Causal Connection Research Articles

Association of Obstructive Sleep Apnea on Heart Failure and Its Risk Factors: A Two-Step Mendelian Randomization Study

Introduction: Recent studies have indicated that obstructive sleep apnea (OSA) is linked to a higher likelihood of heart failure (HF). However, the causal connection between the two conditions is uncertain. We aimed to investigate the causal association of OSA with HF and its risk factors. Methods: The OSA summary statistics are derived from the FinnGen database, including 38,998 cases and 336,659 controls. HF summary statistics come from HERMES, the UK Biobank, and the FinnGen database. A two-sample mendelian randomization (MR) analysis was conducted to examine the causality of OSA on HF risk. Furthermore, the mediator effect of potential risk factors was assessed by a two-step MR. Results: The results of MR analysis demonstrated that genetically determined OSA is causal associated with the higher likelihood of HF (HERME: odds ratio [OR] = 1.222; 95% confidence interval [CI]: 1.091, 1.369; p = 5.19 × 10−4) (FinnGen: OR = 1.233; 95% CI: 1.129, 1.346; p = 3.32 × 10−6) (UK Biobank: OR = 1.002; 95% CI: 1.000, 1.003; p = 0.014). Two-step MR analysis indicated that obesity, blood glucose, depression, and other CVDs have significant mediating effects on the causal effect between OSA and HF. Conclusion: This MR study emphasizes the causal effect of OSA on HF risk. Adiposity traits play a major role in the process of OSA leading to HF. Considering the detrimental impact of OSA on HF, it becomes imperative to prioritize the prevention and management of HF in individuals afflicted with OSA. The foremost intervention strategy should revolve around effective obesity management.

Assessing the causal effect of inflammation-related genes on myocarditis: A Mendelian randomization study.

Prior evidence has shown a significant link between inflammation and the development of myocarditis. This study aimed to investigate the causal relationship between inflammation-related genes (IRGs) and myocarditis. In this study, the causal relationship between 167 IRGs and myocarditis were investigated using datasets from the Gene Set Enrichment Analysis and Integrative Epidemiology Unit open genome-wide association study (IEU OpenGWAS) databases. The GWAS data (finn-b-I9 MYOCARD) contained single nucleotide polymorphisms (SNPs) data from 117755 myocarditis samples (16379455 SNPs, 829 cases vs. 116926 controls). Five algorithms [MR-Egger, weighted median, inverse variance weighted (IVW), simple mode, and weighted mode regression] were employed for the MR analysis, with IVW as the primary method, and sensitivity analysis was conducted. Subcellular localization and protein-protein interaction (PPI) network analyses were performed for selected biomarkers. Results were verified in ebi-a-GCST90018882 (24180570 SNPs, 633 cases vs. 427278 controls) and finn-b-I9 MYOCARD EXNONE (16380466 SNPs, 829 cases vs. 217963 controls) to enhance reliability. IRF7 and ADORA2B were shown to be two exposure factors after screening. Univariable MR (UVMR) analysis revealed that IRF7 was a risk factor for myocarditis [IVW: odd ratio (OR)=1.041, 95% confidence interval (CI)=1.018-1.955, P=0.039], while ADORA2B was a protective factors for myocarditis (IVW: OR=0.799, 95% CI=0.640-0.997, P=0.047). Sensitivity analysis confirmed the robustness of these findings. Multivariable MR (MVMR) analysis further demonstrated a direct causal role of ADORA2B in preventing myocarditis. Subcellular localization analysis indicated predominant cytoplasmic expression and limited mitochondrial expression for both genes. The results of PPI analysis showed that 20 genes were predicted to be associated with IRF7 function, such as response to type I interferon, pattern recognition receptor signalling pathway, and toll-like receptor signalling pathway. The results in finn-b-I9 MYOCARD EXNONE were consistent with MR analysis. The findings indicated there was a causal connection between IRGs (IRF7 and ADORA2B) and myocarditis, which offered a crucial point of reference and guidance for future studies and myocarditis treatment.

