Causal Effect Research Articles

Weighting methods for truncation by death in cluster-randomized trials.

Patient-centered outcomes, such as quality of life and length of hospital stay, are the focus in a wide array of clinical studies. However, participants in randomized trials for elderly or critically and severely ill patient populations may have truncated or undefined non-mortality outcomes if they do not survive through the measurement time point. To address truncation by death, the survivor average causal effect has been proposed as a causally interpretable subgroup treatment effect defined under the principal stratification framework. However, the majority of methods for estimatingthe survivor average causal effect have been developed in the context of individually randomized trials. Only limited discussions have been centered around cluster-randomized trials, where methods typically involve strong distributional assumptions for outcome modeling. In this article, we propose two weighting methods to estimatethe survivor average causal effect in cluster-randomized trials that obviate the need for potentially complicated outcome distribution modeling. We establish the requisite assumptions that address latent clustering effects to enable point identification of thesurvivor average causal effect, and we provide computationally efficient asymptotic variance estimators for each weighting estimator. In simulations, we evaluate our weighting estimators, demonstrating their finite-sample operating characteristics and robustness to certain departures from the identification assumptions. We illustrate our methods using data from a cluster-randomized trial to assess the impact of a sedation protocol on mechanical ventilation among children with acute respiratory failure.

Combining Single-Cell RNA Sequencing and Mendelian Randomization to Explore Novel Drug Targets for Parkinson's Disease.

Neuroinflammation is a key pathological factor of PD, and T cells play a central role in neuroinflammatory progression. However, the causal effect of T cell-related genes on the risk of PD is still unclear. We explored single-cell RNA sequencing (scRNA-Seq) datasets of the peripheral blood T cells of PD patients and healthy controls, and screened the differentially expressed genes (DEGs) in the cytotoxic CD4 + T cells relative to the other T cell subsets. Pseudo-time series analysis, cell-cell communication analysis, and metabolic pathway analysis was performed for the cytotoxic CD4 + T cells. The DEGs were also functionally annotated through GO and KEGG pathway enrichment analyses. The MR approach was used to establish causal effects of the DEGs (exposure) on PD risk (outcome), and explore new drug targets for PD. The findings of MR analysis were further validated by Steiger filtering, bidirectional MR, Bayesian colocalization analysis, and phenotype scanning, and the GWAS data from an independent PD case-control cohort was used for external validation of the results. Finally, differences in gene expression between PD patients and healthy controls were further validated in scRNA-Seq and bulk transcriptome sequencing data. We found that increased expression of IL-32, GNLY, MT2A, and ARPC2 was significantly associated with a higher risk of PD. In contrast, the increase in ARRB2 was closely related to a lower risk of PD. IL32, GNLY, MT2A, ARRB2, and ARPC2 are the causal genes and potential drug targets of PD. Cytotoxic CD4 + T cells are likely the key effectors of PD-related neuroinflammation. These findings provide new insights into the pathogenesis and treatment options for PD, and further research and clinical trials based on the five potential drug targets and neuroinflammation are necessary.

Measuring China’s Policy Stringency on Climate Change for 1954–2022

Efforts on climate change have demonstrated tangible impacts through various actions and policies. However, a significant knowledge gap remains: comparing the stringency of climate change policies over time or across jurisdictions is challenging due to ambiguous definitions, the lack of a unified assessment framework, complex causal effects, and the difficulty in achieving effective measurement. Furthermore, China’s climate governance is expected to address multiple objectives by integrating main effects and side effects, to achieve synergies that encompass environmental, economic, and social impacts. This paper employs an integrated framework comprising lexicon, text analysis, machine learning, and large-language model applied to multi-source data to quantify China’s policy stringency on climate change (PSCC) from 1954 to 2022. To achieve effective, robust, and explainable measurement, Chain-of-Thought and SHAP analysis are integrated into the framework. By framing the PSCC on varied sub-dimensions covering mitigation, adaptation, implementation, and spatial difference, this dataset maps the government’s varied stringency on climate change and can be used as a robust variable to support a series of downstream causal analysis.

