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PubMed2025

From genetic causality to druggable targets: A multiomics framework identifies ZSCAN16 in gout pathogenesis.

ObjectiveGout is a prevalent form of inflammatory arthritis in which many patients respond suboptimally to current therapies. Drug development is hampered by a lack of genetically validated targets, leading to high clinical trial attrition. This study aimed to systematically identify and prioritize novel, druggable targets for gout via a multilayered genetic and functional genomics approach.MethodsWe performed two-sample Mendelian randomization (MR) using cis-expression quantitative trait locus (cis-eQTL) data and dual independent gout genome-wide association study (GWAS) cohorts (openGWAS and FinnGen). The candidate genes were subjected to a rigorous validation pipeline including Bayesian colocalization, phenome-wide association studies (PheWASs) to assess pleiotropy and on-target safety, and single-cell RNA sequencing (scRNA-seq) to delineate the cellular context. Molecular docking was used to evaluate the structural druggability of prioritized targets.ResultsMR analysis revealed 15 genes causally associated with gout. Colocalization analysis (PPH4 > 0.8) prioritized two targets: ZSCAN16 (risk-increasing, OR = 1.04, 95% CI [1.02-1.06]) and TRIM10 (protective, OR = 0.96, 95% CI [0.94-0.98]). Crucially, PheWAS revealed that ZSCAN16 is highly specific to gout, whereas TRIM10 exhibited extensive pleiotropy with hematological and cardiometabolic traits, indicating significant safety risks. Single-cell analysis provided orthogonal validation, demonstrating flare-specific upregulation of ZSCAN16 in cytotoxic T/NK cells. Molecular docking confirmed ZSCAN16 as a structurally druggable target, showing high-affinity binding with known compounds (e.g. digoxin, binding energy = -9.6 kcal/mol).ConclusionsOur study identifies ZSCAN16 as a high-potential, druggable therapeutic target for gout, highlighting its genetic influence on specific immune cell activities during acute flares. Conversely, TRIM10 was deprioritized owing to substantial pleiotropic liabilities and poor chemical tractability. These findings suggest that ZSCAN16 could play a crucial role in the pathogenesis of gout and may provide a valuable lead for future drug discovery efforts.

Humans↗

PubMed2026

The bidirectional genetic causality between immunocyte phenotypes and dilated cardiomyopathy: A bidirectional Mendelian randomization study.

The association between immunocyte phenotypes and dilated cardiomyopathy (DCM) has been explored, however the exact pathogenesis of the relationship between immune cells and DCM is unclear. This bidirectional two-sample Mendelian randomization (MR) research aims to further validate the causal link between 731 immunocyte phenotypes and DCM. Summary statistics from a genome-wide association study data of individuals with European ancestry were utilized, including 1444 DCM cases and 353,937 controls, as well as 3757 European adults for the 731 immunocyte phenotypes. Causal effects were estimated using inverse variance weighted, MR-Egger regression, weight median estimator, weighted mode, and simple mode. Sensitivity analysis was conducted to confirm data robustness and feasibility. Based on the inverse variance weighted findings, 14 immunocyte phenotypes were risk factors for DCM (P < .05, odds ratio [OR] > 1), while 15 immunocyte phenotypes exhibited a protective effect on DCM (P < .05, OR < 1). The results of reverse MR analysis suggested evidence that DCM occurrence might elevate the levels of 17 immunocyte phenotypes (P < .05, OR > 1) and decrease the levels of 9 immunocyte phenotypes (P < .05, OR < 1). Our research indicated that CD28 on secreting regulatory T cell could mitigate the occurrence of DCM, and reciprocally, the progression of DCM could reduce the level of CD28 on secreting regulatory T cell. This study confirmed the bidirectional genetic predictive relationship between immunocyte phenotypes and DCM, underscoring the complex interplay between DCM and the immune system.

Cardiomyopathy, Dilated↗

PubMed2026

Identifying causal genetic variants for high-altitude adaptation through blood eQTL analysis in plateau populations.

