Genome-wide Association Studies Data Research Articles

Identification of association between mitochondrial dysfunction and sarcopenia using summary-data-based Mendelian randomization and colocalization analyses.

Mitochondrial dysfunction has been demonstrated to be an important hallmark of sarcopenia, yet its specific mechanism remains obscure. In this study, mitochondrial-related genes were used as instrumental variables to proxy for mitochondrial dysfunction, and summary data for sarcopenia-related traits were used as outcomes to examine their genetic association. A total of 1,136 mitochondrial-related genes from the human MitoCarta3.0 database were extracted. Genetic instruments for them were obtained from gene expression quantitative trait locus (eQTLs) study (n = 31,684). Aggregated data for sarcopenia-related traits [(including low hand grip strength (LHGS), appendiceal lean mass (ALM), and usual walking pace (UWP) were provided by large-scale genome-wide association studies (GWASs). We integrated eQTLs data with GWAS data to estimate genetic association between mitochondrial dysfunction and sarcopenia using summary-data-based Mendelian randomization (SMR) analysis. Additionally, we implemented colocalization analysis to strengthen their association. Finally, eQTLs data from skeletomuscular tissue (n = 706) was used to validate the primary findings. By integrating the analysis results from the three sarcopenia-related traits, two mitochondrial genes genetically associated with sarcopenia were identified, namely UQCC1 (tier 2 evidence) and ETFDH (tier 3 evidence). Specifically, elevated expression levels of UQCC1 increased LHGS risk (OR = 1.114; 95% CI, 1.078-1.152; P-FDR = 1.70 × 10-7), which matched the negative association between it and UWP (Beta = -0.015; 95% CI, -0.021 - -0.010; P-FDR = 6.70 × 10-5). Furthermore, elevated expression levels of ETFDH were found to be associated with both lower ALM (Beta = 0.031; 95% CI, 0.020-0.042; P-FDR = 1.41 × 10-6) and UWP (Beta = 0.013; 95% CI, 0.006-0.021; P-FDR = 0.029). Of note, consistent results were replicated in specific skeletomuscular tissues, further suggesting our findings were robust. Our analyses revealed the genetic association between two mitochondrial-related genes, i.e., UQCC1 and ETFDH, and sarcopenia, highlighting the pivotal role of mitochondrial dysfunction driven by these genes in the pathogenesis of sarcopenia. Importantly, these candidate genes represent potential clinical drug targets for the treatment of sarcopenia.

Lipids, lipid-lowering drug target genes and pancreatic cancer: a Mendelian randomization study.

Pancreatic cancer (PC) is a malignant tumor with a low survival rate. Lipid modifiers show potential for PC therapy, but evidence is lacking. This Mendelian randomization (MR) study aimed to explore the relationship between lipid traits, and lipid-lowering drug target genes with PC risk. Genetic instrumental variables associated with lipid traits and lipid-lowering drug target genes were used to perform MR analyses of PC risk. MR estimation was based on genome-wide association study data from two large sample sets, and the MR results were meta-analyzed to assess their impact on PC risk. To ensure the reliability of lipid-modifying drug targets, we conducted a Summary Data-based Mendelian Randomization (SMR) analysis. Additionally, a two-step MR analysis was employed to explore potential mediating effects. In two independent datasets, HMG-CoA reductase (HMGCR) inhibition was statistically associated with a lower risk of PC (OR 0.50, [95% CI 0.25-1.00]; p = 0.0453). The results were further supported by SMR analysis, which showed a similar association (OR 0.51, [95% CI 0.28-0.96]; p = 0.0369). Mediation analysis revealed that 11.69% of the protective effect of HMGCR inhibitors on PC is mediated through lower BMI levels. No significant effect of lipid traits and the other eight lipid-lowering drug targets on PC risk was found. This study suggests that HMGCR may be a potential drug target for the treatment or prevention of PC, providing important insights into the use of lipid-targeted drugs in PC therapy.

Correlation between cathepsins and the likelihood of renal cancer: a Mendelian randomization study.