Higher-order motivational constructs as personal-level fictions: A solution in search of a problem.

I argue that Murayama and Jach's claim that higher-order motivational constructs face the "black-box" problem is misconceived because it doesn't clearly distinguish between personal and subpersonal explanations. To solve it they propose interpreting motivations as causal effects of mental computational processes. I suggest that their solution might be more compellingly presented as providing a fictionalist perspective on some personal-level constructs.

Diagnostic changes in a specialized psychiatric outpatient clinic for migrants: An observational study.

Culture significantly influences the understanding, presentation, diagnosis, and treatment of mental disorders, particularly among migrant patients. This observational study examines the frequency and timing of diagnostic changes among migrant patients in a specialized psychiatric outpatient clinic. Furthermore, the study includes a qualitative sub-study to provide insights into the diagnostic process. Out of the 119 migrant patients included in the study, 27.7% changed referral diagnoses during treatment. Diagnostic changes occurred in 15.7% of cases by the end of treatment, 13.4% at midterm, and 9.1% after the initial assessment. No significant associations were found between diagnostic changes and sociodemographic or treatment-related factors. While the qualitative sub-study primarily offered broader insights into the cultural aspects of treatment and the clinical encounter, rather than establishing causal effects on the diagnostic process, it revealed how acculturative stress and cultural identity influenced the presentation of symptoms. The study is conducted in a real-life clinical setting and, thus, reflects the everyday clinical practice of diagnostic changes at a specialized cultural psychiatric clinic. The findings from this study indicate that in addition to a culturally sensitive assessment, time is an important factor for diagnostic changes, which can be essential knowledge for clinical practice when planning diagnostic assessment and treatment. The findings underscore the need for enhancing clinicians' cultural competencies through targeted training, emphasizing cultural awareness in clinical practice.

Gut microbiota, inflammatory cytokines and gastro-esophageal reflux disease: A Mendelian randomization analysis.

Gut microbiota has been recognized as an extrahepatic manifestation of gastro-esophageal reflux disease (GERD) in observational studies. However, the directionality and causality of the association and whether cytokines act as a mediator remain unclear. We aim to estimate the casual relationship between gut microbiota, inflammatory cytokines and GERD using a 2-sample Mendelian randomization method. Gut microbiota, cytokines, and GERD were identified using summary data from the genome-wide association studies and the FinnGen consortium. The primary method for causal estimation was the inverse-variance weighted approach, complemented by a range of sensitivity analyses aimed at assessing heterogeneity, horizontal pleiotropy, and the robustness of the findings. Furthermore, mediation analysis was conducted to evaluate the association between gut microbiota and GERD, with 5 cytokines, and to calculate the mediated proportions. We found 3 positive and 3 negative causal associations observed between genetic predisposition in gut microbiota and GERD. Additionally, 2 positive and 3 negative causal associations were identified between cytokines and GERD. Our analysis unveiled that TNF-related apoptosis-inducing ligand levels (TRAIL) mediated the causal relationships between the genera Family XIII UCG001 and Senegalimassilia, and GERD. We identified causal effects between 6 bacterial traits, 5 inflammatory cytokines, and GERD. Notably, we furnished causal evidence linking TRAIL levels to a substantial proportion of the risk attributed to genus Family XIII UCG001 and genus Senegalimassilia, thereby mediating the risk of GERD. These findings offer novel avenues for therapeutic interventions targeting individuals with GERD.

Effect of weight loss following Roux-en-Y gastric bypass on cancer risk: A Mendelian randomization study.

