Causality of genetically determined blood metabolites on irritable bowel syndrome: A Mendelian randomization study.

BACKGROUND: Irritable bowel syndrome (IBS) is one of the most common functional bowel disorders and dysmetabolism plays an important role in the pathogenesis of disease. Nevertheless, there remains a lack of information regarding the causal relationship between circulating metabolites and IBS. A two-sample Mendelian randomization (MR) analysis was conducted in order to evaluate the causal relationship between genetically proxied 486 blood metabolites and IBS. METHODS: A two-sample MR analysis was implemented to assess the causality of blood metabolites on IBS. The study utilized a genome-wide association study (GWAS) to examine 486 metabolites as the exposure variable while employing a GWAS study with 486,601 individuals of European descent as the outcome variable. The inverse-variance weighted (IVW) method was used to estimate the causal relationship of metabolites on IBS, while several methods were performed to eliminate the pleiotropy and heterogeneity. Another GWAS data was used for replication and meta-analysis. In addition, reverse MR and linkage disequilibrium score regression (LDSC) were employed for additional assessment. Multivariable MR analysis was conducted in order to evaluate the direct impact of metabolites on IBS. RESULTS: Three known and two unknown metabolites were identified as being associated with the development of IBS. Higher levels of butyryl carnitine (OR(95%CI):1.10(1.02-1.18),p = 0.009) and tetradecanedioate (OR(95%CI):1.13(1.04-1.23),p = 0.003)increased susceptibility of IBS and higher levels of stearate(18:0)(OR(95%CI):0.72(0.58-0.89),p = 0.003) decreased susceptibility of IBS. CONCLUSION: The metabolites implicated in the pathogenesis of IBS possess potential as biomarkers and hold promise for elucidating the underlying biological mechanisms of this condition.

From algorithms to action: improving patient care requires causality.

In cancer research there is much interest in building and validating outcome prediction models to support treatment decisions. However, because most outcome prediction models are developed and validated without regard to the causal aspects of treatment decision making, many published outcome prediction models may cause harm when used for decision making, despite being found accurate in validation studies. Guidelines on prediction model validation and the checklist for risk model endorsement by the American Joint Committee on Cancer do not protect against prediction models that are accurate during development and validation but harmful when used for decision making. We explain why this is the case and how to build and validate models that are useful for decision making.

A causal relationship between educational attainment and risk of infectious diseases: A Mendelian randomisation study.

Background: Previous observational studies have investigated the association between educational attainment and sepsis, pneumonia, and urinary tract infections (UTIs). However, their findings have been susceptible to reverse causality and confounding factors. Furthermore, no study has examined the effect of educational level on the risk of infections of the skin and subcutaneous tissue (SSTIs). Thus, we aimed to evaluate the causal relationships between educational level and the risk of four infectious diseases using Mendelian randomisation (MR) techniques. Methods: We used univariable MR analysis to investigate the causal associations between educational attainment (years of schooling (n = 766 345) and holding college or university degree (n = 334 070)) and four infectious diseases (sepsis (n = 486 484), pneumonia (n = 486 484), UTIs (n = 463 010), and SSTIs (n = 218 792)). We included genetic instrumental variables with a genome-wide significance (P < 5 × 10-8) in the study. We used inverse variance-weighted estimation in the primary analysis and explored the stability of the results using multivariable MR analysis after adjusting for smoking, alcohol consumption, and body mass index. Results: Genetically predicted years of schooling were associated with a reduced risk of sepsis (odds ratio (OR) = 0.763; 95% confidence interval (CI) = 0.668-0.870, P = 5.525 × 10-5), pneumonia (OR = 0.637; 95% CI = 0.577-0.702, P = 1.875 × 10-19), UTIs (OR = 0.995; 95% CI = 0.993-0.997, P = 1.229 × 10-5), and SSTIs (OR = 0.696; 95% CI = 0.605-0.801, P = 4.034 × 10-7). We observed consistent results for the correlation between qualifications and infectious diseases. These findings remained stable in the multivariable MR analyses. Conclusions: Our findings suggest that increased educational attainment may be causally associated with a decreased risk of sepsis, pneumonia, UTIs, and SSTIs.