The weather today rocks or sucks for my tree: exploring the understanding of climate impacts on forests at high school level through tweets

Abstract. With the progression of global warming, impacts on the human sphere will undoubtedly increase. One prominent example at mid-latitudes is the stress on forests caused by climate change, which the BayTreeNet project (https://baytreenet.de/, last access: 30 July 2024) addresses from an interdisciplinary viewpoint. Scientists from physical climatology, dendroecology, and educational research collaborate to examine how long-term changes in weather patterns affect the state of trees, and how the atmosphere–tree relation can be used to the advantage of improving the communication of climate change effects to, in particular, high school students. This article presents a 1-week case study for the summer of 2021, when a distinct variability in weather patterns induced significant tree responses. The students of seven selected partner schools commented on the measured tree and weather data, which were available in real time, in the form of tweets and in conjunction with their educational geography program. The analyses of the tweets reveal that the students succeed in verbalizing the measured weather and, furthermore, manage to draw links between the stem diameter changes in trees and the weather variability. Problems arise with the use of less perceivable variables like the sap flow in the trees; also, the student posts exhibit shortcomings in establishing causal connections. Hence, the case study points to a discrepancy between describing basic environmental information and appreciating or understanding the underlying mechanistic links. This point will serve to refine future classroom concepts and, moreover, to enhance the communication of climate change effects on forests to the general public.

The 1400 metabolite-mediated relationship between 91 inflammatory cytokines and migraine: An exploratory two-step Mendelian randomization study.

Inflammatory cytokines and migraines have been associated in previous research, but the underlying mechanisms of action are still elusive. The biological functions of metabolites are crucial in the onset of migraine. Our goals were to clarify the cause-and-effect connection between inflammatory cytokines and migraines and explore the potential mediating function of metabolites. Utilizing summary-level data from genome-wide association studies (GWAS), we conducted two-sample Mendelian randomization (MR) analyses to evaluate the possible causal connection between inflammatory cytokines and migraines. A two-step MR analysis was employed to further investigate the potential mediating pathways of metabolites. MR analysis identified a total of 9 inflammatory cytokines that were genetically associated with migraines, and we subsequently identified 21 mediated relationships, with 20 metabolites (13 metabolites, 7 ratios) acting as potential mediators between 8 inflammatory cytokines and migraine. The 9 inflammatory cytokines were beta-nerve growth factor levels (β-NGF), T-cell surface glycoprotein CD5 levels (CD5), T-cell surface glycoprotein CD6 isoform levels (CD6), C-X-C motif chemokine 11 levels (CXCL11), interleukin-4 levels (IL-4), oncostatin-M levels (OSM), signalling lymphocytic activation molecule levels (SLAM), C-C motif chemokine 25 levels (CCL25) and monocyte chemoattractant protein-1 levels (MCP-1). Our research findings provide evidence for both a causal connection between inflammatory cytokines and migraines, as well as a metabolite-mediated pathway. These biomarkers facilitate the detection, diagnosis and treatment of migraines while offering fresh perspectives on their underlying mechanisms.

Causal influence of plasma metabolites on age-related macular degeneration: A Mendelian randomization study.

