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PubMed2026

A causal relationship between chronic pancreatitis and cardiovascular disease: A two-sample Mendelian randomization analysis.

Current research suggests a link between chronic pancreatitis (CP) and cardiovascular disease (CVD), although the causality remains unclear. The aim of this study was therefore to conduct a 2-sample Mendelian randomization (MR) analysis to determine whether a causal relationship exists between CP and CVD. Summary-level data from publicly available genome-wide association studies of European populations were utilized for the MR analysis. Following quality control measures, independent single-nucleotide polymorphisms associated with CP and CVD were chosen as the genetic instruments. Four complementary MR methods were performed, namely the inverse variance weighted (IVW) method, weighted median, MR-Egger, and leave-one-out sensitivity. The IVW method revealed correlations between alcohol-induced CP and myocardial infarction (odds ratio [OR] = 1.001, 95% confidence interval [CI]: 1.000-1.002, P = .0010), as well as with large artery atherosclerosis stroke (OR = 1.067, 95% CI: 1.030-1.105, P = .0003). The IVW method also suggested that CP was significantly associated with stroke (OR = 1.040, 95% CI: 1.015-1.065, P = .0015) and with ischemic stroke (OR = 1.041, 95% CI: 1.005-1.078, P = .0024). These results remained robust and consistent in the sensitivity analysis. This MR study indicates a significant causal relationship between alcohol-induced CP and elevated risks of myocardial infarction and large artery atherosclerosis stroke, and a causal link between CP and stroke as well as ischemic stroke.

Mendelian Randomization Analysis↗

PubMed2004

A cognitive neuroscience framework for understanding causal reasoning and the law.

Over the past couple of decades, there have been great developments in the fields of psychology and cognitive neuroscience that have allowed the advancement of our understanding of how people make judgements about causality in several domains. We provide a review of some of the contemporary psychological models of causal thinking that are directly relevant to legal reasoning. In addition, we cover some exciting new research using advanced neuroimaging techniques that have helped to uncover the underlying neural signatures of complex causal reasoning. Through the use of functional imaging, we provide a first-hand look at how the brain responds to evidence that is either consistent or inconsistent with one's beliefs and expectations. Based on the data covered in this review, we propose some ideas for how the effectiveness of causal reasoning, especially as it pertains to legal decision-making, may be facilitated.

Brain↗

PubMed2003

Sensitivity analysis for the assessment of causal vaccine effects on viral load in HIV vaccine trials.

Vaccines with limited ability to prevent HIV infection may positively impact the HIV/AIDS pandemic by preventing secondary transmission and disease in vaccine recipients who become infected. To evaluate the impact of vaccination on secondary transmission and disease, efficacy trials assess vaccine effects on HIV viral load and other surrogate endpoints measured after infection. A standard test that compares the distribution of viral load between the infected subgroups of vaccine and placebo recipients does not assess a causal effect of vaccine, because the comparison groups are selected after randomization. To address this problem, we formulate clinically relevant causal estimands using the principal stratification framework developed by Frangakis and Rubin (2002, Biometrics 58, 21-29), and propose a class of logistic selection bias models whose members identify the estimands. Given a selection model in the class, procedures are developed for testing and estimation of the causal effect of vaccination on viral load in the principal stratum of subjects who would be infected regardless of randomization assignment. We show how the procedures can be used for a sensitivity analysis that quantifies how the causal effect of vaccination varies with the presumed magnitude of selection bias.

AIDS Vaccines↗

PubMed2025

Causal association between different types of ametropia and risk of diabetic retinopathy: a two-sample Mendelian randomization study.

OBJECTIVE: To investigate the causal link between ametropia and diabetic retinopathy, as well as to offer genetic support for the association between these two conditions. METHODS: This study employed a methodology involving the utilisation of genome-wide association studies data that are publicly accessible. Specifically, single nucleotide polymorphisms (SNPs) that exhibit a strong association with ametropia were employed as instrumental variables, and a two-sample Mendelian randomization (MR) approach was employed to examine the causal relationship between different types of ametropia and diabetic retinopathy. The main findings were derived from the utilisation of inverse variance weighted (IVW), while supplementary results were obtained through the utilisation of MR Egger, weighted median, simple mode and weighted mode. Additionally, a sensitivity analysis was conducted using the 'leave-one-out' method. Cochran's Q statistics were also used to quantify the heterogeneity of SNPs. RESULTS: 38 SNPs were finally included. The results of the IVW analysis indicate that myopia may exert an inhibitory effect on the development of diabetic retinopathy (OR=0.596, 95% CI (0.371, 0.957), p<0.05). Conversely, hypermetropia (OR=8.882, 95% CI (0.389×10-3, 2.06×105), p>0.05) and astigmatism (OR=1.004, 95% CI (0.888, 1.135), p>0.05) do not exhibit a causal relationship with the risk of diabetic retinopathy. CONCLUSION: This two-sample Mendelian randomization study provides evidence that myopia may impede diabetic retinopathy occurrence, while hypermetropia and astigmatism show no significant causal effects. However, our analysis treats refractive errors as independent entities, which may not reflect their clinical interdependence. Further investigations are warranted to elucidate myopia's protective mechanisms.