The causal relationship of human blood metabolites with the components of Sarcopenia: a two-sample Mendelian randomization analysis.

BACKGROUND: Sarcopenia is a progressive loss of muscle mass and function. Since skeletal muscle plays a critical role in metabolic homeostasis, identifying the relationship of blood metabolites with sarcopenia components would help understand the etiology of sarcopenia. METHODS: A two-sample Mendelian randomization study was conducted to examine the causal relationship of blood metabolites with the components of sarcopenia. Summary genetic association data for 309 known metabolites were obtained from the Twins UK cohort and KORA F4 study (7824 participants). The summary statistics for sarcopenia components [hand grip strength (HGS), walking pace (WP), and appendicular lean mass (ALM)] were obtained from the IEU Open GWAS project (461,089 participants). The inverse variance weighted method was used, and the MR-Egger, weighted median, and MR-PRESSO were used for the sensitivity analyses. Metabolic pathways analysis was further performed. RESULTS: Fifty-four metabolites associated with sarcopenia components were selected from 275 known metabolites pool. Metabolites that are causally linked to the sarcopenia components were mainly enriched in amino sugar and nucleotide sugar metabolism, galactose metabolism, fructose and mannose metabolism, carnitine synthesis, and biotin metabolism. The associations of pentadecanoate (15:0) with ALM, and 3-dehydrocarnitine and isovalerylcarnitine with HGS were significant after Bonferroni correction with a threshold of P < 1.82 × 10- 4 (0.05/275). Meanwhile, the association of hyodeoxycholate and glycine with the right HGS, and androsterone sulfate with ALM were significant in the sensitivity analyses. CONCLUSION: Blood metabolites from different metabolism pathways were causally related to the components of sarcopenia. These findings might benefit the understanding of the biological mechanisms of sarcopenia and targeted drugs development for muscle health.

The causal effects of immune cells on pancreatic cancer: A 2­sample Mendelian randomization study.

Leveraging publicly available genetic datasets, we conducted a comprehensive 2-sample Mendelian randomization (MR) analysis to explore the causal links between 731 immunophenotypes and the risk of pancreatic cancer (PC). To ensure the robustness of our findings, extensive sensitivity analyses were performed, evaluating stability, heterogeneity, and potential horizontal pleiotropy. Our analysis pinpointed 24 immunophenotypes significantly associated with the risk of PC. Notably, phenotypes such as CD4+ CD8dim %leukocyte (OR = 0.852, 95% CI = 0.729-0.995, P = .0430) and HLA DR+ CD4+ AC (OR = 0.933, 95% CI = 0.883-0.986) in TBNK were inversely correlated with PC risk. Conversely, phenotypes like CD28 on CD45RA- CD4 non-Treg (OR = 1.155, 95% CI = 1.028-1.297, P = .016) and CD25 on activated Treg (OR = 1.180, 95% CI = 1.014-1.374, P = .032) in Treg cells, among others, exhibited a positive correlation. These insights offer a valuable genetic perspective that could guide future clinical research in this area.

Causal machine learning for predicting treatment outcomes.

Causal machine learning (ML) offers flexible, data-driven methods for predicting treatment outcomes including efficacy and toxicity, thereby supporting the assessment and safety of drugs. A key benefit of causal ML is that it allows for estimating individualized treatment effects, so that clinical decision-making can be personalized to individual patient profiles. Causal ML can be used in combination with both clinical trial data and real-world data, such as clinical registries and electronic health records, but caution is needed to avoid biased or incorrect predictions. In this Perspective, we discuss the benefits of causal ML (relative to traditional statistical or ML approaches) and outline the key components and steps. Finally, we provide recommendations for the reliable use of causal ML and effective translation into the clinic.

Enhancing system safety in critical architectures: Augmented hypothesis testing with early design knowledge.

