Direct Causal Effect Research Articles

Dynamic effects of energy transition on environmental sustainability: Fresh findings from the BRICS+1

The study aims to fill a critical gap in understanding the multifaceted impact of various economic and environmental factors on sustainability within the BRICS+1 nations. Rapid industrialization and urbanization in these BRICS countries have led to significant environmental challenges, necessitating a comprehensive examination of the effectiveness of energy transitions, green patents, urbanization, environmental policies, and economic growth on environmental sustainability. This research specifically examines the impact of the energy transition (ET), green patents (GPT), and environmental policy on environmental sustainability represented by the Load Capacity Factor (LCF) and using the CS-ARDL, PMG-ARDL, and Dumitrescu Hurlin (DH) panel causality techniques. The panel datasets gathered from BRICS +1 nations from 1993 to 2020 indicated a significant statistically direct causal effect from energy transition to environmental sustainability. The outcome also shows that еnеrgy transition adopted by thе BRICS nations arе inadеquatе in addressing environmental sustainability objectives in the long run. Urbanization and the implementation of environmental policies have a negative effect on the LCF. Simultaneously, green patents substantially and favourably influence, ultimately revealing the lack of concern for environmental matters in global technological innovation. Empirical findings indicate that selected BRICS+1 countries should implement various policy measures to enhance environmental sustainability.

Genetically mimicked effects of thyroid dysfunction on diabetic retinopathy risk: a 2-sample univariable and multivariable Mendelian randomization study.

Thyroid dysfunction exhibits a heightened prevalence among people with diabetes compared to those without diabetes. Furthermore, TD emerges as a notable correlated risk factor for the onset of diabetic retinopathy. Using data from the FinnGen database (R9), we investigated the causal relationship between thyroid dysfunction (TD) and four stages of diabetic retinopathy (DR). A two-sample univariable Mendelian randomization (UVMR) approach was employed to estimate the total causal effect of TD on four stages of DR, while multivariable Mendelian randomization (MVMR) was used to assess the direct causal effect. The meta-analysis was conducted to summarize the collective effect of TD on four stages of DR. The inverse variance weighted (IVW) method was the primary approach for Mendelian randomization analysis, with heterogeneity, horizontal pleiotropy, and leave-one-out sensitivity analyses performed to validate the robustness of the findings. In UVMR analysis, thyrotoxicosis (TOS) was significantly associated with an increased risk of diabetic retinopathy across four stages (OR, 1.10-1.19; P<0.025). However, MVMR analysis, after adjusting for Graves' disease (GD) and/or rheumatoid arthritis (RA), revealed no significant association between TOS and the four stages of diabetic retinopathy. The Meta-analysis demonstrated the collective effect of TOS on diabetic retinopathy across all stages [OR=1.11; 95% CI (1.08-1.15); P<0.01]. In UVMR analysis, the estimates for hypothyroidism (HPT) and GD were similar to those for TOS. In the MVMR analysis, after adjusting for RA, the significant effect of HPT on DR and non-proliferative diabetic retinopathy (NPDR) remained. Additionally, MVMR analysis suggested that the estimates for GD on DR were not affected by TOS, except for GD-proliferative diabetic retinopathy (PDR). However, no significant correlation persisted after adjusting for RA, including for GD-PDR. Our study demonstrated a significant association between thyroid dysfunction TD and DR, with the relationship being particularly pronounced in HPT-DR.

The fed information shocks and the market for corporate control: Predictive and causal effects

We show that contractionary monetary shocks, when reflecting a positive macroeconomic assessment by the Federal Reserve (hereafter “Fed”), predict an economic environment that is characterized by (a) a rise in M&A activity, (b) a higher likelihood of M&A completion, (c) higher bidder gains, (d) limited concerns about M&A overpayment, and (e) higher premia offered by foreign bidders to U.S. targets. Further, Fed information shocks have a standalone and direct causal effect on market expectations of M&A gains. That is, positive Fed information shocks trigger a positive revaluation of pending M&A. This revaluation effect, which holds after controlling for macroeconomic conditions and changes in economic forecasts, is more pronounced in deals that are relatively large, financed with stock, and have received a negative market reaction at the M&A announcement period. Overall, our results highlight the independent and credible signaling role of the Fed in the realm of M&A.

