Genome-wide Association Studies Datasets Research Articles

Uncovering novel drug targets for bipolar disorder: a Mendelian randomization analysis of brain, cerebrospinal fluid, and plasma proteomes.

There is a clear demand for innovative therapeutics for bipolar disorder (BD). We integrated the largest BD genome-wide association study (GWAS) dataset (NCase = 41 917, NControl = 371 549) with protein quantitative trait loci from brain, cerebrospinal fluid, and plasma. Using a range of integrative analyses, including Mendelian randomization (MR), Steiger filter analysis, Bayesian colocalization, and phenome-wide MR analysis, we prioritized novel drug targets for BD. Additionally, we incorporated data from the UK Biobank (NCase = 1064, NControl = 365 476) and the FinnGen study (NCase = 7006, NControl = 329 192) for robust biological validation. Through MR analysis, we found that in the brain, downregulation of DNM3, MCTP1, ABCB8 and elevation of DFNA5 and PDF were risk factors for BD. In cerebrospinal fluid, increased BD risk was associated with increased levels of FRZB, AGRP, and IL36A and decreased CTSF and LRP8. Plasma analysis revealed that decreased LMAN2L, CX3CL1, PI3, NCAM1, and TIMP4 correlated with increased BD risk, but ITIH1 did not. All these proteins passed Steiger filtering, and Bayesian colocalization confirmed that 12 proteins were colocalized with BD. Phenome-wide MR analysis revealed no significant side effects for potential drug targets, except for LRP8. External validation further underscored the concordance between the primary and validation cohorts, confirming MCTP1, DNM3, PDF, CTSF, AGRP, FRZB, LMAN2L, NCAM1, and TIMP4 are intriguing targets for BD. Our study identified druggable proteins for BD, including MCTP1, DNM3, and PDF in the brain; CTSF, AGRP, and FRZB in cerebrospinal fluid; and LMAN2L, NCAM1, and TIMP4 in plasma, delineating promising avenues to development of novel therapies.

Association between diabetes mellitus and primary biliary cholangitis: a two-sample Mendelian randomization study

BackgroundPrevious observational studies have demonstrated a link between diabetes mellitus(DM) and primary biliary cholangitis (PBC). Nevertheless, since these relationships might be confused, whether there is any causal connection or in which direction it exists is unclear. Our investigation aimed to identify the causal associations between DM and PBC.MethodsWe acquired genome-wide association study (GWAS) datasets for PBC, Type 1 diabetes(T1DM), and Type 2 diabetes(T2DM) from published GWASs. Inverse variance-weighted (IVW), MR-Egger, weighted median (WM), Simple mode, and weighted mode methods were used to determine the causal relationships between DM(T1DM or T2DM) and PBC. Sensitivity analyses were also carried out to ensure the results were robust. To determine the causal relationship between PBC and DM(T1DM or T2DM), we also used reverse MR analysis.ResultsT1DM was associated with a higher risk of PBC (OR 1.1525; 95% CI 1.0612-1.2517; p = 0.0007) in the IVW method, but no evidence of a causal effect T2DM on PBC was found (OR 0.9905; 95% CI 0.8446-1.1616; p = 0.9071) in IVW. Results of the reverse MR analysis suggested genetic susceptibility that PBC was associated with an increased risk of T1DM (IVW: OR 1.1991; 95% CI 1.12-1.2838; p = 1.81E-07), but no evidence of a causal effect PBC on T2DM was found (IVW: OR 1.0101; 95% CI 0.9892-1.0315; p = 0.3420).ConclusionThe current study indicated that T1DM increased the risk of developing PBC and vice versa. There was no proof of a causal connection between PBC probability and T2DM. Our results require confirmation through additional replication in larger populations.

Investigation of causal effects of blood metabolites on insomnia and circadian rhythm sleep wake disorders

