with bidirectional evidence. CONCLUSION: These item-resolved analyses identify widespread but heterogeneous genetic sharing between personality-related phenotypes and psychiatric disorders. The findings provide a pair-specific map of shared loci and prioritized genes, while the Mendelian randomization results should be interpreted cautiously because of residual heterogeneity and potential horizontal pleiotropy. Further validation in diverse populations and functional studies is required.

Colocalization↗

PubMed2022

Association of Vitamin D Polygenic Risk Scores and Disease Outcome in People With Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: Observational studies suggest low levels of 25-hydroxyvitamin D (25[OH]D) may be associated with increased disease activity in people with multiple sclerosis (PwMS). Large-scale genome-wide association studies (GWAS) suggest 25(OH)D levels are partly genetically determined. The resultant polygenic scores (PGSs) could serve as a proxy for 25(OH)D levels, minimizing potential confounding and reverse causation in analyses with outcomes. Herein, we assess the association of genetically determined 25(OH)D and disease outcomes in MS. METHODS: We generated 25(OH)D PGS for 1,924 PwMS with available genotyping data pooled from 3 studies: the CombiRx trial (n = 575), Johns Hopkins MS Center (n = 1,152), and Immune-Mediated Inflammatory Diseases study (n = 197). 25(OH)D-PGS were derived using summary statistics (p < 5 × 10-8) from a large GWAS including 485,762 individuals with circulating 25(OH)D levels measured. We included clinical and imaging outcomes: Expanded disability status scale (EDSS), timed 25-foot walk (T25FW), nine-hole peg test (9HPT), radiologic activity, and optical coherence tomography-derived ganglion cell inner plexiform layer (GCIPL) thickness. A subset (n = 935) had measured circulating 25(OH)D levels. We fitted multivariable models based on the outcome of interest and pooled results across studies using random effects meta-analysis. Sensitivity analyses included a modified p value threshold for inclusion in the PGS (5 × 10-5) and applying Mendelian randomization (MR) rather than using PGS. RESULTS: Initial analyses demonstrated a positive association between generated 25(OH)D-PGS and circulating 25(OH)D levels (per 1SD increase in 25[OH]D PGS: 3.08%, 95% CI: 1.77%, 4.42%; p = 4.33e-06; R2 = 2.24%). In analyses with outcomes, we did not observe an association between 25(OH)D-PGS and relapse rate (per 1SD increase in 25[OH]D-PGS: 0.98; 95% CI: 0.87-1.10), EDSS worsening (per 1SD: 1.05; 95% CI: 0.87-1.28), change in T25FW (per 1SD: 0.07%; 95% CI: -0.34 to 0.49), or change in 9HPT (per 1SD: 0.09%; 95% CI: -0.15 to 0.33). 25(OH)D-PGS was not associated with new lesion accrual, lesion volume or other imaging-based outcomes (whole brain, gray, white matter volume loss or GCIPL thinning). The results were similarly null in analyses using other p value thresholds or those applying MR. DISCUSSION: Genetically determined lower 25(OH)D levels were not associated with worse disease outcomes in PwMS and raises questions about the plausibility of a treatment effect of vitamin D in established MS.

Humans↗

PubMed1996

Reliable computer-assisted classification of the EEG: EEG variants in index cases and their first degree relatives.