Humans↗

PubMed1988

Patterns of depression in medical patients and their relationship with causal attributions for illness.

The present study investigated the factor structure of the Beck Depression Inventory (BDI), and causal attributions for the development of illness in a sample of 102 inpatients of a thoracic surgery department, with the main objective of examining the power of causal attributions and functional support in predicting different factors derived from the BDI. The results revealed that the BDI clusters into affective/motivational, somatic/vegetative, self-blame and self-punitiveness dimensions. Causal attributions for the development of illness were represented by family conflicts, environmental adversity, finance/health problems, bad luck, and four self-related clusters. Examination of the predictors of the BDI dimensions showed that causal attributions to uncontrollable, unmodifiable variables were predictors for the affective/motivational dimension, whereas illness severity and greater age were related to the somatic/vegetative symptomatology. The results supported the recommendations for the exclusion of such symptoms in assessing depression severity among medical patients.

Adolescent↗

PubMed1990

"Meaning" connections and causal connections in the human sciences: the poverty of hermeneutic philosophy.

In much of psychoanalytic theory and therapy, Freud repeatedly inferred a causal connection between thematically kindred events by relying on the kinship between their thematic contents. This paper strongly endorses his search for causal explanations. But it argues in detail that (1) his causal inferences from thematic connections rest on an important fallacy, which undermines major etiologic conclusions in psychoanalysis; (2) a related, weighty inferential error is damaging to the Freudian theory of transference, when it infers the pathogenic role of an early childhood scenario from the thematic reenactment (recapitulation) of that scenario in the adult patient's interactions with the analyst, and with other people. Both arguments draw on subject matter in psychoanalysis, physics, evolutionary biology, common-sense psychology, history, and medicine to arrive at a fundamental caveat for all of the sciences: Even when the thematic kinship (or so-called "meaning connection") between events is indeed of very high degree, this fact itself does not license the inference of a causal linkage between these events. A corollary of this result is that we must reject the accusation of Karl Jaspers and the hermeneutic philosophers that Freud's own conception of the psychoanalytic enterprise suffered from a "scientistic self-misunderstanding."

Defense Mechanisms↗

PubMed1977

Causal orientation and personal adjustment of hospitalized veterans.

Continues a line of theory and research which sees human behavior as basically teleological. Groups of hospitalized male alcoholics, psychotics, and normals were administered the Causal Construct Scale, the Minnesota Multiphasic Personality Inventory, and the Shipley Institute of Living Scale. It was predicted that extent of pathology across experimental groups as well as general tendencies to abnormality would follow telic considerations. Intentional causal orientation was positively related and subtance causal orientation was negatively related to mental health. The impetus and pattern causal constructs failed to be predictive of personal adjustment.

Adult↗

PubMed2001

[Causal attribution and personality in psychotherapy patients].

The present study addressed the relationship between patients' causal attributions of their disorders on one hand and their personality traits on the other. The investigation was based on the self-reports of 197 psychotherapy patients who presented at a university outpatient department for diagnostic evaluation. Personality traits were measured using the Giessen-Test (Beckmann et al., 1991), causal attributions were assessed by a check list (Faller 1997). Intrapsychic causal factors were rated highest; after those, interpersonal and social factors followed next, while somatic factors were judged to be least important. Psychosocial attributions showed strong correlations with the self-report of depressed mood in the Giessen-Test. Similar relations were found with other personality traits such as low ratings of social resonance, low openness, and low social potency. The reported interrelations suggest that psychological symptoms, personality and causal atttributions are closely intertwined.

Adolescent↗

PubMed2001

Spontaneous, elicited and cued causal attributions in the year following a first myocardial infarction.

OBJECTIVES: To assess myocardial infarction (MI) patients' causal beliefs, how they change over time and the effects of different assessment methods. METHOD: The study used a longitudinal design with a follow-up to 1 year. The participants were 100 MI patients who were recruited within 72 hours of admission. Each participant was interviewed and their causal attributions (spontaneous, elicited and cued) were assessed using four different methods. RESULTS: 'Stress', 'smoking', 'it is in the family', 'eating fatty foods' and 'work' items were the most commonly mentioned causes for the MI at all times of measurement and across all measures. On each occasion 'stress' and 'smoking' were selected as the most important causes and patients made fewer attributions over time. Finally, the attributional assessment method used did not affect type of attributions but fewer attributions were reported using the spontaneous method. CONCLUSION: Patients do provide causal attributions following an MI. While many are similar to causal factors identified by medicine, patients appear to place more emphasis on 'stress'. As predicted by attribution theory, attributions changed over time. The method of obtaining the attributions does not appear to affect the attributions made but greatly affects their number. While all the methods used have their place, the cued method with a list of possible attributions offers a rich return for effort expended.

