Causal Association Research Articles

Variational Attention-Based Interpretable Transformer Network for Rotary Machine Fault Diagnosis.

Deep learning technology provides a promising approach for rotary machine fault diagnosis (RMFD), where vibration signals are commonly utilized as input of a deep network model to reveal the internal state of machinery. However, most existing methods fail to mine association relationships within signals. Unlike deep neural networks, transformer networks are capable of capturing association relationships through the global self-attention mechanism to enhance feature representations from vibration signals. Despite this, transformer networks cannot explicitly establish the causal association between signal patterns and fault types, resulting in poor interpretability. To tackle these problems, an interpretable deep learning model named the variational attention-based transformer network (VATN) is proposed for RMFD. VATN is improved from transformer encoder to mine the association relationships within signals. To embed the prior knowledge of the fault type, which can be recognized based on several key features of vibration signals, a sparse constraint is designed for attention weights. Variational inference is employed to force attention weights to samples from Dirichlet distributions, and Laplace approximation is applied to realize reparameterization. Finally, two experimental studies conducted on bevel gear and bearing datasets demonstrate the effectiveness of VATN to other comparison methods, and the heat map of attention weights illustrates the causal association between fault types and signal patterns.

The causal relationship between COVID-19 and ten esophageal diseases: a study utilizing Mendelian randomization.

Clinical signs of dysphagia, pancreatic achalasia, and esophagitis have been reported in patients with COVID-19. However, the causal relationship between COVID-19 and esophageal diseases is not clear. Therefore, we utilized Mendelian randomization to explore the potential association between COVID-19 and esophageal diseases. The summary statistics for a Genome-wide association study (GWAS) were obtained from The COVID-19 Host Genetics Initiative, encompassing four types of COVID-19 as exposure: severe COVID-19, hospitalized COVID-19 versus ambulatory COVID-19, hospitalized COVID-19 versus uninfected, and confirmed COVID-19. Additionally, summary statistics for ten esophageal diseases as outcomes were sourced from the GWAS Catalog and FinnGen databases. Univariate Mendelian randomization (MR) analysis was utilized to thoroughly investigate and validate the potential causal association between COVID-19 and various esophageal conditions, including esophageal varices, Barrett's esophagus, esophagitis, esophageal obstruction, esophageal ulcer, esophageal perforation, gastroesophageal reflux, congenital esophageal malformations, benign esophageal tumors, and esophageal adenocarcinoma. An inverse variance-weighted (IVW) model was utilized for univariate Mendelian randomization (MR) analysis, which revealed that genetic liability in patients with confirmed COVID-19 was associated with esophageal obstruction (OR [95% CI]: 0.5275458 [0.2822400-0.9860563]; p-value = 0.0450699). Furthermore, a suggestive causal association was found between genetic liability and a reduced risk of benign esophageal tumors (OR [95% CI]: 0.2715453 [0.09368493-0.7870724]; p-value = 0.0163510), but with a suggestively increased risk of congenital esophageal malformations (OR [95% CI]: 6.959561 [1.1955828-40.51204]; p-value = 0.03086835). Additionally, genetic liability in hospitalized COVID-19 patients, compared to non-hospitalized COVID-19 patients, was suggestively associated with an increased risk of esophagitis (OR [95% CI]: 1.443859 [1.0890568-1.914252]; p-value = 0.01068201). The reliability of these causal findings is supported by Cochran's Q statistic and the MR-Egger intercept test. The results of this study suggest the existence of a causal relationship between COVID-19 and esophageal diseases, highlighting differing risk effects of COVID-19 on distinct esophageal conditions.

