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PubMed2025

Genetic evidence for repurposing GLP-1 receptor agonists in chronic kidney disease and IgA nephropathy: Metabolic and anti-inflammatory pathways beyond glycaemic control.

AIMS: Despite observational links between glucagon-like peptide-1 receptor agonists (GLP-1RAs) and kidney benefits, causal mechanisms remain unclear. This study aims to dissect genetic causality and mediation pathways underlying the effects of GLP-1RAs on chronic kidney disease (CKD) and related renal outcomes. MATERIALS AND METHODS: Using large-scale Genome - Wide Association Study (GWAS) data, we applied two-sample Mendelian randomisation (MR) to estimate the causal effects of GLP-1RAs on CKD, estimated glomerular filtration rate (eGFR) and subtypes (IgA nephropathy, membranous nephropathy, nephrotic syndrome and chronic glomerulonephritis), with sensitivity analyses. The glycaemic markers (glycated haemoglobin [HbA1c] and blood glucose), type 2 diabetes mellitus (T2DM) and diabetic nephropathy (DN) served as positive controls. Mediation MR assessed body mass index (BMI), lipids, glycaemic markers and inflammatory proteins. Data were sourced from MRC Integrative Epidemiology Unit Open Genome - Wide Association Studies OpenGWAS, FinnGen, GWAS Catalogue and cohort-specific studies. RESULTS: Positive control analyses revealed that genetically predicted GLP-1R activation was associated with reduced levels of HbA1c (p = 4.93E-15) and blood glucose (p = 9.73E-5), as well as a decreased risk of T2DM (p = 2.45E-4) and DN (p = 6.35E-4), fully validating the reliability of the genetic instruments. Genetic proxies for GLP-1R activation lowered risks of CKD (odds ratio [OR] = 0.83, p = 9.22E-9), immunoglobulin A nephropathy (IgAN) (OR = 0.70, p = 2.11E-3) and kidney function preservation (β = 0.01, p = 9.11E-3), but showed null effects on other CKD subtypes. Mediation analyses indicated that fibroblast growth factor 23 (FGF23) suppression mediated 26.57% of the effect on eGFR and 13.50% of CKD protection, whereas metabolic traits (BMI: 2.08% for CKD, 5.51% for eGFR; high-density lipoprotein: 0.79% for CKD, 2.34% for eGFR; HbA1c: 8.25% for eGFR) partially explained the benefits on CKD and eGFR. Only BMI exhibited a mediation effect on IgAN. Sensitivity analyses confirmed minimal pleiotropy. CONCLUSIONS: This study provides robust genetic evidence for repurposing GLP-1RAs in CKD and IgAN through anti-inflammatory (FGF23) and metabolic pathways, extending their utility beyond glucose control. While European ancestry data limit generalisability, our framework prioritises FGF23 and metabolic modulation as key targets for clinical trials in renal protection.

Humans↗

PubMed2026

Integrative proteogenomic and observational analysis identifies potential biomarkers for latent autoimmune diabetes in adults.

BACKGROUND: Latent autoimmune diabetes in adults (LADA) shares core genetic and immunological features with type 1 diabetes (T1D) but is frequently misdiagnosed as type 2 diabetes (T2D). With few biomarkers for its timely diagnosis and management, this study integrated proteome-wide Mendelian randomisation (MR) and observational clinical analysis to identify potential LADA biomarkers. METHODS: We performed proteome-wide MR using cis-protein quantitative trait loci (cis-pQTLs) for 1,389 plasma proteins from the deCODE study (n = 35,559) and genome-wide association study (GWAS) data for LADA (2,634 cases and 5,947 controls, European ancestry). Robustness was enhanced via multiple sensitivity analyses. Pathway enrichment analysis, druggability evaluation, phenome-wide MR, and interaction analyses were performed to investigate the clinical relevance and biological context of candidate proteins. Candidate proteins were further evaluated using enzyme-linked immunosorbent assays in a matched Chinese clinical study (n = 241) to assess their discriminative ability for LADA. RESULTS: Proteome-wide MR and colocalisation analyses indicated associations between genetically predicted plasma levels of C-X-C motif chemokine ligand 10 (CXCL10; OR [95% CI] per 1-SD increase in protein levels: 5.49 [1.74,17.32]), serum amyloid A1 (SAA1; 1.28 [1.14,1.45]), and SAA2 (1.22 [1.11,1.34]) with LADA risk. Replication, multi-tissue eQTL, and multivariable MR supported CXCL10's association. Druggability evaluation suggested CXCL10 as a drug target under investigation, and phenome-wide MR of 1,006 diseases and traits indicated no major safety concerns for CXCL10 as a potential biomarker. In the observational clinical study, CXCL10 differentiated LADA from healthy controls (area under the receiver operating characteristic curve [ROC-AUC]: 0.889; precision-recall area under the curve [PR-AUC]: 0.919) and T2D (ROC-AUC: 0.838; PR-AUC: 0.921), with both models showing adequate calibration. CONCLUSIONS: This study suggests that CXCL10 is a putative biomarker associated with LADA, demonstrating discriminative ability to distinguish LADA from T2D in an observational clinical cohort. These findings contribute to understanding the autoimmune molecular aetiology of LADA and support its diagnostic potential in resolving the clinical ambiguity between LADA and T2D.