Causality between atopic diseases and osteoarthritis:a Mendelian randomization study

To explore causal relationship between atopic diseases (asthma and atopic dermatitis) and osteoarthritis (OA) by using mendelian randomization(MR). Asthma and atopic dermatitis as instrumental variables were selected, searched them through IEU database, and selected the latest data with a large number of cases and single nucleotide polymorphism (SNP). Data were collected and processed using R language, inverse varianceweighted (IVW) method was adopted as main MR Evaluation method. Single linear regression was performed to estimate causality based on pooled knee and hip data from genome-wide association studies (GWAS). The forest map was drawn to visualize the results, and gene pleiotropy and sensitivity were analyzed by scatter plot and funnel plot. At the same time, asthma, atopic dermatitis, body mass index (BMI), osteoporosis and OA were selected for multivariate MR Analysis to exclude the effect of horizontal pleiotropy on the results in GWAS data. Analysis of MR-IVW results showed asthma was positively correlated with causal effect of OA [OR=1.41, 95%CI(1.07, 1.85), P=0.02], multivariate Mendelian randomization (MVMR) adjusted for BMI and osteoporosis and a direct causal effect on OA was observed [OR=1.57, 95%CI(1.03, 2.39), P=0.03)]. MR Results of two samples of atopic dermatitis and OA were [OR=1.01, 95%CI(0.97, 1.04), P=0.76], and MVMR results were [OR=1.02, 95%CI(0.99, 1.05), P=0.25], indicating no clear causal relationship between two samples. Asthma could increase risk of OA, atopic dermatitis has no obvious relationship with OA, and the relationship between atopic diseases and OA still needs to be discussed.

Evaluating the distinct effects of body mass index at childhood and adulthood on adult major psychiatric disorders.

Children with high body mass index (BMI) are at heightened risk of developing health issues in adulthood, yet the causality between childhood BMI and adult psychiatric disorders remains unclear. Using a life course Mendelian randomization (MR) framework, we investigated the causal effects of childhood and adulthood BMI on adult psychiatric disorders, including Alzheimer's disease, anxiety, major depressive disorder, obsessive-compulsive disorder (OCD), and schizophrenia, using data from the Psychiatric Genomics Consortium and FinnGen study. Childhood BMI was significantly associated with an increased risk of schizophrenia, while adulthood BMI was associated with a decreased risk of OCD and schizophrenia. Multivariable MR analyses indicated a direct causal effect of childhood BMI on schizophrenia, independent of adulthood BMI and lifestyle factors. No evidence of causal associations was found between childhood BMI and other psychiatric outcomes. The sensitivity analyses yielded broadly consistent findings. These findings highlight the critical importance of early-life interventions to mitigate the long-term consequences of childhood adiposity.

The Portfolio Diet and HbA1c in Adults Living with Type 2 Diabetes Mellitus: A Patient-Level Pooled Analysis of Two Randomized Dietary Trials.