Cancer incidence and development are strongly correlated with obesity, however there is insufficient data to support a causal relationship between intentional weight loss and the prevention or promotion of cancer. We investigated the causal relationship between weight loss following Roux-en-Y gastric bypass (RYGB) and the incidence of 18 cancers using Mendelian randomization (MR). A genome-wide association studies (GWAS) data related to weight loss following RYGB from the GWAS catalog database were used as exposure, and GWAS data related to 18 cancers from the Medical Research Council integrative epidemiology unit open GWAS project were used as outcomes. In order to investigate the causal relationship between exposure and results, we used a two-sample MR approach. The primary analysis technique was inverse variance weighting, with weighted median, and MR-Egger regression utilized as supplemental techniques to confirm the findings. Heterogeneity and horizontal pleiotropy were investigated using a variety of sensitivity studies, including the Cochran Q test, MR-Egger regression pleiotropy test, MR pleiotropy residual sum and outlier, and leave-one-out analysis. We included a total of 4 single-nucleotide polymorphisms as instrumental variables through rigorous quality control screening. Under the limitations of Bonferroni correction threshold (P < 2.78 × 10-3), our results suggest that the weight loss following RYGB has a significant causal relationship with a reduced risk of breast (odds ratio [OR]: 0.784; 95% confidence interval [CI]: 0.762-0.808; P = 2.167e-58) and lung cancer (OR: 0.992; 95% CI: 0.987-0.997; P = .0023), and a potential causal relationship with a decreased risk of hematological cancer (OR: 0.9998462; 95% CI: 0.9997088-0.9999836; P = .028) and an increased risk of cervical cancer (OR: 1.000123; 95% CI: 1.0000313-1.000215; P = .009). Sensitivity analysis confirms the robustness of our analysis results. Genetically predicted weight loss following RYGB has significant causal effects in reducing the risk of breast and lung cancer. It also has potential benefits in lowering the risk of hemotological cancers and increasing the risk of cervical cancer. Considering the limitations of our study, the reliability of its results and the underlying mechanisms require further investigation.

Emotion malleability beliefs prompt cognitive reappraisal: evidence from an online longitudinal intervention for adolescents

ABSTRACT Emotion malleability beliefs (EMB) have been shown to be a potential predictor of cognitive reappraisal use. However, the nature of the relationship between EMB and cognitive reappraisal use remains unclear. The present study manipulated EMB with an online intervention and measured participants’ EMB and cognitive reappraisal before the intervention as well as at three follow-ups. Eighty-six late adolescents who scored in the bottom 50% on EMB in a previous investigation were randomly assigned to the intervention group (increasing EMB) and the control group. The intervention significantly increased EMB, and this effect remained one week and one month after the intervention. More importantly, the results showed that the lag paths from a previous measure of EMB on later cognitive reappraisal were positive and significant. The cross-lagged paths from cognitive reappraisal to EMB were not significant. The intervention to increase EMB showed significant indirect effects on cognitive reappraisal via EMB. The findings not only support that the intervention of EMB had a sustained effect but also evidenced that EMB had a causal effect on cognitive reappraisal. This suggests a promising way to enhance cognitive reappraisal for application in the treatment of clinical emotion disorders.

Firm environment and employee’s crime rate: evidence from Denmark

ABSTRACT We study the effect of the firm’s crime environment on individual crime rates. Using Danish registry data, we show the effects of individuals moving between high-crime (HC) and low-crime (LC) environments. We use a difference-in-difference estimator and mass layoffs to identify (statistically) causal effects. Individuals moving from high to low-crime firms experience a small but statistically significant decrease in crime rates. Analogously, individuals moving from low to high-crime firms experience a low but statistically significant increase in crime rates.

Role of Immune Cells in Mediating the Causal Effect of Gut Microbiota on Type 2 Diabetes.

Previous studies have suggested that gut microbiota and immune system regulation have potential links with type 2 diabetes (T2D). However, the causal association between gut microbiota and T2D and whether immune cells mediate this interaction is unclear. A two-sample, two-step Mendelian randomization (MR) study utilizing an initial inverse-variance weighted (IVW) method was performed to explore the causal impact of gut microbiota on T2D and the intermediary role of immune cells. The MR analysis assigned 4 gut microbiota and metabolic pathways that increase the risk of T2D (G_Prevotella, g_Anaerotruncus, g_Streptococcus.s_ Streptococcus_parasanguinis, and the pathway of PANTO-PWY) and 4 other gut microbiota and metabolic pathways that have a protective effect against T2D (PWY5667, PWY-6892, PWY-7221, and the bacterial g_Paraprevotella.s_Paraprevotella_ clara). Furthermore, 17 immune cell traits have been identified as associated with T2D. The finding from mediation MR analysis revealed that PANTO-PWY increases T2D risk via CD3 on HLA DR+ CD4+, whereas PWY-7221 reduces T2D risk through CD4 on CD4 Treg. The research reveals a mediated causal link between the gut microbiota and T2D via immune cells.