Humans↗

PubMed2026

Hypothesis-free evaluation of circulating metabolome provides cell-specific insights regarding the role of energy substrate availability in amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with limited therapeutic options. The circulating metabolome comprises small molecules present in plasma/serum which are the intermediates and end-products of cellular metabolism, and is linked to ALS pathogenesis. METHODS: We conducted hypothesis-free two-sample Mendelian randomisation (MR) analysis of the concentration of 575 plasma/serum metabolites, to determine which are causally linked to risk of ALS. Significant metabolites were validated in an independent GWAS of plasma/serum metabolite concentrations and evaluated for sex-specific effects. Correlations between directly measured patient biofluid metabolite concentrations and ALS risk/severity were examined in 94 ALS patients and 40 controls. We experimentally assessed metabolic function in a murine neurons and human astrocytes carrying an ALS-associated G4C2-repeat expansion within C9orf72. RESULTS: MR causally associated five metabolites with ALS risk after multiple-testing correction. Higher serum concentration of glycoprotein acetyls (P = 9.7e - 9, β = 0.21) and the peptide DSGEGDFXAEGGGVR (P = 8.0e - 6, β = 0.22) was associated with increased ALS risk, whereas higher plasma concentration of phenylalanylserine, isobutyrylcarnitine, and acetylcarnitine was protective (P < 5e - 5, β = - 0.29 to - 0.72). DSGEGDFXAEGGGVR has been linked to glucose metabolism but we have used genetic fine-mapping to link DSGEGDFXAEGGGVR, neuronal glucose uptake through GLUT3, and ALS risk. Direct measurement of metabolite concentrations in patient biofluids revealed elevated acetylcarnitine levels in patients with ALS, which were associated with delayed symptom onset (Cox regression, P = 0.02, HR = 0.4). Similarly, lactate is elevated in ALS patient CSF (ANOVA, P = 1.3e - 3) and in patients with longer survival time (Cox regression, P = 0.03, HR = 0.3). Plasma fructose is elevated in ALS patients with shorter survival time (Cox regression, P = 0.02, HR = 1.1). In vitro, neurons and astrocytes carrying an ALS-associated G4C2-repeat expansion within C9orf72 demonstrated reduced metabolic flexibility. CONCLUSIONS: We provide evidence that impaired energy substrate availability contributes to ALS risk and severity. CNS cell types differ in their use of energy substrates and therefore we postulate the relative importance of different cell types for different stages of disease. Our findings support further investigation of metabolic interventions to treat or prevent ALS.

Amyotrophic Lateral Sclerosis↗

PubMed2026

Genetic architecture of endometriosis: risk factors, comorbidities and clinical implications.