(1) Background: The Portfolio Diet, a dietary pattern of cholesterol-lowering foods, is also rich in low glycemic index (GI) foods. While strong evidence supports clinically meaningful reductions in cholesterol, evidence on the relationship between the Portfolio Diet and diabetes management is lacking. (2) Objective: To evaluate the relationship between the Portfolio Diet and glycated hemoglobin (HbA1c) as a determinant of glycemic control among adults living with type 2 diabetes mellitus (T2DM). (3) Methods: Patient-level data was pooled from two randomized dietary trials of low glycemic index interventions compared to high cereal fibre control diets in adults living with T2DM where HbA1c was collected (clinicaltrials.gov identifiers: NCT00438698, NCT00438698). Dietary exposure was assessed using weighed 7-day diet records. Adherence to the Portfolio Diet and its pillars (nuts and seeds, plant protein, viscous fibre, plant sterols, monounsaturated fatty acid [MUFA] oils) was determined using the validated clinical Portfolio Diet Score (c-PDS). Multiple linear regression was used to assess the association between change in the c-PDS and change in HbA1c over 6-months with covariate adjustments. (4) Results: A total of 267 participants, predominantly White (67%) and male (63%), were included, with a mean ± standard error age of 62 ± 0.5 years, baseline BMI of 30.2 ± 0.3 kg/m2, HbA1c of 7.08 ± 0.03%, and a c-PDS of 4.1 ± 0.3 points out of 25. Change in the c-PDS was significantly associated with a change in HbA1c (β: -0.04% per point, 95% CI: -0.07, -0.02, p = 0.001). A 7.5-point (30%) increase in the c-PDS was associated with a 0.3% reduction in HbA1c. Of the individual pillars, a 1-point change in nut and seeds intake (β: -0.07%, 95% CI: -0.12, -0.02, p = 0.009) or in plant protein intake (β: -0.11%, 95% CI: -0.18, -0.03, p = 0.009) was associated with a change in HbA1c. Further analysis of plant protein intake revealed that an increase in dietary pulse intake, a particularly low-GI food, was significantly associated with a reduction in HbA1c (β: -0.24% per 1-cup points cooked pulses (226 g) or 2 c-PDS points, 95% CI: -0.45, -0.03, p = 0.028). (5) Conclusions: Among adults living with T2DM, the Portfolio Diet was associated with lower HbA1c over a 6-month period, predominantly driven by two pillars: nuts and seeds and plant protein, particularly dietary pulses. These data have implications for including the Portfolio Diet in dietary recommendations for glycemic control in T2DM. A trial demonstrating the direct causal effect of the Portfolio Diet in a diverse group is warranted.

Integrative analysis of causal associations between neurodegenerative diseases and colorectal cancer

BackgroundObservational studies have shown that the correlation between neurodegenerative diseases and colorectal cancer (CRC) remains controversial. Therefore, this study aimed to verify the causal association between these two diseases. MethodsMendelian randomization (MR) analysis was used to assess the causal relationships between five major neurodegenerative diseases and CRC. Multivariable MR (MVMR) analysis was conducted to assess the direct causal effect of neurodegenerative diseases on CRC. Colocalization and pathway enrichment analyses were conducted to further elucidate our results. Sensitivity analysis was conducted to assess the robustness of the results. ResultsGenetically predicted Alzheimer's disease (AD) nominally increased CRC risk (OR = 1.0620, 95%CI = 1.0127–1.1136, P = 0.013). There was no causal effect of genetically predicted CRC on neurodegenerative diseases. Furthermore, we demonstrated that genetically predicted AD marginally increased colon cancer risk (OR = 1.1621, 95%CI = 1.0267–1.3153, P = 0.017). Genetically predicted Lewy body dementia (LBD) had a significant causal effect on the increasing risk of colon cancer (IVW OR = 1.1779, 95%CI = 1.0694–1.2975, P = 0.001). MVMR indicated that effect of AD on colon cancer was driven by LBD, type 2 diabetes, body mass index, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglyceride, total cholesterol (TC), processed meat consumption, smoking, alcohol consumption, and educational attainment, whereas the effect of LBD on colon cancer was only influenced by TC. Colocalization and pathway enrichment analysis suggested that LBD and colon cancer possibly shared causal variants (nearby gene APOE), and ERBB4 signaling and lipid metabolism may mediate the causal association between LBD and colon cancer. Sensitivity analysis confirmed the reliability of our findings. ConclusionsOur study demonstrated that genetic vulnerabilities to AD nominally increased the overall risk of CRC and colon cancer. Genetically predicted LBD indicated an elevated risk of colon cancer, potentially linked to ERBB4 signaling and lipid metabolism.

Model-agnostic counterfactual reasoning for identifying and mitigating answer bias in knowledge tracing

Knowledge tracing (KT) aims to monitor students’ evolving knowledge states through their learning interactions with concept-related questions, and can be indirectly evaluated by predicting how students will perform on future questions. In this paper, we observe that there is a common phenomenon of answer bias, i.e., a highly unbalanced distribution of correct and incorrect answers for each question. Existing models tend to memorize the answer bias as a shortcut for achieving high prediction performance in KT, thereby failing to fully understand students’ knowledge states. To address this issue, we approach the KT task from a causality perspective. A causal graph of KT is first established, from which we identify that the impact of answer bias lies in the direct causal effect of questions on students’ responses. A novel COunterfactual REasoning (CORE) framework for KT is further proposed, which separately captures the total causal effect and direct causal effect during training, and mitigates answer bias by subtracting the latter from the former in testing. The CORE framework is applicable to various existing KT models, and we implement it based on the prevailing DKT, DKVMN, and AKT models, respectively. Extensive experiments on three benchmark datasets demonstrate the effectiveness of CORE in making the debiased inference for KT. We have released our code at https://github.com/lucky7-code/CORE.