Exploring the role of circulating proteins in multiple myeloma risk: a Mendelian randomization study

Multiple myeloma (MM) is an incurable blood cancer with unclear aetiology. Proteomics is a valuable tool in exploring mechanisms of disease. We investigated the causal relationship between circulating proteins and MM risk, using two of the largest cohorts with proteomics data to-date. We performed bidirectional two-sample Mendelian randomization (MR; forward MR = causal effect estimation of proteins and MM risk; reverse MR = causal effect estimation of MM risk and proteins). Summary statistics for plasma proteins were obtained from genome-wide association studies performed using SomaLogic (N = 35,559; deCODE) and Olink (N = 34,557; UK Biobank; UKB) proteomic platforms and for MM risk from a meta-analysis of UKB and FinnGen (case = 1649; control = 727,247) or FinnGen only (case = 1085; control = 271,463). Cis-SNPs associated with protein levels were used to instrument circulating proteins. We evaluated proteins for the consistency of directions of effect across MR analyses (with 95% confidence intervals not overlapping the null) and corroborating evidence from genetic colocalization. In the forward MR, 994 (SomaLogic) and 1570 (Olink) proteins were instrumentable. 440 proteins were analysed in both deCODE and UKB; 302 (69%) of these showed consistent directions of effect in the forward MR. Seven proteins had 95% confidence intervals (CIs) that did not overlap the null in both forward MR analyses and did not have evidence for an effect in the reverse direction: higher levels of dermatopontin (DPT), beta-crystallin B1 (CRYBB1), interleukin-18-binding protein (IL18BP) and vascular endothelial growth factor receptor 2 (KDR) and lower levels of odorant-binding protein 2b (OBP2B), glutamate-cysteine ligase regulatory subunit (GCLM) and gamma-crystallin D (CRYGD) were implicated in increasing MM risk. Evidence from genetic colocalization did not meet our threshold for a shared causal signal between any of these proteins and MM risk (h4 < 0.8). Our results highlight seven circulating proteins which may be involved in MM risk. Although evidence from genetic colocalization suggests these associations may not be robust to the effects of horizontal pleiotropy, these proteins may be useful markers of MM risk. Future work should explore the utility of these proteins in disease prediction or prevention using proteomic data from patients with MM or precursor conditions.

Causal associations between immune cells and psychiatric disorders: a bidirectional mendelian randomization analysis.

Extensive researches illuminate a potential interplay between immune traits and psychiatric disorders. However, whether there is the causal relationship between the two remains an unresolved question. We conducted a two-sample bidirectional mendelian randomization by utilizing summary data of 731 immune cell traits from genome-wide association studies (GCST90001391-GCST90002121)) and 11 psychiatric disorders including attention deficit/hyperactivity disorder (ADHD), anxiety disorder, autism spectrum disorder (ASD), bipolar disorder (BIP), anorexia nervosa (AN), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), Tourette syndrome (TS), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), and substance use disorders (cannabis) (SUD) from the Psychiatric Genomics Consortium (PGC). A total of four types of immune signatures (median fluorescence intensities [MFI], relative cell [RC], absolute cell [AC], and morphological parameters [MP]) were included. Effect estimates were obtained by using the inverse-variance-weighted (IVW), weighted median method, Mendelian randomization (MR)-Egger, and corrected by false discovery rate. Outliers were evaluated through the leave-one-out technique. Horizontal pleiotropy was assessed using the MR pleiotropy residual sum and outlier (MR-PRESSO) and MR-Egger intercept tests. MR analysis results suggested several immune cell subtypes were casually associated with psychiatric disorders. It was found that CD33br HLA DR + CD14 - AC (Myeloid cell, AC) may contribute to decreasing the risk of BIP (odds ratio [OR] = 0.9179, confidence interval [CI] = 0.8829-0.9542, PFDR = 7.06 × 10-3), and likewise, CD38 on transitional (B cell, MFI) also showed negative causal effect on SCZ risk (OR = 0.9551, CI = 0.9330-0.9776, PFDR = 0.0441). While IgD - CD27 - %lymphocyte (B cell, RC) has causal effect on increasing BIP risk (OR = 1.0184, CI = 1.0079-1.0291, PFDR = 0.0201). In addition, HLA DR + + monocyte %monocyte (TBNK, RC) is likely to increase AN onset (OR = 1.0746, CI = 1.0324-1.1186, PFDR = 0.0506), and CCR2 on CD14 - CD16 + monocyte (Monocyte, MFI) may contribute to PTSD (OR = 1.0591, CI = 1.0275-1.0917, PFDR = 0.0369). Sensitivity analysis revealed consistency of results. Our research elucidates there may be causal links between immune traits and the onset of psychiatric disorders, which established a groundwork for the prospective clinical utilization of immune cells as markers for the diagnosis and early intervention of psychiatric disorders.