BACKGROUND: In 1999, Dr Susan Treloar and colleagues conducted a landmark twin study in Australia and reported their estimate of 51% for the heritability of endometriosis. This important result led several groups to begin mapping genetic factors contributing to increased endometriosis risk. Despite early challenges, advances in genome-wide association studies (GWAS) have identified multiple genetic risk factors and some target genes implicated in follow-up studies on genetic regulation of transcription. Access to large publicly available genetic datasets and analysis with endometriosis GWAS results is also providing new opportunities to answer important questions about comorbid conditions associated with endometriosis and their implications for clinical practice. OBJECTIVE AND RATIONALE: The objective of the review is to summarize the last 25 years of genetic studies in endometriosis, outline contributions to our understanding of the disease, and suggest future directions to accelerate biological insights from genetic studies to improve clinical outcomes. SEARCH METHODS: A comprehensive review of scientific literature on the genetics of endometriosis was conducted through searches in PubMed and Google Scholar up to June 2026. Search terms included "endometriosis AND (genetics OR GWAS OR genetic risk factors)", For studies addressing the functional characterization of genetic risk loci, additional searches employed the terms "endometriosis AND (genotype-phenotype associations OR colocalization OR eQTL OR mQTL OR multi omics methods)". To identify studies examining shared genetic risk between endometriosis and comorbid conditions, the search strategy included "endometriosis AND (genetic correlation OR colocalization OR Mendelian randomisation)". Publications reporting discoveries related to genetic risk factors for endometriosis and studies interpreting their biological and clinical significance were critically evaluated, and 144 publications were discussed in the review. OUTCOMES: Discovery of genetic risk factors started slowly and has accelerated in recent years with developments in technology and international collaborations to combine data and increase statistical power. GWAS have mapped 80 genetic risk factors that implicate gene regulation of hormonal targets, development of the reproductive tract, regulation of cell proliferation, and regulation of epithelial cell differentiation. In common with most other complex diseases, effects of individual common genetic risk factors are small. However, several examples demonstrate that small effect sizes are not a good predictor for the impact of drugs developed against genetically validated targets. Genetic risk factors implicate five genes regulating gonadotrophin release and oestrogen action, the major target pathway of current drugs for treatment of endometriosis demonstrating proof-of-principal for biologically meaningful results. Genetic correlation and Mendelian Randomization studies highlight important causal relationships between endometriosis and comorbid conditions including a possible role for testosterone during development and shared genetic risk factors for gynaecological, gastrointestinal, pain, psychiatric, and inflammatory conditions. Understanding causal relationships between endometriosis and related conditions will aid clinical management and more personalized treatments. WIDER IMPLICATIONS: Genetic studies provide novel insights into endometriosis pathogenesis and associations with related comorbid conditions. Genetic factors modifying gene regulation and disease risk likely act in specific cell types, and access to datasets from genetically informed cell-based models, single-cell and spatial omics data are needed to accelerate progress. Future studies should address critical questions of heterogeneity and disease subtypes, expand the search for genetic risk factors to non-European populations, evaluate the role of rare and structural variants, and better integrate data from functional, genomics, genetics, and clinical studies to reduce diagnostic delay, develop novel treatment strategies, and translate discoveries into personalized management strategies for affected individuals. REGISTRATION NUMBER: N/A.

comorbid conditions↗

PubMed2025

New insights into genetic comorbidity mechanisms: type 2 diabetes and primary open-angle glaucoma.

AIMS: To investigate the shared genetic mechanisms between type 2 diabetes (T2D) and primary open-angle glaucoma (POAG). Using large-scale genome-wide association study (GWAS) data, we performed single nucleotide polymorphism (SNP) level analysis to detect pleiotropic variants and loci, paired eQTL mapping analysis and gene-level analysis to identify candidate pleiotropic genes. In addition, Mendelian randomisation (MR) analysis was performed to assess causal associations. MATERIALS AND METHODS: We used POAG GWAS data from Finngen (9565 cases and 430 250 controls) and T2D GWAS data from 55 555 European ancestry samples. We used Linkage Disequilibrium SCore (LDSC) regression to assess the genetic association between T2D and POAG and further used PLeiotropic Analysis under the COmposite null hypothesis (PLACO) to identify shared genetic variants between paired traits. Finally, we further used MR analysis to explore the causal association between T2D and POAG at the genetic level. RESULTS: The LDSC results and MR analysis revealed that the T2D effect was significantly higher than that of the POAG (OR=1.09, 95% CI 1.03 to 1.14, p=1.50×10-3). The PLACO property analysis determined that the T2D sum POAG shared 178 individual SNPs, separate localisation of 79 individual causes. The five most popular choices are based on the effectiveness of CCND2, SVEP1, ST6GAL1, TCF7L2 and HMGA2. expression quantitative trait loci mapping further revealed 36 genes with regulatory roles in optic nerve-related brain tissues. Functional enrichment analyses indicated that these pleiotropic genes are involved in neurodevelopmental, neuroprotective and metabolic pathways, with tissue-specific enrichment observed in neural, pancreatic, adipose and retinal tissues. It is possible to present the main comorbid mechanisms of T2D and POAG. CONCLUSIONS: Our study provides new insights into the aetiology and pathogenesis of T2D and POAG at the genetic level.

Humans↗

PubMed2026

Predicting risk of ischemic stroke: A transformer model using genomic data.

