Direct Causal Effect Research Articles

Travelling abroad and geopolitical preferences – case of Kharkiv, Dnipro and Mariupol, Ukraine

The paper investigates the relationship between travel abroad experience and individual geopolitical preferences in three geopolitical fault-line cities in the eastern part of Ukraine. Employing binary logistic regression as a principal research method, we show that travel experience to European countries positively correlates with pro-European attitudes and corresponds to weaker pro-Soviet sentiments. On the contrary, travel experience to Russia is associated with somewhat weaker support for European geopolitical and cultural integration but stronger pro-Soviet sentiments. Travel experience to Russia is less important predictor of geopolitical preferences than visiting European countries. Pro-European attitudes, compared with pro-Soviet sentiments, are much more interlinked with international travel experience. The data on bilateral travellers evidences that possible effect of visiting European countries basically neutralises the effect of visiting Russia in terms of impact on geopolitical preferences. Although the relationship between travel abroad experience and geopolitical preferences is similar in all three cities under investigation, certain variations between them may be explained by different economic, socio-cultural and institutional background. The revealed correlations seem to cover both direct causal effect of travel abroad on geopolitical preferences and a reverse causality, namely self-selection of destination country according to personal pre-existing geopolitical views. The importance of discovered relationships for the integration of Ukrainian society into European civilization project is apparent not only considering visa-free regime between Ukraine and the European Union (EU), but also in view of the Russian military invasion in 2022 as a cause of flows of refugees from Ukraine to Europe.

Combining Mendelian randomization and network deconvolution for inference of causal networks with GWAS summary data.

Mendelian randomization (MR) has been increasingly applied for causal inference with observational data by using genetic variants as instrumental variables (IVs). However, the current practice of MR has been largely restricted to investigating the total causal effect between two traits, while it would be useful to infer the direct causal effect between any two of many traits (by accounting for indirect or mediating effects through other traits). For this purpose we propose a two-step approach: we first apply an extended MR method to infer (i.e. both estimate and test) a causal network of total effects among multiple traits, then we modify a graph deconvolution algorithm to infer the corresponding network of direct effects. Simulation studies showed much better performance of our proposed method than existing ones. We applied the method to 17 large-scale GWAS summary datasets (with median N = 256879 and median #IVs = 48) to infer the causal networks of both total and direct effects among 11 common cardiometabolic risk factors, 4 cardiometabolic diseases (coronary artery disease, stroke, type 2 diabetes, atrial fibrillation), Alzheimer's disease and asthma, identifying some interesting causal pathways. We also provide an R Shiny app (https://zhaotongl.shinyapps.io/cMLgraph/) for users to explore any subset of the 17 traits of interest.

A network causal relationship between type-1 diabetes mellitus, 25-hydroxyvitamin D level and systemic lupus erythematosus: Mendelian randomization study.

Observational studies have suggested a relationship between type-1 diabetes mellitus (T1DM) and systemic lupus erythematosus (SLE). In both autoimmunities, 25-hydroxyvitamin D (25-OHD) deficiency is common. However, the causality between T1DM, 25-OHD level and SLE remains largely unknown. Independent genetic variants associated with T1DM, 25-OHD level, and SLE from the largest genome-wide association studies were used to conduct two-sample bidirectional Mendelian randomization (BIMR) and two-step Mendelian randomization (MR) analysis to estimate causal relationship between T1DM, 25-OHD level and SLE, and further multivariable Mendelian randomization (MVMR) was used to verify direct causality of T1DM and 25-OHD level on SLE. A series of sensitivity analysis as validation of primary MR results were performed. Consistent with the results of BIMR, there was strong evidence for a direct causal effect of T1DM on the risk of SLE (ORMVMR-IVW = 1.249, 95% CI = 1.148-1.360, PMVMR-IVW = 1.25×10-5), and 25-OHD level was negatively associated with the risk of SLE (ORMVMR-IVW = 0.305, 95% CI = 0.109-0.857, PMVMR-IVW = 0.031). We also observed a negative causal effect of T1DM on 25-OHD level (ORBIMR-IVW = 0.995, 95% CI = 0.991-0.999, PBIMR-IVW = 0.030) while the causal effect of 25-OHD level on the risk of T1DM did not exist (PBIMR-IVW = 0.106). In BIMR analysis, there was no evidence for causal effects of SLE on the risk of T1DM and 25-OHD level (PBIMR-IVW > 0.05, respectively). Our MR analysis suggested that there was a network causal relationship between T1DM, 25-OHD level and SLE. T1DM and 25-OHD level both have causal associations with the risk of SLE, and 25-OHD level could be a mediator in the causality of T1DM and SLE.

