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PubMed2026

Identifying potential therapeutic targets for high myopia via a case-control study and Mendelian randomisation analyses of the human blood metabolome.

BACKGROUND: High myopia increases the risk of pathological ocular changes that may lead to irreversible vision loss. Therefore, the identification of potential biomarkers and therapeutic targets for high myopia is essential for early intervention and prevention. METHODS: Summary statistics for 122 blood metabolites were obtained from three genome-wide association studies (GWASs), whereas data on high myopia were derived from a large GWAS conducted with 50,372 participants from the UK Biobank. Mendelian randomisation (MR) analyses were conducted to assess the causal relationships between blood metabolites and high myopia. A real-world case-control study was conducted to validate the causal associations identified in the MR analyses. RESULTS: The systematic MR analysis identified 5 blood metabolites as both biomarkers and potential drug targets for high myopia, including glutamine (odds ratio [OR]: 0.98, 95% confidence interval [CI]: 0.97-1.00), tyrosine (OR: 0.98; 95% CI: 0.97-0.99), degree of unsaturation (OR: 0.98, 95% CI: 0.98-0.99), docosahexaenoic acid (DHA) (OR: 0.99; 95% CI: 0.98-1.00) and isobutyrylcarnitine (OR: 1.09, 95% CI: 1.05-1.13). The case-control study indicated that the levels of glutamine (OR = 0.76, 95% CI: 0.58-0.98) and tyrosine (OR = 0.72, 95% CI: 0.55-0.94) were significantly associated with a decreased risk of high myopia. CONCLUSIONS: Systematic MR analysis suggested that glutamine, tyrosine, the degree of unsaturation, DHA, and isobutyrylcarnitine may represent promising drug targets for high myopia prevention. Further investigations are needed to validate the therapeutic efficacy and elucidate the underlying mechanisms involved.

Humans↗
PubMed2026

APOE-stratified genome-wide association analyses provide insights into the genetic etiology of Alzheimers's disease.

Among the more than 90 identified genetic risk loci for late-onset Alzheimer's disease (AD) and related dementias, the apolipoprotein E (APOE) gene ɛ2/ɛ3/ɛ4 polymorphisms remain the longstanding benchmark for genetic disease risk with a consistently large effect across studies1-10. Despite this massive signal, the exact mechanisms by which ɛ4 increases and ɛ2 decreases dementia risk remain poorly understood. Notably, recent trials of anti-amyloid therapies suggest less efficacy and higher risks of severe side effects in ε4 carriers11-13, hampering the treatment of those with the highest unmet need. To improve our understanding of the genetic architecture of AD in the context of its main genetic driver, we performed genome-wide association studies (GWASs) stratified by ε4 and ε2 carrier status. HP1BP3, SLC50A1, PTPRC, NPAS3, DDHD1, CHST9, SMYD2, PRAMEF1 and GFRA1 emerged as new genomic signals for AD risk, appearing only when stratified by APOE carrier status. DDHD1 appeared especially promising, showing protective effects in ε4 carriers, being identified as an expression quantitative trait locus and being involved in rare neuronal diseases. Such APOE-stratified insights may help understand and overcome side effects, inform clinical trial enrollment strategies, and create the scientific basis for targeted, mechanism-driven therapies in neurodegenerative diseases.

Journal Article↗
PubMed2025

Exploiting pleiotropy to enhance variant discovery with functional false discovery rates.

The cost of recruiting participants for genome-wide association studies (GWASs) can limit sample sizes and hinder the discovery of genetic variants. Here we introduce the surrogate functional false discovery rate (sfFDR) framework that integrates summary statistics of related traits to increase power. The sfFDR framework provides estimates of FDR quantities such as the functional local FDR and q value, and uses these estimates to derive a functional P value for type I error rate control and a functional local Bayes' factor for post-GWAS analyses. Compared with a standard analysis, sfFDR substantially increased power (equivalent to a 52% increase in sample size) in a study of obesity-related traits from the UK Biobank and discovered eight additional lead SNPs near genes linked to immune-related responses in a rare disease GWAS of eosinophilic granulomatosis with polyangiitis. Collectively, these results highlight the utility of exploiting related traits in both small and large studies.

Humans↗
PubMed2025

Asthma causally affects the brain cortical structure: a Mendelian randomization study.