A substantial number of genetic variants have been associated with high-altitude adaptation (HAA), yet most of them are located in non-coding genomic regions, leaving their specific functions and underlying mechanisms largely unknown. In this study, we analyze whole-genome and transcriptome sequencing data from a self-established cohort comprising 61 native highlanders (NHs) and 164 acclimatized newcomers (ANs), identifying 6,586 cis- and 34,203 trans-expression quantitative trait loci (eQTLs), along with 130 cell type-specific eQTLs. By further combining these data with a large East Asia (~30% Tibetan) genome-wide association study (GWAS) cohort, we employ colocalization and causal inference analyses to prioritize 85 cis-eQTLs associated with HAA and identify several novel candidate causal genes, including EXOC8, which is experimentally confirmed to regulate erythroid differentiation. Additionally, network analysis of these causal genes uncovers multiple regulatory pathways, mainly involving energy metabolism, autophagy, ubiquitination and inflammation. Our study offers a comprehensive eQTL map and reveals causal chains of "variant-gene-phenotype" for HAA-related traits, which provides new insights into potential regulatory mechanisms and targets for prevention and treatment of altitude sickness.

Quantitative Trait Loci↗

PubMed2026

Sex differences in the genetic and causal relationships between depression, smoking, and alcohol use: the role of socioeconomic status.

Major depressive disorder (MDD), smoking, and drinking frequently co-occur, with evidence suggesting these relationships may differ by sex. However, the direction of causality and the extent of sex-specific associations remain unclear. We investigated sex-specific genetic relationships between MDD and substance use phenotypes using genome-wide association studies (GWAS) from the UK Biobank and publicly available sex-stratified GWAS for MDD and problematic alcohol use (PAU). Causal effects were assessed using bidirectional, sex-stratified Mendelian randomization (MR). We further applied multivariable MR (MVMR) to evaluate the influence of socioeconomic status (SES). Genetic correlation analyses indicated significant shared genetic architecture between MDD and all substance use traits in sex-combined GWAS. In sex-specific analyses, the correlation between cigarettes per day and MDD was significantly stronger in females, and drinks per week were correlated with MDD only in females. MR analyses showed that genetic liability to MDD increased the risk of smoking initiation and PAU in females, and was associated with reduced alcohol drinking frequency in males. In contrast, no tested substance use trait showed evidence of a causal effect on MDD in either sex. MVMR adjusting for SES attenuated the association between MDD and smoking initiation. The effect on PAU in females remained. In males, the negative association between MDD and drinking frequency became non-significant after SES adjustment. These findings reveal sex-specific genetic and causal relationships between smoking, drinking, and MDD, and highlight the role of SES as a potential confounder. Incorporating sex and socioeconomic context is critical when examining these associations.

Humans↗

PubMed2024

Risk relationship between inflammatory bowel disease and urolithiasis: A two-sample Mendelian randomization study.