Previous studies have established a relationship between cathepsins and renal cancer. Nonetheless, the specific causal connection between the two factors continues to be ambiguous. The aim of this study is to evaluate the causal relationship between cathepsins and renal cancer via employing Mendelian randomization (MR). The summary data of genome-wide association study were used for univariable MR (UVMR), reverse MR, and multivariable MR (MVMR) analyses. The primary MR method used in this study was Inverse variance weighting. UVMR analysis showed that cathepsin Z increased the overall risk of renal cancer and cathepsin F were observed increased the risk of clear cell renal cell carcinoma. Furthermore, the concentration of cathepsin S had a significant positive correlation with the risk of papillary renal cell carcinoma (pRCC), whereas that of cathepsin G was negatively correlated with the risk of pRCC. Reverse MR analysis showed that renal cancer reduced the concentration of cathepsin H. MVMR analysis showed that the concentration of cathepsin B had a significant positive correlation with overall risk of renal cancer and pRCC. In addition, a higher concentration of cathepsin S was significantly associated with an increased risk of pRCC. This study confirmed a direct link between cathepsins and the risk of renal cancer. Specifically, cathepsin S has a significant positive correlation with the risk of pRCC. The findings of our research could provide significant contributions to both fundamental and clinical investigations pertaining to renal cancer. Key message What is already known on this topic? - Previous studies have suggested the role of some cathepsins in renal cancer occurrence and progression. However, the causal link between different cathepsins and renal cancer is unknown. What this study adds? - Our Mendelian randomization (MR) study revealed that the effects of different cathepsins on the risk of renal cancer. Remarkably, both univariable MR and multivariable MR demonstrated that the levels of cathepsin S increases the risk of papillary renal cell carcinoma. How this study might affect research, practice or policy? - The findings offer novel insights into the relationship between cathepsins and renal cancer, which may have implications for the prevention and management of renal cancer.

Mendelian Randomization Analysis Reveals a Causal Relationship Between Membranous Nephropathy and the Gut Microbiome.

With the increasing prevalence of membranous nephropathy (MN), the gut microbiome (GM) is increasingly implicated in its cause, yet the intricate mechanisms remain unclear. Whether changes in the diversity and richness of gut microbial populations among MN patients contribute to disease prevalence is still unanswered, necessitating further exploration into the potential causative link between the GM and MN. We conducted a comprehensive bidirectional Mendelian randomization (MR) study. We selected 211 bacterial taxa using Genome-wide association study (GWAS) data provided by the MiBioGen consortium, while GWAS data relevant to MN were obtained from ebi-a-GCST010005. The inverse-variance weighted (IVW) method was the primary technique used to delineate the causal relationship between exposures and outcomes. To confirm the robustness of our results, we used additional methods, including MR-Egger, weighted median, simple mode, and weighted mode. Sensitivity analyses included tests for pleiotropy, heterogeneity, and leave-one-out sensitivity to ensure the integrity of our conclusions. Finally, reverse MR analyses were conducted to assess the likelihood of reverse causality. Using various analytical methods, including the IVW approach, MR-Egger, weighted median, simple mode, and weighted mode, our study identified six microbial taxa with a statistically significant causal link to MN, as indicated by p-values less than 0.05. The implicated taxa are Butyrivibrio (OR= 1.25, 95 % CI: 1.001-1.565, P = 0.048), Butyricicoccus (OR = 2.15, 95 % CI: 1.005-4.621, P = 0.048), Catenibacterium (OR = 1.49, 95 % CI: 1.043-2.134, P = 0.028), Ruminiclostridium5 (OR = 1.78, 95 % CI: 1.140-2.763, P = 0.03), RuminococcaceaeUCG003 (OR = 1.78, 95 % CI: 1.140-2.763, P = 0.011) and Bacillales (OR = 1.52, 95 % CI: 1.135-2.025, P = 0.005). Each of these taxa has been established as a risk factor for MN. Notably, Ruminococcaceae UCG-003 and Bacillales were identified as having a bidirectional causal relationship with the disease. Our MR study has revealed a causal link between six microbial taxa and MN, highlighting their potential involvement in the disease's development. These findings represent an initial step into this complex field and underscore the need for more in-depth research.

GWAS-Assisted and multi-trait genomic prediction for improvement of seed yield and canning quality traits in a black bean breeding panel.