Causal association and shared genetics between telomere length and COVID-19 outcomes: new evidence from the latest large-scale summary statistics

BackgroundObservational studies suggested that leukocyte telomere length (LTL) is shortened in COVID-19 patients. However, the genetic association and causality remained unknown. MethodsBased on the genome-wide association of LTL (N = 472,174) and COVID-19 phenotypes (N = 1,086,211-2,597,856), LDSC and SUPERGNOVA were used to estimate the genetic correlation. Cross-trait GWAS meta-analysis, colocalization, fine-mapping analysis and transcriptome-wide association study were conducted to explore the shared genetic etiology. Mendelian randomization (MR) was utilized to infer the causality. Upstream and downstream two-step MR was performed to investigate the potential mediating effects. ResultsLDSC identified a significant genetic association between LTL and all COVID-19 phenotypes (rG < 0, p < 0.05). Six significant regions were observed for LTL and COVID-19 susceptibility and hospitalization, respectively. Colocalization analysis found rs144204502, rs34517439, and rs56255908 were shared causal variants between LTL and COVID-19 phenotypes. Numerous biological pathways associated with LTL and COVID-19 outcomes were identified, mainly involved in immune related pathways. MR showed that longer LTL was significantly associated with a lower risk of COVID-19 severity (OR [95% CI] = 0.81 [0.71-0.92], p = 1.24×10-3) and suggestively associated with lower risks of COVID-19 susceptibility (OR [95% CI] = 0.96 [0.92-1.00], p = 3.44×10-2) and COVID-19 hospitalization (OR [95% CI] = 0.89 [0.80-0.98], p = 1.89×10-2). LTL partially mediated the effects of BMI, smoking, and education on COVID-19 outcomes. Furthermore, six proteins partially mediated the causality of LTL on COVID-19 outcomes, including BNDF, QPCT, FAS, MPO, SFTPB, and APOF. ConclusionsOur findings suggested that shorter LTL was genetically associated with higher risk of COVID-19 phenotypes, with shared genetic etiology and potential causality.

Association between adding salt in food and dementia in European descent: A mendelian randomization study.

High salt intake has been proposed as a risk factor for dementia. However, causal relationship between salt intake and dementia remains uncertain. The aim of this study was to employ a mendelian randomization (MR) design to investigate the causal impact of salt intake on the risk of dementia. Genome-wide association study (GWAS) data of exposures and outcomes (any dementia, cognitive performance, different types of dementia, Alzheimer's disease [AD], and Parkinson's disease) were obtained from the IEU database. MR estimates were generated though inverse-variance weighted model. MR-Egger, weighted median, and MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) method also used in our study. Sensitivity analyses included Cochran's Q test, MR-Egger intercept, MR-PRESSO global test and outlier test, leave-one-out analysis, and funnel plot assessment. Our MR analysis provided evidence of a causal association between high salt added to food and dementia (odds ratio [OR]=1.73, 95% confidence interval [CI]: 1.21-2.49, and p=.003), dementia in AD (OR=2.10, 95% CI: 1.15-3.83, and p=.015), and undefined dementia (OR=2.61, 95% CI: 1.26-5.39, and p=.009). Higher salt added was also associated with increased risk of AD (OR=1.80, 95% CI: 1.12-2.87, and p=.014) and lower cognitive performance (β=-.133, 95% CI: -.229 to -.038, and p=.006). This study provides evidence suggesting that high salt intake is causally associated with an increased risk of developing dementia, including AD and undefined dementia, highlighting the potential importance of reducing salt consumption as a preventive measure.

Associations of Proteomics With Hypertension and Systolic Blood Pressure: KORA S4/F4/FF4 and KORA Age1/Age2 Cohort Studies.

Hypertension, a complex condition, is primarily defined based on blood pressure readings without involving its pathophysiological mechanisms. We aimed to identify biomarkers through a proteomic approach, thereby enhancing the future definition of hypertension with insights into its molecular mechanisms. The discovery analysis included 1560 participants, aged 55 to 74 years at baseline, from the KORA (Cooperative Health Research in the Region of Augsburg) S4/F4/FF4 cohort study, with 3332 observations over a median of 13.4 years of follow-up. Generalized estimating equations were used to estimate the associations of 233 plasma proteins with hypertension and systolic blood pressure (SBP). For validation, proteins significantly associated with hypertension or SBP in the discovery analysis were validated in the KORA Age1/Age2 cohort study (1024 participants, 1810 observations). A 2-sample Mendelian randomization analysis was conducted to infer causalities of validated proteins with SBP. Discovery analysis identified 49 proteins associated with hypertension and 99 associated with SBP. Validation in the KORA Age1/Age2 study replicated 7 proteins associated with hypertension and 23 associated with SBP. Three proteins, NT-proBNP (N-terminal pro-B-type natriuretic peptide), KIM1 (kidney injury molecule 1), and OPG (osteoprotegerin), consistently showed positive associations with both outcomes. Five proteins demonstrated potential causal associations with SBP in Mendelian randomization analysis, including NT-proBNP and OPG. We identified and validated 7 hypertension-associated and 23 SBP-associated proteins across 2 cohort studies. KIM1, NT-proBNP, and OPG demonstrated robust associations, and OPG was identified for the first time as associated with blood pressure. For NT-proBNP (protective) and OPG, causal associations with SBP were suggested.