BackgroundInsomnia (IS) and circadian rhythm sleep-wake disorders (CRSWD) are complex disorders with limited and unsatisfactory treatment options that can even cause some side effects. By analyzing blood metabolites to reveal underlying biological processes, studies of sleep and the complex interactions between its influencing factors can be elucidated. Therefore, we hope to bring new hope for the treatment of these diseases through blood metabolites.AimsInvestigating the causal link between blood metabolites and IS and CRSWD.MethodsA genome-wide association study (GWAS) for 486 metabolites was used as the exposure, whereas two different GWAS datasets for sleep disorders were the outcome, and all datasets were obtained from publicly available databases. We employed the standard inverse variance weighting (IVW) method for causal analysis, supported by the MR-Egger method, weighted median (WM) method, and MR-PRESSO method for sensitivity analysis to mitigate the impact of pleiotropy. Genetic correlation between IS, CRSWD, and blood metabolites was explored through linkage disequilibrium analysis (LDSC), while Multivariable MR analysis (MVMR) elucidated whether these metabolites exhibit a direct association with IS and CRSWD. Further, we conducted metabolic pathway analysis to identify the specific metabolites driving these relationships.ResultsEmploying meticulous MVMR analysis, we have identified specific metabolites that independently influence IS, including 2-hydroxypalmitate (OR 2.95, 95%CI 1.05–8.31 P = 0.040), X-11786-Methylcysteine (OR = 0.25, 95%CI 0.08–0.76 P = 0.014), and salicylate (OR 0.89, 95%CI 0.83–0.95 P = 9 × 10–4). In the context of CRSWD, our findings reveal direct associations with metabolites such as carnitine (OR 0.02, 95%CI: 0.00–0.20, P = 0.002), levulinate (OR 0.06, 95%CI: 0.01–0.64, P = 0.020), p-cresol sulfate (OR 0.25, 95% CI: 0.09–0.67, P = 0.006), and X-14208-Phenylalanylserine (OR 0.36, 95% CI: 0.16–0.81, P = 0.014). These discoveries contribute to a nuanced understanding of the distinct metabolic signatures underlying IS and CRSWD.

Dietary factors and Alzheimer’s disease risk: a Mendelian randomization study

BackgroundPrior observational research has investigated the association between dietary patterns and Alzheimer’s disease (AD) risk. Nevertheless, due to constraints in past observational studies, establishing a causal link between dietary habits and AD remains challenging.MethodsMethodology involved the utilization of extensive cohorts sourced from publicly accessible genome-wide association study (GWAS) datasets of European descent for conducting Mendelian randomization (MR) analyses. The principal analytical technique utilized was the inverse-variance weighted (IVW) method.ResultsThe MR analysis conducted in this study found no statistically significant causal association between 20 dietary habits and the risk of AD (All p > 0.05). These results were consistent across various MR methods employed, including MR-Egger, weighted median, simple mode, and weighted mode approaches. Moreover, there was no evidence of horizontal pleiotropy detected (All p > 0.05).ConclusionIn this MR analysis, our finding did not provide evidence to support the causal genetic relationships between dietary habits and AD risk.

No genetic causal association between circulating alpha-tocopherol levels and osteoarthritis, a two-sample Mendelian randomization analysis

The causal association between vitamin E status and osteoarthritis (OA) remains controversial in previous epidemiological studies. We employed a Mendelian randomization (MR) analysis to explore the causal relationship between circulating alpha-tocopherol levels (main forms of vitamin E in our body) and OA. The instrumental variables (IVs) of circulating alpha-tocopherol levels were obtained from a Genome-wide association study (GWAS) dataset of 7781 individuals of European descent. The outcome of OA was derived from the UK biobank. Two-sample MR analysis was used to estimate the causal relationship between circulating alpha-tocopherol levels and OA. The inverse-variance weighted (IVW) method was the primary analysis in this analysis. We used the MR-Egger method to determine horizontal pleiotropic in this work. The heterogeneity effect of instrumental IVs was detected by MR-Egger and IVW analyses. Sensitivity analysis was performed by removing single nucleotide polymorphism (SNP) one by one. Three SNPs (rs964184, rs2108622, and rs11057830) (P < 5E−8) strongly associated with circulating alpha-tocopherol levels were used in this analysis. The IVW-random effect indicated no causal relationship between circulating alpha-tocopherol levels and clinically diagnosed OA (OR = 0.880, 95% CI 0.626, 1.236, P = 0.461). Similarly, IVW analysis showed no causal association between circulating alpha-tocopherol levels and self-reported OA (OR = 0.980, 95% CI 0.954, 1.006, P = 0.139). Other methods of MR analyses and sensitivity analyses revealed consistent findings. MR-Egger and IVW methods indicated no significant heterogeneity between IVs. The MR–Egger intercept showed no horizontal pleiotropic. The results of this linear Mendelian randomization study indicate no causal association between genetically predicted alpha-tocopherol levels and the progression of OA. Alpha-tocopherol may not provide beneficial and more favorable outcomes for the progression of OA. Further MR analysis based on updated GWASs with more IVs is required to verify the results of our study.