A method which optimizes on global properties of sample recordings is proposed for the definition of and the discrimination between electroencephalogram (EEG) classes. The sample was drawn from students at the University of Heidelberg from 1974 to 1978 and consists of 15 healthy index cases clinically ascertained as belonging to the low voltage EEG group. In addition, the three clinically defined groups: diffuse beta (18 index cases), borderline alpha (12 index cases) and monomorphous alpha (18 index cases) have been included in the study, as well as the first degree relatives of the index cases, thus providing a clinical classification into four groups. The proposed method provides an automatic and reliable classification algorithm using discriminant and cluster analysis. The relation between such an automatized classification and clinical classification schemes is investigated. In particular, the inheritance of the low voltage EEG, the question on sex differences and the question of a simple Mendelian mechanism had been examined. The method of random splittings had been applied for discriminant and cluster analysis. Our findings can be summarized as follows: (1) except for the monomorphous alpha EEG group, the clinical classification shows rather marginal separation (discriminating performance 60% to 75%), while a new and more reliable grouping scheme improves the discriminating performance up to 87% to 91%. The latter scheme leads to the concept of personal channel pattern (PCP) and was compared to the clinical classification scheme by means of contingency tables; (2) only a weak correlation between the clinically and PCP-based groups could be found (Cramér Index: 0.27). Accordingly, we continued to investigate the extent to which the proposed EEG classification scheme can nevertheless explain the genetic mechanisms apparently involved in the low voltage EEG. We thus considered the role of sex differences manifest in our proposed new grouping scheme; (3) males occurred more frequently in the new group 3 and females more frequently in the new group 1. In this regard, a much better correlation of the new groups between mothers and children than between fathers and children was observed; and (4) with help of our new PCP scheme, we have been able to reproduce a simple two gene Mendelian scheme to explain inheritance of the clinical low voltage EEG group. In this PCP-based scheme, the low voltage property does not occur when dominance of a certain gene (called gene A) is absent.

Adult↗

PubMed2026

Identification of potential key genes involved in iron deficiency for sepsis: A retrospective cohort and transcriptomic study.

Iron overload has been associated with sepsis, but the role of iron deficiency and its molecular links remain unclear. We investigated the association between iron deficiency and sepsis and identified candidate genes potentially linking these conditions. MIMIC-IV data were used to assess the association between serum iron and sepsis status. Transcriptomic datasets from dietary iron-deficient mice (GSE10421), LPS-induced septic mice (GSE267388), and a human blood sepsis cohort (GSE137340) were sequentially analyzed to identify and externally evaluate candidate genes. IEU Open GWAS summary statistics were used for exploratory Mendelian randomization (MR). Exploratory drug prediction was performed using L1000FWD, followed by molecular docking analysis. Patients with sepsis had significantly lower serum iron levels, and restricted cubic spline analysis showed a nonlinear association between serum iron and the odds of sepsis. Cross-tissue transcriptomic analysis identified Sqle, Lss, and Rdh11 as candidate genes. In the human blood cohort, SQLE and RDH11 were significantly increased, whereas LSS was not significantly altered. Exploratory MR showed that genetically proxied SQLE expression was associated with higher odds of sepsis (odds ratio [OR] = 1.23, P = 1.67 × 10-3), whereas LSS expression was associated with lower odds (OR = 0.97, P = 8.90 × 10-4); RDH11 showed no significant association (OR = 1.01, P = .90). Drug prediction identified ML106 as the top-ranked candidate drug, and molecular docking predicted potential binding poses with SQLE and LSS. Serum iron showed a nonlinear association with sepsis status. SQLE, LSS, and RDH11 emerged as candidate genes, with concordant expression changes of SQLE and RDH11 observed in human blood. MR findings for SQLE and LSS were exploratory and require further validation. ML106 was identified through exploratory drug prediction and requires experimental validation before its therapeutic relevance can be established.

Sepsis↗

PubMed2026

Integrative multi-omics identifies DOC2A as a novel pharmacological target for bipolar disorder.