In recent years, black beans (Phaseolus vulgaris L.) have gained popularity in the U.S., with improved seed yield and canning quality being critical traits for new cultivars. Achieving genetic gains in these traits is often challenging due to negative trait associations and the need for specialized equipment and trained sensory panels for evaluation. This study investigates the integration of genomics and phenomics to enhance selection accuracy for these complex traits. We evaluated the prediction accuracy of single and multi-trait genomic prediction (GP) models, incorporating near-infrared spectroscopy (NIRS) data and markers identified through genome-wide association studies (GWAS). The models demonstrated moderate prediction accuracies for yield and canning appearance, and high accuracies for color retention. No significant differences were found between single-trait and multi-trait models within the same breeding cycle. However, across breeding cycles, multi-trait models outperformed single-trait models by up to 45% and 63% for canning appearance and seed yield, respectively. Interestingly, incorporating significant SNP markers identified by GWAS and NIRS data into the models tended to decrease prediction accuracy both within and between breeding cycles. As genotypes from the new breeding cycle were included, the models' prediction accuracy generally increased. Our findings underscore the potential of multi-trait models to enhance the prediction of complex traits such as seed yield and canning quality in dry beans and highlight the importance of continually updating the training dataset for effective GP implementation in dry bean breeding.

Vitamin D-related genetic variants and prostate cancer risk in Black men.

The relationship between vitamin D and prostate cancer has primarily been characterized among White men. Black men, however, have higher prostate cancer incidence and mortality rates, chronically low circulating vitamin D levels, and ancestry-specific genetic variants in vitamin D-related genes. Here, we examine critical genes in the vitamin D pathway and prostate cancer risk in Black men. We assessed a total of 73 candidate variants in genes (namely GC, CYP27A1, CYP27B1, CYP24A1, VDR, and RXRA) including functional variants previously associated with prostate cancer and circulating 25(OHD) in White men. Associations with prostate cancer risk were examined using genome-wide association study data for approximately 10,000 prostate cancer cases and 10,000 controls among Black men and over 85,000 cases and 91,000 controls among White men for comparison. A statistical significance threshold of 0.000685 was used to account for the 73 variants tested. None of the variants examined were significantly associated with prostate cancer risk among Black men after multiple comparison adjustment. Suggestive associations (P < 0.05) for four variants were found in Black men, including two in RXRA (rs41400444 OR=1.09, 95 % CI: 1.01-1.17, P = 0.024 and rs10881574 OR = 0.93, 0.87-1.00, P = 0.046) and two in VDR (rs2853563 OR = 1.07, 1.01-1.13, P = 0.017 and rs1156882 OR = 1.06, 1.00-1.12, P = 0.045). Two variants in VDR were also positively associated with risk in White men (rs11568820 OR = 1.04, 1.02-1.06, P = 0.00024 and rs4516035 OR = 1.03, 1.01-1.04, P = 0.00055). We observed suggestive associations between genetic variants in RXRA and VDR and prostate cancer risk in Black men. Future research exploring the relationship of vitamin D with cancer risk in Black men will need larger sample sizes to identify ancestry-specific variants relevant to risk in this population.

The relationship between smoking and recurrent aphthous stomatitis: A Mendelian randomization study.

Existing research suggests an association between smoking and the incidence of recurrent aphthous stomatitis (RAS); however, the causal relationship remains ambiguous. We employed Mendelian randomization (MR) to clarify the potential causal association between smoking and the risk of developing RAS. We utilized genome-wide association study (GWAS) sequencing data related to smoking from the Finnish database as instrumental variables (IVs) and GWAS data for RAS from the UK Biobank (UKB) as the outcome to perform a two-sample MR analysis. The selection of IVs was rigorously controlled according to the three principal assumptions of relevance, independence, and exclusivity. The primary analytical methods utilized were inverse variance weighting (IVW) and weighted median (WM), supplemented by MR-Egger, simple mode, and weighted mode techniques to infer causality between smoking and RAS. Sensitivity analyses were conducted using MR-PRESSO, Cochran's Q, and the MR-Egger intercept to ensure the robustness of the findings. The findings from the IVW and WM analyses suggest a causal association between smoking and an elevated risk of RAS (IVW: OR=1.003; 95% CI: 1.0002-1.005, p=0.033; WM: OR=1.003; 95% CI: 1.00006-1.007, p=0.044). Compared to non-smokers, smokers have a 0.3% increase in the risk of RAS. Furthermore, the sensitivity analysis did not reveal any inconsistencies that would contradict the MR results. Our findings provide preliminary evidence of a potential causal relationship between smoking and the risk of RAS, which may contribute to a deeper understanding of the underlying mechanisms. Further research is needed to confirm these results and explore their implications for clinical practice.