Genomic prediction of resistance to Hymenoscyphus fraxineus in common ash (Fraxinus excelsior L.) populations.

The increase in introduced insect pests and pathogens due to anthropogenic environmental changes has become a major concern for tree species worldwide. Common ash (Fraxinus excelsior L.) is one of such species facing a significant threat from the invasive fungal pathogen Hymenoscyphus fraxineus. Some studies have indicated that the susceptibility of ash to the pathogen is genetically determined, providing some hope for accelerated breeding programs that are aimed at increasing the resistance of ash populations. To address this challenge, we used a genomic selection strategy to identify potential genetic markers that are associated with resistance to the pathogen causing ash dieback. Through genome-wide association studies (GWAS) of 300 common ash individuals from 30 populations across Poland (ddRAD, dataset A), we identified six significant SNP loci with a p-value ≤1 × 10-4 associated with health status. To further evaluate the effectiveness of GWAS markers in predicting health status, we considered two genomic prediction scenarios. Firstly, we conducted cross-validation on dataset A. Secondly, we trained markers on dataset A and tested them on dataset B, which involved whole-genome sequencing of 20 individuals from two populations. Genomic prediction analysis revealed that the top SNPs identified via GWAS exhibited notably higher prediction accuracies compared to randomly selected SNPs, particularly with a larger number of SNPs. Cross-validation analyses using dataset A showcased high genomic prediction accuracy, predicting tree health status with over 90% accuracy across the top SNP sets ranging from 500 to 10,000 SNPs from the GWAS datasets. However, no significant results emerged for health status when the model trained on dataset A was tested on dataset B. Our findings illuminate potential genetic markers associated with resistance to ash dieback, offering support for future breeding programs in Poland aimed at combating ash dieback and bolstering conservation efforts for this invaluable tree species.

Causal effects of genetically determined metabolites on androgenetic alopecia: A two-sample Mendelian randomization analysis.

Androgenic alopecia (AGA) is the most common non-scarring alopecia disorder. Given its increasing incidence and onset during adolescence, AGA significantly impacts both the physical and psychological well-being of affected individuals. Emerging evidence suggests a pivotal role of metabolites in AGA. This study aims to elucidate the causal relationship between metabolites and AGA using Mendelian randomization (MR) analysis. We conducted a two-sample Mendelian randomization (TSMR) analysis based on a genome-wide association study (GWAS) to assess the causality of 452 metabolites on AGA. The main approach employed for inferring causal effects was inverse variance weighted (IVW), which was complemented by MR-Egger regression, weighted median, as well as MR pleiotropy residual sum and outlier (MR-PRESSO) approaches. Additionally, sensitivity analyses were performed to ensure result robustness. Single nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs) in GWAS dataset comprising 452 metabolites. Notably, we identified Scyllo-inositol and Alpha-ketoglutarate as the most potent protective factors against AGA, while Heme* and 2-palmitoylglycerophosphocholine* emerged as significant risk factors for AGA. Furthermore, sensitivity analysis revealed no heterogeneity in these findings. Overall, our research suggests a potential causal link between metabolites and AGA, offering a more comprehensive insight into the pathogenesis of AGA and present additional strategies for prevention and treatment.

Roles of negative emotions and personality traits in psoriasis vulgaris: A mendelian randomization study.

Many studies have indicated that negative emotions and personality traits are related to psoriasis, though few have provided causal evidence. Our analysis utilized 15 genome-wide association study datasets to identify instrumental variables associated with negative emotions, personality traits and psoriasis vulgaris. Two-sample Mendelian randomization was conducted to identify the causal associations of negative emotions and personality traits with psoriasis vulgaris. To mitigate bias from multiple tests, we adjusted p-values using the Benjamini-Hochberg method. Our study revealed causal links between negative emotions and psoriasis vulgaris, including depressed affect, worry too long, feeling hurt, guilty feelings, mood swings, unenthusiasm, miserableness, fed-up feelings. However, there was no significant evidence of a causal relationship between feeling lonely and psoriasis vulgaris. Additionally, personality traits including neuroticism and openness to experience were found to have causal effects on psoriasis vulgaris. However, no significant evidence supported a causal relationship between agreeableness, conscientiousness, and extraversion with psoriasis vulgaris. Our findings suggest that experiencing negative emotions including depressed affect, worrying excessively, feeling hurt, guilty feelings, mood swings, lack of enthusiasm, miserableness and fed-up feelings may pose risks for psoriasis vulgaris. Additionally, neuroticism is associated with a risk of psoriasis vulgaris. Conversely, the openness trait may serve a protective role against psoriasis vulgaris.