Genetic causal relationship between multiple immune cell phenotypes and Parkinson's disease: a two sample bidirectional Mendelian randomization study.

The exact etiology of Parkinson's disease (PD), a degenerative disease of the central nervous system, is unclear. It is currently believed that its main pathological basis is a decrease in dopamine concentration in the striatum of the brain. Although many researchers have previously focused on the critical role of the immune response in PD, there has been a lack of valid genetic evidence for a causal association between specific immune cell traits and phenotypes and PD. We employed Mendelian randomisation (MR) as an analytical method to effectively assess genetic associations between exposure and outcome. Based on the largest genome-wide association study (GWAS) data to date, causal associations between multiple immune cell phenotypes and PD were validly assessed by using single nucleotide polymorphisms (SNPs), which are randomly assigned and not subject to any causality. By testing 731 immune cell phenotypes and their association with PD, the results of IVW analysis suggested that some phenotypes were considered to have a causal effect on PD(P＜0.05) . In addition, PD could have an effect on certain immunophenotypes located on Myeloid cell panel, Monocyte panel, the specific immunophenotypic results and statistical analysis values are shown in the text. The results of sensitivity analyses suggested that none of them observed the presence of horizontal pleiotropy. Our study identified a close link between immune cells and PD, and the results of this study provide ideas for the study of the immune mechanism of PD and the exploration of effective therapeutic means.

Mendelian randomization identifies causal effects of major depressive disorder on accelerated aging

BackgroundEvidence links major depressive disorder (MDD) with aging, but it's unclear if MDD accelerates aging and what factors mediate this transition. MethodsTwo-sample Mendelian randomization (MR) analyses were applied to estimate the causal association between MDD and frailty index (FI), telomere length (TL), and appendicular lean mass (ALM) from available genome-wide association studies in populations of European ancestry. Furthermore, we conducted mediation MR analyses to assess the mediating effects of 31 lifestyle factors or diseases on the causal relationship between MDD and aging. ResultsMDD was significantly causally associated with increased FI (βIVW = 0.23, 95 % CI = 0.18 to 0.28, p = 1.20 × 10−17), shorter TL (βIVW = −0.04, 95 % CI = −0.07 to −0.01, p = 0.01), and decreased ALM (βIVW = −0.07, 95 % CI = −0.11 to −0.03, p = 3.54 × 10−4). The mediation analysis through two-step MR revealed smoking initiation (9.09 %), hypertension (6.67 %) and heart failure (5.36 %) mediated the causal effect of MDD on FI. Additionally, alcohol use disorders and alcohol dependence on the causal relationship between MDD and TL were found to be 17.52 % and 17.13 % respectively. LimitationsConfounding, statistical power, and Euro-centric focus limit generalization. ConclusionOverall, individuals with MDD may be at a higher risk of experiencing premature aging, and this risk is partially influenced by the pathways involving smoking, alcohol use, and cardiovascular health. It underscores the importance of early intervention and comprehensive health management in individuals with MDD to promote healthy aging and overall well-being.

Causal association between autoimmune liver disease and Sjögren's syndrome: A Mendelian randomization study.