Causal Relationship Between Psoriasis and Bullous Pemphigoid: A Mendelian Randomization Analysis

Introduction: Psoriasis and bullous pemphigoid (BP) are the 2 major types of immune-mediated inflammatory skin diseases. Studies have reported the association between psoriasis and BP; however, no studies reported whether a causal relationship exists between these 2 skin diseases. Objectives: In order to explore the causal relationship between psoriasis and BP, we performed a bidirectional two-sample Mendelian randomization (MR) study. Methods: Genome-wide association study (GWAS) data related to psoriasis and BP were collected. The inverse variance weighted (IVW) method was primarily applied for our MR analysis, MR-Egger, weighted median, simple mode, and weighted mode methods were used additionally. Heterogeneity, horizontal pleiotropy, and potential outliers were assessed for the MR analysis results. Results: GWAS data for psoriasis (3 cohorts) and BP (1 cohort) from publicly available trials were selected. Our MR results showed that psoriasis was causally associated with BP, psoriasis could increase the risk of BP, reversed MR showed BP has no causal effect on psoriasis. No heterogeneity or pleiotropy was detected. Conclusion: These findings provided new evidence of the causal relationship between psoriasis and BP, our MR suggested that psoriasis is potentially causal to BP, which help us improving the treatment strategy for patients with psoriasis. The mechanism remains open for further investigation.

Genome-wide aggregated trans- effects analysis identifies genes encoding immune checkpoints as core genes for rheumatoid arthritis.

The sparse effector "omnigenic" hypothesis postulates that the polygenic effects of common SNPs on a typical complex trait are mediated by trans- effects that coalesce on expression of a relatively sparse set of core genes. The objective of this study was to identify core genes for rheumatoid arthritis by testing for association of rheumatoid arthritis with genome-wide aggregated trans- effects (GATE) scores for expression of each gene as transcript in whole blood or as circulating protein levels. GATE scores were calculated for 5400 cases and 453705 non-cases of primary rheumatoid arthritis in UK Biobank participants of European ancestry. Testing for association with GATE scores identified 16 putative core genes for rheumatoid arthritis outside the HLA region, of which six - TP53BP1, PDCD1, TNFRSF14, LAIR1, LILRA4, and IDO1 - were supported by Mendelian randomization analysis based on the marginal likelihood of the causal effect parameter. Five of these 16 genes were validated by a reported association of rheumatoid arthritis with SNPs within 200 kb of the transcription site, 8 by association of the measured protein level with rheumatoid arthritis in UK Biobank, 10 by experimental perturbation in mouse models of inflammatory arthritis, and two - CTLA4 and PDCD1 - by evidence that drugs targeting the gene cause or ameliorate inflammatory arthritis in humans. 14 of these 16 genes are in pathways affecting immunity or inflammation and six - CD5, CTLA4, TIGIT, LAIR1, TNFRSF14, PDCD1 - encode receptors that have been characterized as immune checkpoints exploited by cancer cells to escape the immune response. These results highlight the key role of immune checkpoints in rheumatoid arthritis and identify possible therapeutic targets.