BACKGROUND: Current bipolar disorder (BD) therapies suffer from limited efficacy and adverse effects, necessitating mechanistically grounded targets. METHODS: We integrated BD genome-wide association study data (158,036 cases; 2,796,499 controls) with brain proteomics (ROSMAP and Banner dorsolateral prefrontal cortex, n = 376 and 152) to perform proteome-wide association studies (PWAS). Bayesian colocalization and summary-data-based Mendelian randomization (SMR) prioritized causal genes. Cell-type-specific transcriptomics validated dysregulation in iPSC-derived neurons, astrocytes, and postmortem hippocampus/prefrontal cortex. Weighted gene co-expression networks (WGCNAs), functional enrichment, and molecular docking assessed functional pathways and druggability. RESULTS: PWAS identified eight BD-associated genes (false discovery rate < 0.05), with DOC2A emerging as the top candidate. Colocalization (H4 > 0.8) and SMR supported a causal association of DOC2A with BD, with no pleiotropy (heterogeneity in dependent instruments P > 0.01); DOC2A expression decreased in BD across neurons (P = 4.26 × 10-2), astrocytes (P = 2.09 × 10-2), hippocampus (P = 9.80 × 10-3, t = -2.738), and prefrontal cortex (P = 1.44 × 10-2, t = -2.580); WGCNA positioned DOC2A as a key regulator (module membership/gene significance P < 0.05) of co-expression networks enriched for BD-associated processes including neurotransmitter secretion and postsynaptic actin cytoskeleton organization (P < 0.05); molecular docking revealed favorable-affinity binding (ΔG < -4 kcal/mol) between DOC2A and BD-related drugs and neuroprotective compounds. CONCLUSIONS: Our convergent multi-omics framework highlights DOC2A dysregulation as a key contributor to synaptic dysfunction in BD and nominates it as a promising therapeutic target. The demonstrated interaction with existing neuroactive compounds provides immediate translational avenues.

Bipolar Disorder↗

PubMed2026

Shared genetic architecture and neurobiological pathways of problematic alcohol use and anxiety disorders.

Problematic alcohol use (PAU) and anxiety disorders (ANX) frequently co-occur, implying shared genetic and neurobiological foundations. However, the directionality of potential causal relationships and the specific mechanisms underlying the overlap remain unclear. Thus, we investigated the shared genetic architecture and neurobiological pathways between PAU and ANX using a multimethod genomic approach. We analyzed summary statistics from genome-wide association studies (GWAS) of PAU and ANX using Mendelian Randomization to assess causal associations between ANX and PAU. We used MiXeR to assess the overall shared genomic architecture, Local Analysis of (co)Variant Association to estimate regional genetic correlations, and conjunctional false discovery rate (conjFDR) to identify individual overlapping loci. We used FUMA to map single-nucleotide polymorphisms (SNPs) to independent loci, conduct differential gene expression analyses across 30 general and 54 specific tissue types, and perform cell-type specificity analyses using a human brain cell atlas. Druggability of identified targets was also evaluated. Mendelian Randomization analyses indicated bidirectional causal associations between ANX and PAU. MiXeR identified moderate polygenic overlap (52.5%) and genetic correlation (rg = 0.44) between the traits, with high effect direction concordance among shared estimated causal variants (86.4%). ConjFDR identified 97 shared lead SNPs, of which 89 had concordant and 8 discordant effects on PAU and ANX. These loci mapped to 97 genes, including DRD2 and PDE4B, genes linked to dopaminergic and cAMP signaling pathways, respectively. Concordant gene expression was enriched in brain, nerve, adrenal gland, esophagus, stomach, and colon, with enriched expression specifically in the prefrontal cortex, anterior cingulate cortex, hippocampus, hypothalamus, substantia nigra and amygdala. FUMA cell-type enrichment analysis identified associations predominantly in neurons from the cerebral cortex, hippocampus, and thalamus. We found substantial genetic and neurobiological overlap between PAU and ANX, highlighting reciprocal, causal relationships between the traits, with differentially expressed genes enriched in addiction- and anxiety-relevant brain regions. These findings support shared genetic and neurobiological mechanisms linking PAU and ANX, while acknowledging that some signals may reflect broader internalizing or psychiatric liability.

Journal Article↗

PubMed2024

MONOCYTES AND B CELLS MEDIATE ALTERATIONS IN THE GENETIC ASSOCIATION BETWEEN PLATELETS AND SEPSIS VIA CLEC SIGNALING PATHWAY.