Evaluating the causality between skin tanning, radiated disorders, and basal cell carcinoma: a multivariable Mendelian randomization analysis.

The causality of ease of skin tanning and radiation-related disorders of the skin and subcutaneous tissue with basal cell carcinoma (BCC) remains unclear. Our objective was to investigate whether ease of skin tanning and radiation-related disorders of the skin and subcutaneous tissue have a relation with the occurrence and development of BCCs. In this work, independent genetic variants strongly associated (P < 5e-08) with ease of skin tanning and radiation-related disorders of the skin and subcutaneous tissue were selected as instrumental variables from corresponding genome-wide association studies (GWASs). Summary-level data for BCC was obtained from the European Bioinformatics Institute (EBI). Two-sample univariable and multivariable Mendelian randomization (MR) were performed. Sensitivity analyses were preformed via MR-Egger regression, heterogeneity test, pleiotropy test, and leave-one-out sensitivity test. We observed positive causal effect both for ease of skin tanning [odds ratio (OR) = 2.102, 95% confidence interval (CI) = 1.915-2.306, P = 2.71e-55] and radiation-related disorders of the skin and subcutaneous (OR = 1.603, 95% CI = 1.483-1.734, P = 3.41e-32) on occurrence of BCCs based on univariable MR analyses. In the multivariable mendelian randomization (MVMR) analysis of BCC risk, we also observed a direct causal effect of ease of skin tanning (ORMVMR = 1.623, 95% CI = 1.445-1.824, PMVMR =3.41e-16) and radiation-related disorders of the skin and subcutaneous (ORMVMR = 1.208, 95% CI = 1.107-1.319, PMVMR = 2.46e-05) on BCCs. The findings suggest that the high risk of BCCs can be attributed to ease of skin tanning and radiation-related disorders of the skin and subcutaneous tissue.

Aging Population and Automated Mobility: Exploring the Impacts of Land Use Patterns and Attitudes

This study explores the aging population’s behavior toward the adoption of and willingness to pay (WTP) for autonomous vehicles (AVs), with a focus on the roles of attitudes and land use variables. A structural equation model with interaction effects was developed to explore the impacts of socioeconomic and demographic attributes, mobility profiles, attitudes collected through a user behavior survey, and land use variables extracted from the Smart Location database. Among different structures tested, a direct causal effect from adoption to WTP shows the best model fit, implying that any parameter affecting the adoption will indirectly affect WTP in the same direction. Focusing on the older population, the model results show that they were positively affected by their interest in driving assistance and safety features. Older adults also seemed to be more sensitive to mobility costs compared with younger travelers. We further explored the impact of land use characteristics. In general, it appears that living in areas associated with higher population density and higher centrality index (based on auto accessibility) tends to lower AV adoption rates. Comparing the older population with younger people, no significant difference was observed in view of land use impacts on AV adoption. However, the older population’s WTP tends to increase in urban areas with higher roadway network densities (e.g., urban areas) and is likely to decrease in neighborhoods with higher employment density and higher percentage of single-vehicle households. We suggest that the latter effect might be associated with other micro-level attributes such as their income and lifestyle patterns.

Preoperative glucose in surgical oncology patient is not associated with postoperative outcomes after adjustment for frailty.

