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PubMed2026

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

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

Connectome↗

PubMed2026

Genetic overlap between estimated glomerular filtration rate and cardiovascular disease identifies potential targets for cardiorenal syndrome.

Heart and kidney diseases frequently coexist, but the genetic basis of this relationship remains unclear. We analyzed genetic data from large-scale studies to investigate how kidney function (estimated glomerular filtration rate, eGFR) and six common cardiovascular diseases share genetic risk factors. Using MiXeR method, and conjunctional false discovery rate (conjFDR) to identify overlapping genetic regions, we found 478 shared genomic loci between eGFR and cardiovascular diseases. These shared genes are involved in tissue development and structure. We also identified 29 genes that could be targeted by existing medications approved by the US Food and Drug Administration, such as PRKAG2, PDE1A, and IGF1R. Among these, genetically predicted higher level of IGF1R expression is associated with a higher eGFR, which reflects good kidney function and is protective against cardiorenal diseases, such as atrial fibrillation, and myocardial infarction. These findings reveal genetic overlap between kidney function and cardiovascular diseases, highlighting potential targets for understanding and treating cardiorenal syndrome.

Humans↗

PubMed2025

Deciphering the Impact of Temperature on Pleiotropic Consequences of RNA Polymerase Mutations.

Despite occurring in an essential molecule, mutations in RNA polymerase readily emerge and elicit complex pleiotropic effects across different levels of biological organization, which are all modulated by environment. We investigated the impact of temperature on the effects of six mutations on sequence, structure, transcriptome, and organismal traits. We found temperature altered the transcriptomic response and key organismal traits such as growth rate and biofilm formation in a genotype-specific manner. Critically, mechanistic insights into the possible drivers of mutational effects emerged only when examining the relationships between different levels of organization: location of mutations in the tertiary structure and distance to key interacting molecules partly explained the observed transcriptomic differences, which in turn drove the impact of mutations on organismal traits. While falling short of capturing the full complexity of the system, our findings underscore the benefits of integrating insights across multiple biological levels to understand the relationship between environment and mutational effects in molecules with extensive pleiotropic effects.

Mutation↗

PubMed2026

A genome-wide cross-trait analysis characterizes the shared genetic architecture between rheumatoid arthritis and psychiatric disorders.

OBJECTIVES: Patients with RA have a 2- to 3-fold elevated risk of psychiatric disorders, suggesting an underlying genetic link between these phenotypes. However, the shared genetic architectures and pathological mechanisms driving RA-psychiatric disorder comorbidity remain to be fully elucidated. Herein, we performed cross-trait analysis to investigate the shared genetic architecture between RA and psychiatric disorders. METHODS: Leveraging European-ancestry genome-wide association studies (GWASs) datasets of RA (n = 1 026 690) and 10 major psychiatric disorders (n = 14 307-1 222 882), we performed cross-trait pleiotropic analysis to identify the shared pleiotropic loci and genes between RA and psychiatric disorders, followed by functional annotation and Mendelian randomization analysis to explore the pathological mechanisms underlying RA-psychiatric disorder comorbidity. RESULTS: Our analysis revealed significant positive genetic correlations between RA and seven psychiatric disorders, such as major depressive disorder. From these correlations, we identified 61 pleiotropic loci jointly influencing RA and psychiatric disorder risk, along with 208 pleiotropic genes predominantly involved in immune and inflammatory response biological processes. Druggable target exploration identified 21 drug-gene interactions involving pleiotropic genes, with two genes (RHOA and TRAF3) classified in the clinically actionable category, representing potential therapeutic targets for both RA and psychiatric disorders. Mendelian randomization further demonstrated a bidirectional causal relationship between RA and schizophrenia, while supporting the causal roles of attention-deficit/hyperactivity disorder, major depressive disorder and post-traumatic stress disorder in increasing RA risk. CONCLUSION: Our findings elucidate the shared genetic architecture between RA and psychiatric disorders, providing novel insights into the pathological mechanisms underlying their comorbidity and laying the groundwork for improved comorbidity management.

Arthritis, Rheumatoid↗

PubMed2025

Shared Genetic Architecture Between Atopic Dermatitis and Autoimmune Diseases.

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

Humans↗

PubMed2026

Determinants of functional burden pleiotropy and gene dosage responses across human traits.