Hypothesis testing is a valuable method used to investigate ideas and test predictions arising from theories based on available data. In the context of critical system architecture, there is a need to effectively utilize hypothesis testing to identify faulty paths and improve system safety. This research aims to propose guidelines and best practices for presenting hypothesis testing in critical system architecture. The problem addressed in this study is the underutilization of hypothesis testing in life-critical system methods, resulting in a lack of identification of faulty paths. To address this challenge, we propose an enhanced pathway analysis technique that integrates error-derived information from a system's architectural description, thereby augmenting traditional hypothesis testing methods. By investigating various paths, we aim to identify false positive and false negative errors in life-critical system architecture. Furthermore, the proposed method is validated based on specific validation criteria for each step such as system boundary, assumption, content/architecture, and traceability validations. Also, the method is evaluated based on our claims. The results of our research highlight the significance of tracing errors in early system knowledge. By leveraging the augmented hypothesis testing method, we are able to identify hazards, safety constraints, and specific causes of unsafe actions more effectively. The findings emphasize the importance of integrating early design knowledge into hypothesis testing for enhanced hazard identification and improved system safety.

Recoverability and estimation of causal effects under typical multivariable missingness mechanisms.

In the context of missing data, the identifiability or "recoverability" of the average causal effect (ACE) depends not only on the usual causal assumptions but also on missingness assumptions that can be depicted by adding variable-specific missingness indicators to causal diagrams, creating missingness directed acyclic graphs (m-DAGs). Previous research described canonical m-DAGs, representing typical multivariable missingness mechanisms in epidemiological studies, and examined mathematically the recoverability of the ACE in each case. However, this work assumed no effect modification and did not investigate methods for estimation across such scenarios. Here, we extend this research by determining the recoverability of the ACE in settings with effect modification and conducting a simulation study to evaluate the performance of widely used missing data methods when estimating the ACE using correctly specified g-computation. Methods assessed were complete case analysis (CCA) and various implementations of multiple imputation (MI) with varying degrees of compatibility with the outcome model used in g-computation. Simulations were based on an example from the Victorian Adolescent Health Cohort Study (VAHCS), where interest was in estimating the ACE of adolescent cannabis use on mental health in young adulthood. We found that the ACE is recoverable when no incomplete variable (exposure, outcome, or confounder) causes its own missingness, and nonrecoverable otherwise, in simplified versions of 10 canonical m-DAGs that excluded unmeasured common causes of missingness indicators. Despite this nonrecoverability, simulations showed that MI approaches that are compatible with the outcome model in g-computation may enable approximately unbiased estimation across all canonical m-DAGs considered, except when the outcome causes its own missingness or causes the missingness of a variable that causes its own missingness. In the latter settings, researchers may need to consider sensitivity analysis methods incorporating external information (e.g., delta-adjustment methods). The VAHCS case study illustrates the practical implications of these findings.

The causal relationship between gut microbiota and biliary tract cancer: comprehensive bidirectional Mendelian randomization analysis.

Background: Growing evidence has shown that gut microbiome composition is associated with Biliary tract cancer (BTC), but the causality remains unknown. This study aimed to explore the causal relationship between gut microbiota and BTC, conduct an appraisal of the gut microbiome's utility in facilitating the early diagnosis of BTC. Methods: We acquired the summary data for Genome-wide Association Studies (GWAS) pertaining to BTC (418 cases and 159,201 controls) from the Biobank Japan (BBJ) database. Additionally, the GWAS summary data relevant to gut microbiota (N = 18,340) were sourced from the MiBioGen consortium. The primary methodology employed for the analysis consisted of Inverse Variance Weighting (IVW). Evaluations for sensitivity were carried out through the utilization of multiple statistical techniques, encompassing Cochrane's Q test, the MR-Egger intercept evaluation, the global test of MR-PRESSO, and a leave-one-out methodological analysis. Ultimately, a reverse Mendelian Randomization analysis was conducted to assess the potential for reciprocal causality. Results: The outcomes derived from IVW substantiated that the presence of Family Streptococcaceae (OR = 0.44, P = 0.034), Family Veillonellaceae (OR = 0.46, P = 0.018), and Genus Dorea (OR = 0.29, P = 0.041) exerted a protective influence against BTC. Conversely, Class Lentisphaeria (OR = 2.21, P = 0.017), Genus Lachnospiraceae FCS020 Group (OR = 2.30, P = 0.013), and Order Victivallales (OR = 2.21, P = 0.017) were associated with an adverse impact. To assess any reverse causal effect, we used BTC as the exposure and the gut microbiota as the outcome, and this analysis revealed associations between BTC and five different types of gut microbiota. The sensitivity analysis disclosed an absence of empirical indicators for either heterogeneity or pleiotropy. Conclusion: This investigation represents the inaugural identification of indicative data supporting either beneficial or detrimental causal relationships between gut microbiota and the risk of BTC, as determined through the utilization of MR methodologies. These outcomes could hold significance for the formulation of individualized therapeutic strategies aimed at BTC prevention and survival enhancement.