Observational studies have found an association between autoimmune liver disease (AILD) and Sjögren's syndrome (SS). However, the causal relationship between the two remains unknown. Clinical guidelines indicate that the coexistence of AILD with other autoimmune diseases may impact prognosis and quality of life; hence, early recognition and management of extrahepatic autoimmune diseases is particularly crucial. Against this backdrop, this study aimed to utilize Mendelian randomization (MR) methods to investigate the potential causal relationship between AILD and SS. We extracted summary statistics on AILD and SS from publicly available genome-wide association studies (GWAS) databases to identify appropriate instrumental variables (IVs). The inverse-variance weighted (IVW) method was utilized as the primary approach, with the weighted median (WM) method and MR-Egger method employed as supplementary methods to evaluate the potential causal relationship between the two conditions. Sensitivity analyses, including Cochran's Q test, MR-polynomial residuals and outliers (MR-PRESSO), MR-Egger intercept test, and the leave-one-out test, were performed to assess the stability of the results. The MR study results indicate a significant causal relationship between PBC and PSC with the risk of SS in the European population (IVW: odds ratio [OR] = 1.155, 95% confidence interval [CI]: 1.092-1.222, p < .001; IVW: OR = 1.162, 95% CI: 1.051-1.284, p = .003). A series of sensitivity analyses have confirmed the reliability of the results. Our study indicates that the presence of both PBC and PSC increases the susceptibility to SS. However, no reliable causal relationship was found between SS and the risk of PBC or PSC. These findings contribute to elucidating the potential pathogenic mechanisms of the disease and are of significant importance for the management of patients with PBC and PSC.

Causal associations between dietary factors and colorectal cancer risk: a Mendelian randomization study.

Previous epidemiological studies have found a link between colorectal cancer (CRC) and human dietary habits. However, the inherent limitations and inevitable confounding factors of the observational studies may lead to the inaccurate and doubtful results. The causality of dietary factors to CRC remains elusive. We conducted two-sample Mendelian randomization (MR) analyses utilizing the data sets from the IEU Open GWAS project. The exposure datasets included alcoholic drinks per week, processed meat intake, beef intake, poultry intake, oily fish intake, non-oily fish intake, lamb/mutton intake, pork intake, cheese intake, bread intake, tea intake, coffee intake, cooked vegetable intake, cereal intake, fresh fruit intake, salad/raw vegetable intake, and dried fruit intake. In our MR analyses, the inverse variance weighted (IVW) method was employed as the primary analytical approach. The weighted median, MR-Egger, weighted mode, and simple mode were also applied to quality control. Heterogeneity and pleiotropic analyses were implemented to replenish the accuracy of the results. MR consequences revealed that alcoholic drinks per week [odds ratio (OR): 1.565, 95% confidence interval (CI): 1.068-2.293, p = 0.022], non-oily fish intake (OR: 0.286; 95% CI: 0.095-0.860; p = 0.026), fresh fruit intake (OR: 0.513; 95% CI: 0.273-0.964; p = 0.038), cereal intake (OR: 0.435; 95% CI: 0.253-0.476; p = 0.003) and dried fruit intake (OR: 0.522; 95% CI: 0.311-0.875; p = 0.014) was causally correlated with the risk of CRC. No other significant relationships were obtained. The sensitivity analyses proposed the absence of heterogeneity or pleiotropy, demonstrating the reliability of the MR results. This study indicated that alcoholic drinks were associated with an increased risk of CRC, while non-oily fish intake, fresh fruit intake, cereal intake, and dried fruit were associated with a decreased risk of CRC. This study also indicated that other dietary factors included in this research were not associated with CRC. The current study is the first to establish the link between comprehensive diet-related factors and CRC at the genetic level, offering novel clues for interpreting the genetic etiology of CRC and replenishing new perspectives for the clinical practice of gastrointestinal disease prevention.