Causal relationships between gut microbrome and digestive system diseases: A two-sample Mendelian randomization study.

Growing evidences of recent studies have shown that gut microbrome are causally related to digestive system diseases (DSDs). However, causal relationships between the gut microbiota and the risk of DSDs still remain unclear. We utilized identified gut microbiota based on class, family, genus, order and phylum information and digestive system diseases genome-wide association study (GWAS) dataset for two-sample Mendelian randomization (MR) analysis. The inverse variance weighted (IVW) method was used to evaluate causal relationships between gut microbiota and 7 DSDs, including chronic gastritis, colorectal cancer, Crohn's disease, gastric cancer, gastric ulcer, irritable bowel syndrome and esophageal cancer. Finally, we verified the robustness of MR results based on heterogeneity and pleiotropy analysis. We discovered 15 causal associations with genetic liabilities in the gut microbiota and DSDs, such as genus Victivallis, genus RuminococcaceaeUCG005, genus Ruminococcusgauvreauiigroup, genus Oxalobacter and so on. Our MR analysis revealed that the gut microbiota is causally associated with DSDs. Further researches of the gut microbiota and the pathogenesis of DSDs are still significant and provide new methods for the prevention and treatment of DSDs.

XWAS analysis in neuropsychiatric disorders by integrating multi-molecular phenotype quantitative trait loci and GWAS summary data

BackgroundIntegrating quantitative trait loci (QTL) data related to molecular phenotypes with genome-wide association study (GWAS) data is an important post-GWAS strategic approach employed to identify disease-associated molecular features. Various types of molecular phenotypes have been investigated in neuropsychiatric disorders. However, these findings pertaining to distinct molecular features are often independent of each other, posing challenges for having an overview of the mapped genes.MethodsIn this study, we comprehensively summarized published analyses focusing on four types of risk-related molecular features (gene expression, splicing transcriptome, protein abundance, and DNA methylation) across five common neuropsychiatric disorders. Subsequently, we conducted supplementary analyses with the latest GWAS dataset and corresponding deficient molecular phenotypes using Functional Summary-based Imputation (FUSION) and summary data-based Mendelian randomization (SMR). Based on the curated and supplemented results, novel reliable genes and their functions were explored.ResultsOur findings revealed that eQTL exhibited superior ability in prioritizing risk genes compared to the other QTL, followed by sQTL. Approximately half of the genes associated with splicing transcriptome, protein abundance, and DNA methylation were successfully replicated by eQTL-associated genes across all five disorders. Furthermore, we identified 436 novel reliable genes, which enriched in pathways related with neurotransmitter transportation such as synaptic, dendrite, vesicles, axon along with correlations with other neuropsychiatric disorders. Finally, we identified ten multiple molecular involved regulation patterns (MMRP), which may provide valuable insights into understanding the contribution of molecular regulation network targeting these disease-associated genes.ConclusionsThe analyses prioritized novel and reliable gene sets related with five molecular features based on published and supplementary results for five common neuropsychiatric disorders, which were missed in the original GWAS analysis. Besides, the involved MMRP behind these genes could be given priority for further investigation to elucidate the pathogenic molecular mechanisms underlying neuropsychiatric disorders in future studies.

OA08 GWAS meta-analysis of ankylosing spondylitis and Behçet's disease identifies novel MHC-I-opathy genes