BACKGROUND: The causal genetic relationship between common parenteral manifestations of inflammatory bowel disease (IBD) and urolithiasis remains unclear because their timing is difficult to determine. This study investigated the causal genetic association between IBD and urolithiasis using Mendelian randomization (MR) based on data from large population-based genome-wide association studies (GWASs). METHODS: A two-sample MR analysis was performed to assess the potential relationship between IBD and urolithiasis. Specific single nucleotide polymorphism data were obtained from GWASs, including IBD (n = 59957) and its main subtypes, Crohn's disease (CD) (n = 40266) and ulcerative colitis (UC) (n = 45975). Summarized data on urolithiasis (n = 218792) were obtained from different GWAS studies. A random-effects model was analyzed using inverse-variance weighting, MR-Egger, and weighted medians. RESULTS: Genetic predisposition to IBD and the risk of urolithiasis were significantly associated [odds ratio (OR), 1.04 (95% confidence interval [CI], 1.00-.08), P = 0.01]. Consistently, the weighted median method yielded similar results [OR, 1.06 (95% CI, 1.00-1.12), P = 0.02]. The MR-Egger method also demonstrated comparable findings [OR, 1.02 (95% CI, 0.96-1.08), P = 0.45]. Both funnel plots and MR-Egger intercepts indicated no directional pleiotropic effects between IBD and urolithiasis. CD was strongly associated with it in its subtype analysis [OR, 1.04 (95% CI, 1.01-1.07), P = 0.01], and UC was also causally associated with urolithiasis, although the association was not significant [OR, 0.99 (95% CI, 0.95-1.03), P = 0.71]. CONCLUSION: A unidirectional positive causal correlation was identified between IBD and urolithiasis, with varying degrees of association observed among the different subtypes of IBD. Recognizing the increased incidence of urolithiasis in patients with IBD is crucial in clinical practice. Early detection and surveillance of IBD, improved patient awareness, adoption of preventive strategies, and promotion of collaborative efforts among healthcare providers regarding treatment methodologies are vital for improving patient outcomes.

Humans↗

PubMed2026

Causality between genetically predicted type 2 diabetes and ankle fracture risk: A 2-sample Mendelian randomization study.

It has been proven that diabetes mellitus plays an important role in the occurrence and development of joint fractures. In this study, a 2-sample Mendelian randomization (MR) analysis was conducted to investigate the causal relationship between diabetes and ankle fractures. We pooled the data from the published genome-wide association studies. Diabetes mellitus type 2 was derived from pooled genome-wide association study data of 655,666 European individuals (61,714 patients and 1178 controls). Data on ankle fractures were derived from pooled genome-wide association study data in a total of 460,340 European individuals (6479 patients and 453,861 controls). Using diabetes-associated loci as instrumental variables, we used inverse variance weighting, MR-Egger, weighted median, simple multivariate analysis and weighted multivariate analysis to evaluate the association between diabetes and ankle fracture risk. Reverse MR analysis was performed on the Diabetes mellitus type 2 that were found to be causally associated with ankle fractures in forward MR analysis. Sensitivity analysis was used to evaluate the robustness of the results. Statistical analysis showed a significant causal relationship between diabetes and ankle fractures (inverse variance weighting: OR = 1.07, 95% CI = 1.01-1.32, P = .02). Diabetes mellitus is associated with an increased risk of ankle fracture. The results of MR analysis can be used as a guide for the screening of diabetes and ankle fractures, which is helpful to improve the awareness of screening, early diagnosis and early treatment.

Humans↗

PubMed2025

Post-traumatic stress disorder and REM-sleep behavior disorder: exploring genetic associations and causal links.

OBJECTIVE: To explore potential genetic and/or causal associations between Post-Traumatic Stress Disorder and neurodegeneration-related isolated/idiopathic rapid-eye-movement sleep behavior disorder. METHODS: We conducted polygenic risk score, genetic correlation, and Mendelian randomization analyses using the latest genome-wide association studies summary statistics and individual genotyping data. Next, a blinded observer examined dopamine transporter imaging binding status-a marker of neurodegeneration-in patients with isolated/idiopathic rapid-eye movement sleep behavior disorder, with (N = 6) and without Post-Traumatic Stress Disorder (N = 32). RESULTS: Polygenic risk scores for Post-Traumatic Stress Disorder were associated with isolated/idiopathic rapid-eye-movement sleep behavior disorder, with each standard deviation increase linked to 14.7% higher odds (odds ratio = 1.15, 95% confidence interval: 1.04 to 1.26, p = 0.005). However, genetic correlation was weak, and Mendelian randomization did not support a potential causal relationship. The proportion of individuals with abnormal dopamine transporter imaging binding status was significantly higher in the Post-Traumatic Stress Disorder group compared to those without the disorder (p=0.01, X2 = 6.62). INTERPRETATION: Polygenic risk scores analysis identified an association between Post-Traumatic Stress Disorder and neurodegeneration-related isolated/idiopathic rapid-eye-movement sleep behavior disorder, consistent with the result from the small exploratory substudy. The lack of strong genetic correlation or causation may reflect limited sample size. Further research with larger and more diverse cohorts is crucial to clarify the genetic, biological and physiological mechanisms underlying this association.