Association between lung function and risk of microvascular diseases in patients with diabetes: A prospective cohort and mendelian randomization study

Background and aimsTo investigate causal relationships of lung function with risks microvascular diseases among participants with diabetes, type 2 diabetes mellitus (T2DM) and type 1 diabetes mellitus (T1DM), respectively, in prospective and Mendelian randomization (MR) study. Methods and results14,617 participants with diabetes and without microvascular diseases at baseline from the UK Biobank were included in the prospective analysis. Of these, 13,421 had T2DM and 1196 had T1DM. The linear MR analyses were conducted in the UK Biobank with 6838 cases of microvascular diseases and 10,755 controls. Lung function measurements included forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). The study outcome was microvascular diseases, a composite outcome including chronic kidney diseases, retinopathy and peripheral neuropathy. During a median follow-up of 12.1 years, 2668 new-onset microvascular diseases were recorded. FVC (%predicted) was inversely associated with the risk of new-onset microvascular diseases in participants with diabetes (Per SD increment, adjusted HR = 0.86; 95%CI:0.83–0.89), T2DM (Per SD increment, adjusted HR = 0.86; 95%CI:0.82–0.90) and T1DM (Per SD increment, adjusted HR = 0.87; 95%CI: 0.79–0.97), respectively. Similar results were found for FEV1 (%predicted). In MR analyses, genetically predicted FVC (adjusted RR = 0.55, 95%CI:0.39–0.77) and FEV1 (adjusted RR = 0.48, 95%CI:0.28–0.83) were both inversely associated with microvascular diseases in participants with T1DM. No significant association was found in those with T2DM. Similar findings were found for each component of microvascular diseases. ConclusionThere was a causal inverse association between lung function and risks of microvascular diseases in participants with T1DM, but not in those with T2DM.

The Association of Multidimensional Sleep Health With HbA1c and Depressive Symptoms in African American Adults With Type 2 Diabetes.

Sleep is important for diabetes-related health outcomes. Using a multidimensional sleep health framework, we examined the association of individual sleep health dimensions and a composite sleep health score with hemoglobin A1c (HbA1c) and depressive symptoms among African American adults with type 2 diabetes. Participants (N = 257; mean age = 62.5 years) were recruited through local churches. Wrist-worn actigraphy and sleep questionnaire data assessed multidimensional sleep health using the RuSATED framework (regularity, satisfaction, alertness, timing, efficiency, duration). Individual sleep dimensions were dichotomized into poor or good sleep health and summed into a composite score. HbA1c was assessed using the DCA Vantage™ Analyzer or A1CNow® Self Check. Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-9). Regression models examined the association of individual sleep dimensions and composite sleep health with HbA1c and depressive symptoms. Higher composite sleep health scores were associated with a lower likelihood of having greater than minimal depressive symptoms (PHQ-9 ≥ 5) (odds ratio [OR] = 0.578, 95% confidence interval [CI] = 0.461-0.725). Several individual sleep dimensions, including irregularity (OR = 1.013, CI = 1.005-1.021), poor satisfaction (OR = 3.130, CI = 2.095-4.678), and lower alertness (OR = 1.866, CI = 1.230-2.833) were associated with a greater likelihood of having depressive symptoms. Neither composite sleep health scores nor individual sleep dimensions were associated with HbA1c. Better multidimensional sleep health is associated with lower depressive symptoms among African American adults with type 2 diabetes. Longitudinal research is needed to determine the causal association between multidimensional sleep health and depressive symptoms in this population. ClinicalTrials.gov identifier NCT04282395.

Neuroticism polygenic risk predicts conversion from mild cognitive impairment to Alzheimer's disease by impairing inferior parietal surface area.

The high prevalence of conversion from amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD) makes early prevention of AD extremely critical. Neuroticism, a heritable personality trait associated with mental health, has been considered a risk factor for conversion from aMCI to AD. However, whether the neuroticism genetic risk could predict the conversion of aMCI and its underlying neural mechanisms is unclear. Neuroticism polygenic risk score (N-PRS) was calculated in 278 aMCI patients with qualified genomic and neuroimaging data from ADNI. After 1-year follow-up, N-PRS in patients of aMCI-converted group was significantly greater than those in aMCI-stable group. Logistic and Cox survival regression revealed that N-PRS could significantly predict the early-stage conversion risk from aMCI to AD. These results were well replicated in an internal dataset and an independent external dataset of 933 aMCI patients from the UK Biobank. One sample Mendelian randomization analyses confirmed a potentially causal association from higher N-PRS to lower inferior parietal surface area to higher conversion risk of aMCI patients. These analyses indicated that neuroticism genetic risk may increase the conversion risk from aMCI to AD by impairing the inferior parietal structure.