Using genome-wide association study data from European populations, this research clarifies the causal relationship between plasma metabolites and age-related macular degeneration (AMD) and employs Metabo Analyst 5.0 for enrichment analysis to investigate their metabolic pathways. Employing Mendelian randomization analysis, this study leveraged single nucleotide polymorphisms significantly associated with plasma metabolites as instrumental variables. This approach established a causal link between metabolites and AMD. Analytical methods such as inverse-variance weighted, Mendelian randomization-Egger, and weighted median were applied to validate causality. Mendelian Randomization Pleiotropy Residual Sum and Outlier was utilized for outlier detection and correction, and Cochran's Q test was conducted to assess heterogeneity. To delve deeper into the metabolic characteristics of AMD, metabolic enrichment analysis was performed using Metabo Analyst 5.0. These combined methods provided a robust framework for elucidating the metabolic underpinnings of AMD. The 2-sample MR analysis, after meticulous screening, identified causal relationships between 88 metabolites and AMD. Of these, 16 metabolites showed a significant causal association. Following false discovery rate correction, 3 metabolites remained significantly associated, with androstenediol (3 beta, 17 beta) disulfate (2) exhibiting the most potent protective effect against AMD. Further exploration using Metabo Analyst 5.0 highlighted 4 metabolic pathways potentially implicated in AMD pathogenesis. This pioneering MR study has unraveled the causal connections between plasma metabolites and AMD. It identified several metabolites with a causal impact on AMD, with 3 maintaining significance after FDR correction. These insights offer robust causal evidence for future clinical applications and underscore the potential of these metabolites as clinical biomarkers in AMD screening, treatment, and prevention strategies.

Causal relationship between immune cells and pulmonary arterial hypertension: Mendelian randomization analysis.

Immunity and inflammation in pulmonary arterial hypertension (PAH) has gained more attention. This research aimed to investigate the potential causal connections between 731 immunophenotypes and the likelihood of developing PAH. We obtained immunocyte data and PAH from openly accessible database and used Mendelian randomization (MR) analysis to evaluate the causal association between each immunophenotype and PAH. Various statistical methods were employed: the MR-Egger, weighted median, inverse variance weighted (IVW), simple mode, and weighted mode. In the study of 731 different types of immune cells, it was found that 9 showed a potential positive connection (IVW P < .05) with increased risk of PAH, while 19 had a possible negative link to decreased risk. Following false discovery rate (FDR) adjustment, the analysis using the IVW method demonstrated that 5 immune phenotypes were significantly associated with PAH (FDR < 0.05, OR > 1). Conversely, there was a negative correlation between PAH and 4 immune cell types (FDR < 0.05, OR < 1). Sensitivity analyses suggested the robustness of all MR findings. This research, for the first time, has revealed indicative evidence of a causal link between circulating immune cell phenotypes and PAH through genetic mechanisms. These results underscore the importance of immune cells in the pathogenesis of PAH.

The Impact of Ethnic Identity on Language Attitudes

ABSTRACT Few studies have explored the relationship between ethnic identity and language attitudes in heritage language speakers. Via self-reported questionnaire data, the present study examined correlational and causal connections between ethnic identity and language attitudes in three generations of Israeli and American Mountain Jews. Native to the eastern Caucasus, Mountain Jews immigrated in the 1990s to Israel and the United States, bringing with them two heritage languages, Juhuri and Russian. The effect of ethnic identity on language attitudes emerged as strong for both Juhuri and Russian, but varied across countries, generations, languages, and types of attitudes. Strong correlations between ethnic identity and language attitudes were found for both heritage languages in Israel, but in the United States the connection between Russian and Mountain Jewish identity was lost across generations. Results are discussed in terms of previous research on heritage languages, identity and attitudes, and highlight the revival of ethnic identity among second-generation immigrants.

Neuroelectrophysiology-compatible electrolytic lesioning.

Lesion studies have historically been instrumental for establishing causal connections between brain and behavior. They stand to provide additional insight if integrated with multielectrode techniques common in systems neuroscience. Here, we present and test a platform for creating electrolytic lesions through chronically implanted, intracortical multielectrode probes without compromising the ability to acquire neuroelectrophysiology. A custom-built current source provides stable current and allows for controlled, repeatable lesions in awake-behaving animals. Performance of this novel lesioning technique was validated using histology from ex vivo and in vivo testing, current and voltage traces from the device, and measurements of spiking activity before and after lesioning. This electrolytic lesioning method avoids disruptive procedures, provides millimeter precision over the extent and submillimeter precision over the location of the injury, and permits electrophysiological recording of single-unit activity from the remaining neuronal population after lesioning. This technique can be used in many areas of cortex, in several species, and theoretically with any multielectrode probe. The low-cost, external lesioning device can also easily be adopted into an existing electrophysiology recording setup. This technique is expected to enable future causal investigations of the recorded neuronal population's role in neuronal circuit function, while simultaneously providing new insight into local reorganization after neuron loss.