Observational studies have shown associations between even small elevations in preoperative glucose and poorer outcomes, including increased length of stay (LOS) and higher mortality. This has led to calls for aggressive glycemic control in the preoperative period, including delay of treatment until glucose is reduced. However, it is not known whether there is a direct causal effect of blood glucose or whether adverse outcomes result from overall poorer health in patients with higher glucose. Analysis was performed using a retrospective database of patients aged 65 and older who underwent cancer surgery. The last measured preoperative glucose was the exposure variable. The primary outcome was extended LOS (>4 days). Secondary outcomes included mortality, acute kidney injury (AKI), major postoperative complications during the admission period, and readmission within 30 days. The primary analysis was a logistic regression with prespecified covariates: age, sex, surgical service, and the Memorial Sloan Kettering-Frailty Index. In an exploratory analysis, lasso regression was used to select covariates from a list of 4160 candidate variables. This study included 3796 patients with a median preoperative glucose of 104 mg/dL (interquartile range: 93-125). Higher preoperative glucose was univariately associated with increased odds of LOS > 4 days (odds ratio [OR]: 1.45, 95% confidence interval [CI]: 1.22-1.73), with similar results for AKI, readmission, and mortality. Adjustment for confounders eliminated these associations for LOS (OR: 0.97 [95% CI: 0.80-1.18]) and attenuated all other glucose-outcome associations. Lasso regression gave comparable results to the primary analysis. Using the upper bound of the respective 95% confidence interval, we estimated that, at best, successful reduction of elevated preoperative glucose would reduce the risk of LOS > 4 days, 30-day major complication, and 30-day mortality by 4%, 0.5%, and 1.3%, respectively. Poor outcomes following cancer surgery in older adults with elevated glucose are most likely related to poorer overall health in these patients rather than a direct causal effect of glucose. Aggressive glycemic management in the preoperative period has very limited potential benefits and is therefore unwarranted.

On distinguishing the direct causal effect of an intervention from its efficiency-enhancing effects

This paper proposes an innovative methodology for handling endogeneity issues in the evaluation of policy performance. By estimating a regression discontinuity design with a four-component stochastic frontier panel data model, we estimate the causal impact of a policy intervention on the outcome variable, whenever the treatment status depends on an exogenous threshold. We distinguish between (i) the direct effect of the intervention, (ii) the efficiency-enhancing effect, or (iii) their combination. Moreover, we distinguish between persistent (time-invariant) and transient (time-varying) inefficiency components while accounting for unobserved heterogeneity, which is important for policy implications. We showcase the practical usefulness of the proposed approach by estimating the effect of providing additional resources on schools that exceed an exogenously set share of disadvantaged students in secondary schools in Flanders, Belgium. We also demonstrate the trade-off between balance of the covariates in the treated and control group and statistical power. Thus, despite insignificant effects in a balanced but smaller sample close to the discontinuity, the results become significant in the unbalanced sample with more statistical power. In both samples, we observe that the policy had an effect on the outcome mostly through the efficiency-enhancing channel. To this extent, we show that the model specification including both direct and indirect effects outperforms the other two specifications and it offers a more exhaustive perspective from a policy view point.

Causal modelling of the influence of demographic variables on work-stimulated stress among early childhood educators in South Africa

Work-related stress has emerged as a pervasive global issue that needs to be investigated by specialists around the world. Work stress is a condition of pressure brought on by one's line of work and occurs when the demands of the job are too great for an employee's abilities or resources. The study was undertaken to examine the direct and indirect causal effect of some demographic variables on work-stimulated stress among early childhood educators in South Africa. Hence, the researchers developed and validated a model involving causal linkages between early childhood educators’ demographic variables such as age, gender, race, marital status, income and educational qualification, and work-stimulated stress. The study adopted an ex-post-facto research design. The sample comprised one hundred and twenty (120) early childhood educators across twenty (20) Early Childhood Education (ECE) centres. A stratified random sampling technique was used to select the early childhood educators for the study. One validated instrument on work-stimulated stress developed by the researchers on a four-point rating scale was used to collect the data for the study, while path analysis and multiple regression analysis were employed for data analysis. The findings of this study documented the more parsimonious model, which effectively predicts the influence of demographic variables on work-stimulated stress among early childhood educators. The results further indicated that three (Age, Gender, and Marital Status) out of the six predictor variables caused early childhood educators’ work-stimulated stress more than the other variables. The implications of these findings for education policymakers, administrators, and teachers are discussed.