Journal Article↗

PubMed2026

Deciphering the Microbiome-Gut-Eye Axis: A Mendelian Randomization Analysis of the Causal Influence of Gut Microbiota on Myopia.

INTRODUCTION: The intricate relationship between the gut microbiome and myopia is increasingly recognized, underscoring the need to explore its causal dynamics. Despite emerging evidence, the influence of Gut Microbiota (GM) on ocular development remains underexplored. METHODS: This study utilized Mendelian Randomization (MR) to investigate the causal impact of GM on the development of myopia. Instrumental variables (IVs) were identified from Genome-Wide Association Studies (GWAS), focusing on genetic variants significantly associated with microbiome composition. A comprehensive array of MR techniques was applied to ensure a robust estimation of causal effects and to adjust for potential confounders and pleiotropy. RESULTS: The Inverse-Variance Weighted (IVW) method was used to identify significant associations between GM and myopia. Increased risk of myopia was linked to the class Betaproteobacteria (OR=1.01, 95% CI 1.004-1.017, P=0.003), the order Burkholderiales (OR=1.009, 95% CI 1.001-1.016, P=0.02), the family Oxalobacteraceae (OR=1.005, 95% CI 1.001-1.01, P=0.023), and several genera including Eubacterium xylanophilum group (OR=1.007, 95% CI 1.001-1.013, P=0.033), and Bifidobacterium (OR=1.005, 95% CI 1-1.01, P=0.038). Protective effects were noted for the order Mollicutes RF9 (OR=0.994, 95% CI 0.99-0.999, P=0.014), the genus Allisonella (OR=0.996, 95% CI 0.993-0.999, P=0.019), the genus Lachnospiraceae UCG001 (OR=0.994, 95% CI 0.989-1, P=0.045), and the family Enterobacteraceae (OR=0.991, 95% CI 0.982-1, P=0.047) and order Enterobacteriales (OR=0.991, 95% CI 0.982-1, P=0.047). Sensitivity analyses further confirmed the robustness of these findings. DISCUSSION: This study provides causal evidence for the "Microbiome-Gut-Eye Axis" in myopia development, identifying specific gut microbiota that influence myopia risk. These findings suggest potential for microbiota-targeted interventions, warranting further research in diverse populations. CONCLUSIONS: The findings support the "Microbiome-Gut-Eye Axis" as a potential factor in myopia pathogenesis and highlight microbiota-targeted interventions as novel therapeutic strategies for managing myopia. This study lays the groundwork for further research on how modifying GM can influence eye health and offers new perspectives on preventive health strategies.

Humans↗

PubMed2026

Mendelian Randomization Using a Japanese GWAS Identifies an HLA-Linked Causal Effect of Chronic Hepatitis B on Cholangiocarcinoma Risk.

BACKGROUND: Cholangiocarcinoma (CCA) is a highly malignant cancer that develops in the bile ducts. Its incidence is particularly high in East Asian populations, but the underlying genetic factors remain unclear. To investigate potential risk factors for CCA, we conducted a Mendelian randomization study to infer causality. METHODS: Using large-scale genome-wide association study data from the BioBank Japan resource, we systematically investigated the causal effects of genetic predisposition to seven conditions, chronic hepatitis B (CHB), chronic hepatitis C, autoimmune hepatitis, type 1 diabetes, type 2 diabetes, chronic gastritis, and chronic pancreatitis, on CCA risk. RESULTS: Our analysis reveals a significant association between genetic susceptibility to CHB with a 24% higher likelihood of developing CCA than non-susceptible individuals (Inverse-Variance Weighted Odds Ratio = 1.24, 95% Confidence Interval: 1.08-1.42; p = 0.002). This genetic association is significantly driven by instrumental variables enriched in the immune-regulatory HLA class II region (6p21), suggesting a plausible biological mechanism. For the primary outcome (CCA), statistical significance was assessed across seven exposures at a Bonferroni-corrected threshold (two-sided p<0.0071). Notably, the CHB-CCA association remains significant after correction. This primary finding is strongly supported by comprehensive sensitivity analyses that showed no evidence of confounding by horizontal pleiotropy or heterogeneity. Conversely, no significant causal effects on CCA were identified for the other six conditions. CONCLUSIONS: Our MR analysis supports a causal role of HBV infection in CCA development, highlighting the importance of targeted HBV screening and surveillance.