BACKGROUND AND OBJECTIVE: Ischemic stroke is a leading cause of mortality and long-term disability worldwide. Genetic factors contribute to IS susceptibility, yet conventional polygenic risk score approaches are primarily based on additive effects and may not fully capture non-linear relationships or positional context and interactions among genetic variants. This study aimed to develop and evaluate a transformer-based genomic model incorporating position-wise genotype embedding for IS risk prediction. METHODS: We conducted a genome-wide association study using the UK Biobank dataset to identify IS-associated loci. Gene prioritisation was subsequently performed using tissue-specific expression quantitative trait locus-based Mendelian randomisation and colocalization analyses in whole blood and brain cortex. We then developed a transformer-based model that encoded genotype and SNP-position information using a position-wise embedding layer. Model performance was evaluated across three UK Biobank control definitions and externally assessed in the independent All of Us cohort. Performance metrics included the area under the receiver operating characteristic curve (AUROC), precision, recall, and F1 score. RESULTS: Across the three UK Biobank control definitions, the proposed method achieved the numerically highest discrimination among the evaluated models, with AUROCs of 0.8109, 0.7843, and 0.7468 using MRF-negative, combined, and MRF-positive controls, respectively. In the external All of Us cohort, the proposed method achieved an AUROC of 0.7251 and retained the highest AUROC among the evaluated models. In a separate incident-stroke survival analysis, medium- and high-score groups had hazard ratios of 1.13 and 1.21, respectively, relative to the low-score group. A total of 18 IS-associated loci were identified. Among the tissue-specific MR results, EDEM2 in the brain cortex remained significant after Bonferroni correction, while DCHS2 showed a nominal association. CONCLUSIONS: The proposed transformer-based framework provides a genomic modelling approach that achieved the highest discrimination among the evaluated models in this study and retained comparative performance in an independent external cohort. In further applications, integrating this genomic framework with conventional clinical, lifestyle, and environmental risk factors may support more comprehensive and personalised IS risk assessment. Prospective, population-representative, and multi-ancestry validation will be important to establish its potential role in future prevention-oriented risk management.

Genomics and bioinformatics↗

PubMedDate not supplied

Genetic epidemiology and public health: hope, hype, and future prospects.

Genetic epidemiology is a rapidly expanding research field, but the implications of findings from such studies for individual or population health are unclear. The use of molecular genetic screening currently has some legitimacy in certain monogenic conditions, but no established value with respect to common complex diseases. Personalised medical care based on molecular genetic testing is also as yet undeveloped for common diseases. Genetic epidemiology can contribute to establishing the causal nature of environmentally modifiable risk factors, through the application of mendelian randomisation approaches and thus contribute to appropriate preventive strategies. Technological and other advances will allow the potential of genetic epidemiology to be revealed over the next few years, and the establishment of large population-based resources for such studies (biobanks) should contribute to this endeavour.

Adult↗

PubMed2026

Genetics of sensory nutrition.

Sensory nutrition is an emerging research area that examines how chemosensory perception, particularly taste and smell, shapes dietary behaviours, nutritional status, and disease risk. Variation in how individuals perceive the same foods may help explain differences in diet quality and responsiveness to behavioural dietary interventions, yet chemosensory phenotypes are rarely measured at the population level. Genetic variation contributes to this perceptual diversity and provides a framework for investigating sensory determinants of diet using genomic approaches. This review summarises evidence linking chemosensory genetics to perception and dietary behaviours, and discusses applications for causal inference and for precision and personalised nutrition. Twin studies reveal moderate to high heritability for bitter taste traits, with more modest and phenotype-dependent estimates for sweetness, sourness, saltiness, fat-related traits, and olfactory measures. Genome-wide association studies have identified loci in taste and olfactory receptor genes associated with specific chemosensory traits as well as liking and intake of various foods, although the evidence remains concentrated on bitter taste and populations of European ancestry. These genetic variants have been used in Mendelian randomisation, a genetics-based approach that strengthens causal inference, to test whether sensory traits influence dietary behaviour. For precision nutrition, evidence for taste genotype-stratified interventions remains limited and mixed. Realising the promise of sensory nutrition will require scalable and standardised chemosensory phenotyping, Findable, Accessible, Interoperable, and Reusable (FAIR) data infrastructure, expanded research in diverse populations, and integration with broader biological and sociocultural determinants of dietary intake.

Genetics↗

PubMed2025

Genome-wide association study of adolescent-onset depression.

Adolescent depression is a heritable psychiatric condition with rising global prevalence and severe long-term outcomes, yet its biological underpinnings remain poorly understood. We conducted the first genome-wide association study of adolescent-onset depression, comprising 102,428 cases (diagnosis or clinical symptom thresholds) and 286,911 controls, including diverse ancestries. Cross-ancestry meta-analysis identified 52 independent variants across 17 loci; European-only analysis found 61 variants at 29 loci, with a SNP-based heritability of 9.8%. Comparative analyses revealed two genes unique to adolescent-onset versus lifetime depression, enriched in neuronal subtypes, and two genes as potential drug repurposing targets. Polygenic scores were associated with adolescent-onset depression across ancestries, persistent depression trajectories, more severe outcomes, as well as reduced cortical volume, surface area and white matter integrity. Genetic correlation and Mendelian randomisation analyses support shared genetic liability and causal links with early puberty and modifiable health and behavioural risk factors. These findings uncover novel genetic loci and refine biological pathways underlying adolescent-onset depression, revealing age-specific mechanisms and early intervention opportunities.