Assessing the causal relationship between gut microbiota and diabetic nephropathy: insights from two-sample Mendelian randomization.

Background: The causal association between gut microbiota (GM) and the development of diabetic nephropathy (DN) remains uncertain. We sought to explore this potential association using two-sample Mendelian randomization (MR) analysis. Methods: Genome-wide association study (GWAS) data for GM were obtained from the MiBioGen consortium. GWAS data for DN and related phenotypes were collected from the FinngenR9 and CKDGen databases. The inverse variance weighted (IVW) model was used as the primary analysis model, supplemented by various sensitivity analyses. Heterogeneity was assessed using Cochran's Q test, while horizontal pleiotropy was evaluated through MR-Egger regression and the MR-PRESSO global test. Reverse MR analysis was conducted to identify any reverse causal effects. Results: Our analysis identified twenty-five bacterial taxa that have a causal association with DN and its related phenotypes (p < 0.05). Among them, only the g_Eubacterium_coprostanoligenes_group showed a significant causal association with type 1 DN (p < Bonferroni-adjusted p-value). Our findings remained consistent regardless of the analytical approach used, with all methods indicating the same direction of effect. No evidence of heterogeneity or horizontal pleiotropy was observed. Reverse MR analysis did not reveal any causal associations. Conclusions: This study established a causal association between specific GM and DN. Our findings contribute to current understanding of the role of GM in the development of DN, offering potential insights for the prevention and treatment strategies for this condition.

Avoidance of causality outside experiments: Hypotheses from cognitive dissonance reduction.

The avoidance of causality in the design, analysis and interpretation of non-experimental studies has often been criticised as an untenable scientific stance, because theories are based on causal relations (and not associations) and a rich set of methodological tools for causal analysis has been developed in recent decades. Psychology researchers (n = 106 with complete data) participated in an online study presenting a causal statement about the results of a fictitious paper on the potential effect of drinking clear water for years on the risk of dementia. Two randomised groups of participants were then asked to reflect on the conflict between the goal of approaching a causal answer and the prevailing norm of avoiding doing so. One of the two groups was also instructed to think about possible benefits of addressing causality. Both groups then responded to a list of 19 items about attitudes to causal questions in science. A control group did this without reflecting on conflict or benefits. Free-text assessments were also collected during reflection, giving some indication of how and why causality is avoided. We condense the exploratory findings of this study into five new hypotheses about the how and why, filtered through what can be explained by cognitive dissonance reduction theory. These concern the cost of addressing causality, the variety of ways in which dissonance can be reduced, the need for profound intervention through teaching and social aspects. Predictions are derived from the hypotheses for confirmation trials in future studies and recommendations for teaching causality. Open data are provided for researchers' own analyses.

Causal Selection of Covariates in Regression Calibration for Mismeasured Continuous Exposure.