Uncovering a Causal Connection between Gut Microbiota and Six Thyroid Diseases: A Two-Sample Mendelian Randomization Study.

Recent studies have established associations between the gut microbiota (GM) and thyroid diseases (TDs). However, their causal relationships remain elusive. To investigate this causality, we conducted a two-sample Mendelian randomization (MR) analysis using genome-wide association study (GWAS) data from MiBioGen and FinnGen, with GM as the exposure and six TDs as outcomes. We identified 32 microbial taxa linked to the risk of six TDs. The Clostridium innocuum group, Ruminiclostridium5, and Lachnoclostridium exhibited protective effects against nontoxic diffuse goiter (NDG). Conversely, an increased risk of NDG was associated with Ruminococcaceae UCG002, Alistipes, Methanobrevibacter, Marvinbryantia, and Ruminococcaceae UCG014. Bifidobacterium and Sutterella were protective against nontoxic multinodular goiter (NMG), while the Ruminococcus gauvreauii group and Rikenellaceae RC9 gut group heightened NMG risk. Protective effects against nontoxic single thyroid nodule (NSTN) were observed with Defluviitaleaceae UCG011, Ruminococcus1, and Ruminococcaceae UCG010, whereas increased risk was linked to Alistipes, the Ruminococcus gauvreauii group, and Lachnospiraceae UCG010. Ruminiclostridium9, Victivallis, and Butyricimonas offered protection against thyrotoxicosis with Graves' Disease (GD), while the Eubacterium rectale group, Desulfovibrio, Bifidobacterium, Collinsella, Oscillospira, and Catenibacterium were risk factors. For thyrotoxicosis with Plummer Disease (PD), protective taxa included Butyricimonas and Lachnospira, whereas Dorea, Eggerthella, Odoribacter, Lactobacillus, Intestinimonas, and Phascolarctobacterium increased risk. Lastly, Parasutterella was protective against thyrotoxicosis with toxic single thyroid nodule (TSTN), while increased risk was associated with Sutterella, Oscillibacter, and Clostridium sensu stricto1. Our findings support a causal relationship between specific GM and TDs at the genetic level, laying the foundation for future research into potential mechanisms and the identification of novel therapeutic targets.

The vicious cycle of frailty and pain: a two-sided causal relationship revealed.

The decline in physiological functions in the older people is frequently accompanied with pain and frailty, yet the causal connection between frailty and pain remains uncertain. In this study, we utilized a two-sample Mendelian randomization (MR) approach to investigate the potential causal association between frailty and pain. Two-sample bidirectional MR was conducted using summary data from genome-wide association studies to examine the potential causal relationship between frailty (defined by the frailty index and frailty phenotype) and pain. Summary genome wide association statistics were extracted from populations of European ancestry. We also investigated the causal relationship between frailty and site-specific pain, including joint pain, limb pain, thoracic spine pain and low back pain. Causal effects were estimated using the inverse variance weighting method. Sensitivity analyses were performed to validate the robustness of the results. Genetic predisposition to frailty was associated with an increased risk of pain (frailty phenotype odds ratio [OR]: 1.73; P = 3.54 × 10-6, frailty index OR: 1.36; P = 2.43 × 10-4). Meanwhile, individuals with a genetic inclination toward pain had a higher risk of developing frailty. Regarding site-specific pain, genetic prediction of the frailty phenotype increased the occurrence risk of joint pain, limb pain and low back pain. Reverse MR analysis further showed that limb pain and low back pain were associated with an increased risk of frailty occurrence. This study presented evidence supporting a bidirectional causal relationship between frailty and pain. We highlighted the significance of addressing pain to prevent frailty and recommend the inclusion of pain assessment in the evaluation system for frailty.

Modifications in the Composition of the Gut Microbiota in Rats Induced by Chronic Sleep Deprivation: Potential Relation to Mental Disorders.