Bowel Habits, Obesity, Intestinal Microbiota and Their Influence on Hemorrhoidal Disease: a Mendelian Randomization Study.

Hemorrhoids (HEM) are the most common perianal disease, but current observational studies have yielded inconsistent results in investigating the risk factors. Our further exploration of the risk factors will help prevent the disease. We conducted a two-sample bidirectional Mendelian randomization (MR) analysis using publicly available genome-wide association studies (GWAS) statistics from multiple consortia. The inverse-variance weighted (IVW) method was used for the primary analysis. We applied four complementary methods, including weighted median, weighted mode, MR-Egger regression, and Cochrane's Q value, to detect and correct the effects of horizontal pleiotropy. Genetically determined constipation (OR = 0.97, 95% CI: 0.91-1.03, P = 0.28) and diarrhea (OR = 1.00, 95% CI: 0.99-1.01, P = 0.90) did not have a causal effect on HEM but stool frequency (OR = 1.28, 95% CI: 1.05-1.55, P = 0.01), waist-to-hip ratio adjusted for BMI (OR = 1.11, 95% CI: 1.06-1.64, P = 1.59×10-5), and order Burkholderiales (OR = 1.09, 95% CI = 1.04-1.14, p = 1.63×10-4) had a causal effect on. Furthermore, we found a significant causal effect of constipation on HEM in the reverse MR analysis (OR = 1.21, 95% CI: 1.13-1.28, P = 3.72×10-9). The results of MR-Egger regression, Weighted Median, and Weighted Mode methods were consistent with those of the IVW method. Horizontal pleiotropy was unlikely to distort the causal estimates, as indicated by the sensitivity analysis. Our MR analysis reveals a causal association between stool frequency and waist-to-hip ratio with HEM, despite variations in results reported by observational studies. Unexpectedly, we found a relationship between the order Burkholderiales in the gut flora and HEM, although the mechanism is unclear.

Investigating the Impact of Gut Microbiota on Gout Through Mendelian Randomization.

The relationship between gout and gut microbiota has attracted significant attention in current research. However, due to the diverse range of gut microbiota, the specific causal effect on gout remains unclear. This study utilizes Mendelian randomization (MR) to investigate the causal relationship between gut microbiota and gout, aiming to elucidate the underlying mechanism of microbiome-mediated gout and provide valuable guidance for clinical prevention and treatment. The largest genome-wide association study meta-analysis conducted by the MiBioGen Consortium (n=18,340) was utilized to perform a two-sample Mendelian randomization investigation on aggregate statistics of intestinal microbiota. Summary statistics for gout were utilized from the data released by EBI. Various methods, including inverse variance weighted, weighted median, weighted model, MR-Egger, and Simple-mode, were employed to assess the causal relationship between gut microbiota and gout. Reverse Mendelian randomization analysis revealed a causal association between bacteria and gout in forward Mendelian randomization analysis. Cochran's Q statistic was used to quantify instrumental variable heterogeneity. The inverse variance weighted estimation revealed that Rikenellaceae exhibited a slight protective effect on gout, while the presence of Ruminococcaceae UCG_011 is associated with a marginal increase in the risk of gout. According to the reverse Mendelian Randomization results, no significant causal relationship between gout and gut microbiota was observed. No significant heterogeneity of instrumental variables or level pleiotropy was detected. Our MR analysis revealed a potential causal relationship between the development of gout and specific gut microbiota; however, the causal effect was not robust, and further research is warranted to elucidate its underlying mechanism in gout development. Considering the significant association between diet, gut microbiota, and gout, these findings undoubtedly shed light on the mechanisms of microbiota-mediated gout and provide new insights for translational research on managing and standardizing treatment for this condition.