OBJECTIVE: The potential causal relationship between asthma and brain structures remains uncertain. We performed a two-sample Mendelian randomization to investigate the causal effects of various asthma phenotypes - unspecified asthma, moderate-to-severe asthma, childhood-onset asthma, and adult-onset asthma (AOA) - on cerebral cortex structure. METHODS: We utilized phenotype data derived from genome-wide association studies (GWASs). The ENIGMA Consortium GWAS provided outcome variables for surface area (SA) and thickness across the whole brain and 34 region-specific areas of the cerebral cortex. Using the inverse variance-weighted method as our primary estimation approach, we employed several techniques, including Cochran's Q statistic, the MR-PRESSO global test, MR-Egger, and weighted median, to assess heterogeneity and pleiotropy, thereby ensuring the robustness of our findings. Additionally, we conducted enrichment analyses of gene sets with causal effects on cortical structure and applied bioinformatics techniques to construct interaction networks and identify hub nodes. RESULTS: At the global level, AOA was associated with a significant reduction in full cortical SA (β = -58.49 mm2, p = 0.017). In regional analyses, moderate-to-severe asthma exhibited a more pronounced impact on the cerebral cortex compared to other phenotypes. Enrichment analysis revealed that pathways implicated in brain morphology among asthma patients were primarily linked to immune and inflammation-driven pathways. CONCLUSIONS: Our findings provide new evidence supporting a causal relationship between asthma and alterations in cortical structure, offering potential explanations for cognitive and psychiatric impairments observed in individual post-asthma.

Humans↗
PubMed2025

Distinguishing specific from broad genetic associations between external correlates and common factors.

MOTIVATION: Within the genomic structural equation modelling (genomic SEM) framework, common factors are often used to index shared genetic etiology across constellations of genome-wide associations studies (GWASs) phenotypes. A standard common pathway model, in which a genetic association is estimated between an external GWAS phenotype and a common factor, assumes that all genetic associations between the external GWAS phenotype and the individual indicator phenotypes are mediated through the factor. This assumption can be tested using the QTrait statistic, which compares the common pathway model to an independent pathways model that allows for direct genetic associations between the external GWAS phenotype and the individual indicators of the factor. However, QTrait is not designed to identify either the magnitude or the source of this heterogeneity. RESULTS: We expand upon the QTrait approach by describing an effect size index that quantifies the degree to which the common pathways model is violated, and we provide a systematic approach for empirically identifying specific direct pathways between an external trait and indicator traits. Our method comprises a series of omnibus tests and outlying indicator detection algorithms indexing the heterogeneity of associations between the genetic component of external traits and the individual indicators of common factors. We provide a set of automated functions which we apply to investigate the patterns of genetic associations across a set of external correlates with respect to indicators of general cognitive ability and case-control and proxy GWAS indices of Alzheimer's disease. AVAILABILITY AND IMPLEMENTATION: The Genomic SEM R package and the QTrait function is available at https://github.com/GenomicSEM/GenomicSEM. The QTrait function tutorial is available at https://github.com/GenomicSEM/GenomicSEM/wiki/8.-Tutorials. To ensure reproducibility of the analyses presented in this manuscript, the exact version of the QTrait function used, along with input data and scripts, has been archived on Zenodo (DOI: https://doi.org/10.5281/zenodo.17186083).

Genome-Wide Association Study↗
PubMed2026

SNPannotator: automated functional annotation of genetic variants and linked proxies.

SUMMARY: Genome-wide association studies (GWASs) have identified thousands of genetic variants associated with complex traits and diseases. However, explaining the mechanisms underlying phenotypic variation remains challenging. Here, we introduce SNPannotator, an automated post-GWAS analysis software package designed to streamline the interpretation of GWAS findings. Our pipeline implements a multi-step process that identifies proxy variants in high linkage disequilibrium (LD) with associated lead variants, then queries comprehensive resources (including Ensembl, the GTEx Portal, the eQTL Catalog, and STRING DB) for genomic position, deleteriousness, regulatory annotations, clinical significance, trait associations, expression (eQTLs) and splicing quantitative trait loci (sQTLs), and functional enrichment analyses and compiles the results into user-friendly reports. This package is implemented in the R programming language and includes auxiliary functions for variant lookup and LD exploration. SNPannotator provides a practical framework for efficiently deriving biologically meaningful insights from GWAS data and for assisting researchers in prioritizing candidate variants for functional validation. AVAILABILITY AND IMPLEMENTATION: The SNPannotator package is available from the Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/web/packages/SNPannotator. The development version and tutorial is available on GitHub (https://github.com/omicslaboratory/SNPannotator). The online version of the package is available at https://omicslab.org/snpannotator.