Drug-Induced Psychosis: Causes, Symptoms, and Treatment

IntroductionA relationship between drug abuse and the onset of psychotic symptoms is strongly supported. A struggling clinical dilemma is how to clearly identify a substance-induced psychosis from a primary psychotic illness or a psychotic illness with comorbid substance use.ObjectivesIn this review, the presence of associated psychotic symptoms and the differences in clinical presentation will be analyzed for each substance.MethodsΑ bibliographical review was performed using the PubMED platform. All relevant articles were found using the keywords: substance-Induced Psychoses, symptoms, treatmentResultsPresent review shows a picture of the complex relationship between psychotic symptoms and the use and abuse of illicit drugs. Furthermore, in most cases, chronological criteria are not sufficient to prove a direct causal effect between the substance and psychosis. The subjects who presented psychotic symptoms after substance abuse seemed to have a higher risk of the development of a primary psychotic illness.ConclusionsPsychosis due to substance abuse is a common issue in clinical practice and the propensity to develop psychosis seems to be associated with the severity of use and dependence.Disclosure of InterestNone Declared

Diabetes and intervertebral disc degeneration: A Mendelian randomization study.

Intervertebral disc degeneration (IVDD) is an important contributor of low back pain, which represents one of the most disabling symptoms within the adult population. Recently, increasing evidence suggests the potential association between Type 2 diabetes mellitus (T2DM) and IVDD. However, the causal relationship between these two common diseases remains unclear. We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal association between T2DM and IVDD. Sensitivity analysis was performed to test for heterogeneity and horizontal pleiotropy. Multivariable MR was also conducted to adjust for the effect of BMI on IVDD. A total of 128 independent single-nucleotide polymorphisms (SNPs) that were significantly associated with T2DM were selected as instrumental variables in univariable MR analysis. Our results showed that patients with T2DM had a higher risk of developing IVDD (OR, 1.069; 95% CI, 1.026-1.115; p = 0.002). The relationship remained stable in sensitive analysis including multivariable MR, which implicated the direct causal effect of T2DM on IVDD (OR, 1.080; 95% CI, 1.041-1.121; p < 0.001) after adjusting for BMI. MR analysis indicated a causal effect of T2DM on IVDD, and the effect persisted even when we accounted for the impact of BMI.

Causal association between cardiovascular diseases and erectile dysfunction, a Mendelian randomization study.

Cardiovascular diseases (CVD), including coronary heart disease (CHD), heart failure, ischemic heart disease (IHD), and atrial fibrillation, are prevalent in the aged. However, the influence of CVD on ED is less investigated. This study was performed to clarify the causal association between CVD and ED. Genome-wide association studies (GWAS) datasets targeting CHD, heart failure, IHD, and atrial fibrillation were downloaded to retrieve single nucleotide polymorphisms (SNPs). Further, single-variable Mendelian randomization and multivariable Mendelian randomization (MVMR) were adopted to explore the causal association between CVD and ED. Genetically predicted CHD and heart failure were found to increase the risks of ED (OR = 1.09, P < 0.05 and OR = 1.36, P < 0.05, respectively). However, no causal association was disclosed among IHD, atrial fibrillation and ED (all P > 0.05). These findings remained consistent in sensitivity analyses. After controlling for body mass index, alcohol, low density lipoprotein, smoking and total cholesterol levels, the results of MVMR support the causal role of CHD on ED (P < 0.05). Similarly, the direct causal effect estimates of heart failure on ED were significant in MVMR analyses (P < 0.05). Using genetic data, this study revealed that genetically predicted CHD and heart failure may predict better ED compared with atrial fibrillation and IHD. The results should be interpreted with caution and the insignificant causal inference of IHD still needs further verification in future studies.

Causal associations of sleep apnea and snoring with type 2 diabetes and glycemic traits and the role of BMI.

Sleep apnea and snoring have been associated with type 2 diabetes, with BMI playing a role in the pathway, but the directions of causality are unclear. This study examined the causal associations of sleep apnea and snoring with type 2 diabetes while assessing the role of BMI using multiple genetic methods. Five genetic methods were used: two-sample; bidirectional univariable Mendelian randomization (MR) inverse variance-weighted (MR-IVW); multivariable MR-IVW; network MR; and latent causal variable method. Compared with univariable MR-IVW, the odds ratio (95% CI) of type 2 diabetes for genetically predicted sleep apnea and snoring using the largest genome-wide association study decreased dramatically, from 1.61 (95% CI: 1.16-2.23) to 1.08 (95% CI: 0.59-1.97) and from 1.98 (95% CI: 1.25-3.13) to 1.09 (95% CI: 0.64-1.86) after adjustment for BMI. Network MR showed that BMI accounts for 67% and 62% of the total effect of sleep apnea and snoring on type 2 diabetes, respectively. The latent causal variable suggested that sleep apnea and snoring have no direct causal effect on type 2 diabetes. These results first suggest that the associations of sleep apnea and snoring with type 2 diabetes were mainly driven by BMI. The possible indirect effects of sleep apnea and snoring on type 2 diabetes through BMI cannot be ruled out.