The causal association of cheese intake with type 2 diabetes mellitus result from a two-sample Mendelian randomization study

IntroductionWorldwide, type 2 diabetes is a major health concern with numerous risk factors. In observational studies, cheese consumption has been linked to type 2 diabetes, however it is still unclear whether these relationships are causal. To ascertain these relationships, we performed a two-sample Mendelian randomization (MR) study.Material and methodsA summary of cheese intake statistics from UK Biobank and publicly available genome-wide association studies (GWAS) for type 2 diabetes from IEU OpenGWAS, FinnGen Biobank, EBI GWAS, and Biobank Japan, respectivel. The primary method was pooled meta-analysis with the inverse variance weighting method. The sensitivity analyses included MR-Egger regression, weighted median, weighted mode, and leave-one-out. MR estimations of causation were reported as odds ratios (OR) with 95% confidence intervals (CI).ResultsIn the pooled meta-analysis of the fixed and random effect model, the combined ORs for type 2 diabetes were 0.58 (95% CI: 0.50-0.68, P&lt;0.001) and 0.50 (95%CI: 0.32-0.78, P=0.003) per standard deviation rise in the levels of cheese intake. Sensitivity analysis revealed no horizontal pleiotropy (all P&gt;0.05) but heterogeneity (all P&lt;0.05).ConclusionsWe found that moderate consumption of beneficial cheese may reduce the risk of type 2 diabetes. These findings suggested that increasing cheese intake appropriate for humans may help prevent and control type 2 diabetes.

Proteomic analysis reveals potential therapeutic targets for childhood asthma through Mendelian randomization.

Asthma is the most common chronic disease among children and poses a significant threat to their health. This study aims to assess the relationship between various plasma proteins and childhood asthma, thereby identifying potential therapeutic targets. Based on publicly available genome-wide association study summary statistics, we employed a two-sample Mendelian randomization (MR) approach to elucidate the causal relationship between plasma proteins and asthma. Mediation analysis was then conducted to evaluate the indirect influence of plasma proteins on childhood asthma mediated through risk factors. Comprehensive analysis was also conducted to explore the association between plasma proteins and various phenotypes using the UK Biobank dataset. MR analysis uncovered a causal relationship between 10 plasma proteins and childhood asthma. Elevated levels of seven proteins (TLR4, UBP25, CBR1, Rac GTPase-activating protein 1 [RGAP1], IL-21, MICB, and PDE4D) and decreased levels of three proteins (GSTO1, LIRB4 and PIGF) were associated with an increased risk of childhood asthma. Our findings further validated the connections between reported risk factors (body mass index, mood swings, hay fever or allergic rhinitis, and eczema or dermatitis) and childhood asthma. Mediation analysis revealed the influence of proteins on childhood asthma outcomes through risk factors. Furthermore, the MR analysis identified 73 plasma proteins that exhibited causal associations with at least one risk factor for childhood asthma. Among them, RGAP1 mediates a significant proportion (25.10%) of the risk of childhood asthma through eczema or dermatitis. Finally, a phenotype-wide association study based on these 10 proteins and 1403 diseases provided novel associations between these biomarkers and multiple phenotypes. Our study comprehensively investigated the causal relationship between plasma proteins and childhood asthma, providing novel insights into potential therapeutic targets.

Causal Links Between Systemic Disorders and Keratoconus in European Population

PurposeThe objective of this study was to establish the presence of a causal linkage between prevalent systemic diseases and keratoconus (KC). DesignMendelian randomization (MR) analysis. MethodsAfter an exhaustive screening process, genetic variants linked to various systemic diseases were identified as instrumental variables at the genome-wide significance level. Subsequently, MR analyses were conducted to elucidate their potential causal connection with KC (N = 26,742). The encompassed systemic ailments comprise diabetes, hay fever/allergic rhinitis/eczema, obstructive sleep apnea, thyroid dysfunction, aortic aneurysm, major depressive disorder, inflammatory bowel disease (including Crohn's disease and ulcerative colitis), and mitral valve prolapse. Our study adheres to the principles of Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization guidelines. ResultsUsing inverse variance weighting as the primary MR analysis method, our findings revealed that hay fever/allergic rhinitis/eczema (odds ratio, 10.144; 95% CI, 2.441 - 42.149; P = 0.001) and ulcerative colitis (odds ratio, 1.147; 95% CI, 1.054 - 1.248; P = 0.002) were associated with an increased risk of KC within the largest population under scrutiny. Conversely, the prolonged hyperglycemic state did not exhibit a potentially protective effect in delaying the pathogenesis of KC, and no correlation was observed between the two (odds ratio, 0.320; 95% CI, 0.029 - 3.549; P = 0.353). Also, obstructive sleep apnea, thyroid function, aortic aneurysm, major depressive disorder, Crohn's disease, and mitral valve prolapse did not exhibit a causal association with KC (P > 0.05 for all comparisons). ConclusionsThis study indicates an increased risk of KC related to hay fever/allergic rhinitis/eczema and ulcerative colitis, with diabetes not providing a protective effect. These findings may potentially contribute some insights to inform clinical interventions.