Sleep deprivation(SD) has numerous negative effects on mental health. A growing body of research has confirmed the implication of gut microbiota in mental disorders. However, the specific modifications in mammalian gut microbiota following SD exhibit variations across different studies. Male specific-pathogen-free Wistar rats were given a modified multiple-platform exposure for 7 days of SD. Fecal samples were obtained from the control and SD groups both at baseline and after 7 days of SD. We utilized 16S rDNA gene sequencing to investigate the gut microbial composition and functional pathways in rats. Analysis of the microbiota composition revealed a significant change in gut microbial composition after chronic SD, especially at the phylum level. The relative abundances of p_Firmicutes, g_Romboutsia, and g_Enterococcus increased, whereas those of p_Bacteroidetes, p_Verrucomicrobia, p_Fusobacteria, g_Akkermansia, and g_Cetobacterium decreased in animals after chronic SD compared with controls or animals before SD. The ratio of Firmicutes to Bacteroidetes exhibited an increase following SD. The relative abundance of gut microbiota related to the functional pathways of GABAergic and glutamatergic synapses was observed to be diminished in rats following SD compared to pre-SD. Collectively, these findings suggest that chronic SD causes significant alterations in both the structural composition and functional pathways of the gut microbiome. Further researches are necessary to investigate the chronological and causal connections among SD, the gut microbiota and mental disorders.

Promoting green taxation and sustainable energy transition for low-carbon development

Since there is a scientific consensus that the energy sector has brought the planet to the tipping point of climate change, transitioning to sustainable energy sources is inevitable to halt foreseeable climatic adversities. This study looks at how promoting green taxation and sustainable energy transition affected the G7 nations’ goal of low-carbon development between 1994 and 2020. This study used Generalized Least Squares Random Effects Regression and Driscoll-Kraay Standard Errors-based Least Sqaures approaches for empirical analysis. The latter approach accounts for cross-sectional dependence, heteroscedasticity, and autocorrelation to provide robust empirical outcomes. The empirical results are as follows: Firstly, through lowering CO2 intensity and greenhouse gas emissions, the environmental tax revenues have enhanced the condition of the environment. The total tax revenues linked to the environment had a greater overall impact than the tax revenues related to the energy industry. Furthermore, compared to CO2 intensity, both of the environmental tax revenue factors contributed considerably more to greenhouse gas emissions. Second, the sustainable energy transition helped to lower greenhouse gas and CO2 intensity. Among covariates, international trade was supportive of low-carbon development, but industrialization and GDP per capita did the opposite. The panel bootstrap causality revealed a unidirectional causal connection from all independent variables, except foreign direct investment, to CO2 intensity and greenhouse gas emissions. These results demonstrated that the G7 nations’ environmental policies supported their commitment to achieving low-carbon development goals. In this respect, the G7 nations’ environmental emission reduction efforts benefited more from the overall environmental tax revenues. To secure the industrial emissions reduction for a future with net-zero carbon emissions, it is thus advised to continue using policies that price environmental emissions, such as the carbon taxation regulations. Additionally, plans for the sustainable energy transition that includes a quick rise in renewable energy sources in the overall energy mix are successful in lowering environmental emissions. For environmental sustainability and low-carbon development, it is thus advised to divert the taxation burden from renewable energy technologies to the fossil fuel industry to enhance the sustainable energy transition phenomenon for achieving Sustainable Development Goals (especially SDG-7 and SDG-13).