How effective is reducing traffic speed for safer work zones? Methodology and a case study in Pennsylvania

Transportation agencies post and enforce reduced speed limits in work zones to ensure work zone safety, since traffic speed is found to be associated with work zone crash risks. However, prior findings on the relationship between speed and crash rate in work zones are inconsistent. This may be attributed to the methods of statistical associations between traffic speed and crash risks that do not necessarily discover true causal relations. In fact, work zone presence could lead to the reduction of actual traffic speed that influences crash risks, where it may also directly impose effects on crash risks as a result of work zone configurations. The actual traffic speed (not posted speed limit) is also known as a “mediator” where work zones can indirectly impact the crash risks. It is challenging to rigorously separate the causal effect of traffic speed on work zone crash risk from that directly caused by work zones. The underlying causal relation could help to determine what reduced post speed limit (with enforcement) is necessary to ensure work zone safety under the most desired “actual traffic speed”. This study proposes to use the sequential g-estimation and the regression discontinuity design to estimate the controlled direct effect of traffic speed on work zone crashes. Two research gaps are identified and filled: inaccurate inferences of the effect of reduced speed limit in work zones as a result of ignoring (1) potential post-treatment bias since traffic speed is a mediator; and (2) potential confounding bias caused by unobservable roadway characteristics. The proposed methodology was applied to 4008 work zones in Pennsylvania from 2015 to 2017, and the results were validated through a series of robustness tests. The results indicate that the direct causal effect of the presence of work zones on crash risk is significantly positive when the traffic speed is relatively low (i.e., lower than 55 mph in this case study), while traffic speed has a positive causal effect on crash occurrences when the actual traffic speed is high (i.e., greater or equal to 55 mph). It suggests that strictly enforcing reduced posted speed limits in work zones is particularly effective when the actual traffic speed is greater than 55 mph. This is particularly true on roadways with high traffic volume (i.e., AADT > 20,000 vehicles per day), long, and daytime work zones (i.e., > 3000 m). On the other hand, the effect of enforcing reduced speed on work zone safety is unclear when the actual speed is already low. In this case, improving work zone configurations and driving behaviors may be more effective in reducing crash risks.

SAĞLIK ÇALIŞANLARININ KİŞİLİK ÖZELLİKLERİNİN ONLARIN ÖRGÜTSEL DESTEK VE ÖRGÜTSEL GÜVEN ALGILARI ÜZERİNDEKİ ETKİSİ

Aim: The main purpose of this study is to determine the effect of the personality characteristics of healthcare workers on their perceptions of organizational support and organizational trust. Method: The population of the research consisted of the employees of the private hospital providing secondary care in three different regions in Istanbul. The convenience sampling method was preferred in the study. The data were collected using the online questionnaire technique. The total number of questionnaires that were evaluated and used in the data analysis is 510. SPSS 23 and AMOS 26 package programs were used to analyze the data. Descriptive statistics, multiple linear regression analysis, and structural equation modeling were applied to the data. Findings: The findings obtained with the structural equation analysis showed that the construct validity of the model was provided. The direct causal effect of the personality traits of health workers on their perceptions of organizational support is positive, and the effect level is 0.122; On the other hand, it has been determined that the direct causal effect on organizational trust perceptions is positive, and the effect level is 0.225. Results: According to the results obtained from the regression analysis, it is seen that the high level of extraversion, responsibility, and openness characteristics of health workers positively affected their perceptions of organizational support. Therefore, healthcare professionals who are more extrovert, adaptable, and responsible show higher organizational support and organizational trust. It is suggested that personality traits being compatible with the organization may have a positive effect on outputs such as employee performance, job satisfaction, commitment, and motivation, and the study should be expanded in this direction.