Background: Sepsis is a life-threatening condition characterized by multiple organ dysfunction. Blood cells abnormalities play a significant role in the onset and progression of sepsis; however, the potential causal relationship between platelets and sepsis remains unclear, as does whether immune cells mediate the interaction between platelets and sepsis. This study aims to explore the potential causal relationship between platelets and sepsis and analyze the mediating effect of immune cells. In addition, cell-to-cell communication was analyzed to explore the interaction between blood cells and immune cells. Material and methods: In this study, genome-wide association study data were utilized to examine the association between blood cells and sepsis. Two-sample Mendelian randomization (MR) and reverse MR were performed to investigate the potential causal relationship between blood cells and sepsis, with a specific focus on the relationship between platelets and sepsis. Subsequently, two-step MR was employed to identify the immune cells that mediate the interaction between platelets and sepsis and to assess their potential mediating effects. Cellchat software was used to analyze cell-to-cell communication. Results: The results of two-sample MR indicated that platelets were negatively correlated with sepsis (OR = 0.976, 95% CI 0.959-0.993, P = 0.005), suggesting that platelets have a protective effect against sepsis. Additionally, reverse MR demonstrated that sepsis had no significant effect on platelets (OR = 0.909, 95% CI 0.156-5.296, P = 0.916). The mediating effect analysis revealed that monocytes and B cells were important mediators in the relationship between platelets and sepsis. Notably, the correlation between platelets and sepsis shifted from negative to positive with the involvement of monocytes and B cells. The number and strength of cell-cell interactions were decreased in sepsis. Monocytes and B cells primarily regulate platelets through the CLEC signaling pathway, contributing to the pathogenesis of sepsis. Conclusion: This study confirmed the protective role of platelets in sepsis. Monocytes and B cells mediate changes in the genetic association between platelets and sepsis. Monocytes and B cells primarily interact with platelets via the CLEC pathway, thereby modulating the genetic association between platelets and sepsis. These findings indicate that thrombocytopenia, especially when accompanied by elevated monocytes and B cells, may serve as a potential marker for sepsis.

Humans↗

PubMed2026

Conventional and Shared Genetic Association Analysis Between Diabetes Mellitus and Sensorineural Hearing Loss.

PURPOSE: This study aims to investigate the epidemiological and genetic associations between diabetes mellitus (DM) and sensorineural hearing loss (SNHL) across different subtypes. METHODS: We analyzed 502,490 participants from the UK Biobank using multivariate logistic regression to examine the association between DM and SNHL, considering gender, age, and HbA1c levels. Genetic correlations and causality were examined by linkage disequilibrium score regression and bidirectional Mendelian randomization. Cross-trait meta-analyses identified shared loci between DM and SNHL, followed by gene annotation, functional analysis, and drug candidate exploration for the shared traits. RESULTS: Observational analysis revealed significant associations between DM and SNHL, consistent in subgroups based on age, sex, and certain HbA1c levels. A positive genetic correlation was found between type 2 diabetes mellitus (T2D) and SNHL (Rg = 0.0982, p = 0.0095) between T2D and SNHL, and four loci were identified, with ARHGEF28 and TCF7L2 prioritized as credible pleiotropic genes. Enrichment was indicated in glucose metabolism and organogenesis, with shared heritability in metabolic tissues and outer hair cells. Metformin was identified as potential drug candidates for the T2D-SNHL comorbidity. CONCLUSION: These findings progress our understanding of the epidemiological association, shared genetic basis, and potential therapeutic targets between T2D and SNHL, which might contribute to the management of their comorbidity.

Humans↗

PubMed2024

Whole -genome survival analysis of 144 286 people from the UK Biobank identifies novel loci associated with blood pressure.