Pleiotropic and monotonic effects of gene dosage are central to understanding comorbidities in developmental pediatric and psychiatric disorders, yet the underlying biological processes are not well characterized. Here we develop a functional burden analysis to investigate the association of all protein-coding copy-number variants, genome-wide, with 43 complex traits in approximately 500,000 UK Biobank participants. We test variant associations disrupting 172 tissue or cell-type gene sets, finding associations for all traits, which we replicate in the All of Us cohort. Functional burden pleiotropy, defined as the number of traits significantly associated with a gene set, correlates with genetic constraint and is higher for brain than non-brain functions, even after normalizing for genetic constraint. Levels of pleiotropy, measured by burden correlation, are similar in deletions and loss-of-function single-nucleotide variants, and higher than in common variants and duplications. Most gene dosage responses are non-monotonic, with deletions and duplications showing same-direction effects, and monotonic responses decrease with genetic constraint. We observe associations between functional gene sets and traits for either deletions or duplications, but rarely both, with negatively correlated effect sizes. Together, these results link genetic constraint and brain-specific mechanisms to the whole-body multimorbidity of neurodevelopmental and psychiatric conditions.

Humans↗

PubMed2026

Genomic basis of developmental defects of enamel and sex-specific effects.

We conducted a multi-ancestry genome-wide association study (GWAS) of developmental defects of enamel (DDE) in the primary dentition among 6,061 U.S. preschool-aged children (3-5 years). We investigated four DDE phenotypes (demarcated opacities, diffuse opacities, hypoplastic defects, and a combined DDE trait) leveraging main-effect models, joint gene-sex interaction testing (2df), and sex-stratified analyses. SNP-based heritability for the combined DDE trait was estimated at 20%, with concordance analyses robustly supporting a genetic etiology. We identified 39 unique genome-wide significant loci (P<5×10 ), with five surpassing a study-wide Bonferroni-corrected statistical significance criterion (P<1.25×10 9), including Y RNA and ALDH1A1. The main-effect GWAS identified 20 loci, including HBS1L and MYB, genes regulating hematopoiesis with plausible roles in amelogenesis. Joint test and sex-stratified analyses revealed 19 additional loci, including ALDH1A1, TENM2, and DLGAP2, demonstrating sex-specific heterogeneity. Nineteen loci exhibited sex-specific differences after Bonferroni correction (P<2x10-3), including genes involved in retinoic acid signaling (ALDH1A1), odontogenesis (TENM2), and neurodevelopment (DLGAP2, CDH10). Pathway enrichment highlighted ectodermal and synapse organization networks, suggesting shared etiological mechanisms between DDE and systemic conditions like neurofibromatosis and autism spectrum disorder. Notably, no locus generalized in an external GWAS of permanent dentition DDE, underscoring fundamental biological differences in the genetic architectures governing primary versus permanent enamel formation. Crucially, a comprehensive cross-trait pleiotropy lookup against early childhood caries (ECC) revealed no shared genetic architecture, supporting the notion that the established clinical and epidemiological association between DDE and ECC is likely driven by structural defects increasing caries lesion susceptibility rather than genetic pleiotropy. By integrating gene-sex interaction testing, this study offers novel insights into the complex, sexually dimorphic genetic etiology of DDE and augments the biological evidence base that can support the development of precision pediatric dentistry.

developmental defects of enamel↗

PubMed2026

A Guide for Exploring Pleiotropic Associations in Genome-Wide Association Studies Using Summary Statistics.

Genome-wide association studies (GWAS) have shown that pleiotropy, whereby a single genetic variant or gene influences multiple traits, is common in complex human diseases. Detecting cross-phenotype associations from GWAS summary statistics remains challenging because of small effect sizes, extensive multiple testing, heterogeneous effects, and possible differences in effect direction across traits. Methods that jointly analyze multiple traits can improve the ability to detect pleiotropic signals while retaining the practical advantages of summary statistic-based analyses. Although a range of statistical approaches has been developed for this purpose, practical guidance on their application, assumptions, and interpretation remains limited. This tutorial reviews several widely used methods for pleiotropy detection from GWAS summary statistics, including ASSET, PLACO, GPA, CPBayes, and GCPBayes, and demonstrates their application using breast and thyroid cancer datasets. We also highlight the importance of accounting for effect heterogeneity, correlation, and biological group structure at the gene and pathway levels in the detection and interpretation of pleiotropic association signals.

Genome-Wide Association Study↗

PubMed2025

Saturating the eQTL map in Drosophila: Genome-wide patterns of cis and trans regulation of transcriptional variation in outbred populations.