Leveraging AI for Promoting Sustainable Environments in G-7: The Impact of Financial Development and Digital Economy via MMQR Approach

This study investigates the role of Artificial Intelligence (AI) in promoting a sustainable environment within the G-7 countries by testing the Load Capacity Curve (LCC) hypothesis. Additionally, it examines the effects of financial development, the digital economy, and urbanization on the load capacity factor using data from 2010 to 2022. The research employs cross-sectional dependence and slope homogeneity tests, revealing issues of cross-sectional dependence and heterogeneity. Panel unit root tests, both first and second generation, confirm that the variables are free from unit root problems. Furthermore, panel cointegration tests indicate that the variables are cointegrated in the long run. To assess the impact of the explanatory variables on the load capacity factor, the study utilizes the Method of Moments Quantile Regression (MMQR). The findings reveal a U-shaped relationship between income and the load capacity factor, supporting the LCC hypothesis in the G-7 region. The results also indicate that AI innovation and financial development have a significant positive correlation with the load capacity factor. In contrast, the digital economy and urbanization are found to significantly reduce the load capacity factor. Robustness checks, including the Driscoll-Kraay standard error, Augmented Mean Group, and Common Correlated Effect Mean Group estimation approaches, validate the findings obtained from the MMQR method. Moreover, the Dumitrescu-Hurlin (D-H) causality assessment is utilized to explore the causal connections between variables. The results reveal a unidirectional causal relationship between income and the load capacity factor. Additionally, bidirectional causal relationships are the remaining explanatory variables and load capacity factors.

Plasma Proteome, Metabolome Mendelian Randomization Identifies Sepsis Therapeutic Targets.

The interrelation between the plasma proteome and plasma metabolome with sepsis presents a multifaceted dynamic that necessitates further research to elucidate the underlying causal mechanisms. Our investigation used public genome-wide association study (GWAS) data to explore the relationships among the plasma proteome, metabolome, and sepsis, considering different sepsis subgroup. Initially, two-sample MR established causal connections between the plasma proteome and metabolome with sepsis. Subsequently, multivariate and iterative MR analyses were performed to understand the complex interactions in plasma during sepsis. The validity of these findings was supported by thorough sensitivity analyses. The study identified 25 plasma proteins that enhance risk and 34 that act as protective agents in sepsis. Post p-value adjustment (0.05/1306), ICAM5 emerged with a positive correlation to sepsis susceptibility (p-value = 2.14E-05, OR = 1.10, 95% CI = 1.05-1.15), with this significance preserved across three sepsis subgroup examined. Additionally, 29 plasma metabolites were recognized as risk factors, and 15 as protective factors for sepsis outcomes. Following p-value adjustment (0.05/997), elevated levels of 1,2,3-benzenetriol sulfate (2) was significantly associated with increased sepsis risk (p-value = 3.37E-05, OR = 1.18, 95% CI = 1.09-1.28). Further scrutiny revealed that this plasma metabolite notably augments the abundance of ICAM5 protein (p-value = 3.52E-04, OR = 1.11, 95% CI = 1.04-1.17), devoid of any detected heterogeneity, pleiotropy, or reverse causality. Mediated MR revealed ICAM5 mediated 11.9% of 1,2,3-benzenetriol sulfate (2)'s total effect on sepsis progression. This study details the causal link between the plasma proteome and metabolome with sepsis, highlighting the roles of ICAM5 and 1,2,3-benzenetriol sulfate (2) in sepsis progression, both independently and through crosstalk.

Causal associations of obstructive sleep apnea with Chronic Respiratory Diseases: a Mendelian Randomization study

PurposeThis study aimed to elucidate the causal relationship between Obstructive Sleep Apnea (OSA) and Chronic Respiratory Diseases (CRDs), employing Mendelian Randomization (MR) to overcome limitations inherent in observational studies.MethodsUtilizing a two-sample MR approach, this study analyzed genetic variants as instrumental variables to investigate the causal link between OSA and various CRDs, including chronic obstructive pulmonary disease (COPD), asthma, bronchiectasis, and idiopathic pulmonary fibrosis (IPF). Data were sourced from the FinnGen Consortium (OSA, n = 375,657) and UK Biobank, focusing on genome-wide associations between single-nucleotide polymorphisms (SNPs) and the diseases. Instrumental variables were selected based on strict criteria, and analyses included a random-effects inverse-variance weighted method supplemented by several sensitivity analyses.ResultsThe study suggests a protective effect of OSA against COPD (OR = 0.819, 95% CI 0.722–0.929, P-value = 0.002), which becomes non-significant after adjusting for BMI, indicating a potential mediating role of BMI in the OSA-COPD nexus. No significant causal links were found between OSA and other CRDs (asthma, IPF, bronchiectasis) or between COPD, asthma, and OSA.ConclusionsOur findings reveal a BMI-mediated protective effect of OSA on COPD, with no causal connections identified between OSA and other CRDs. These results emphasize the complex relationship between OSA, BMI, and COPD, guiding future clinical strategies and research directions, particularly in light of the study’s genetic analysis limitations.