Journal Article↗

PubMed2026

Genetic Evidence That Stroke Causally Increases Circulating PDGFB Levels: a Two-Sample Mendelian Randomization Study.

Platelet-derived growth factor subunit B (PDGFB) is a key regulator of vascular remodeling, angiogenesis, and blood-brain barrier integrity. Although elevated PDGFB levels have been reported after ischemic injury, whether stroke liability itself causally influences circulating PDGFB levels remains unclear. We performed a two-sample Mendelian randomization (MR) analysis to assess the causal effects of genetically predicted all stroke, ischemic stroke, and cardioembolic stroke on plasma PDGFB concentrations. Genetic instruments were obtained from large-scale GIGASTROKE genome-wide association studies, and outcome data were derived from a proteomics GWAS. Instruments were then filtered by removing variants associated with established cardiovascular risk factors in a phenome-wide screen and outliers identified by RadialMR. The inverse variance-weighted (IVW) method was used as the primary analysis, complemented by weighted median, weighted mode, and MR-Egger approaches. Sensitivity analyses included Cochran's Q statistics, MR-Egger intercept tests, single-SNP analyses, leave-one-out analyses, and MR-PRESSO. IVW analysis demonstrated a significant positive causal association between genetic liability to all stroke and plasma PDGFB levels (β = 0.209, SE = 0.062, 95% CI 0.088 to 0.331, p = 7.3 × 10-4). A similar association was observed for ischemic stroke (β = 0.155, SE = 0.059, 95% CI 0.039 to 0.270, p = 0.009), with directionally consistent results across sensitivity analyses. MR-Egger regression for ischemic stroke initially suggested pleiotropy.After removal of a radial-MR outlier (rs2289252), the intercept was attenuated and no longer statistically significant (- 0.0190, p = 0.282). In contrast, no evidence of a causal association was found between cardioembolic stroke liability and plasma PDGFB levels across all MR methods (β = - 0.078, SE = 0.087, 95% CI - 0.248 to 0.092, p = 0.368). These findings provide genetic evidence that liability to stroke, particularly ischemic stroke, is causally associated with increased circulating PDGFB levels, whereas cardioembolic stroke does not show such an effect. This suggests that elevated PDGFB reflects vascular responses specific to ischemic stroke rather than a general consequence of all stroke subtypes.

Humans↗

PubMed2026

Immune cell-specific genetic architecture of Alzheimer's disease revealed by multi-omics analysis for therapeutic target discovery and prioritization.

Alzheimer's disease (AD) is a multifactorial neurodegenerative condition in which accumulating genetic and molecular evidence implicates dysregulation of peripheral immune processes in disease pathogenesis. Nevertheless, the contribution of distinct peripheral immune cell subsets and associated gene regulatory landscapes to AD risk remains incompletely defined. To address this gap, we integrated single-cell expression quantitative trait loci (sc‑eQTL) data from the OneK1K cohort with AD GWAS summary statistics. We systematically interrogated immune cell-specific genes for their contributions to AD risk by integrating genetic causal inference with Bayesian colocalization analyses, and identified 24 eGenes that passed both the MR significance threshold (P < 0.05) and the criterion for strong shared genetic signals (PP.H4 > 0.8). Notable candidates included GATS, HLA-DOB, HLA-DQA1, PM20D1, and others, with each gene demonstrating a cell-type-specific association restricted to its corresponding immune cell type, such as monocytes, CD8 + T cells, or B cells. Independent peripheral blood single-cell transcriptomic data further supported disease-associated shifts in cell-type-specific expression patterns in AD. Phenome-wide association studies (PheWAS) indicated limited associations with off-target traits, indicating a favorable safety profile for therapeutic intervention, with the exceptions of B4GALNT3, PM20D1, and CNN2. Integration of immune gene targets with pharmacological databases yielded three candidate compound, including NSC321521 (targeting HLA-DQA1), phenoxybenzamine (targeting GSTP1), and rimexolone (targeting BIN1). Among these compounds, Predicted blood-brain barrier permeability was observed only for phenoxybenzamine and rimexolone, with docking studies indicating stable interactions, such as those between NSC321521 and HLA-DQA1, phenoxybenzamine and GSTP1, and rimexolone and BIN1. This integrative approach highlights key immune‑cell‑specific genes involved in AD and proposes repurposable drugs with central nervous system potential, paving the way for more targeted immunomodulatory strategies in AD.