Causal Impacts of Psychiatric Disorders on Cognition and the Mediating Effect of Oxidative Stress: A Mendelian Randomization Study

Many psychiatric disorders are associated with major cognitive deficits. However, it is uncertain whether these deficits develop as a result of psychiatric disorders and what shared risk factors might mediate this relationship. Here, we utilized the Mendelian randomization (MR) analysis to investigate the complex causal relationship between nine major psychiatric disorders and three cognitive phenotypes, while also examining the potential mediating role of oxidative stress as a shared biological underpinning. Schizophrenia (SZ), major depressive disorder (MDD), and attention deficit hyperactivity disorder (ADHD) showed a decreasing effect on cognitive performance, intelligence, and education, while bipolar disorder (BPD) increased educational attainment. MR-Clust results exhibit the shared genetic basis between SZ and other psychiatric disorders in relation to cognitive function. Furthermore, when oxidative stress was considered as a potential mediating factor, the associations between SZ and the three dimensions of cognition, as well as between MDD and intelligence and ADHD and intelligence, exhibited larger effect sizes than the overall. Mediation MR analysis also supported the causal effects between psychiatric disorders and cognition via oxidative stress traits, including carotene, vitamin E, bilirubin, and uric acid. Finally, summary-based MR identified 29 potential causal associations of oxidative stress genes with both cognitive performance and psychiatric disorders. Our findings highlight the importance of considering oxidative stress in understanding and potentially treating cognitive impairments associated with psychiatric conditions.

The Hidden Value of Adult Informal Care in Europe.

The hidden value of adult informal care (IC) refers to the unaccounted value of informal care in overall costs of long-term care (LTC) estimates. This paper estimates the net value of adult IC in Europe, drawing on a well-being-based methodology. We use an instrumental variable strategy and a longitudinal and cross-country dataset to estimate the causal effect of the extensive and intensive margin of caregiving on subjective well-being. We estimate the so-called compensating surplus (CS), namely the income equivalent transfer, to compensate for the net disutility of caregiving. We show that IC reduces average subjective well-being by about 1% compared to the mean (6% among co-residential caregivers). Relative to a country's Gross Domestic Product (GDP), the value of IC ranges between 4.2% in France and 0.85% in Germany. Such relative value declines as the country's share of formal LTC spending increases. These results call for a reconsideration of the existing classifications of LTC regimes. We estimate that the average CS per hour for IC is 9.55€, with a range from 22€ per hour in Switzerland to 5€ per hour in Spain. Additionally, we estimate that the long-term CS (estimated using an individual's permanent income) tends to be lower than short-term CS (estimated using an individual's current income).

Genetic Evidence for Causal Effects of circulating remnant lipid profile on cerebral hemorrhage and ischemic stroke: A Mendelian Randomization Study.

Mendelian randomization was employed to investigate the impact of circulating lipids, specifically residual lipids, on the risk of susceptibility to cerebral hemorrhage and ischemic stroke. According to previously studies, we chose 19 circulating lipids, comprising 6 regular lipids and 13 residual lipids, to investigate their potential causal relationship with intracranial hemorrhage and ischemic stroke. The effect estimates were computed utilizing the random-effects inverse-variance-weighted methodology. The findings revealed negative correlations between HDL-C and cerebral hemorrhage and large artery stroke. HDL-C, Apo A1, XS.VLDL.TG, and IDL.TG were found to be negatively correlated with any ischemic stroke. Apo B, TG, LDL-C, L.VLDL-TG, M.VLDL-TG, and S.VLDL-TG exhibited positive correlations with large artery stroke. XL.HDL-TG and IDL.TG were positively correlated with cardioembolic stroke. No significant causal relationship was observed between circulating lipids, with the exception of HDL-C, and cerebral hemorrhage. No causal relationship was identified between any circulating lipids and small vessel stroke. Furthermore, the causal relationships were only found between residual lipids and ischemic stroke. This study provides evidence for the beneficial impact of Apo A1 and HDL-C in reducing the risk of ischemic stroke, as well as the protective effect of HDL-C against cerebral hemorrhage. It highlights the detrimental effects of Apo B, TG, and LDL-C in increasing the risk of ischemic stroke, particularly in cases of large artery stroke. Furthermore, the study underscores the heterogeneity and two-sided effects of the causal relationship between triglyceride-rich lipoproteins and ischemic stroke, offering a promising avenue for the treatment of ischemic stroke.