Abstract Background/Aims Spondyloarthropathies (SpA) and Behçet's disease (BD) have clinical and HLA locus overlap and have been grouped under MHC-I-opathy [1]. Genetic overlap can help elucidate MHC-I-opathy pathogenesis. Ankylosing spondylitis (AS) is a primary SpA. Here, a cluster-based approach helps to identify overlapping loci between AS and BD of even modest significance. Methods Association clustering methods such as OASIS [2] reduce the multiple-testing burden and are therefore more powerful than single variant analysis for identifying modest genetic effects. Here, two large genome-wide association studies (GWAS) of AS (921 cases, 907 controls) and BD (1215 cases and 1278 healthy controls) from Turkiye, were subjected to OASIS meta-analyses to identify common non-HLA loci [3, 4]. Statistics used to identify significant loci included the novel OASIS locus index (OLI), defined as the product of maximum -logP at a locus with the ratio of actual to predicted number of significant SNPs. Results GWAS for both diseases had the highest significance at the HLA-locus. OASIS avoids the proportional signals problem, inherent in GWAS, by separately analysing highly significant loci (P &amp;lt; 10-8). Hence, of the 234 independent modestly significant non-HLA loci, there were 16 loci common to both AS and BD (Figure 1). These included known MHC-I-opathy loci, 1p31.3 for IL23R (P = 5.37 E-06, OLI = 52.7) and 13q14.11 for LACC1 (P = 7.41 E-06, OLI= 65.3) [1, 5]. Novel loci included 3p21.31 containing CCR9 (P = 2.46 E-05, OLI=25.8), 3q22.3 containing CLDN18 (P = 5.37 E-05, OLI=31.4) and 4q27-4q28.1 containing FGF2 (P = 1.1 E-04, OLI=29.5). Conclusion Five loci containing pathologically relevant genes for MHC-I-opathy were identified using a cluster-based approach in AS and BD GWAS datasets. These large meta-analyses will help identify pathogenic pathways for MHC-I-opathy, an entity that has so far largely remained elusive [6]. Disclosure M. Saeed: None.

Assessing the Occurrence and Influence of Cancer Chemotherapy-Related Pharmacogenetic Alleles in the Chilean Population.

Pharmacogenomic knowledge as a biomarker for cancer care has transformed clinical practice, however, as current guidelines are primarily derived from Eurocentric populations, this limits their application in Latin America, particularly among Hispanic or Latino groups. Despite advancements, systemic chemotherapy still poses challenges in drug toxicity and suboptimal response. This study explores pharmacogenetic markers related to anticancer drugs in a Chilean cohort, filling a gap in Latin American research. Notably, the influence of native South American Mapuche-Huilliche ancestry. To explore pharmacogenetic markers related to anticancer drugs, we utilized an ethnically Admixed Chilean genome-wide association studies (GWAS) dataset of 1095 unrelated individuals. Pharmacogenomic markers were selected from PharmGKB, totaling 36 level 1 and 2 evidence single nucleotide polymorphisms (SNPs) and 571 level 3 SNPs. Comparative analyses involved assessing SNP frequencies across diverse populations from the 1000 Genomes Project. Haplotypes were estimated, and linkage disequilibrium was examined. Ancestry-based association analyses explored relationships between SNPs and Mapuche-Huilliche and European ancestries. Chi-square distribution with p ≤ 0.05 and Bonferroni's multiple adjustment tests determined statistical differences between allele frequencies. Our study reveals significant disparities in SNP frequency within the Chilean population. Notably, dihydropyrimidine dehydrogenase (DPYD) variants (rs75017182 and rs67376798), linked to an increased risk of severe fluoropyrimidine toxicity, exhibit an exceptionally low frequency (minor allele frequency (MAF) < 0.005). Nudix hydrolase 15 (NUDT15) rs116855232, associated with hematological mercaptopurine toxicity, is relatively common (MAF = 0.062), and is further linked to Mapuche-Huilliche ancestry. Thiopurine methyltransferase enzyme (TPMT), implicated in severe toxicity to mercaptopurines, SNPs rs1142345 and rs1800460 of TMPT gene demonstrate higher MAFs in Admixed Americans and the Chilean population (MAF range 0.031-0.057). Finally, the variant in the UDP-glucuronosyltransferase 1 gene (UGT1A1) rs4148323, correlated with irinotecan neutropenia, exhibits the highest MAF in East Asian (MAF = 0.136) and Chilean (MAF = 0.025) populations, distinguishing them from other investigated populations. This study provides the first comprehensive pharmacogenetic characterization of cancer therapy-related SNPs and highlights significant disparities in SNP frequencies within the Chilean population. Our findings underscore the necessity for inclusive research and personalized therapeutic strategies to ensure the equitable and effective application of precision medicine across diverse global communities.