Humans↗

PubMed2025

Whole-genome phenotype prediction with machine learning: open problems in bacterial genomics.

MOTIVATION: How can we identify causal genetic mechanisms governing bacterial traits? Initial efforts entrusting machine learning models to handle the task of predicting phenotype from genotype yield high accuracy scores. However, attempts to extract meaningful interpretations from the predictive models are found to be corrupted by falsely identified 'causal' features. Relying solely on pattern recognition and correlations is unreliable, significantly so in bacterial genomics settings where high-dimensionality and spurious associations are the norm. Though it is not yet clear whether we can overcome this hurdle, significant efforts are being made towards discovering potential high-risk bacterial genetic variants. In view of this, we set up open problems surrounding phenotype prediction from bacterial whole-genome datasets and extending those approaches to learning causal effects, and discuss challenges that impact the reliability of a machine's decision-making when faced with datasets of this nature. RESULTS: We identify major sources of non-injectivity in the formulation of the genotype-to-phenotype mapping function-linkage-disequilibrium, limited sampling, information loss in representations, unmeasured confounders and observational noise-and analyse their implications for machine learning applications. Using a collection of 4,140 Staphylococcus aureus isolates, we illustrate challenges surrounding the defined open problems. AVAILABILITY AND IMPLEMENTATION: Raw sequencing data are available from the European Nucleotide Archive (ENA) under project accessions ERP001012, PRJEB3174, PRJEB2655, PRJEB2756, and PRJEB2944. Assemblies and annotations were generated with the Sanger bacterial pipeline (https://github.com/sanger-pathogens/vr-codebase) and unitigs extracted using DBGWAS (https://gitlab.com/leoisl/dbgwas).

Machine Learning↗

PubMed2025

Towards improved fine-mapping of candidate causal variants.

Fine-mapping in genome-wide association studies aims to identify potentially causal genetic variants among a set of candidate variants that are often highly correlated with each other owing to linkage disequilibrium. A variety of statistical approaches are used in fine-mapping, almost all of which are based on a multiple regression framework to model the relationship between genotype and phenotype, while accommodating specific assumptions about the distribution of variant effect sizes and using different inference algorithms. Owing to their modelling flexibility and the ease of making inferential statements, these approaches are predominantly Bayesian in nature. Recently, these approaches have been improved by refining modelling assumptions, integrating additional information, accommodating summary statistics, and developing scalable computational algorithms that improve computation efficiency and fine-mapping resolution.

Humans↗

PubMed2025

Enhancer-targeting CRISPR screens at coronary artery disease loci suggest shared mechanisms of disease risk.