Most genetic polymorphisms associated with complex traits are found in non-coding regions of the genome. Characterizing their effect presents a formidable challenge, and expression quantitative trait locus (eQTLs) mapping has been a key approach to do so. As comprehensive eQTL maps are available only for a few species, here we developed the Drosophila outbred synthetic population (Dros-OSP) and used it to characterize the landscape of transcriptional regulation in Drosophila melanogaster. We collected head and body transcriptomes and genomes from 1,286 outbred flies and mapped local and distant eQTLs for 98% of the genes. We characterized the network organization of the transcriptome across tissues and described the properties of local and distal eQTLs in terms of genetic diversity, heritability, connectivity, and pleiotropy. These results provide new insights into the genetic basis of transcriptional regulation in the fruit fly and offer a new mapping resource that will expand the possibilities currently available for the Drosophila community.

Animals↗

PubMed2026

A flexible framework for robust and efficient Mendelian randomization with debiasing.

Mendelian randomization (MR) has been widely used to infer causal relationships between exposures and outcomes in epidemiological studies. However, classical MR assumptions can be violated when genetic variants are associated with outcomes through pathways other than the exposure, leading to uncorrelated and/or correlated pleiotropy. Additionally, measurement error arising from the inherent uncertainty in summary statistics obtained from large-scale genome-wide association studies can introduce bias into the causal effect estimate. To address these issues, we develop a debiased mixture inverse variance weighting ($\mathsf{dmIVW}$) method with three major advantages. First, it is capable of simultaneously handling various types of pleiotropy and eliminating the bias caused by uncertainty. Second, it can guard against distortion caused by invalid genetic variants while effectively harnessing their information. Third, our unified framework facilitates a fair comparison and combination of a series of submodels, encompassing several popular MR methods as special cases. Through real data applications, the effectiveness and robustness of $\mathsf{dmIVW}$ in estimating the causal effects of risk factors on common diseases are demonstrated.

Mendelian Randomization Analysis↗

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↗

PubMed2026

Shared genetic architecture and cellular convergence between female reproductive disorders and pulmonary function: a genome-wide cross-trait analysis.

Female reproductive disorders (FRDs), including polycystic ovary syndrome, endometriosis, uterine leiomyomata, and infertility, have been epidemiologically associated with impaired pulmonary function. However, it remains unclear whether this cross-organ link reflects shared genetic etiology and, if so, which cellular mechanisms mediate it. We performed a systematic genome-wide cross-trait analysis of three FRDs and lung function traits (FEV₁, FVC, FEV₁/FVC) using GWAS summary statistics from individuals of European ancestry, integrating genetic correlation, bidirectional causal inference, pleiotropy mapping, and single-cell enrichment analyses. We identified significant negative genetic correlations between FRDs and lung volume traits, most prominently for FVC (rg range: - 0.077 to - 0.178). Bidirectional causal analyses indicated that FRDs have a detrimental effect on lung volume, with higher FRD genetic liability associated with reduced lung volume. Cross-trait meta-analysis identified 17 pleiotropic variants across 11 loci, with the 19q13.2 (LTBP4) and 12q13.13 (HOXC6/HOXC9) loci showing strong evidence of shared causal variants. Critically, single-cell analyses revealed that shared genetic risk converged on mesenchymal lineages across organs, specifically alveolar adventitial fibroblasts in the lung and stromal/smooth muscle cells in the endometrium. Transcriptome-wide analyses further nominated the estrogen-responsive gene RERG as a convergent gene linking these conditions with lung function. Our study revealed a shared genetic architecture between female reproductive disorders and lung function traits, providing a basis for further mechanistic investigations and potential clinical evaluation. Furthermore, our findings suggest that shared fibroproliferative and hormone-responsive pathways may offer insights into the biological mechanisms underlying these conditions.

Female↗

PubMed2025

Robust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk.