Journal Article↗

PubMed2026

Multi-omics causal inference of childhood asthma triggered by ambient particulate matter.

BACKGROUND: The causal impact of fine particulate matter (PM2.5), an established environmental risk factor, on childhood asthma and its biological mechanisms remain to be elucidated. The objective of the present study was to evaluate the causal association between PM2.5 and childhood asthma and to dissect the mediating role of plasma proteins through a multi-omics integrated Mendelian randomisation (MR) framework. METHODS: Two-sample MR was performed on large-scale genome-wide association data to estimate the causal effect of PM2.5 on childhood asthma. Genes commonly associated with PM2.5 and childhood asthma were screened by transcriptome-wide association study (TWAS) and subjected to enrichment analyses and MR. Mediator proteins were identified by two-step MR. Potential adverse effects were scanned by phenome-wide MR (Phe-MR). RESULTS: MR revealed a significant positive causal effect of PM2.5 on childhood asthma (OR=1.897, 95% CI: 1.063-3.388, p=0.030). TWAS highlighted 70 genes co-expressed in PM2.5 and childhood asthma that were enriched in inflammatory pathways such as lysosome- and leukocyte-mediated immunity. MEAF6 was validated as a protective gene and RNF40 as a risk gene for childhood asthma. Two-step MR identified FUT10 as a positive mediator mediating 19.3% of the causal effect, and CD200 and MANBA as negative mediator proteins. Phe-MR indicated the association of these genes and proteins with multiple other diseases, implying possible adverse effects from therapeutic intervention. CONCLUSION: Long-term PM2.5 exposure is causally linked to childhood asthma with MEAF6, RNF40, CD200, MANBA and FUT10 identified as key molecules. The study provides new evidence for the biological mechanisms linking PM2.5 to childhood asthma.

Journal Article↗

PubMed2003

Hyperhomocysteinaemia as a risk factor for venous thrombosis: an update of the current evidence.

Classical homocystinuria is associated with arterial vascular diseases and venous thrombosis. In the last decade, many studies, including some prospective studies, have been published indicating that moderate hyperhomocysteinaemia is also a risk factor for venous thrombosis. The 677C>T mutation in the methylenetetrahydrofolate reductase (MTHFR) gene is an important cause of mild hyperhomocysteinaemia. Recent metaanalyses show an elevated risk of venous thrombosis for subjects with the TT-genotype. Based on the concept of 'Mendelian randomisation', this observation supports the hypothesis that hyperhomocysteinaemia is a causal risk factor for venous thrombosis. The results of one homocysteine-lowering trial regarding venous thrombosis are awaited at the end of 2003. In this paper the current evidence for hyperhomocysteinaemia as a risk factor for venous thrombosis is being discussed.

Humans↗

PubMed2025

Steroid hormone biosynthesis and dietary related metabolites associated with excessive daytime sleepiness.

BACKGROUND: Excessive daytime sleepiness (EDS) is a complex sleep problem that affects approximately 33% of the United States population. Although EDS usually occurs in conjunction with insufficient sleep and other sleep and circadian disorders, recent studies have shown unique genetic markers and metabolic pathways underlying EDS. Here, we aimed to further elucidate the biological profile of EDS using large-scale single- and pathway-level metabolomics analyses. METHODS: Metabolomics data were available for 877 metabolites in 6071 individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). EDS was assessed using the Epworth Sleepiness Scale (ESS) questionnaire. We performed linear regression for each metabolite on the continuous ESS score, adjusting for demographic, lifestyle, and physiological confounders, and in sex specific groups. Subsequently, gaussian graphical modelling was performed coupled with pathway and enrichment analyses to generate a holistic interactive network of the metabolomic profile of EDS associations. FINDINGS: We identified seven metabolites belonging to steroids, sphingomyelin, and long-chain fatty acids sub-pathways in the primary model associated with EDS, and an additional three metabolites in the male-specific analysis. INTERPRETATION: Our findings indicate that an EDS metabolomic profile is characterised by endogenous and dietary metabolites within the steroid hormone biosynthesis pathway, with some pathways that differ by sex. These pathways may be useful for understanding the causes or consequences of EDS and related sleep disorders. FUNDING: Details regarding funding supporting this work and all studies involved are provided in the acknowledgements section.

Humans↗