To systematically identify causal genetic mechanisms that confer risk for coronary artery disease (CAD) in GWAS loci, we mapped genome-wide variant-to-enhancer-to-gene (V2E2G) links in vascular smooth muscle cells (SMC). Enhancers identified by active chromatin features, and further prioritized by base-resolution deep learning models of chromatin accessibility in 108 CAD loci, were studied with CRISPRi targeting and Direct-Capture Targeted Perturb-seq (DC-TAP-seq) evaluation of 470 genes. Seventy-six V2E2G links were identified for 59 candidate CAD genes representing gene programs including epithelial-mesenchymal transformation, ubiquitination, and protein folding as well as BMP and TGFB signaling. Similar methods employed with an independent focused screen targeting one candidate locus at 9p21.3 identified 10 enhancers regulating expression of multiple genes at this location. Detailed molecular studies revealed that two enhancers mediating transcription factor binding and transcriptional regulation contribute to ancestry-specific and sex-specific risk for CAD and the surrogate biomarker vascular calcification. Together, these studies advance our identification of GWAS CAD V2E2G links across the genome, and specific mechanisms of risk at the complex 9p21.3 locus.

Journal Article↗

PubMed2025

Shared genetic risk and causal associations between Post-traumatic stress disorder and migraine with antithrombotic agents and other medications.

Post-traumatic stress disorder (PTSD) is a psychiatric disorder that frequently co-occurs with pain disorders including migraine. There are proposed biological, genetic and environmental factors associated with both PTSD and migraine suggesting shared etiology. Genome-Wide Association Studies (GWAS) have been used to identify genomic risk loci associated with various disorders and to investigate genetic overlap between traits. There is a significant genetic correlation between PTSD and migraine with no evidence of a causal relationship that could be attributed to pleiotropy. Cross-disorder genetic analyses were applied to investigate the genetic overlap and causal associations using GWAS summary statistics of PTSD (n = 214408), migraine (n = 873341) and 23 medication use traits (n = 78808-305913) including anti-depressants, anti-migraine preparations and beta-blocking agents. Across the entire genome, anti-thrombotic agents had a significant and negative genetic correlation with PTSD (rG = -0.2, P FDR = 0.032) and a positive genetic correlation with migraine (rG = 0.26, P FDR = 2.23 x 10-8). PTSD showed significant genetic correlation with 11 other medication use traits including beta blocking agents (rG = -0.11, P FDR = 0.034). Of the 2495 genomic regions tested, PTSD showed significant local genetic correlation with 12 medication use traits at 43 loci; while migraine showed significant genetic correlation with only anti-inflammatory agents and anti-rheumatic products at locus 12:57522282-57607142 (DAB1) (P < 2 x 10-5). The genetic liability to PTSD had a causal effect on increased risk of using pain medication such as opioids (β ivw = 0.59, P = 5.21 x 10-5) while the genetic liability to migraine had a causal effect on the increased risk of using anti-thrombotic agents (β ivw = 0.59, P = 1.69 x 10-7). The genes in the genomic regions shared between PTSD and medication use traits were enriched in neural-related pathways such as neuron development, neurogenesis and protein kinase activity. These results provide further insight into the genetically controlled biological and environmental factors underlying the shared etiology between PTSD and migraine. The identified biomarkers can be used as a basis for investigation as potential drug targets for both disorders. These findings are significant for drug re-purposing and treatment of PTSD and migraine using monotherapy.

GWAS↗

PubMed2025

Assessing the causal effect of genetically predicted metabolites and metabolic pathways on vitiligo: Evidence from Mendelian randomization and animal experiments.

Vitiligo is a common chronic skin depigmentation disorder that seriously decreases the patients' overall quality of life. Human blood metabolites could contribute to unraveling the underlying biological mechanisms of vitiligo. We used GWAS summary statistics to assess the causal association between genetically predicted 1400 serum metabolites and vitiligo risk by Mendelian randomization (MR). Then, after constructing the mouse model of vitiligo, we did non-targeted metabolomics analysis on the mouse serum and validated MR's pathway enrichment results ulteriorly. In the initial phase, MR analysis revealed causative associations between 36 metabolites and vitiligo risk, including 8 metabolite ratios and 28 individual metabolites (19 known and 9 unknown metabolites). In the validation stage, 7 metabolites were successfully validated. Of the 28 individual metabolites, most are related to lipid metabolism. Genetically predicted higher 4-oxo-retinoic acid showed the strongest protective effect on vitiligo, while the most potent risk effect was the increase in quinate. The metabolites associated with vitiligo risk are mainly enriched in alpha-linolenic acid metabolism, linoleic acid metabolism, arginine biosynthesis and metabolism pathways, validated through the serum metabolomics of vitiligo mouse. By integrating genomics and metabolomics, this study provides new insights into the association between metabolites and vitiligo, highlighting the potential roles of specific metabolites in the pathogenesis of vitiligo. These metabolites associated with vitiligo could serve as new biomarkers, further research could help to reveal how these metabolites influence specific pathways in the development of vitiligo.