Reverse causation between multiple sclerosis and psoriasis: a genetic correlation and Mendelian randomization study

Observational studies have found a potential bidirectional positive association between multiple sclerosis and psoriasis, but these studies are susceptible to confounding factors. We examined the directionality of causation using Mendelian randomization and estimated the genetic correlation using the linkage disequilibrium score. We performed Mendelian randomization analysis using large-scale genome-wide association studies datasets from the International Multiple Sclerosis Genetics Consortium (IMSGC, 115,803 individuals of European ancestry) and FinnGen (252,323 individuals of European ancestry). We selected several Mendelian randomization methods including causal analysis using summary effect (CAUSE), inverse variance-weighted (IVW), and pleiotropy-robust methods. According to CAUSE and IVW the genetic liability to MS reduces the risk of psoriasis (CAUSE odds ratio [OR] 0.93, p = 0.045; IVW OR 0.93, p = 2.51 × 10–20), and vice versa (CAUSE OR 0.72, p = 0.001; IVW OR 0.71, p = 4.80 × 10–26). Pleiotropy-robust methods show the same results, with all p-values < 0.05. The linkage disequilibrium score showed no genetic correlation between psoriasis and MS (rg =  − 0.071, p = 0.2852). In summary, there is genetic evidence that MS reduces the risk of psoriasis, and vice versa.

Mood disorders influencing endometriosis and adenomyosis: Mendelian randomisation study.

Many studies have found an association between mood-disorder-related traits and endometriosis and adenomyosis. However, the cause-effect relationship remains unclear. We conducted Mendelian randomisation analyses to evaluate any causal relationship between mood disorders and endometriosis as well as different sites of endometriosis. Summary-level statistics for mood-disorder-related traits and endometriosis (8288 cases, 68 969 controls) in European populations were derived from large-scale data-sets of genome-wide association studies. A two-sample Mendelian randomisation was performed using the inverse-variance weighted and weight median methods. Further sensitivity analyses, including heterogeneity, pleiotropy and leave-one-out analyses, were conducted to test the consistency of the results. Genetically determined mood swings (odds ratio = 2.557, 95% CI: 1.192-5.483, P = 0.016) and major depression (odds ratio = 1.233, 95% CI: 1.019-1.493, P = 0.031) were causally associated with an increased risk of endometriosis. Mood swings (odds ratio = 4.238, 95% CI: 1.194-15.048, P = 0.025) and major depression (odds ratio = 1.512, 95% CI: 1.052-2.173, P = 0.025) were also causally associated with the risk of adenomyosis. Sensitivity analyses confirmed the reliability of the results. Our results suggest that mood-disorder-related traits increase the risk of endometriosis and adenomyosis. This study provides new insights into the potential pathogenesis of endometriosis and adenomyosis, and highlights the importance of preventing endometriosis and adenomyosis in patients with mood-disorder-related traits.

The causal relationship between genetically predicted blood metabolites and idiopathic pulmonary fibrosis: A bidirectional two-sample Mendelian randomization study.

Numerous metabolomic studies have confirmed the pivotal role of metabolic abnormalities in the development of idiopathic pulmonary fibrosis (IPF). Nevertheless, there is a lack of evidence on the causal relationship between circulating metabolites and the risk of IPF. The potential causality between 486 blood metabolites and IPF was determined through a bidirectional two-sample Mendelian randomization (TSMR) analysis. A genome-wide association study (GWAS) involving 7,824 participants was performed to analyze metabolite data, and a GWAS meta-analysis involving 6,257 IPF cases and 947,616 control European subjects was conducted to analyze IPF data. The TSMR analysis was performed primarily with the inverse variance weighted model, supplemented by weighted mode, MR-Egger regression, and weighted median estimators. A battery of sensitivity analyses was performed, including horizontal pleiotropy assessment, heterogeneity test, Steiger test, and leave-one-out analysis. Furthermore, replication analysis and meta-analysis were conducted with another GWAS dataset of IPF containing 4,125 IPF cases and 20,464 control subjects. Mediation analyses were used to identify the mediating role of confounders in the effect of metabolites on IPF. There were four metabolites associated with the elevated risk of IPF, namely glucose (odds ratio [OR] = 2.49, 95% confidence interval [95%CI] = 1.13-5.49, P = 0.024), urea (OR = 6.24, 95% CI = 1.77-22.02, P = 0.004), guanosine (OR = 1.57, 95%CI = 1.07-2.30, P = 0.021), and ADpSGEGDFXAEGGGVR (OR = 1.70, 95%CI = 1.00-2.88, P = 0.0496). Of note, the effect of guanosine on IPF was found to be mediated by gastroesophageal reflux disease. Reverse Mendelian randomization analysis displayed that IPF might slightly elevate guanosine levels in the blood. Conclusively, hyperglycemia may confer a promoting effect on IPF, highlighting that attention should be paid to the relationship between diabetes and IPF, not solely to the diagnosis of diabetes. Additionally, urea, guanosine, and ADpSGEGDFXAEGGGVR also facilitate the development of IPF. This study may provide a reference for analyzing the potential mechanism of IPF and carry implications for the prevention and treatment of IPF.