Identification of lipid-modifying drug targets for autoimmune diseases: insights from drug target mendelian randomization

BackgroundsA growing body of evidence has highlighted the interactions of lipids metabolism and immune regulation. Nevertheless, there is still a lack of evidence regarding the causality between lipids and autoimmune diseases (ADs), as well as their possibility as drug targets for ADs.ObjectivesThis study was conducted to comprehensively understand the casual associations between lipid traits and ADs, and evaluate the therapeutic possibility of lipid-lowering drug targets on ADs.MethodsGenetic variants for lipid traits and variants encoding targets of various lipid-lowering drugs were derived from Global Lipid Genetics Consortium (GLGC) and verified in Drug Bank. Summary data of ADs were obtained from MRC Integrative Epidemiology Unit (MER-IEU) database and FinnGen consortium, respectively. The causal inferences between lipid traits/genetic agents of lipid-lowering targets and ADs were evaluated by Mendelian randomization (MR), summary data-based MR (SMR), and multivariable MR (MVMR) analyses. Enrichment analysis and protein interaction network were employed to reveal the functional characteristics and biological relevance of potential therapeutic lipid-lowering targets.ResultsThere was no evidence of causal effects regarding 5 lipid traits and 9 lipid-lowering drug targets on ADs. Genetically proxied 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) inhibition was associated with a reduced risk of rheumatoid arthritis (RA) in both discovery (OR [odds ratio] = 0.45, 95%CI: 0.32, 0.63, P = 6.79 × 10− 06) and replicate datasets (OR = 0.37, 95%CI: 0.23, 0.61, P = 7.81 × 10− 05). SMR analyses supported that genetically proxied HMGCR inhibition had causal effects on RA in whole blood (OR = 0.48, 95%CI: 0.29, 0.82, P = 6.86 × 10− 03) and skeletal muscle sites (OR = 0.75, 95%CI: 0.56, 0.99, P = 4.48 × 10− 02). After controlling for blood pressure, body mass index (BMI), smoking and drinking alchohol, HMGCR suppression showed a direct causal effect on a lower risk of RA (OR = 0.33, 95%CI: 0.40, 0.96, P = 0.042).ConclusionsOur study reveals causal links of genetically proxied HMGCR inhibition (lipid-lowering drug targets) and HMGCR expression inhibition with a decreased risk of RA, suggesting that HMGCR may serve as candidate drug targets for the treatment and prevention of RA.

Causal and common risk pathways linking childhood maltreatment to later intimate partner violence victimization.

Childhood maltreatment and intimate partner violence (IPV) victimization are major psychiatric risk factors. Maltreatment substantially increases the likelihood of subsequent IPV victimization, but what drives this association is poorly understood. We analyzed retrospective self-reports of maltreatment and IPV in 12794 participants (58% women, 42% men) from the Twins Early Development Study at ages 21 and 26 using quantitative genetic methods. We estimated the etiological influences common to maltreatment and IPV, and the direct causal effect of maltreatment on IPV beyond such common influences. Participants exposed to maltreatment (~7% of the sample) were 3 times more likely to experience IPV victimization than their peers at age 21, 4 times more likely at 26. The association between maltreatment and IPV was mostly due to environmental influences shared by co-twins (42-43%) and genetic influences (30-33%). The association between maltreatment and IPV was similar for women and men, but its etiology partly differed by sex. Maltreatment had a moderate-to-large effect on IPV in phenotypic models (β = 0.23-0.34), decreasing to a small-to-moderate range in causal models accounting for their common etiology (β = 0.15-0.21). Risk factors common to maltreatment and IPV victimization are largely familial in origin, environmental and genetic. Even considering common risk factors, experiencing maltreatment is causally related to subsequent IPV victimization. Interventions promoting safe intimate relationships among young adults exposed to maltreatment are warranted and should address family-level environmental risk and individual-level risk shaped by genetics.