Towards agricultural groundwater sustainability behaviour: Effects of place attachment

AbstractThe study aimed to analyse the causal effects of place attachment (PA) on farmers' groundwater (GW) sustainability behaviour using the developed model of cultural environmental bias (CEB). The analysis unit in this descriptive and causal study was the hydrological areas of GW resources studies and Agricultural GW Users (AGWU) of agricultural wells. Causal analysis showed that place identity structure (PI) is a strong determinant of GW sustainability behaviour and has the most direct and indirect causal effect on farmers' behaviour. The fitted model of the study is a combined model that explains 47% of the variance changes in GW sustainability behaviour. This study showed that in cultural and social contexts, beliefs and norms of farmers are vital in the decisions of the agriculture sector. Farmers' place attachment affects environmental cultural beliefs and activities and their public participation for the purpose of environmental‐groundwater sustainability.

Adaptation of Partial Mutual Information from Mixed Embedding to Discrete-Valued Time Series.

A causality analysis aims at estimating the interactions of the observed variables and subsequently the connectivity structure of the observed dynamical system or stochastic process. The partial mutual information from mixed embedding (PMIME) is found appropriate for the causality analysis of continuous-valued time series, even of high dimension, as it applies a dimension reduction by selecting the most relevant lag variables of all the observed variables to the response, using conditional mutual information (CMI). The presence of lag components of the driving variable in this vector implies a direct causal (driving-response) effect. In this study, the PMIME is appropriately adapted to discrete-valued multivariate time series, called the discrete PMIME (DPMIME). An appropriate estimation of the discrete probability distributions and CMI for discrete variables is implemented in the DPMIME. Further, the asymptotic distribution of the estimated CMI is derived, allowing for a parametric significance test for the CMI in the DPMIME, whereas for the PMIME, there is no parametric test for the CMI and the test is performed using resampling. Monte Carlo simulations are performed using different generating systems of discrete-valued time series. The simulation suggests that the parametric significance test for the CMI in the progressive algorithm of the DPMIME is compared favorably to the corresponding resampling significance test, and the accuracy of the DPMIME in the estimation of direct causality converges with the time-series length to the accuracy of the PMIME. Further, the DPMIME is used to investigate whether the global financial crisis has an effect on the causality network of the financial world market.

Mendelian randomization identifies age at menarche as an independent causal effect factor for gestational diabetes mellitus.

The relationship between age at menarche (AAM) and gestational diabetes mellitus (GDM) risk is still inconclusive. This Mendelian randomization (MR) analysis was used to assess systematically the causal relationship between AAM and GDM risk in human beings. Single-nucleotide polymorphisms associated with AAM, oestradiol levels, sex hormone-binding globulin (SHBG) levels and bioavailable testosterone (BioT) levels were screened via the genome-wide association study enrolling individuals of European descent. Summary-level data for GDM (123 579 individuals) were extracted from the UK Biobank. An inverse-variance-weighted method was used for the primary MR analysis. Sensitivity analyses were examined via MR-Egger regression, heterogeneity tests, pleiotropy tests and leave-one-out tests. The directionality that exposure causes the outcome was verified using the MR-Steiger test. Genetically predicted early AAM was found to have a causal positive association with a higher risk of GDM (odds ratio=0.798, 95% confidence interval=0.649-0.980, p=.031). In the multivariable MR analysis adjusted for oestradiol, SHBG and BioT levels, the causal association between AAM and GDM risk remained (odds ratio=0.651, 95% confidence interval=0.481-0.881, p=.006). A 1-SD increase in SHBG or BioT levels was significantly associated with a 41.4% decrease or 20.8% increase in the overall GDM risk (p=3.71E-05 and .040), respectively. However, after controlling for AAM, oestradiol levels and BioT levels by multivariable MR analysis, there was no direct causal effect of SHBG levels on GDM risk (p=.084). Similarly, after adjusting for AAM, oestradiol levels and SHBG levels by multivariable MR analysis, there was no direct causal effect of BioT levels on the risk of GDM (p=.533). In addition, no direct causal association was identified between oestradiol levels and GDM risk in univariable MR analysis or multivariable MR analysis. Genetic variants predisposing individuals to early AAM were independently associated with higher GDM risk. Further research is required to understand the mechanisms underlying this putative causative association. In addition, AAM may be helpful in clinical practice to identify women at risk for GDM; pregnant women who are young for menarche may need to take precautions before GDM develops.