Regression calibration as developed by Rosner, Spiegelman, and Willett is used to adjust the bias in effect estimates due to measurement error in continuous exposures. The method involves two models: a measurement error model relating the mismeasured exposure to the true (or gold-standard) exposure and an outcome model relating the mismeasured exposure to the outcome. However, no comprehensive guidance exists for determining which covariates should be included in each model. In this article, we investigate the selection of the minimal and most efficient covariate adjustment sets under a causal inference framework. We show that to address the measurement error, researchers must adjust for, in both measurement error and outcome models, any common causes (1) of true exposure and the outcome and (2) of measurement error and the outcome. We also show that adjusting for so-called prognostic variables that are independent of true exposure and measurement error in the outcome model, may increase efficiency, while adjusting for any covariates that are associated only with true exposure generally results in efficiency loss in realistic settings. We apply the proposed covariate selection approach to the Health Professional Follow-up Study dataset to study the effect of fiber intake on cardiovascular disease. Finally, we extend the originally proposed estimators to a nonparametric setting where effect modification by covariates is allowed.

Antenatal Ureaplasma Infection Causes Colonic Mucus Barrier Defects: Implications for Intestinal Pathologies.

Chorioamnionitis is a risk factor for necrotizing enterocolitis (NEC). Ureaplasma parvum (UP) is clinically the most isolated microorganism in chorioamnionitis, but its pathogenicity remains debated. Chorioamnionitis is associated with ileal barrier changes, but colonic barrier alterations, including those of the mucus barrier, remain under-investigated, despite their importance in NEC pathophysiology. Therefore, in this study, the hypothesis that antenatal UP exposure disturbs colonic mucus barrier integrity, thereby potentially contributing to NEC pathogenesis, was investigated. In an established ovine chorioamnionitis model, lambs were intra-amniotically exposed to UP or saline for 7 d from 122 to 129 d gestational age. Thereafter, colonic mucus layer thickness and functional integrity, underlying mechanisms, including endoplasmic reticulum (ER) stress and redox status, and cellular morphology by transmission electron microscopy were studied. The clinical significance of the experimental findings was verified by examining colon samples from NEC patients and controls. UP-exposed lambs have a thicker but dysfunctional colonic mucus layer in which bacteria-sized beads reach the intestinal epithelium, indicating undesired bacterial contact with the epithelium. This is paralleled by disturbed goblet cell MUC2 folding, pro-apoptotic ER stress and signs of mitochondrial dysfunction in the colonic epithelium. Importantly, the colonic epithelium from human NEC patients showed comparable mitochondrial aberrations, indicating that NEC-associated intestinal barrier injury already occurs during chorioamnionitis. This study underlines the pathogenic potential of UP during pregnancy; it demonstrates that antenatal UP infection leads to severe colonic mucus barrier deficits, providing a mechanistic link between antenatal infections and postnatal NEC development.

Is There Evidence of Crohn's Disease Exclusion Diet (CDED) in Remission of Active Disease in Children and Adults? A Systematic Review.

Crohn's disease (CD) is an inflammatory bowel disease. Previous research has explored the impact of diet on CD, as specific dietary components can influence gut microbiota and immune responses, contributing to damage in the gastrointestinal tract. The Crohn's Disease Exclusion Diet (CDED) is based on an exclusion diet; it is a recent dietary approach that is often used alongside partial enteral nutrition (PEN) and aims to induce disease remission by excluding certain dietary components. This study assesses the current evidence for the effectiveness of the CDED + PEN in achieving remission in both children and adults with active CD. Our systematic review followed PRISMA recommendations and was registered in PROSPERO with CRD number 42022335076. The searched databases were PubMed/MEDLINE, Cochrane Library, Scopus, and Web of Science. The included studies were analyzed using Rayyan software, and the risk of bias was assessed with Cochrane RevMan 5.0 software. The primary assessed outcome was clinical remission, evaluated with validated questionnaire scores such as PCDAI, CDAI, or HBI. All analyzed papers yielded promising results. Notably, the CDED + PEN demonstrated better tolerance than exclusive enteral nutrition (EEN), resulting in higher adherence rates. Therefore, the CDED + PEN appears to be a viable alternative for induction remission in active disease for both children and adults with CD.

Multi-center study on mortality in children, and adults with sickle cell anemia-risk factors and causes of death.