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.

Genetically Proxied Autoimmune Diseases and the Risk of Facial Aging.

Previous studies have suggested a relationship between autoimmune diseases and the risk of facial skin aging. However, evidence from population-based studies on this topic is limited, leaving the causal association between these factors unknown. This study aimed to systematically evaluate the causal effects of 18 autoimmune diseases on the risk of facial skin aging, aim of providing strategies to mitigate early facial aging in patients with autoimmune diseases. We conducted univariate Mendelian randomization (UVMR) analyses to examine the causal relationship between 18 autoimmune diseases and facial aging using publicly available summary data from genome-wide association studies (GWASs). We also conducted multivariate Mendelian randomization (MVMR) analyses to adjust for confounding factors, including smoking, alcohol consumption, and body mass index (BMI). The main inverse variance weighted (IVW) method revealed that genetically proxied ankylosing spondylitis (AS) (OR 1.017; 95% CI: 1.003-1.031; P=0.018), sicca syndrome (SS) (OR 1.008; 95% CI: 1.005-1.011; P= 2.66×10-6), systemic lupus erythematosus (SLE) (OR 1.006; 95% 1.001-1.011; P=0.014), multiple sclerosis (MS) (OR 1.004; 95% CI: 1.001-1.007; P=0.021), primary sclerosing cholangitis (PSC) (OR 1.002; 95% CI: 1.000-1.004; P=0.023), and celiac disease (CeD) (OR 1.002; 95% CI: 1.001-1.004; P=0.009) were significantly associated with higher risk of facial aging. After adjusting for potential confounding factors, the association persisted between AS, SLE, and CeD. These findings indicated that autoimmune diseases play a causal role in facial skin aging. Therefore, patients with autoimmune diseases should take appropriate measures to prevent early facial aging.

Comparative mathematical modeling of causal association between metal exposure and development of chronic kidney disease.

Previous studies have identified several genetic and environmental risk factors for chronic kidney disease (CKD). However, little is known about the relationship between serum metals and CKD risk. We investigated associations between serum metals levels and CKD risk among 100 medical examiners and 443 CKD patients in the medical center of the First Hospital Affiliated to China Medical University. Serum metal concentrations were measured using inductively coupled plasma mass spectrometry (ICP-MS). We analyzed factors influencing CKD, including abnormalities in Creatine and Cystatin C, using univariate and multiple analysis such as Lasso and Logistic regression. Metal levels among CKD patients at different stages were also explored. The study utilized machine learning and Bayesian Kernel Machine Regression (BKMR) to assess associations and predict CKD risk based on serum metals. A chained mediation model was applied to investigate how interventions with different heavy metals influence renal function indicators (creatinine and cystatin C) and their impact on diagnosing and treating renal impairment. Serum potassium (K), sodium (Na), and calcium (Ca) showed positive trends with CKD, while selenium (Se) and molybdenum (Mo) showed negative trends. Metal mixtures had a significant negative effect on CKD when concentrations were all from 30th to 45th percentiles compared to the median, but the opposite was observed for the 55th to 60th percentiles. For example, a change in serum K concentration from the 25th to the 75th percentile was associated with a significant increase in CKD risk of 5.15(1.77,8.53), 13.62(8.91,18.33) and 31.81(14.03,49.58) when other metals were fixed at the 25th, 50th and 75th percentiles, respectively. Cumulative metal exposures, especially double-exposure to serum K and Se may impact CKD risk. Machine learning methods validated the external relevance of the metal factors. Our study highlights the importance of employing diverse methodologies to evaluate health effects of metal mixtures.