Software↗
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↗
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↗
PubMed2026

Integrative genomic and transcriptomic analysis of hypertension in a Taiwanese population.

OBJECTIVES: Hypertension is highly prevalent in Asian populations and represents a major cardiovascular risk factor. However, most genome-wide association studies (GWASs) and transcriptome-wide association studies (TWASs) have focused primarily on Caucasian cohorts. This study aimed to identify genetic loci and gene expression signatures associated with hypertension in an Asian population. METHODS: We analyzed 10 739 hypertensive patients and 49 668 controls from the Taiwan Biobank, testing 4 512 191 genome-wide single nucleotide polymorphisms (SNPs). Integrated GWAS, TWAS, and expression quantitative trait locus (eQTL) analyses were conducted to characterize genetic risk. Additionally, a polygenic risk score (PRS) was constructed using a split-sample design to evaluate genetic risk stratification. RESULTS: We identified 14 loci significantly associated with hypertension, including a novel locus at 5p13.1. eQTL analysis linked this locus to DAB2 expression in whole blood. TWAS detected 55 hypertension-associated genes, with 20 (36%) overlapping GWAS loci. Several novel genes outside GWAS loci, including FBXL15, KCNIP2, and CRIP3, were highly significant and implicated in vascular biology and hypertension mechanisms. PRS analysis effectively differentiated hypertension risk, with individuals in the top 10% showing a > 3.5-fold increased risk compared to the bottom 10%. CONCLUSIONS: Our findings provide new insights into the genetic and transcriptomic landscape of hypertension in Asians. The identification of novel loci and genes advances understanding of disease biology and may guide precision medicine approaches for risk prediction and therapeutic development.

Female↗
PubMed2026

The causal relationships and potential pathways between birth weight and cardiovascular diseases: A human genomics study.

The causal relationships and potential pathways between birth weight (BW) and various cardiovascular diseases (CVDs) remain unclear, particularly when discriminating maternal and fetal contributions of BW to CVDs. Leveraging the genome-wide association studies (GWASs) of BW (N = 321,223) and a range of CVDs (ncases = 43,676-181,522), we performed a 2-sample Mendelian randomization (MR) analysis to estimate the causal effect of BW, fetal-specific BW, and maternal-specific BW on coronary artery disease (CAD), myocardial infarction (MI), heart failure (HF), atrial fibrillation (AF), and stroke. Furthermore, we applied a stepwise MR analysis approach to assess the potential involvement of childhood body mass index (CBMI) and age at menarche (AAM) in the causal pathways from BW to CVDs, while considering adult BMI. Finally, we performed colocalization analyses to justify the different biological mechanisms of maternal-specific and fetal-specific BW. The 2-sample MR analysis revealed that genetically predicted higher BW per standard deviation (SD) was associated with a decreased risk of CAD (odds ratio [OR] = 0.804, 95% confidence interval [CI]: 0.731-0.883), MI (OR = 0.720, 95% CI: 0.638-0.814), and stroke (OR = 0.900, 95% CI: 0.823-0.985), but an increased risk of AF (OR = 1.279, 95% CI: 1.160-1.410). Similar associations were observed for fetal-specific/maternal-specific BW. The stepwise MR analysis indicated that CBMI and AAM could serve as factors linking BW/fetal-specific BW and CVDs, albeit in different roles, by displaying an indirect causal effect through adult BMI. However, for maternal-specific BW, our results failed to support a causal effect on CBMI or AAM. Colocalization analyses supported the distinct biological mechanisms for maternal-specific and fetal-specific BW by showing different causal genes. The study suggested that both fetal genotype and intrauterine environmental exposure contribute to the causal associations. Additionally, AAM and CBMI may play a role in the pathways linking BW and CVDs, though the effect was only observed for fetal-specific BW.

Humans↗
PubMed2026

Massively parallel characterization of adolescent idiopathic scoliosis risk variants.