Investigating genetic links between blood metabolites and preeclampsia

BackgroundObservational studies have revealed that metabolic disorders are closely related to the development of preeclampsia (PE). However, there is still a research gap on the causal role of metabolites in promoting or preventing PE. We aimed to systematically explore the causal association between circulating metabolites and PE.MethodsSingle nucleotide polymorphisms (SNPs) from genome-wide association study (GWAS) of 486 blood metabolites (7,824 participants) were extracted as instrumental variables (P < 1 × 10− 5), GWAS summary statistics for PE were obtained from FinnGen consortium (7,212 cases and 194,266 controls) as outcome, and a two-sample Mendelian randomization (MR) analysis was conducted. Inverse variance weighted (IVW) was set as the primary method, with MR–Egger and weighted median as auxiliary methods; the instrumental variable strength and confounding factors were also assessed. Sensitivity analyses including MR-Egger, Cochran’s Q test, MR-PRESSO and leave-one-out analysis were performed to test the robustness of the MR results. For significant associations, repeated MR and meta-analysis were performed by another metabolite GWAS (8,299 participants). Furthermore, significantly associated metabolites were subjected to a metabolic pathway analysis.ResultsThe instrumental variables for the metabolites ranged from 3 to 493. Primary analysis revealed a total of 12 known (e.g., phenol sulfate, citrulline, lactate and gamma-glutamylglutamine) and 11 unknown metabolites were associated with PE. Heterogeneity and pleiotropy tests verified the robustness of the MR results. Validation with another metabolite GWAS dataset revealed consistency trends in 6 of the known metabolites with preliminary analysis, particularly the finding that genetic susceptibility to low levels of arachidonate (20:4n6) and citrulline were risk factors for PE. The pathway analysis revealed glycolysis/gluconeogenesis and arginine biosynthesis involved in the pathogenesis of PE.ConclusionsThis study identifies a causal relationship between some circulating metabolites and PE. Our study presented new perspectives on the pathogenesis of PE by integrating metabolomics with genomics, which opens up avenues for more accurate understanding and management of the disease, providing new potential candidate metabolic molecular markers for the prevention, diagnosis and treatment of PE. Considering the limitations of MR studies, further research is needed to confirm the causality and underlying mechanisms of these findings.

Identification of potential candidate genes associated with milk protein differences in Holstein cows: a meta-analysis integrating GWAS and RNA-Seq transcriptome

Despite the identification of candidate genes influencing milk protein, the connections between genes and regulatory pathways remains elusive. This study aimed integrate findings from genome-wide association studies (GWAS) and RNA sequencing (RNA-Seq) through meta-analysis to pinpoint single nucleotide polymorphisms (SNPs) and genes responsible for high and low protein yield in cows. Previous GWAS and RNA-Seq analyses had identified 663 SNPs and 1106 genes ( P &lt; 0.05). Twenty SNPs from GWAS, 10 genes from RNA-Seq, and 49 SNP/gene associations from both datasets, were identified using meta-analysis. Meta-analysis validated several SNPs previously identified through GWAS, such as rs135549651 ( P = 2.6 × 10−256), rs109146371 ( P = 3.1 × 10−208), rs109350371 ( P = 4.0 × 10−207), and rs109774038 ( P = 8.6 × 10−587). Genes identified in RNA-Seq experiments, including NR4A1 ( P = 3.2 × 10−7), ATF3 ( P = 9.6 × 10−7), CDH16 ( P = 9.9 × 10−7), VEGFA ( P = 1.0 × 10−6), and SAA3 ( P = 7.3 × 10−11), were confirmed. The combined GWAS and RNA-Seq datasets highlighted CCND2 ( P = 8.9 × 10−111), MAPK15 ( P = 1.3 × 10−151), and CPSF1 ( P = 1.2 × 10−306) as the most significant genes. Additionally, significant gene ontology (GO) terms, including ionizing radiation ( P = 1.5 × 10−4), nuclear pore cytoplasmic filaments ( P = 9.4 × 10−5), and phenylalanine 4-monooxygenase activity ( P = 1.4 × 10−5), were identified. In conclusion, the integration of GWAS and RNA-Seq, coupled with GO enrichment, allowed identification of candidate SNPs and genes with higher accuracy. These findings improve our knowledge about genomic architecture of milk protein and enhance evaluation of Holstein cows.