Association between hyperuricemia and diabetic nephropathy: insights from the national health and nutrition examination survey 2007–2016 and mendelian randomization analysis

BackgroundThis study aimed to investigate the role of uric acid (UA) in diabetic nephropathy (DN) from epidemiological and genetic perspectives.MethodsWe used data from the 2007–2016 National Health and Nutrition Examination Survey to evaluate the relationship between UA and DN risk using weighted multivariate-adjusted logistic regression. Subsequently, a two-sample Mendelian randomization study was conducted using genome-wide association study summary statistics. The main inverse variance weighting (IVW) method and supplementary MR method were used to verify the causal relationship between UA and DN, and sensitivity analysis was conducted to confirm the credibility of the results.ResultsOur observational study enrolled 4363 participants with diabetes mellitus from NHANES, among them, 2682 (61.4%) participants were identified as DN. The multivariate logistic regression model showed that compared with those without hyperuricemia, the DN risk of the hyperuricemia population was significantly increased (P < 0.05). The MR results suggest a direct causal effect of hyperuricemia on DN (IVW odds ratio (OR): 1.37 (95% confidence interval 1.07–1.76); P = 0.01), which is consistent with findings from other MR methods.ConclusionThe evidence from observational studies indicates a positive correlation between HUA and the onset of DN. And the causal effects of HUA on DN were supported by the MR analysis.

Causal relationship between depression and hypercholesterolemia: A bidirectional 2-sample Mendelian randomization study.

Although observational studies have found both a positive and negative association between depression and hypercholesterolemia, the findings are mixed and contradictory. To our knowledge, this is the first study that employs the bidirectional Mendelian randomization (MR) and multivariable MR analysis with extensive genome-wide association studies (GWAS) data to examine the causal effect between depression and hypercholesterolemia. Using summary statistics obtained from GWAS of individuals with European ancestry, we utilize a bidirectional 2-sample MR approach to explore the potential causal association between hypercholesterolemia and depressive symptoms. Multivariable Mendelian randomization analysis was used to examine whether the direct causal effect of depression on the risk of hypercholesterolemia can be affected by traits associated with the increased risk of hypercholesterolemia. This MR analysis utilized inverse variance weighted (IVW), MR-Egger regression, weighted mode, and weighted median methods. Data on the summary level of depression were acquired from a GWAS that involved 500,199 participants. We used summary GWAS datasets for hypercholesterolemia including 206,067 participants. We also used another GWAS databases of hypercholesterolemiat (n = 463,010) to validate our results. By utilizing IVW, it was discovered that there is a possibility of a 31% rise in the risk of hypercholesterolemia due to depression (OR = 1.31, 95% CI = 1.10-1.57, P = .002). We found a consistent causal effect of depression on hypercholesterolemia from the IVW analyses using different hypercholesterolemia datasets. After adjustment of smoking, physical activity, and obesity, there remains significant causal relationship between depression and hypercholesterolemia (OR = 1.25, 95% CI = 1.01-1.54, P = .040). However, we did not find any evidence indicating that hypercholesterolemia leads to depression in the opposite direction. Directional pleiotropy was not observed in the MR-Egger regression analysis. Additionally, the MR-PRESSO analysis validated these discoveries. Neither the leave-one-out sensitivity test nor the funnel plots revealed any outliers. In both the unadjusted and adjusted estimates, depression has a consistent direct causal effect on hypercholesterolemia. Our study has led to an improved comprehension of the causal connections between hypercholesterolemia and depression, which could aid in the prevention and treatment of hypercholesterolemia.

Antidepressant treatment and mortality in people with comorbid depression and type 2 diabetes: UK electronic health record study.