Integrative multi-omics analysis for identifying novel therapeutic targets and predicting immunotherapy efficacy in lung adenocarcinoma

Aim: Lung adenocarcinoma (LUAD), the most prevalent subtype of non-small cell lung cancer (NSCLC), presents significant clinical challenges due to its high mortality and limited therapeutic options. The molecular heterogeneity and the development of therapeutic resistance further complicate treatment, underscoring the need for a more comprehensive understanding of its cellular and molecular characteristics. This study sought to delineate novel cellular subpopulations and molecular subtypes of LUAD, identify critical biomarkers, and explore potential therapeutic targets to enhance treatment efficacy and patient prognosis. Methods: An integrative multi-omics approach was employed to incorporate single-cell RNA sequencing (scRNA-seq), bulk transcriptomic analysis, and genome-wide association study (GWAS) data from multiple LUAD patient cohorts. Advanced computational approaches, including Bayesian deconvolution and machine learning algorithms, were used to comprehensively characterize the tumor microenvironment, classify LUAD subtypes, and develop a robust prognostic model. Results: Our analysis identified eleven distinct cellular subpopulations within LUAD, with epithelial cells predominating and exhibiting high mutation frequencies in Tumor Protein 53 (TP53) and Titin (TTN) genes. Two molecular subtypes of LUAD [consensus subtype (CS)1 and CS2] were identified, each showing distinct immune landscapes and clinical outcomes. The CS2 subtype, characterized by increased immune cell infiltration, demonstrated a more favorable prognosis and higher sensitivity to immunotherapy. Furthermore, a multi-omics-driven machine learning signature (MOMLS) identified ribonucleotide reductase M1 (RRM1) as a critical biomarker associated with chemotherapy response. Based on this model, several potential therapeutic agents targeting different subtypes were proposed. Conclusion: This study presents a comprehensive multi-omics framework for understanding the molecular complexity of LUAD, providing insights into cellular heterogeneity, molecular subtypes, and potential therapeutic targets. Differential sensitivity to immunotherapy among various cellular subpopulations was identified, paving the way for future immunotherapy-focused research.

Functional Annotation of Bipolar Disorder 2 Risk Location Implicates Novel Susceptibility Genes.

Bipolar 2 disorder (BD2) is an independent disease with specific familial aggregation, significant functional impairment, specific treatment challenges and several distinctive clinical features. However, unlike bipolar 1 disorder, studies investigating causal and functional genes are lacking. This study aims to identify and prioritize causal genetic variants and genes for BD2 by analyzing brain-specific gene expression markers, to improve the understanding of its genetic underpinnings and support advancements in diagnosis, treatment and prognosis. We used FUMA, a genome wide association study (GWAS) annotation tool, to pinpoint potential causal variants and genes from the largest BD2 GWAS data. Candidate causal variants most likely affecting brain gene expression were prioritized using the following criteria: (1) variants identified as eSNPs in any brain region within any brain expression quantitative trait loci (eQTL) dataset; (2) variants annotated in the Regulome database with a score <5, indicating likely functional localization; (3) the most common 15-core chromatin state across all cell types in the Roadmap Epigenomics data being ≤7, reflecting an open chromatin state; (4) localization in genomic regions with evidence of 3D chromatin interactions, as such interactions mediate genetic effects on gene expression. We identified AGRN, ORMDL3, SLC25A39, RUNDC3A, NOS2, C1orf159, RP11-5407.18, RP11-465B22.3, RP11-5407.17 as candidate causal genes. These genes are associated with important pathways such as synapse formation, mitochondrial and oxidative metabolism, intracellular transport, neurotransmission and lipid metabolism-related pathways. This study provides a guide for further experimental validation of functional variants, BD2-associated genes and novel drug targets.