BACKGROUND: Polygenic risk score (PRS) have proved to offer robust risk prediction for coronary artery disease (CAD). However, the global CAD PRS summarizes the joint effects of all the markers in the genome, masking potential genetic heterogeneity that may be important for disease interpretation and targeted interventions. METHODS: Using summary-level data, we identified 43 significant CAD-related traits based on genetic correlations, and further classified them into eight pleiotropy clusters based on their biological functions. We then partitioned the genome into 2,353 near-independent regions. Variants in each region were assigned to the trait most genetically similar to CAD, and then were labeled with the corresponding pleiotropy cluster. We grouped variants without labels into a ninth, non-specific cluster. The Pleiotropy Decomposed (PD) PRSs for each of the nine clusters were calculated using variants assigned to each cluster for 407,903 samples of European ancestry from the UK Biobank (UKBB). RESULTS: We decomposed the CAD PRS into nine PD-PRSs and further stratified individuals with high CAD-PRS into nine subgroups. Each PD-PRS accounted for a higher proportion of the global CAD-PRS within its corresponding subgroup than in the remaining subjects with high CAD-PRS (e.g., 25.2% (0.07) vs. 10.06% (0.07) for lipids-PD-PRS). Additionally, these subgroups showed distinct clinical features. For example, in the lipids-related subgroup, lipoprotein(a) and LDL-cholesterol levels were 67.5% and 18.3% higher, respectively, compared to the remaining high-risk individuals. Furthermore, significant interactions were observed between blood pressure and BP PD-PRS, and between current smoking and respiratory system PD-PRS. CONCLUSION: Our findings suggest that PD-PRSs may reveal substantial genetic and phenotypic heterogeneity among individuals with high CAD-PRS. The unique PD-PRS compositions of each individual can highlight the relative importance of different pleiotropic regions.

Humans↗

PubMed2026

Common genetic variants are associated with increased likelihood of latent co-occurring neurodevelopmental and mental health factors among autistic individuals.

Autistic individuals show elevated rates of co-occurring neurodevelopmental and mental health conditions, yet the genetic architecture of those comorbidities remains unclear. Using phenotypic (N = 74,204) and genetic (N = 17,582) data from the SPARK study, we investigated the factor structure, heritability, genetic correlation with autism (pleiotropy) and corresponding conditions in the general population (additivity). First, confirmatory factor analysis identified three correlated factors mirroring general population patterns: behavioural (ADHD, disruptive behaviour disorders), cothymic (depression, anxiety), and thought disorder (schizophrenia, bipolar). Second, all three factors had significant SNP heritabilities whilst rare variants were not associated with the tested factors in our sample. Third, polygenic scores and genetic correlations revealed positive shared genetics between the three factors and corresponding conditions in the general population but not with autism, supporting the additivity hypothesis. Fourth, within-family analyses (N = 5236 trios) demonstrated direct but not indirect genetic effects for the behavioural and cothymic factors. In sum, we find evidence for additive effects of other genetic factors in contributing to some latent co-occurring neurodevelopmental and mental health conditions in autism.

Journal Article↗

PubMed2026

Genetic Evidence Links Sex Hormone-binding Globulin to Total Body Bone Mineral Density at Age 45-60 Years: A Two-sample Mendelian Randomization Study.

The menopausal transition and early postmenopause represent important periods for women's skeletal health, but the genetic relevance of metabolic, behavioral, and hormone-related factors to bone mineral density during midlife remains incompletely understood. This study used publicly available genome-wide association study summary statistics to examine associations between body mass index, 25-hydroxyvitamin D, sex hormone-binding globulin, high-density lipoprotein cholesterol, smoking initiation, and alcohol intake frequency and total body bone mineral density at ages 45-60 years. Exposure genome-wide association study summary statistics were derived from large European-ancestry populations and were not restricted to midlife women, whereas the outcome genome-wide association study captured an age-stratified total body bone mineral density phenotype at age 45-60 years. This age range overlaps with the menopausal transition and early postmenopause in women. Univariable, reverse, and multivariable Mendelian randomization analyses were performed, with inverse-variance weighting as the primary method and complementary sensitivity analyses used to assess heterogeneity, pleiotropy, and result stability. Genetically predicted higher sex hormone-binding globulin was associated with lower total body bone mineral density (β = -0.111, 95% CI: -0.170 to -0.051; P = 0.0003). Reverse Mendelian randomization did not support reverse causation from bone mineral density to sex hormone-binding globulin. Multivariable analyses suggested that this association persisted after adjustment for selected metabolic biomarkers. The other examined exposures did not show consistent evidence of association. These findings provide genetic evidence linking sex hormone-binding globulin to total-body bone mineral density at ages 45-60 years. Further prospective and predictive studies are needed to evaluate its clinical relevance beyond established bone health assessment tools.

Humans↗

PubMed2025

Meta-analysis models with group structure for pleiotropy detection at gene and variant level using summary statistics from multiple datasets.