Depression is associated with higher rates of premature mortality in people with physical comorbidities, such as type 2 diabetes. Conceptually, the successful treatment of depression in people with type 2 diabetes could prevent premature mortality. To investigate the association between antidepressant prescribing and the rates of all-cause and cause-specific (endocrine, cardiovascular, respiratory, cancer, unnatural) mortality in individuals with comorbid depression and type 2 diabetes. Using UK primary care records between years 2000 and 2018, we completed a nested case-control study in a cohort of people with comorbid depression and type 2 diabetes who were starting oral antidiabetic treatment for the first time. We used incident density sampling to identify cases who died and matched controls who remained alive after the same number of days observation. We estimated incidence rate ratios for the association between antidepressant prescribing and mortality, adjusting for demographic characteristics, comorbidities, medication use and health behaviours. We included 5222 cases with a recorded date of death, and 18 675 controls, observed for a median of 7 years. Increased rates of all-cause mortality were associated with any antidepressant prescribing during the observation period (incidence rate ratio 2.77, 95% CI 2.48-3.10). These results were consistent across all causes of mortality that we investigated. Antidepressant prescribing was highly associated with higher rates of mortality. However, we suspect that this is not a direct causal effect, but that antidepressant treatment is a marker of more severe and unsuccessfully treated depression.

Identifiability of Direct Effects from Summary Causal Graphs

Dynamic structural causal models (SCMs) are a powerful framework for reasoning in dynamic systems about direct effects which measure how a change in one variable affects another variable while holding all other variables constant. The causal relations in a dynamic structural causal model can be qualitatively represented with an acyclic full-time causal graph. Assuming linearity and no hidden confounding and given the full-time causal graph, the direct causal effect is always identifiable. However, in many application such a graph is not available for various reasons but nevertheless experts have access to the summary causal graph of the full-time causal graph which represents causal relations between time series while omitting temporal information and allowing cycles. This paper presents a complete identifiability result which characterizes all cases for which the direct effect is graphically identifiable from a summary causal graph and gives two sound finite adjustment sets that can be used to estimate the direct effect whenever it is identifiable.

De-biased Attention Supervision for Text Classification with Causality

In text classification models, while the unsupervised attention mechanism can enhance performance, it often produces attention distributions that are puzzling to humans, such as assigning high weight to seemingly insignificant conjunctions. Recently, numerous studies have explored Attention Supervision (AS) to guide the model toward more interpretable attention distributions. However, such AS can impact classification performance, especially in specialized domains. In this paper, we address this issue from a causality perspective. Firstly, we leverage the causal graph to reveal two biases in the AS: 1) Bias caused by the label distribution of the dataset. 2) Bias caused by the words' different occurrence ranges that some words can occur across labels while others only occur in a particular label. We then propose a novel De-biased Attention Supervision (DAS) method to eliminate these biases with causal techniques. Specifically, we adopt backdoor adjustment on the label-caused bias and reduce the word-caused bias by subtracting the direct causal effect of the word. Through extensive experiments on two professional text classification datasets (e.g., medicine and law), we demonstrate that our method achieves improved classification accuracy along with more coherent attention distributions.

Genetic confounding in the association of early motor development with childhood and adolescent exercise behavior

IntroductionEarly motor development has been found to be a predictor of exercise behavior in children and adolescents, but whether this reflects a causal effect or confounding by genetic or shared environmental factors remains to be established.MethodsFor 20,911 complete twin pairs from the Netherlands Twin Register a motor development score was obtained from maternal reports on the timing of five motor milestones. During a 12-year follow-up, subsamples of the mothers reported on the twins’ ability to perform seven gross motor skills ability (N = 17,189 pairs), and weekly minutes of total metabolic equivalents of task (MET) spent on sports and exercise activities at age 7 (N = 3632 pairs), age 10 (N = 3735 pairs), age 12 (N = 7043 pairs), and age 14 (N = 3990 pairs). Multivariate phenotypic and genetic regression analyses were used to establish the predictive strength of the two motor development traits for future exercise behavior, the contribution of genetic and shared environmental factors to the variance in all traits, and the contribution of familial confounding to the phenotypic prediction.ResultsSignificant heritability (h2) and shared environmental (c2) effects were found for early motor development in boys and girls (h2 = 43-65%; c2 = 16-48%). For exercise behavior, genetic influences increased with age (boys: h2age7 = 22% to h2age14 = 51%; girls: h2age7 = 3% to h2age14 = 18%) paired to a parallel decrease in the influence of the shared environment (boys: c2age7 = 68% to c2age14 = 19%; girls: c2age7 = 80% to c2age14 = 48%). Early motor development explained 4.3% (p < 0.001) of the variance in future exercise behavior in boys but only 1.9% (p < 0.001) in girls. If the effect in boys was due to a causal effect of motor development on exercise behavior, all of the factors influencing motor development would, through the causal chain, also influence future exercise behavior. Instead, only the genetic parts of the regression of exercise behavior on motor development were significant. Shared and unique environmental parts of the regression were largely non-significant, which is at odds with the causal hypothesis.ConclusionNo support was found for a direct causal effect in the association between rapid early motor development on future exercise behavior. In boys, early motor development appears to be an expression of the same genetic factors that underlie the heritability of childhood and early adolescent exercise behavior.