Exploring potential therapeutic targets for small cell lung cancer based on transcriptomics combined with Mendelian randomization analysis

ObjectiveThe main objective of this study was to explore and identify new genetic targets in small-cell lung cancer (SCLC) through transcriptomics analysis and Mendelian randomization (MR) analysis, which will help in the subsequent development of new therapeutic interventions.MethodsIn this study, we extracted the SCLC dataset from the Gene Expression Omnibus (GEO) database, processed the data, and screened out differentially expressed genes (DEGs) using R software. Based on expression quantitative trait loci data and the genome-wide association study data of SCLC, MR analysis was used to screen the genes closely related to SCLC disease, which intersect with DEGs to obtain co-expressed genes (CEGs), and the biological functions and pathways of CEGs were further explored by enrichment analysis. In addition, the CIBERSORT algorithm was applied to assess the level of immune cell infiltration in SCLC and to analyze the correlation between CEGs and immune cells. Meanwhile, we performed a survival analysis on these five CEGs using an independent cohort of SCLC patients. Finally, the results for the target genes were validated.ResultsIn this study, 857 DEGs were identified, including 443 up-regulated and 414 down-regulated genes, and 5 CEGs (PSAT1, PSRC1, COLEC12, PLLP, HP) that were significantly associated with SCLC were identified through further intersecting. The results of enrichment analyses indicated that CEGs play important roles in several key functions and pathways. Immune-cell-related analysis revealed the unique distribution of immune cell infiltration in SCLC and the mechanism of immune cell regulation by CEGs. Survival analysis results indicated that PSRC1 was significantly correlated with the overall survival of SCLC, and the survival rate of the high-expression group was markedly lower than that of the low-expression group. Finally, the consistency of the results between the validation group analyses and MR analysis confirmed that the results of this study is reliable.ConclusionThe CEGs and their associated functions and pathways screened in this study may be potential targets of therapeutic intervention in SCLC by targeting specific molecular pathways.

Polygenic risk scores in relation to suicidality among youth with or at risk for bipolar disorder.

The risk of suicide among individuals with bipolar disorder (BD) is among the highest of all psychiatric disorders. The etiology of suicidality is complex and multifactorial, with genetic factors playing a prominent role according to twin-, family-, and molecular genetic studies. This study examines polygenic risk scores from adult studies in relation to suicidality in youth with or at risk for BD. Primary analyses examined the association of polygenic risk scores for suicide attempt, based on adult genome-wide association study data, with suicidal ideation, self-harm, and suicide attempt in 232 youth (mean age 16.7 years), including 125 with, and 107 at high-risk for, BD. We also tested polygenic risk scores for risk tolerance, schizophrenia, major depressive disorder, BD, and attention-deficit hyperactivity disorder in secondary analyses. Polygenic risk scores for suicide attempt were not significantly associated with suicidal ideation, self-harm, or suicide attempt. Higher polygenic risk scores for major depressive disorder were nominally associated with increased risk of suicidal ideation in the overall sample (beta = 0.36, se(beta) = 0.16, p = 0.017), controlling for covariates. Our finding that polygenic risk for depression is associated with suicidal ideation converges with prior findings in youth and adults. While present findings are constrained by sample size, they underscore the importance of undertaking genome-wide association studies in youth, rather than relying solely on prior adult genome-wide association studies.

The identification of plasma and cerebrospinal fluid metabolites causally associated with mental disorders from a genetic perspective.

Metabolomics research is a promising orientation for the diagnosis and intervention of several diseases, and observational studies have found many metabolic profiles to be associated with mental disorders. However, the causal relationship between plasma and cerebrospinal fluid (CSF) metabolites and mental disorders has not been established. We identified independent genetic variants associated with plasma, CSF metabolites, and mental disorders from pooled data in the published Genome-wide association studies (GWASs) and performed Mendelian randomization (MR) to investigate causal relationships. Genetic information on the screened mental disorders were derived from separate GWAS data sources as exploratory and validation datasets. Inverse variance weighting (IVW) was adopted as the primary method for MR analysis. We also applied sensitivity analyses to examine the reliability of the MR analysis results. Further enrichment analyses provided a deeper insight into the biological mechanisms of the three mental disorders. A dual analysis of the exploratory and validation datasets identified eight plasma metabolites and three CSF metabolites causally associated with MDD, two plasma metabolites and one CSF metabolite causally associated with anxiety disorders, and four plasma metabolites and two CSF causally associated with ASD. Horizontal pleiotropy and heterogeneity tests indicate the validity of our MR studies. Enrichment analysis uncovered metabolic pathways associated with disease. Our study identified plasma and cerebrospinal fluid metabolites that were causally associated with 3 mental disorders. Characterization of disease-associated metabolites not only deepens the understanding of pathological mechanisms, but also supports clinical diagnosis and prognosis.