Genome-wide association studies (GWASs) have highlighted the importance of pleiotropy in human diseases, where one gene can impact 2 or more unrelated traits. Examining shared genetic risk factors across multiple diseases can enhance our understanding of these conditions by pinpointing new genes and biological pathways involved. Furthermore, with an increasing wealth of GWAS summary statistics available to the scientific community, leveraging these findings across multiple phenotypes could unveil novel pleiotropic associations. Existing selection methods examine pleiotropic associations one by one at a scale of either the genetic variant or the gene, and thus cannot consider all the genetic information at the same time. To address this limitation, we propose a new approach called MPSG (Meta-analysis model adapted for Pleiotropy Selection with Group structure). This method performs a penalized multivariate meta-analysis method adapted for pleiotropy and takes into account the group structure information nested in the data to select relevant variants and genes (or pathways) from all the genetic information. To do so, we implemented an alternating direction method of multipliers algorithm. We compared the performance of the method with other benchmark meta-analysis approaches such as GCPBayes, PLACO, and ASSET by considering as inputs different kinds of summary statistics. We provide an application of our method to the identification of potential pleiotropic genes between breast and thyroid cancers.

Humans↗

PubMed2024

Association between Branched-Chain amino acids and Epilepsy: A Mendelian randomized study.

BACKGROUND: Branched-chain amino acids (BCAAs) have been affected epilepsy, yet conclusions remain inconclusive, lacking causal evidence regarding whether BCAAs affect epilepsy. Systematic exploration of the causal relationship between BCAAs and epilepsy could hand out new ideas for the treatment of epilepsy. METHODS: Utilizing bidirectional Mendelian randomization (MR) study, we investigated the causal relationship between BCAA levels and epilepsy. BCAA levels from genome-wide association studies (GWAS), including total BCAAs, leucine levels, isoleucine levels, and valine levels, were employed. Causal relationships were explored applying the method of inverse variance-weighted (IVW) and MR-Egger, followed by sensitivity analyses of the results to evaluate heterogeneity and pleiotropy. RESULTS: Through strict genetic variant selection, we find some related SNPs, total BCAA levels (9), leucine levels (11), isoleucine levels (7), and valine levels (6) as instrumental variables for our MR analysis. Following IVW and sensitivity analysis, total BCAAs levels (OR = 1.14, 95 % CI = 1.019 ∼ 1.285, P = 0.022) and leucine levels (OR = 1.15, 95 % CI = 1.018 ∼ 1.304, P = 0.025) had significant correlation with epilepsy. CONCLUSIONS: There exists a causal relationship between the levels of total BCAAs and leucine with epilepsy, offering the new ideas into epilepsy potential mechanisms, holding significant implications for its prevention and treatment.

Humans↗

PubMed2026

Hyperthyroidism Is Genetically Associated With Reduced Risk of Parkinson's Disease: A Mendelian Randomization Analysis.

Parkinson's disease (PD) is a progressive neurodegenerative disorder whose aetiology involves an intricate interplay of genetic, immune, metabolic and environmental factors. Endocrine dysfunction-particularly disturbances of thyroid hormone signalling-has been proposed as a contributor to neurodegeneration, but conventional observational studies have produced inconsistent results, and prior Mendelian randomization (MR) work has largely focused on continuous thyroid biomarkers rather than clinically defined hyperthyroid disease states. To clarify this relationship, we performed a two-sample bidirectional and multivariable MR (MVMR) analysis using large-scale genome-wide association study (GWAS) summary statistics from the FinnGen and IEU Open GWAS databases (European ancestry). Single-nucleotide polymorphisms (SNPs) reaching genome-wide significance (p < 5 × 10-8) for Graves' disease and thyrotoxicosis with diffuse goitre served as instrumental variables. The inverse-variance weighted (IVW) method was the primary analysis, complemented by MR-Egger, weighted median, weighted mode and simple mode estimators, and MVMR adjusted for smoking, alcohol consumption, and body mass index (BMI). In forward analyses, genetically proxied Graves' disease (OR = 0.942, 95% CI 0.901-0.985, p = 0.008) and thyrotoxicosis with diffuse goitre (OR = 0.929, 95% CI 0.879-0.982, p = 0.009) were associated with a lower risk of PD, whereas reverse analyses showed no significant effect of genetic liability to PD on either thyroid trait. The inverse associations remained stable across MVMR models, and sensitivity analyses (Cochran's Q, MR-Egger intercept, MR-PRESSO, leave-one-out) showed no evidence of heterogeneity or horizontal pleiotropy. Collectively, these findings provide genetic evidence consistent with a protective relationship between hyperthyroid disease states and PD, independent of major lifestyle confounders. By focusing on clinically defined hyperthyroid entities rather than continuous thyroid indices, our study complements prior MR work and highlights the thyroid-brain axis-encompassing thyroid hormone signalling and autoimmune-mediated immune modulation-as a biologically plausible and potentially modifiable contributor to PD risk that warrants further mechanistic and translational investigation.

Humans↗