Animals↗

PubMed2026

Mapping the causal chain from genetic risk variants to lipid dysmetabolism in Parkinson's disease.

The molecular pathways linking genetic variants to Parkinson's disease (PD) onset and progression remain incompletely defined; however, risk alleles in multiple genes, including GBA1, strongly implicate lipid metabolism. To systematically identify causal biomarker signatures, we analysed comprehensive metabolome profiles from blood plasma in 149 PD patients and 150 controls, along with complementary genetic, RNA-sequencing and metabolic data from other available clinical and pathologic cohorts. Using colocalization and summary-data-based Mendelian randomization, we tested whether expression and metabolic quantitative trait loci mediate the association between implicated genetic variants and PD risk. We further integrated differential metabolomics and proteomics from blood and brain to reveal pertinent mechanisms. We show that common PD risk variants at the serine palmitoyltransferase small subunit B (SPTSSB) locus, a key regulator of de novo sphingolipid biosynthesis, are associated with increased SPTSSB brain expression and elevated plasma ceramides. Additional analyses strongly support our hypothesis that a common SPTSSB causal variant is responsible for PD risk as well as the expression and metabolic quantitative trait loci. Multiple sphingolipids and fatty acid derivatives were perturbed in PD, and we identified both unique and shared features with the Alzheimer's disease metabolome. A PD acylcarnitine signature was further replicated in human post-mortem brain tissue, when comparing those with or without preclinical Lewy body pathology. Integrated analysis of complementary brain proteomic profiles revealed dysregulation of mitochondrial processes dependent on acylcarnitines, including fatty acid beta-oxidation, the tricarboxylic acid cycle and oxidative phosphorylation. Our results identify promising biomarkers and reveal a causal chain linking genetic variation to altered gene/protein expression, lipid dysmetabolism, and the manifestation of PD.

Humans↗

PubMed2026

Genetic evidence for causality of late chronotype on metabolic syndrome in East Asians and Europeans.

CONTEXT: The impact of chronotype-defined as an individuals' inherent preference of sleep timing-and its genetic determinants on metabolic syndrome (MetS) has been less studied. OBJECTIVE: This study investigated the causal relationship between late chronotype and MetS using Mendelian randomization (MR) analysis, based on data from the Taiwan Biobank (TWB) and parallel analyses in the UK Biobank (UKB). METHODS: A total of 36,845 participants from TWB served as the discovery cohort, and 235,639 participants from UKB served as the replication cohort. Late chronotype was defined in TWB as a preference for bedtime after midnight, and in UKB as self-report as being an 'evening' person. The association between late chronotype and MetS, along with its components, was evaluated in TWB, and validated in UKB. Genome-wide association analyses for late chronotype were first conducted in TWB and then meta-analyzed with UKB. Polygenic risk scores (PRS) for late chronotype were constructed and tested for association with MetS. Causality between late chronotype and MetS was examined using one-sample MR analysis in TWB and validated in UKB. RESULTS: Late chronotype was significantly associated with MetS, as well as with central obesity, hyperglycemia, and hypertriglyceridemia, in both TWB and UKB (all P < 0.0083, considering Bonferroni correction). The constructed PRS of late chronotype also showed significant associations with MetS and several of its components (several P < 0.0083, considering Bonferroni correction). Findings from the one-sample MR analysis indicated a potential causal effect of late chronotype on MetS. CONCLUSIONS: This study provides evidence of a robust association between late chronotype and MetS across populations of diverse ancestry, including Taiwanese and European.