Adolescent idiopathic scoliosis (AIS) is a common pediatric musculoskeletal disorder characterized by lateral spinal curvature, often leading to chronic pain and deformity. Although a significant genetic component to AIS is recognized, the functional impact of most associated genetic variants, particularly those in noncoding regions, remains largely unknown. Using massively parallel reporter assays, we characterize 1664 variant positions in linkage disequilibrium with 26 AIS lead variants identified by genome-wide association studies (GWASs) in chondrocytes, a major cell type implicated in AIS pathogenesis. Using a library of 7173 candidate regulatory sequences, we compare the 1664 reference alleles against 4708 alternate alleles in two human chondrocyte cell lines (TC28a2 and SW1353). Our analysis identifies 92 variants that exhibit significant differential regulatory activity between their reference and alternate alleles, 79 of which are predicted to disrupt transcription factor binding sites, often correlating with their observed regulatory effect. Notably, we validate rs9496392, a single-nucleotide variant near the ADGRG6 locus, which shows consistent differential regulatory activity in both cell lines. ADGRG6 is a key regulator of cartilage homeostasis, and its cartilage-specific knockout in mice results in a scoliosis-like phenotype. The AIS risk allele of rs9496392 (T) is predicted to strongly disrupt several TFBSs, including SP1. This study provides a foundational catalog of functional AIS-associated regulatory variants active in chondrocytes, offering crucial insights into the perturbed gene regulatory networks in AIS. These findings lay the groundwork for identifying biomarkers and potential therapeutic targets for this complex childhood disease.

Journal Article↗
PubMed2026

The Neanderthal-Derived 3p21 Haplotype at LZTFL1 in Modern-Day Moroccans Is Associated With COVID-19 Severity and Further Suggests the Presence of Neanderthals in North Africa.

There is considerable variability in the clinical presentation of COVID-19 among patients infected with SARS-CoV-2. Genome-wide association studies (GWASs) have identified the 12q24.13 and 3p21.31 regions, derived from Neanderthal DNA, as the human genetic loci most strongly associated with COVID-19 severity. We examined in this study the 3p locus in the Moroccan population by analysing allele and haplotype frequencies at the LZTFL1 gene and their associations with COVID-19 outcomes. Three SNPs at LZTFL1, tagging the Neanderthal-derived COVID-19 risk haplotype, were sequenced by Sanger's method in 102 ambulatory participants and 105 hospitalized patients and have been compared to 118 controls negative for SARS-CoV-2 infection using logistic regression analysis. Results showed that the prevalence of the lead variant rs11385942 in this locus was 8.9%, whereas the variants rs35044562 and rs13078854, which tag the Neanderthal haplotype, were present in only 6.3%. Our study showed that only the rs35044562-T and rs13078854-A alleles were associated with a 2.5-fold increased risk of severe COVID-19 (p = 0.028). These two alleles, in LD with the rs11385942-AA one, form the haplotype inherited from the Neanderthal, the only haplotype associated with COVID-19 severity in the Moroccan population (p = 0.030), whereas sub-Saharan African and the rare local haplotype also containing the rs11385942 variant do not influence the COVID-19 outcomes 19 (p > 0.05). Furthermore, our study showed that the Neanderthal haplotype at 3p21 locus exists in the inhabitants of Morocco at a frequency close to that of Europeans and suggests a close connection between North Africa and Eurasia.

Adult↗
PubMed2025

Multipopulation GWAS for venous thromboembolism identifies novel loci followed by experimental validation in zebrafish.

Venous thromboembolisms (VTEs) are a leading cause of morbidity and mortality. Although many genetic risk factors have been identified, a substantial portion of the heritability remains unexplained. In this study, we employed a genome-wide association study (GWAS) for VTE across 9 international cohorts of the Global Biobank Meta-Analysis Initiative to address this question, along with in vivo functional validation. In this multipopulation GWAS (VTE cases, 27 987; controls, 1 035 290), 38 genome-wide significant loci were identified, 4 of which were potentially novel. For each autosomal locus, we performed gene prioritization using 7 independent, yet converging, lines of evidence. Through prioritization, we identified genes associated with VTE through GWAS and/or functional studies (eg, F5, F11, VWF, STAB2, PLCG2, TC2N), functionally validated those that did not have evidence other than GWAS (TC2N, TSPAN15), and discovered 1 not previously associated with coagulation (RASIP1). We evaluated the function of 6 prioritized genes with strong genetic evidence, including F7 as a positive control, using laser-mediated endothelial injury to induce thrombosis in zebrafish after CRISPR/Cas9 knockdown. From this assay, we have supportive evidence for the role of RASIP1 and TC2N in the modification of human VTE and suggestive evidence for STAB2 and TSPAN15. This study expands on the currently identified genomic architecture of VTE through biobank-based, multipopulation GWASs, in silico candidate gene predictions, and in vivo functional follow-up of candidate genes.