Causal Association Between Childhood Body Mass Index and Phlebitis and Thrombophlebitis: An Analysis Using Mendelian Randomization.

Background: Research has indicated a link between obesity and a greater likelihood of venous disorders. However, the specific relationship between obesity in children and conditions such as phlebitis and thrombophlebitis remains undetermined. To explore this, we undertook a two-sample Mendelian randomization (MR) study to investigate the possible causal impact of childhood body mass index (BMI) on the development of phlebitis and thrombophlebitis. Methods: This study utilized genome-wide association studies data from European populations. Childhood BMI was assessed in a sample of 39,620 individuals, while data on phlebitis and thrombophlebitis were obtained from 1613 cases and 335,586 controls. We selected 16 single nucleotide polymorphisms significantly associated with childhood BMI as instrumental variables (IVs). The inverse variance weighting (IVW) method was applied as the primary approach, with weighted median, MR-Egger regression, and weighted mode methods used as complementary analyses. Results: The IVW analysis indicates a significant causal link between childhood BMI and the occurrence of phlebitis and thrombophlebitis (Beta = 0.002739, Standard error (SE) = 0.000740, p = 0.0002147). Results from the weighted median method (Beta = 0.002446, SE = 0.001046, p = 0.01933) aligned with the IVW findings. However, the MR-Egger and weighted mode analyses did not show a significant association (p = 0.1051 and p = 0.2525, respectively). Leave-one-out sensitivity tests and heterogeneity assessments were performed, revealing no evidence of horizontal pleiotropy. Conclusion: The findings from the MR analysis suggest a potential causal relationship between childhood BMI and an elevated risk of phlebitis and thrombophlebitis. This study provides new insights into the impact of childhood obesity on venous health, emphasizing the need for early intervention and prevention strategies.

Molecular and cellular dynamics of the developing human neocortex.

The development of the human neocortex is highly dynamic, involving complex cellular trajectories controlled by gene regulation1. Here we collected paired single-nucleus chromatin accessibility and transcriptome data from 38 human neocortical samples encompassing both the prefrontal cortex and the primary visual cortex. These samples span five main developmental stages, ranging from the first trimester to adolescence. In parallel, we performed spatial transcriptomic analysis on a subset of the samples to illustrate spatial organization and intercellular communication. This atlas enables us to catalogue cell-type-specific, age-specific and area-specific gene regulatory networks underlying neural differentiation. Moreover, combining single-cell profiling, progenitor purification and lineage-tracing experiments, we have untangled the complex lineage relationships among progenitor subtypes during the neurogenesis-to-gliogenesis transition. We identified a tripotential intermediate progenitor subtype-tripotential intermediate progenitor cells (Tri-IPCs)-that is responsible for the local production of GABAergic neurons, oligodendrocyte precursor cells and astrocytes. Notably, most glioblastoma cells resemble Tri-IPCs at the transcriptomic level, suggesting that cancer cells hijack developmental processes to enhance growth and heterogeneity. Furthermore, by integrating our atlas data with large-scale genome-wide association study data, we created a disease-risk map highlighting enriched risk associated with autism spectrum disorder in second-trimester intratelencephalic neurons. Our study sheds light on the molecular and cellular dynamics of the developing human neocortex.