Causal relationship between feelings and cognitive decline: An univariable and multivariable Mendelian randomization study.

While the impact of depression on cognition is well-documented, the relationship between feelings and cognition has received limited attention. To explore the potential association between feelings and cognition with a two-sample Mendelian randomization (MR) analysis. Our analysis utilized genome-wide association data on various feelings (fed-up feelings, n = 453071; worrier/anxious feelings, n = 450765; guilty feelings, n = 450704; nervous feelings, n = 450700; sensitivity/hurt feelings, n = 449419; miserableness, n = 454982; loneliness/isolation, n = 455364; happiness, n = 152348) in the European population and their impact on cognitive functions (intelligence, n = 269867). Conducting a univariable MR (UVMR) analysis to assess the relationship between feelings and cognition. In this analysis, we applied the inverse variance weighting (IVW), weighted median, and MR Egger methods. Additionally, we performed sensitivity analysis (leave-one-out analysis), assessed heterogeneity (using MR-PRESSO and Cochran's Q test), and conducted multiple validity test (employing MR-Egger regression). Subsequently, a multivariable MR (MVMR) analysis was employed to examine the impact of feelings on cognition. IVW served as the primary method in the multivariable analysis, complemented by median-based and MR-Egger methods. In this study, UVMR indicated that sensitivity/hurt feelings may have a negative causal effect on cognition (OR = 0.63, 95%CI: 0.43-0.92, P = 0.017). After adjustment of other feelings using MVMR, a direct adverse causal effect on cognition was observed (ORMVMR = 0.39, 95%CI: 0.17-0.90, PMVMR = 0.027). While a potential increased risk of cognitive decline was observed for fed-up feelings in the UVMR analysis (ORUVMR = 0.64, 95%CI: 0.42-0.97, PUVMR = 0.037), this effect disappeared after adjusting for other feelings (ORMVMR = 1.42, 95%CI: 0.43-4.74, PMVMR = 0.569). These findings were generally consistent across MV-IVW, median-based, and MR-Egger analyses. MR-Egger regression revealed pleiotropy in the impact of worrier/anxious feelings on cognition, presenting a challenge in identifying the effect. Notably, this study did not demonstrate any significant impact of guilty feelings, nervous feelings, miserableness, or loneliness/isolation on cognition. Due to a limited number of instrumental variables for happiness, this study was unable to analyze the relationship between happiness and cognition. This MR study finds that sensitivity/hurt feelings are associated with cognitive decline, while the link between worrier/anxious feelings and cognition remains inconclusive. Insufficient evidence supports direct associations between happiness, guilty feelings, nervous feelings, miserableness, loneliness/isolation, and cognition.

Association and mediation between educational attainment and respiratory diseases: a Mendelian randomization study