Zebrafish↗
PubMed2024

Leisure television watching exerts a causal effect on gastroesophageal reflux disease: evidence from a two-step mendelian randomization study.

BACKGROUND: Previous studies have shown that physical activity (PA) and leisure sedentary behaviors (LSB, including leisure television watching) are linked to gastroesophageal reflux disease (GERD). However, the associations between PA/LSB and GERD remain controversial. In this study, we aimed to reveal whether these associations reflect causal relationships and reveal the potential mechanisms of these relationships using bidirectional and two-step Mendelian randomization (MR) analyses. METHODS: We obtained genome-wide association study (GWAS) summary statistics for PA/LSB, four common risk factors (including cigarettes smoked per day, alcoholic drinks per week, triglycerides, total cholesterol) and GERD from published GWASs. A bidirectional MR analysis was performed to identify causal relationships between PA/LSB and GERD. Then, a series of sensitivity analyses were performed to verify the robustness of the results. Finally, a mediation analysis via two-step MR was conducted to investigate any effects explained by common risk factors in these relationships. RESULTS: Genetically predicted per 1-SD increase in leisure time television watching significantly increased the risk of GERD in the bidirectional MR analysis (OR = 1.33; 95% CI: 1.14-1.56; P = 2.71 × 10- 4). Sensitivity analyses successfully verified the robustness of the causal relationship. Further mediation analysis showed that this effect was partly mediated by increasing cigarettes smoked per day, with mediated proportions of 18.37% (95% CI: 11.94-39.79%). CONCLUSION: Our findings revealed a causal relationship between leisure television watching and an increased risk of GERD, notably, the causal effect was partially mediated by cigarettes smoked per day. These findings may inform prevention and management strategies directed toward GERD.

Humans↗
PubMed2026

Multiomics analysis reveals that senescent CXCL16+ macrophages promote lung adenocarcinoma progression through TGF-β signalling.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer and remains a leading cause of cancer-related mortality worldwide. Although, immunotherapy has become a cornerstone of first-line treatment, only 20-30% of patients achieve a durable clinical benefit, largely because of the complexity and heterogeneity of the tumour immune microenvironment. Emerging evidence indicates that cellular senescence, particularly within immune cells, contributes to tumour progression by impairing antitumour immunity; however, its mechanistic role in LUAD remains incompletely understood. METHODS: We performed an integrative multiomics analysis incorporating genome-wide association studies (GWASs), bulk RNA sequencing, single-cell RNA sequencing, and spatial transcriptomics to characterize immune heterogeneity in LUAD. Cellular senescence was validated by performing staining for senescence-associated β-galactosidase and the canonical markers p16 and p21. SHAP analysis was applied to evaluate the contribution of CXCL16+ macrophages. Functional roles were assessed using coculture assays, in vitro and in vivo tumour models, orthotopic tumour implantation, and multiplex immunofluorescence staining of clinical specimens. RESULTS: A summary data-based on Mendelian randomization analysis integrating GWAS and TCGA data identified CXCL16 as a senescence-associated gene that is causally linked to the LUAD risk. Single-cell RNA sequencing revealed that CXCL16 is predominantly expressed in macrophages, and the pseudotime analysis together with β-galactosidase staining confirmed its association with macrophage senescence. Spatial transcriptomics and immunofluorescence staining showed the marked enrichment of CXCL16+ macrophages in LUAD tissues. The cell-cell communication analysis further revealed a strong association between the number of CXCL16+ macrophages and the activation of the TGF-β signalling pathway within the tumour microenvironment. Functionally, CXCL16+ macrophages promoted LUAD progression via TGF-β signalling, as validated in vitro and in subcutaneous and orthotopic tumour models. Molecular dynamics simulations additionally suggested that LUAD patients with high levels of CXCL16+ macrophage infiltration may exhibit increased sensitivity to bosutinib. CONCLUSIONS: CXCL16 promotes macrophage senescence, and senescent CXCL16+ macrophages drive LUAD progression through TGF-β signalling. These findings identify CXCL16+ macrophages as a biologically and therapeutically relevant immune cell population, highlighting a potential target for precision intervention in LUAD.

Humans↗
PubMed2024

The associations between functional dyspepsia and potential risk factors: A comprehensive Mendelian randomization study.