Genetic association between smoking and DLCO in idiopathic pulmonary fibrosis patients

BackgroundObservational studies have shown that smoking is related to the diffusing capacity of the lungs for carbon monoxide (DLCO) in individuals with idiopathic pulmonary fibrosis (IPF). Nevertheless, further investigation is needed to determine the causal effect between these two variables. Therefore, we conducted a study to investigate the causal relationship between smoking and DLCO in IPF patients using two-sample Mendelian randomization (MR) analysis.MethodsLarge-scale genome-wide association study (GWAS) datasets from individuals of European descent were analysed. These datasets included published lifetime smoking index (LSI) data for 462,690 participants and DLCO data for 975 IPF patients. The inverse-variance weighting (IVW) method was the main method used in our analysis. Sensitivity analyses were performed by MR‒Egger regression, Cochran’s Q test, the leave-one-out test and the MR-PRESSO global test.ResultsA genetically predicted increase in LSI was associated with a decrease in DLCO in IPF patients [ORIVW = 0.54; 95% CI 0.32–0.93; P = 0.02].ConclusionsOur study suggested that smoking is associated with a decrease in DLCO. Patients diagnosed with IPF should adopt an active and healthy lifestyle, especially by quitting smoking, which may be effective at slowing the progression of IPF.

The causal impact of gut microbiota on circulating adipokine concentrations: a two-sample Mendelian randomization study.

Evidence from previous experimental and observational research demonstrates that the gut microbiota is related to circulating adipokine concentrations. Nevertheless, the debate as to whether gut microbiome composition causally influences circulating adipokine concentrations remains unresolved. This study aimed to take an essential step in elucidating this issue. We used two-sample Mendelian randomization (MR) to causally analyze genetic variation statistics for gut microbiota and four adipokines (including adiponectin, leptin, soluble leptin receptor [sOB-R], and plasminogen activator inhibitor-1 [PAI-1]) from large-scale genome-wide association studies (GWAS) datasets. A range of sensitivity analyses was also conducted to assess the stability and reliability of the results. The composite results of the MR and sensitivity analyses revealed 22 significant causal associations. In particular, there is a suggestive causality between the family Clostridiaceae1 (IVW: β = 0.063, P = 0.034), the genus Butyrivibrio (IVW: β = 0.029, P = 0.031), and the family Alcaligenaceae (IVW: β=-0.070, P = 0.014) and adiponectin. Stronger causal effects with leptin were found for the genus Enterorhabdus (IVW: β=-0.073, P = 0.038) and the genus Lachnospiraceae (NK4A136 group) (IVW: β=-0.076, P = 0.01). Eight candidate bacterial groups were found to be associated with sOB-R, with the phylum Firmicutes (IVW: β = 0.235, P = 0.03) and the order Clostridiales (IVW: β = 0.267, P = 0.028) being of more interest. In addition, the genus Roseburia (IVW: β = 0.953, P = 0.022) and the order Lactobacillales (IVW: β=-0.806, P = 0.042) were suggestive of an association with PAI-1. This study reveals a causal relationship between the gut microbiota and circulating adipokines and may help to offer novel insights into the prevention of abnormal concentrations of circulating adipokines and obesity-related diseases.

Causal Relationship Between Endometriosis and Pelvic Inflammatory Diseases: Mendelian Randomization Study.

This study explores the causal relationship between endometriosis and pelvic inflammatory diseases (PID). The study utilized genome-wide association study (GWAS) datasets for endometriosis ("finn-b-N14_ENDOMETRIOSIS") and PID ("finn-b-N14_OTHFEMPELINF"). Subsequently, two-sample Mendelian randomization (MR) analyses were conducted using inverse variance weighting (IVW), Egger regression (MR-Egger), and weighted median (WM) methods. Heterogeneity was evaluated using Cochran's Q test, and in case of detected outliers, they were removed for re-evaluation of MR causality. From the endometriosis GWAS dataset, 33 single nucleotide polymorphisms (SNPs) were selected as instrumental variables. All three methods, IVW (OR = 1.39, P < 1×10-8), MR-Egger (OR = 1.41, P = 0.003), and WM (OR = 1.37, P = 1.16×10-5) confirmed a causal relationship between endometriosis and PID. The association between endometriosis and pelvic inflammation remained unaffected by the exclusion of individual SNPs. Lastly, Cochran's Q test and funnel plots showed no evidence of SNP asymmetry. The results of the MR analysis support a potential causal relationship between endometriosis and an increased risk of PID.