Humans↗

PubMed2026

Robust human genetic evidence supporting causal effects of FGF21 on reducing alcohol consuming behaviours.

BACKGROUND: Alcohol use disorder (AUD) represents a tremendous societal burden, yet few efficacious therapies are available and widely used. Pre-clinical and human observational data support fibroblast growth factor 21 (FGF21) as a promising therapeutic target for the treatment of AUD. The objective of this study is to identify a robust genetic instrument for FGF21 agonism and leverage it to explore the effects of FGF21 agonism on AUD and related traits, as well as metabolic outcomes more widely. METHODS: We first compared associations with the positive control outcomes of liver fat and liver cirrhosis risk for the FGF21 cis-protein quantitative trait locus (cis-pQTL) (rs838131) to those for the common allele FGF21 L174P missense variant (rs739320). Having identified the L174P missense variant as a plausible genetic instrument, we subsequently performed association analyses investigating effects on AUD, related traits, and metabolic outcomes more widely. Finally, we performed colocalisation analyses to test whether observed association results reflect a causal mechanism that overlaps with the clinical effects of FGF21 on liver fat and liver cirrhosis. RESULTS: Consistent association and colocalisation evidence support a protective association between genetically predicted FGF21 agonism and alcohol consumption (association p = 1 × 10-18, colocalisation posterior probability = 0.90), problematic alcohol use (association p = 0.02, posterior probability = 0.64), and AUD (association p = 9 × 10-8, posterior probability = 0.97). Similar evidence was also observed for favourable effects of FGF21 on improving kidney function, lowering triglyceride levels, lowering proportional energy intake from carbohydrates, increasing proportional energy intake from protein and fat, increasing body weight and lowering waist-to-hip ratio. CONCLUSIONS: This study identifies a genetic instrument for FGF21 effects to provide causal human evidence supporting favourable effects of FGF21 analogues for the treatment of AUD and related traits, as well as on metabolic outcomes more broadly. Further clinical study is duly warranted.

Humans↗

PubMed2024

Genetic evidence for causal association between migraine and dementia: a mendelian randomization study.

BACKGROUND: There is an association between migraine and dementia, however, their causal relationship remains unclear. This study employed bidirectional two-sample Mendelian randomization (MR) to investigate the potential causal relationship between migraine and dementia and its subtypes: Alzheimer's disease (AD), vascular dementia (VaD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB). METHODS: Summary-level statistics data were obtained from publicly available genome-wide association studies (GWAS) for both migraine and five types of dementia. Single nucleotide polymorphisms (SNPs) associated with migraine and each dementia subtype were selected. MR analysis was conducted using inverse variance weighting (IVW) and weighted median (WM) methods. Sensitivity analyses included Cochran's Q test, MR pleiotropy residual sum and outlier (MR-PRESSO) analysis, the intercept of MR-Egger, and leave-one-out analysis. RESULTS: Migraine showed a significant causal relationship with AD and VaD, whereas no causal relationship was observed with all-cause dementia, FTD, or DLB. Migraine may be a potential risk factor for AD (odds ratio [OR]: 1.09; 95% confidence interval [CI]: 0.02-0.14; P = 0.007), while VaD may be a potential risk factor for migraine (OR: 1.04; 95% CI: 0.02-0.06; P = 7.760E-5). Sensitivity analyses demonstrated the robustness of our findings. CONCLUSION: Our study suggest that migraine may have potential causal relationships with AD and VaD. Migraine may be a risk factor for AD, and VaD may be a risk factor for migraine. Our study contributes to unraveling the comprehensive genetic associations between migraine and various types of dementia, and our findings will enhance the academic understanding of the comorbidity between migraine and dementia.

Humans↗