Hypothyroidism has a protective causal association with hepatocellular carcinoma: A two-sample Mendelian randomization study.

ObjectiveObservational studies suggest an association between hypothyroidism and the risk of hepatocellular carcinoma (HCC), but the causality and direction of these effects are still inconclusive. We aim to test whether hypothyroidism is causally associated with the risk of HCC by using Mendelian randomization (MR) analysis.MethodsSingle-nucleotide polymorphisms (SNPs) associated with hypothyroidism were screened via a genome-wide association study (GWAS) on 337,159 individuals of European descent (16,376 cases and 320,783 controls). The SNPs associated with thyroid-stimulating hormone (TSH) and free thyroxine (FT4) were selected from a GWAS of 72,167 individuals of European descent. Summary-level data for HCC (168 cases and 372,016 controls) were extracted from UK Biobank. An inverse-variance-weighted (IVW) method was used as the primary MR analysis. Sensitivity analyses were examined via MR-Egger regression, heterogeneity test, pleiotropy test, and leave-one-out sensitivity test. The assumption that exposure causes outcome was verified using the MR Steiger test.ResultsTwo-Sample MR analysis showed inverse associations between genetically predicted hypothyroidism and HCC risk (OR = 0.997, 95% CI, 0.995-0.999; P = 0.016). There were no statistical indications of heterogeneity among instruments (P-het = 0.667). Across five MR methods, genetically predicted hypothyroidism shows a consistent correlation with HCC. The leave-one-out analysis indicated that no single SNP changed the overall estimate (P = 0.016). In addition, the MR Steiger test revealed that hypothyroidism was causal for HCC and not the opposite (P = 0.000). Finally, there was no evidence for a direct causal effect of TSH level and FT4 level on HCC risk.ConclusionOur results provide some that genetically determined hypothyroidism decreases the risk of HCC, although the size of the causal estimate is small. Further research is required to comprehend the mechanisms underlying this putative causative association, and follow-up clinical trials need to be conducted to establish whether inducing hypothyroidism could be beneficial for patients who are suffering from HCC. During future treatment of hypothyroidism, close attention to liver function may also be required to prevent a possible increased risk of HCC.

Advances in Stroke: Genetics, Genomics, Precision Medicine.

Advances in Stroke: Genetics, Genomics, Precision Medicine.

Osteoporosis and sarcopenia-related traits: A bi-directional Mendelian randomization study.

BackgroundWith the advancement of world population aging, age-related osteoporosis (OP) and sarcopenia (SP) impose enormous clinical and economic burden on society. Evidence from accumulating studies indicates that they mutually influence one another. However, an observational study may be affected by potential confounders. Meanwhile, a Mendelian randomization (MR) study can overcome these confounders to assess causality.ObjectivesThe aim of this study was to evaluate the causality between OP and SP, informing new strategies for prevention, diagnosis, and treatment of osteosarcopenia.MethodsInstrumental variables (IVs) at the genome‐wide significance level were obtained from published summary statistics, and the inverse variance weighted method and several other MR methods were conducted to evaluate the bi-directional causality between SP and OP. Myopia was analyzed as a negative control outcome to test the validity of IVs.ResultsFemoral neck bone mineral density (FN BMD), lumbar spine BMD (LS BMD), and forearm BMD (FA BMD) had a direct causal effect on appendicular lean mass (ALM) [FA BMD-related analysis: odds ratio (OR) = 1.028, 95% confidence interval (CI) = (1.008,1.049), p = 0.006; FN BMD-related analysis: OR (95% CI) = 1.131 (1.092,1.170), p = 3.18E-12; LS BMD-related analysis: OR (95% CI) = 1.080 (1.062,1.098), p = 2.86E-19]. ALM had a significant causal effect on LS BMD [OR (95% CI) = (1.033,1.147), p = 0.001]. There was no evidence for causal association between BMD and low grip strength.ConclusionsOP and SP might mutually have a significant causal effect on each other. Our results supported the idea that the patient with severe OP was more susceptible to lose ALM and severe ALM loss might reduce LS BMD.