BackgroundRespiratory diseases are a major health burden, and educational inequalities may influence disease prevalence. We aim to evaluate the causal link between educational attainment and respiratory disease, and to determine the mediating influence of several known modifiable risk factors.MethodsWe conducted a two-step, two-sample Mendelian randomization (MR) analysis using summary statistics from genome-wide association studies (GWAS) and single nucleotide polymorphisms (SNPs) as instrumental variables for educational attainment and respiratory diseases. Additionally, we performed a multivariable MR analysis to estimate the direct causal effect of each exposure variable included in the analysis on the outcome, conditional on the other exposure variables included in the model. The mediating roles of body mass index (BMI), physical activity, and smoking were also assessed.FindingsMR analyses provide evidence of genetically predicted educational attainment on the risk of FEV1 (β = 0.10, 95% CI 0.06, 0.14), FVC (β = 0.12, 95% CI 0.07, 0.16), FEV1/FVC (β = − 0.005, 95% CI − 0.05, 0.04), lung cancer (OR = 0.54, 95% CI 0.45, 0.65) and asthma (OR = 0.86, 95% CI 0.78, 0.94). Multivariable MR dicated the effect of educational attainment on FEV1 (β = 0.10, 95% CI 0.04, 0.16), FVC (β = 0.07, 95% CI 0.01, 0.12), FEV1/FVC (β = 0.07, 95% CI 0.01, 0.01), lung cancer (OR = 0.55, 95% CI 0.42, 0.71) and asthma (OR = 0.88, 95% CI 0.78, 0.99) persisted after adjusting BMI and cigarettes per day. Of the 23 potential risk factors, BMI, smoking may partially mediate the relationship between education and lung disease.ConclusionHigh levels of educational attainment have a potential causal protective effect on respiratory diseases. Reducing smoking and adiposity may be a target for the prevention of respiratory diseases attributable to low educational attainment.

Estimating the direct effects of the genetic liabilities to bipolar disorder, schizophrenia, and behavioral traits on suicide attempt using a multivariable Mendelian randomization approach.

Bipolar disorder (BD) and schizophrenia (SZ) are associated with higher odds of suicide attempt (SA). In this study, we aimed to explore the effect of BD and SZ genetic liabilities on SA, also considering the contribution of behavioral traits, socioeconomic factors, and substance use disorders. Leveraging large-scale genome-wide association data from the Psychiatric Genomics Consortium (PGC) and the UK Biobank (UKB), we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the putative causal effect of BD (41,917 cases, 371,549 controls) and SZ (53,386 cases, 77,258 controls) on SA (26,590 cases, 492,022 controls). Then, we assessed the putative causal effect of BD and SZ on behavioral traits, socioeconomic factors, and substance use disorders. Considering the associations identified, we evaluated the direct causal effect of behavioral traits, socioeconomic factors, and substance use disorders on SA using a multivariable MR approach. The genetic liabilities to BD and SZ were associated with higher odds of SA (BD odds ratio (OR) = 1.24, p = 3.88 × 10-12; SZ OR = 1.09, p = 2.44 × 10-20). However, while the effect of mental distress (OR = 1.17, p = 1.02 × 10-4) and risk-taking (OR = 1.52, p = 0.028) on SA was independent of SZ genetic liability, the BD-SA relationship appeared to account for the effect of these risk factors. Similarly, the association with loneliness on SA was null after accounting for the effect of SZ genetic liability. These findings highlight the complex interplay between genetic risk of psychiatric disorders and behavioral traits in the context of SA, suggesting the need for a comprehensive mental health assessment for high-risk individuals.

The predictive effect of family genetic risk scores as an indirect measure of causal effects of one disorder on another.

One potential cause of comorbidity is the direct causal effect of one disorder - A - on risk for subsequent onset of disorder B. Could genetic risk scores be utilized to test for such an effect? If disorder A causally impacts on risk for disorder B, then genetic risk for disorder A should be lower in cases of disorder A with v. without a prior onset of B. In all individuals (n = 905 736) born in Sweden from 1980 to 1990, from six psychiatric and drug use disorders (major depression, anxiety disorders, alcohol use disorder, drug use disorder, bipolar disorder, and schizophrenia), we formed 14 pairs of disorders A and B. In these pairs, we compared, using Cox proportional hazards models, the predictive effect of the familial-genetic risk score (FGRS) for disorder B in those who had v. had not had a prior onset of disorder A. In all pairs, the impact of the FGRS for disorder B was significantly stronger in cases without v. with a prior history of disorder A. These effects were similar across sex, stable across levels of FGRS and not likely due to clinician bias. In many of our disorder pairs, previous clinical studies suggest a mechanism for a causal effect of disorder A on B. Our findings provide indirect evidence that the occurrence of one psychiatric or substance use disorder often has a causal effect on risk for subsequent disorders. This mechanism may substantially contribute to the widespread comorbidity among psychiatric conditions.