BACKGROUND: Previous cross-sectional studies have identified multiple potential risk factors for functional dyspepsia (FD). However, the causal associations between these factors and FD remain elusive. Here we aimed to fully examine the causal relationships between these factors and FD utilizing a two-sample MR framework. METHODS: A total of 53 potential FD-related modifiable factors, including those associated with hormones, metabolism, disease, medication, sociology, psychology, lifestyle and others were obtained through a comprehensive literature review. Independent genetic variants closely linked to these factors were screened as instrumental variables from genome-wide association studies (GWASs). A total of 8875 FD cases and 320387 controls were available for the analysis. The inverse variance weighted (IVW) method was employed as the primary analytical approach to assess the relationship between genetic variants of risk factors and the FD risk. Sensitivity analyses were performed to evaluate the consistency of the findings using the weighted median model, MR-Egger and MR-PRESSO methods. RESULTS: Genetically predicted depression (OR 1.515, 95% confidence interval (CI) 1.231 to 1.865, p = 0.000088), gastroesophageal reflux disease (OR 1.320, 95%CI 1.153 to 1.511, p = 0.000057) and years of education (OR 0.926, 95%CI 0.894 to 0.958, p = 0.00001) were associated with risk for FD in univariate MR analyses. Multiple medications, alcohol consumption, poultry intake, bipolar disorder, mood swings, type 1 diabetes, elevated systolic blood pressure and lower overall health rating showed to be suggestive risk factors for FD (all p<0.05 while &#x2265;0.00167). The positive causal relationship between depression, years of education and FD was still significant in multivariate MR analyses. CONCLUSIONS: Our comprehensive MR study demonstrated that depression and lower educational attainment were causal factors for FD at the genetic level.

Humans↗
PubMed2026

Bayesian Genome-Wide Association Study of Feed Efficiency Traits in Pigs.

Feed efficiency traits are increasingly important in pig production for improving profitability and environmental sustainability. Understanding their genetic basis is crucial for uncovering underlying biological mechanisms and informing selection strategies. In this study, we analyzed residual feed intake (RFI), feed conversion ratio (FCR), and average daily feed intake (ADFI) in 201 animals. Three separate Bayesian GWASs were conducted using 29,844 SNPs in a case-control design, with the lowest and highest 15% of the phenotypic distribution selected as controls and cases (N = 30 per group), respectively, for each trait. The results confirmed the polygenic nature of the traits, identifying 4 SNPs for RFI on Sus scrofa chromosomes (SSC) 3, 13, and 15 with high posterior probability for the direction of their effects; 4 SNPs for FCR on SSC 8, 14, and 17; and 8 SNPs for ADFI on SSC 1, 2, 6, 8, and 11. A candidate gene search identified 41 potential genes involved in diverse biological processes, including feed efficiency, intestinal development, tissue remodeling and integrity, nutrient transport and absorption, metabolic homeostasis, cellular signaling, energy sensing, and neurological regulation. These genes formed a highly interconnected network, highlighting the complexity of feed efficiency and the interplay among multiple physiological, metabolic, and regulatory pathways.

Bayesian analysis↗
PubMed2025

CRISPR as a Tool to Uncover Gene Function in Polycystic Ovary Syndrome: A Literature Review of Experimental Models Targeting Ovarian and Metabolic Genes.

Polycystic ovary syndrome (PCOS) is a complex disorder characterized by reproductive abnormalities such as hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology, and is frequently accompanied by metabolic disturbances such as insulin resistance, obesity and dyslipidemia. Genome-wide association studies (GWASs) have identified several susceptibility loci, yet little is known about their functional implications. Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (CRISPR/Cas9) has emerged as a powerful gene editing tool in bridging this gap by allowing researchers to directly target candidate genes in ovarian and metabolic pathways. For instance, experimental models have highlighted the role of CYP17A1 and DENND1A.V2 in androgen excess, anti-M&#xfc;llerian hormone (AMH) in follicular arrest, and insulin receptor substrate 1 (IRS1) and PPAR&#x3b3; in insulin signaling and adipogenesis. To highlight the multifactorial nature of PCOS, animal models, including zebrafish and rodents, have been used to reveal interactions between reproductive and metabolic phenotypes. Nevertheless, most studies remain restricted to single-gene models, and dual-gene models or combined gene editing and hormonal induction models remain underexplored. Future research integrating precision editing, multi-omic platforms, and patient-derived organoids may provide more accurate disease models and novel therapeutic strategies.

Polycystic Ovary Syndrome↗