Mediators of the association between nut consumption and cardiovascular diseases: a two-step mendelian randomization study

Previous observational studies have reported inconsistent associations between nut consumption and cardiovascular diseases (CVD). This study aims to identify the causal relationship between different types of nuts consumption and CVD, and to quantify the potential mediating effects of cardiometabolic factors. We utilized Genome-Wide Association Study (GWAS) data to assess the causal effects of nut consumption on CVD using two-sample Mendelian randomization (MR) and a two-step MR analysis. The inverse variance weighted (IVW) method indicated that processed (salted or roasted) peanuts were potentially and positively associated with ischaemic heart disease (IHD) (OR 1.4866; 95%CI 1.0491-2.1065). No causal relationships were found between nuts consumption and other CVD outcomes, including atrial fibrillation, angina, coronary atherosclerosis, coronary heart disease, IHD, myocardial infarction, subarachnoid hemorrhage, intracerebral haemorrhage and stroke. Both MR-Egger and median-based methods yielded similar results to IVW. Furthermore, in the two-step MR analysis, fasting insulin, low-density lipoprotein cholesterol and fasting blood glucose were identified as mediators in the potential causal relationship between processed peanuts and IHD, explaining 16.98%, 6.38% and 4.91% of the mediation, respectively. In total, these mediators accounted for 28.27% of the association between salted or roasted peanuts and IHD.

Refining breast cancer genetic risk and biology through multi-ancestry fine-mapping analyses of 192 risk regions.

Genome-wide association studies have identified approximately 200 genetic risk loci for breast cancer, but the causal variants and target genes are mostly unknown. We sought to fine-map all known breast cancer risk loci using genome-wide association study data from 172,737 female breast cancer cases and 242,009 controls of African, Asian and European ancestry. We identified 332 independent association signals for breast cancer risk, including 131 signals not reported previously, and for 50 of them, we narrowed the credible causal variants down to a single variant. Analyses integrating functional genomics data identified 195 putative susceptibility genes, enriched in PI3K/AKT, TNF/NF-κB, p53 and Wnt/β-catenin pathways. Single-cell RNA sequencing or in vitro experiment data provided additional functional evidence for 105 genes. Our study uncovered large numbers of association signals and candidate susceptibility genes for breast cancer, uncovered breast cancer genetics and biology, and supported the value of including multi-ancestry data in fine-mapping analyses.

A cross-tissue transcriptome-wide association study identifies new key genes in ischemic stroke.

Ischemic stroke (IS) is an important disease causing death and disability worldwide, and further investigation of IS-related genes through genome-wide association study (GWAS) data is valuable. The study included GWAS data from 62,100 IS patients of European origin and 1,234,808 controls in a cross-tissue transcriptome association study (TWAS). A joint analysis was first performed by the Unified Test for Molecular Markers (UTMOST) and FUSION methods. The results of the joint analysis were also validated by fine-mapping through FOCUS. Mendelian randomisation analysis was performed to determine whether the obtained genes were causally related to IS. Genome Annotated Multiple Marker Analysis (MAGMA) explored which biological functions the genes associated with IS. We used Coloc to co-localise GWAS and eQTL of the genes. We also biologically validated the results by Western blotting and immunofluorescence staining in the middle cerebral artery occlusion/reperfusion (MCAO/R) mouse model. Four TWAS methods identified only one new susceptibility gene (USP38) associated with IS risk. Mendelian randomization and colocalization analysis found that USP38 may be protective against IS development. Functional enrichment analysis indicated IS-related genes were mainly associated with the intrinsic fibrinogen activation, acute myocardial infarction, exogenous fibrinogen activation, coagulation cascade response, TNF signalling pathway and GRB2 signalling pathway. Western blotting and immunofluorescence staining demonstrated a reduction in USP38 expression in MCAO/R mice. Our research indicates that USP38 is an essential gene related to IS, with its expression strongly connected with IS risk, thus providing new perspectives on the genetic framework of IS.

Identifying the Involvement of Gut Microbiota in Retinal Vein Occlusion by Mendelian Randomization and Genetic Correlation Analysis.

Previous researches have suggested an important association between gut microbiota (GM) and vascular pathologies such as atherosclerosis. This study aimed to explore the association between 196 GM taxa and retinal vein occlusion (RVO). This study used Mendelian randomization (MR), linkage disequilibrium score regression (LDSC), and polygenic overlap analysis. Genome-wide association study (GWAS) data associated with 196 GM taxa was obtained from the MiBioGen consortium, involving a large number of European-ancestry participants. GWAS data of RVO was obtained from the FinnGen consortium and another study that also involved European-ancestry participants. Inverse-variance weighted was used as the primary approach for MR estimation. Moreover, LDSC and polygenic overlap analyses were performed to evaluate the genetic correlation between GM taxa and RVO. The MR results identified the association of six GM taxa, including class Bacilli, order Lactobacillales, family Streptococcaceae, genus Clostridium innocuum group, genus Family XIII AD3011 group, and genus Subdoligranulum with the development of RVO. In addition, the polygenic overlap analysis supported the genetic association between GM and RVO. Our findings confirmed the association between six GM taxa and the development of RVO, thereby highlighting the effects of GM on retinal vascular health. The results may provide the rationale for developing GM-based strategies for preventing the onset of RVO.