The Meaning of Causality and the Premise and Root of Its Existence

This article aims to understand the most fundamental operating principles of the phenomenal world and figure out how phenomena within the phenomenal world are interconnected. Causality is the most basic connection, rule, logic and fact of the phenomenal world, since everything in the phenomenal world is originally in the interconnection of three elements: cause, condition and effect. Finding the causal connection between things and utilising it to achieve the goal of avoiding harm and ultimately attaining happiness is the fundamental motivation for all human intellectual activities, including scientific research, philosophical discernment, and religious beliefs. The article gives a universal definition of causation as the primordial, underlying, transcendental, inherent, intrinsic, ultimate, essential, fundamental, inevitable, invariable, timeless, universal, complex, multidimensional, dynamic connection, law, logic, and fact among the three elements of cause, condition and result in the phenomenal world. The article explains in detail why the foregoing definition is universal from both ontological and epistemological perspectives.

The impact of immunity on the risk of coronary artery disease: insights from a multiomics study.

Immune inflammation is intricately associated with coronary artery disease (CAD) progression, necessitating the pursuit of more efficacious therapeutic strategies. This study aimed to uncover potential therapeutic targets for CAD and myocardial infarction (MI) by elucidating the causal connection between regulatory immune-related genes (RIRGs) and these disorders. We performed summary data-based Mendelian randomization analysis to assess the therapeutic targets linked to expression quantitative trait loci and methylation quantitative trait loci of RIRGs in relation to CAD and MI. Independent validation cohorts and datasets from coronary artery and left ventricular heart tissue were analyzed. To strengthen causal inference, colocalization analysis and PhenoScanner phenotype scans were employed. Utilizing multiomics integration, we pinpointed EIF2B2, FCHO1, and DDT as CAD risk genes. Notably, EIF2B2 and FCHO1 displayed significant associations with MI. High EIF2B2 expression, regulated by cg16144293, heightened CAD and MI risk at rs175438. In contrast, enhanced FCHO1 expression, modulated by cg18329931, reduced CAD and MI risk at rs13382133. DDT upregulation influenced by cg11060661 and cg09664220 was associated with decreased CAD risk at rs5760120. Colocalization analysis firmly established these relationships. EIF2B2, FCHO1, and DDT represent risk loci for CAD progression within RIRGs. Our identification of these genes enhances understanding of CAD pathogenesis and directs future drug development efforts.

Causal association of basal metabolic rate on systemic sclerosis: a bidirectional mendelian randomization study.

Prior evidence suggests that altered energy metabolism plays a crucial role in the development of fibrotic diseases. Recent research indicates that systemic sclerosis (SSc) patients have potentially benefited from energy management, implying that basal metabolic rate (BMR), a vital energy metabolic parameter, may be related to SSc. However, the causal effect of BMR on SSc remains unknown. Thus, we aimed to elucidate the causal links between BMR and SSc. Based on summary statistics from the genome-wide association studies (GWAS) database, two-sample Mendelian randomization (MR) was applied to explore causality between BMR and SSc. The causal relationships were assessed employing inverse variance weighted (IVW), MR-Egger, and weighted median (WM) methods. Meanwhile, several sensitivity analyses were carried out to ensure the robustness of the findings. There was an underlying genetic association of BMR on SSc (OR = 0.505, 95% CI: 0.272-0.936, P = 0.030). Moreover, no significant causal effect between SSc and BMR was observed in the reverse MR analysis (OR = 0.999, 95% CI: 0.997-1.001, P = 0.292). According to the sensitivity analysis, the presence of heterogeneity and genetic pleiotropy was not detected. Our findings, derived from a genetic perspective, provide robust evidence of a causal connection between BMR and SSc. To verify these results and clarify the potential mechanisms, further research is warranted.