Sickle cell disease (SCD) is a major public health burden worldwide with increasing morbidity and mortality. The study evaluates the risk factors associated with mortality in SCD patients, between the years 2006 and 2020 at three hospitals in Oman. The analysis includes clinical manifestations, haematological, biochemical, and radiological parameters, use of antibiotics, and blood and exchange transfusions. Our cohort included 123 patients (82 males, 41 females), with a median age of 27 (Interquartile Range 21-35 years). SCD related complications included acute chest syndrome (ACS) in 52.8%, splenic sequestration in 21.1%, right upper quadrant syndrome in 19.5%, more than > 6 VOC/year in 17.9%, and stroke in 13.8%. At the terminal admission, patients had cough, reduced O2 saturation, crepitation and fever in 24.4%, 49.6%, 53.6% and 68.3% respectively. Abnormal chest X-ray and chest CT scan were seen in 57.7%, and 76.4% respectively. Laboratory parameters showed a significant drop in hemoglobin (Hb) and platelet counts from baseline, with a significant rise in WBC, LDH and CRP from baseline (p < 0.05, Wilcoxon Signed Ranks test). All patients received antibiotics, whereas, 95.9% and 93.5% received simple blood transfusions, and exchange transfusions respectively, and 66.6% required non-invasive ventilation. Among the causes of death, ACS is seen in 32 (26%), sepsis in 49 (40%), and miscellaneous in 42 (34%). Sudden death was seen in 32 (26%) of patients. Male gender, with low HbF, rapid drop in Hb and platelet, and increased in WBC, LDH, ferritin, and CRP, correlated significantly with mortality in this cohort.

Deciphering the causal association and co-disease mechanisms between psoriasis and breast cancer.

Background: Prior research has indicated a link between psoriasis and the susceptibility to breast cancer (BC); however, a definitive causal relationship remains elusive. This study sought to elucidate the causal connection and shared underlying mechanisms between psoriasis and BC through bidirectional Mendelian randomization (MR) and bioinformatic approaches. Methods: We employed a bidirectional MR approach to examine the potential causal connection between psoriasis and BC. Genetic data pertaining to psoriasis and BC were sourced from extensive published genome-wide association studies. The inverse -variance weighted or wald ratio served as the primary method for estimating causal effects. Sensitivity analysis of the MR results was applied with multiple methods. Leveraged datasets from the Gene Expression Omnibus and the Cancer Genome Atlas repositories to identify common differentially expressed genes, shedding light on the shared mechanisms underlying these two conditions. Results: The MR analysis revealed that when considering psoriasis as an exposure factor, the incidences of BC (OR=1.027) and estrogen receptor negative (ER-) BC (OR=1.054) were higher than in the general population. When using Her2+ BC as an exposure factor, the risk of psoriasis was 0.822 times higher (OR=0.822) than in the general population. Sensitivity analysis indicated that the results were robust. Transcriptome analysis showed that CXCL13 and CCL20 were activated in both BC and psoriasis. Both diseases were also linked to neutrophil chemotaxis, the IL-17 pathway, and the chemokine pathway. Conclusion: The results suggest that psoriasis may increase the risk of BC, especially ER- BC, while reverse MR suggests a decreased risk of psoriasis in Her2+ BC. Transcriptome analysis revealed a shared mechanism between psoriasis and BC.

Causal association between rheumatoid arthritis and an increased risk of age-related macular degeneration: A Mendelian randomization study.