This study utilized UK Biobank data from 144 286 participants and employed whole-genome sequencing (WGS) data and time-to-event data over a 12-year follow-up period to identify susceptibility in genetic variants associated with hypertension. Following genotype quality control, 6 319 822 single nucleotide polymorphisms underwent analysis, revealing 31 significant variant-level associations. Among these, 29 were novel - 15 in Fibrillin-2 ( FBN2 ) and 4 in Junctophilin-2 ( JPH2 ). Mendelian randomization utilizing two identified variants (rs17677724 and rs1014754) suggested that a genetically induced decrease in heart FBN2 expression and an increase in adrenal gland JPH2 expression were causally linked to hypertension. Phenome-wide association (PheWAS) analysis using the FinnGen dataset confirmed positive associations of rs17677724 and rs1014754 with hypertension, assessed across 2727 traits in 377 277 individuals. Lastly, rs1014754 positively associated with kallistatin, whereas rs17677724 negatively associated with renin in the Fenland study, suggesting a counterregulatory response to high blood pressure. This study, employing WGS data, identified novel genetic loci and potential therapeutic targets for hypertension.

Humans↗

PubMed2005

Obstacles and opportunities in meta-analysis of genetic association studies.

Genetic association studies have the potential to advance our understanding of genotype-phenotype relationships, especially for common, complex diseases where other approaches, such as linkage, are less powerful. Unfortunately, many reported studies are not replicated or corroborated. This lack of reproducibility has many potential causes, relating to study design, sample size, and power issues, and from sources of true variability among populations. Genetic association studies can be considered as more similar to randomized trials than other types of observational epidemiological studies because of "Mendelian randomization" (Mendel's second law). The rationale and methodology for synthesizing randomized trials is highly relevant to the meta-analysis of genetic association studies. Nevertheless, there are a number of obstacles to overcome when performing such meta-analyses. In this review, the impacts of Type I error, lack of power, and publication and reporting biases are explored, and the role of multiple testing is discussed. A number of special features of association studies are especially pertinent, because they may lead to true variability among study results. These include population dynamics and structure, linkage disequilibrium, conformity to Hardy-Weinberg Equilibrium, bias, population stratification, statistical heterogeneity, epistatic and environmental interactions, and the choice of statistical models used in the analysis. Approaches to dealing with these issues are outlined. The supreme importance of complete and consistent study reporting and of making data readily available is also highlighted as a prerequisite for sound meta-analysis. We believe that systematic review and meta-analysis has an important role to play in understanding genetic association studies and should help us to separate the wheat from the chaff.

Epistasis, Genetic↗

PubMed2026

Livestock Multi-Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation.

Livestock multi-omics integration is key to unraveling complex trait regulation, yet systematic, livestock-specific strategies remain scarce. This review traces the progression from single-omics accumulation to multi-dimensional integration, highlighting how large-scale genomic, epigenomic, and transcriptomic projects lay the foundation for functional dissection. We identify core impediments: extreme species diversity, marked data heterogeneity, limited sample sizes, and a pervasive reduction of multi-omics data to simplistic differential screens, resulting in low translational efficiency. We critically appraise four common pitfalls-overinterpreting correlation as causation, relegating proteomics to corroborating transcriptomics, incomplete microbiome-host integration lacking environmental context, and systematic neglect of metabolic fluxomics-and show how exposomics and fluxomics add necessary causal and dynamic dimensions. To address these, we propose a livestock-adapted three-tier analytical framework: (1) statistical association of cross-omics covariation patterns; (2) machine learning-driven feature mining and integrative modeling; and (3) causal interpretation encompassing Mendelian randomization, prior-knowledge-guided network inference, and physical causal evidence via fluxomics and metabolic control analysis. We further discuss how multimodal sequencing (single-cell, spatial, temporal) and generative AI can fundamentally mitigate heterogeneity and strengthen causal evidence. Finally, we outline future priorities in database standardization, livestock-specific benchmarking, and translational pipelines, charting a path from correlation-centric reporting to mechanistic causality and precision breeding.

Animals↗

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↗