Correlation between inflammatory cytokines and the likelihood of developing multiple types of digestive system cancers: A Mendelian randomization study

ObjectiveInflammatory cytokines have been linked to digestive system cancers, yet their exact causal connection remains uncertain. Consequently, we conducted a Mendelian randomization (MR) analysis to gauge how inflammatory cytokines are linked to the risk of five prevalent digestive system cancers (DSCs). MethodsWe collected genetic variation data for 41 inflammatory cytokines from genome-wide association studies (GWAS), and the results data for five common diseases from the Finnish database. Our primary analytical approach involved employing the inverse-variance weighted, residual sum (IVW) method, complemented by the MR-Egger method, the weighted median method, simple mode analysis, and weighted mode analysis as supplementary analytical techniques. Furthermore, we conducted multiple sensitivity analyses. ResultsTumor necrosis factor-related apoptosis-inducing ligand (TRAIL), macrophage colony-stimulating factor (M-CSF), and interleukin (IL)-18 showed a negative association with the risk of hepatocellular carcinoma. Conversely, TRAIL was inversely linked to the risk of gastric cancer, while IL-16 exhibited a positive correlation with gastric cancer risk. Stem cell factor (SCF) acted as a protective factor against pancreatic cancer. For colorectal cancer, IL-7, IL-9, IL-13, and vascular endothelial growth factor (VEGF) were identified as risk factors. Notably, our results did not indicate a significant correlation between inflammatory cytokines and the risk of esophageal cancer. ConclusionOur research unveils potential connections between 41 inflammatory cytokines and the risk of five common DSCs through a MR analysis. These associations offer valuable insights that could aid in the development of diagnostic biomarkers and the identification of novel therapeutic targets for DSCs.

Exploring the causal relationship between psoriasis and osteoarthritis through a 2-sample Mendelian randomization study.

Previous research has demonstrated a robust association between osteoarthritis (OA) and psoriasis. Notably, a significant proportion of psoriasis patients exhibit symptoms of arthritis, particularly psoriatic arthritis. However, a definitive causal relationship between psoriasis, psoriatic arthritis and OA remains to be established. This study aimed to elucidate the causal relationship between psoriasis, psoriatic arthritis, and osteoarthritis using a 2-sample Mendelian randomization approach. The causal relationship between psoriasis, psoriatic arthritis and OA was rigorously investigated using a 2-sample Mendelian Randomization (MR) approach. Instrumental variables pertinent to psoriasis, psoriatic arthritis and 4 distinct types of OA (knee osteoarthritis (KOA), hand osteoarthritis (HOA), total knee replacement (TKR), and total hip replacement (THR)) were sourced from extensive, published genome-wide association studies (GWAS). To estimate the causal effects, methodologies such as inverse variance weighting (IVW), MR-Egger, and weighted median estimation (WM) were employed. Mendelian Randomization analysis suggested a potential causal effect of psoriasis on osteoarthritis (OA). For hand OA (HOA), the P value was .381 (OR = 0.28); for knee OA (KOA), the P value was .725 (OR = 1.46); for TKR, the P value was .488 (OR = 0.274); and for THR, the P value was .454 (OR = 0.216). Furthermore, we explored the causality of psoriatic arthritis on OA. For HOA, the P value was .478 (OR = 0.0095); for KOA, the P value was .835 (OR = 0.345); for THR, the P value was .807 (OR = 0.120); and for TKR, the P value was .860 (OR = 0.190). Our findings indicate that there is no evidence of a causal connection between psoriasis or psoriatic arthritis and OA, suggesting that while psoriasis may contribute to arthritis, it does not influence OA development.