This study's goal is to evaluate if there is a causal connection between rheumatoid arthritis (RA) and age-related macular degeneration (AMD), despite past epidemiological studies suggesting an association between the 2 disorders. The impact of RA on AMD is still unknown. Mendelian randomization (MR) was utilized in this study to assess the two-sample causal relationship between RA and AMD. Summary data from GWAS for RA and AMD in individuals with all European ancestries were gathered using the IEU GWAS database. The GWAS summary statistics of RA (14,361 RA patients and 43,923 healthy controls) and AMD (14,034 AMD patients and 91,214 controls participated) were obtained from the IEU GWAS database. After identifying suitable instrumental variables in line with the 3 MR assumptions, we conducted MR using the Mendelian randomization-Egger (MR-Egger), weighted median, and inverse variance weighting techniques. The MR-Egger intercept and MR-Polyvalent Residuals and Outliers methods were used to investigate the effects of horizontal pleiotropy. The leave-one-out strategy was used to prevent bias caused by certain single nucleotide polymorphisms. Sensitivity analysis was used to detect the heterogeneity. Using 50 single nucleotide polymorphisms as instrumental variables, this study examined the relationship between RA and AMD and discovered that RA increased the risk of AMD (inverse variance weighting odds ratio [OR] = 1.056, 95% confidence interval [CI] = 1.02-1.09, P = 5.44E-04; weighted median OR = 1.085, 95% CI = 1.04-1.14, P = 4.05E-04; MR-Egger OR = 1.074, 95% CI = 1.01-1.14, P = 2.18E-2). The current investigation demonstrated a causal link between AMD and RA. RA increased the risk of AMD. It is advised that future research concentrate on the processes underlying the relationship between RA and AMD.

Causal influence of celiac disease on the risk of sarcoidosis: A Mendelian randomization study.

Observational research shows a link between celiac disease (CeD) and sarcoidosis, but the causal link between CeD and sarcoidosis is still unknown. A two-sample Mendelian randomization (MR) study was conducted to ascertain the causal connection between the 2 disorders. In our two-sample MR analysis, we identified independent genetic variants associated with CeD using publicly accessible GWAS data from people of European ancestry. Summary data for sarcoidosis were obtained from the FinnGen Consortium, the UK-Biobank, and a large GWAS dataset. To assess the association between CeD and sarcoidosis, our MR analysis used inverse variance weighted (IVW) as the primary method, incorporating the MR-Egger, weighted median (WM), and MR-PRESSO (outliers test) as a complementary method. In order to ensure that the findings were reliable, several sensitivity analyses were performed. Our study indicated that CeD had a significant causal relationship with sarcoidosis (IVW odds ratio (OR) = 1.13, 95% confidence interval (CI): 1.07-1.20, P = 5.58E-05; WM OR = 1.12, 95% CI: 1.03-1.23, P = 1.03E-02; MR-Egger OR = 1.07, 95% CI: 0.96-1.19, P = 2.20E-01). Additionally, we obtain the same results in the duplicated datasets as well, which makes our results even more reliable. The results of this investigation did not reveal any evidence of horizontal pleiotropy or heterogeneity. Our MR analysis showed a causal effect between CeD and an elevated risk of sarcoidosis. Further study is still needed to confirm the findings and look into the processes underlying these relationships.

Epidemiology, aetiology and diagnosis of congenital hearing loss via hearing screening of 153 913 newborns.

BACKGROUND: Congenital hearing loss (HL), one of the most common paediatric chronic conditions, significantly affects speech and language development. Its early diagnosis and medical intervention can be achieved via newborn hearing screening. However, data on the prevalence and aetiology of congenital HL in infants who fail newborn hearing screening are limited. METHODS: The sample population included 153 913 infants who underwent newborn hearing screening, and the prevalence of congenital HL, defined as moderate to profound bilateral HL (BHL) or unilateral HL (UHL) (≥40 dB HL), in one prefecture of Japan was measured to minimize the loss-to-follow-up rate, a common factor affecting the screening procedure. Comprehensive aetiological investigation, including physiology, imaging, genetic tests, and congenital cytomegalovirus screening, was performed on children diagnosed with congenital HL. RESULTS: The calculated prevalence of congenital HL was 1.62 per 1000 newborns (bilateral, 0.84; unilateral, 0.77). More than half of the cases with congenital bilateral or severe to profound UHL showed genetic aetiology or cochlear nerve deficiency (CND), respectively. Approximately 4% and 6% of the cases of congenital BHL and UHL were associated with congenital cytomegalovirus infection and auditory neuropathy spectrum disorder, respectively. CONCLUSIONS: This is an epidemiological and comprehensive aetiological study of congenital HL, as determined via newborn hearing screening according to its severity and laterality, in a large-scale general population of a developed country. Our findings can serve as a reference for optimizing care and intervention options for children with HL and their families.