Design of Partial Population Experiments with an Application to Spillovers in Tax Compliance

Abstract We develop a framework to analyze partial population experiments, a generalization of the cluster experimental design where clusters are assigned to different treatment intensities. Our framework allows for heterogeneity in cluster sizes and outcome distributions. We study the large-sample behavior of OLS estimators and cluster-robust variance estimators and show that (i) ignoring cluster heterogeneity may result in severely underpowered experiments and (ii) the cluster-robust variance estimator may be upward-biased when clusters are heterogeneous. We derive formulas for power, minimum detectable effects, and optimal cluster assignment probabilities. All our results apply to cluster experiments, a particular case of our framework. We set up a potential outcomes framework to interpret the OLS estimands as causal effects. We implement our methods in a large-scale experiment to estimate the direct and spillover effects of a communication campaign on property tax compliance. We find an increase in tax compliance among individuals directly targeted with our mailing, as well as compliance spillovers on untreated individuals in clusters with a high proportion of treated taxpayers.

Mendelian randomization analysis reveals genetic evidence for a causal link between inflammatory bowel disease and uterine cervical neoplasms

BackgroundInflammatory bowel disease (IBD) has been reported to be associated with risk of uterine cervical neoplasm. We aimed to evaluate the causal relationship between IBD and uterine cervical neoplasm using a bidirectional Mendelian randomization analysis.MethodsWe derived instrumental variables for IBD, including Crohn’s disease and ulcerative colitis, from the IEU Open genome-wide association study (GWAS) database, and for the histological subtypes of uterine cervical neoplasm from the FinnGen repository’s GWAS data. The collected GWAS data predominantly represent individuals of European ancestry. The inverse-variance weighted (IVW) method was employed as primary analysis approach.ResultsIBD (IVW odds ratio = 1.127, 95% confidence interval = 1.016–1.251; p = 0.024) and CD (IVW odds ratio = 1.119, 95% confidence interval = 1.023–1.224; p = 0.014) exhibited a significant causal effect on malignant cervical carcinoma. Sensitivity analyses confirmed these findings.ConclusionGenetically predicted IBD and CD are risk factors for the development of malignant cervical carcinoma. Patients with IBD and CD require specific attention to prevent cervical squamous cell carcinoma. Further studies to elucidate the underlying mechanisms may reveal new therapeutic targets.

CRAmed: a conditional randomization test for high-dimensional mediation analysis in sparse microbiome data.

Numerous microbiome studies have revealed significant associations between the microbiome and human health and disease. These findings have motivated researchers to explore the causal role of the microbiome in human complex traits and diseases. However, the complexities of microbiome data pose challenges for statistical analysis and interpretation of causal effects. We introduced a novel statistical framework, CRAmed, for inferring the mediating role of the microbiome between treatment and outcome. CRAmed improved the interpretability of the mediation analysis by decomposing the natural indirect effect into two parts, corresponding to the presence-absence and abundance of a microbe, respectively. Comprehensive simulations demonstrated the superior performance of CRAmed in Recall, precision, and F1 score, with a notable level of robustness, compared to existing mediation analysis methods. Furthermore, two real data applications illustrated the effectiveness and interpretability of CRAmed. Our research revealed that CRAmed holds promise for uncovering the mediating role of the microbiome and understanding of the factors influencing host health. The R package CRAmed implementing the proposed methods is available online at https://github.com/liudoubletian/CRAmed. Supplementary data are available at Bioinformatics online.