A semi-empirical Bayes approach for calibrating weak instrumental bias in sex-specific Mendelian randomization studies.

Strong sex differences exist in sleep phenotypes and also cardiovascular diseases (CVDs). However, sex-specific causal effects of sleep phenotypes on CVD-related outcomes have not been thoroughly examined. Mendelian randomization (MR) analysis is a useful approach for estimating the causal effect of a risk factor on an outcome of interest when interventional studies are not available. We first conducted sex-specific genome-wide association studies (GWASs) for suboptimal-sleep phenotypes (insomnia, obstructive sleep apnea (OSA), short and long sleep durations, and excessive daytime sleepiness) utilizing the Million Veteran Program (MVP) dataset. We then developed a semi-empirical Bayesian framework that (i) calibrates variant-phenotype effect estimates by leveraging information across sex groups, and (ii) applies shrinkage sex-specific effect estimates in MR analysis, to alleviate weak instrumental bias when sex groups are analyzed in isolation. Simulation studies demonstrate that the causal effect estimates derived from our framework are substantially more efficient than those obtained through conventional methods. We estimated the causal effects of sleep phenotypes on CVD-related outcomes using sex-specific GWAS data from the MVP and All of Us. Significant sex differences in causal effects were observed, particularly between OSA and chronic kidney disease, as well as long sleep duration on several CVD-related outcomes. By applying shrinkage estimates for instrumental variable selection, we identified multiple sex-specific significant causal relationships between OSA and CVD-related phenotypes.

Sarcopenia and immune-mediated inflammatory diseases: Evaluating causality and exploring therapeutic targets for sarcopenia through Mendelian randomization.

An increasing body of evidence has revealed the association between immune-mediated inflammatory diseases (IMIDs) and sarcopenia. However, a genetically direct causality between IMIDs and sarcopenia remains elusive. To investigate the relationship between IMIDs and sarcopenia-related traits and identify potential therapeutic targets, a Mendelian randomization (MR) was performed. We collected publicly available genome-wide association studies (GWAS) data for seven common IMIDs, including systemic lupus erythematosus (SLE), inflammatory bowel disease (IBD), Crohn's disease (CD), ulcerative colitis (UC), psoriasis (PSO), ankylosing spondylitis (AS), and rheumatoid arthritis (RA). Additionally, summary-level GWAS data for sarcopenia-related traits, including appendicular lean mass (ALM), left-hand grip strength, and right-hand grip strength were collected. To search for therapeutic targets, we used two types of genetic instruments to proxy the exposure of druggable genes, including genetic variants within or nearby drug targets and expression quantitative trait loci (eQTLs) of drug targets. Two-sample MR and summary-data-based MR (SMR) were used to calculate effect estimates, and sensitivity analyses were implemented for robustness. Drug tractability, gene enrichment analysis, and protein-protein interaction (PPI) analysis were used to validate the biological and clinical significance of the selected drug targets. The two-sample MR analysis indicated the existence of casual associations between IMIDs and sarcopenia-related traits in the overall and sex-stratified populations. In particular, PSO had causal effects on decreased ALM, which showed significance in all six MR analysis tests with directional consistency in the overall population. Grounded in this robust association, HLA-DRB5, HLA-DRB1, and AGER were identified as potential therapeutic targets for ALM decline by drug target MR and further confirmed by SMR analysis. These genes were associated with therapeutic agents currently undergoing evaluations in clinical trials. Gene enrichment and PPI analysis indicated a strong association of these genes with immune functions. This MR study contributes novel genetic evidence supporting the causal link between IMIDs and sarcopenia, with a particular emphasis on the association between PSO and decreased ALM. Additionally, AGER, HLA-DRB1, and HLA-DRB5 emerge as potential therapeutic targets for ALM decline.