Female↗

PubMed2005

Causal coherence and the availability of locations and objects during narrative comprehension.

The aim of this study was to examine whether locations of objects are encoded and available to the reader at different points in a narrative, depending on their causal relevance. Participants in five experiments read narratives in which the spatial relation between an object and its location either did or did not provide a causal explanation for a later critical event. Object and location target words were presented to the participants immediately before or after the critical event. Speeded recognition response times to target words demonstrated that both locations and objects were reactivated, but only after they became causally relevant. The results suggest that the causal structure of a text can influence the availability of spatial information and that at least some spatial relations are encoded during reading and are available to the reader when they are needed to build coherence.

Cognition↗

PubMed2004

Causal models frame interpretation of mathematical equations.

We offer evidence that people can construe mathematical relations as causal. The studies show that people can select the causal versions of equations and that their selections predict both what they consider most understandable and how they expect variables to influence one another. When asked to write down equations, people have a strong preference for the version that matches their causal model. Causal models serve to structure equations by determining the preferred order of variables: Causes should be on one side of an equality, and a single effect should appear on the other.

Humans↗

PubMed1999

Effect of causal structure on category construction.

In four experiments, the question of how the causal structure of features affects the creation of new categories was examined. Features of exemplars to be sorted were related in a single causal chain (causal chain), were caused by the same factor (common cause), or caused the same effect (common effect). The results showed that people are more likely to rely on common-cause or common-effect background knowledge than on causal-chain background knowledge in category construction. Such preferences suggest that the common-cause or the common-effect structures are considered more natural conceptual structures.

Adult↗

PubMed1994

Influence of the cost of responding on human causality judgments.

In three experiments, the effect of costs associated with responding on judgments of the causal effectiveness of the response was examined. In Experiment 1, the temporal interval between outcomes was matched on a variable interval (VI) and a variable ratio (VR) schedule. When each response was made at some "cost," and outcomes represented some "gain" for the subject, the rating of causal effectiveness for responses was higher on the VR than on the VI schedule. This relationship was absent when the outcome was a triangle flash. In Experiment 2, the number of responses required per outcome on a VI and a VR schedule were matched, and responses on the VR schedule were rated as more causally effective. In Experiment 3, a VI-to-VR yoking procedure was used. With minimal response costs, judgments were similar on the VI and VR schedules, but with greater response costs, responses performed on the VR schedule were rated as more causally effective than those emitted on the VI schedule.

Adult↗

PubMed2026

Causal Relationship Between Ischemic Stroke and Vascular Dementia: A Mendelian Randomization Study.

Ischemic stroke (IS) is a major cause of disability and mortality worldwide, and vascular dementia (VaD) is a common dementia subtype associated with cerebrovascular injury. Observational studies have suggested a relationship between IS and VaD, but these studies are vulnerable to confounding and reverse causality. This protocol describes a reproducible two-sample Mendelian randomization (MR) workflow for evaluating the potential causal association between IS and VaD using publicly available genome-wide association study (GWAS) summary statistics. Genetic instruments associated with IS were extracted from a public GWAS dataset, and outcome associations for VaD were obtained from a public VaD GWAS dataset. The corresponding dataset IDs are provided in the Protocol section. After outcome matching and allele harmonization, 51 single-nucleotide polymorphisms (SNPs) were retained for the final MR analysis. The workflow includes instrumental variable selection, linkage disequilibrium clumping, allele harmonization, instrument strength assessment, inverse variance weighted (IVW) analysis, weighted median analysis, MR-Egger analysis, heterogeneity testing, horizontal pleiotropy assessment, and leave-one-out sensitivity analysis. In the representative analysis, the IVW method showed a positive association between genetically predicted IS and VaD risk, and the weighted median method yielded a directionally concordant result. The MR-Egger estimate was directionally consistent but did not reach statistical significance. Therefore, these findings should be interpreted as suggestive evidence of a possible causal effect, rather than definitive proof of causality. This protocol may help researchers apply a transparent and reproducible MR workflow to investigate cerebrovascular disease-related outcomes using public GWAS data.

Humans↗

PubMed2026

The causal effect of family history of cardiovascular disease on erectile dysfunction: a randomized clinical study and Mendelian randomization study.

Erectile dysfunction (ED) is increasingly recognized as an early clinical marker of cardiovascular disease (CVD); however, the causal role of familial predisposition to CVD in ED development remains insufficiently defined. This study investigated whether genetic susceptibility associated with a parental history of CVD exerts a causal influence on ED risk, integrating clinical data with Mendelian randomization (MR) analysis. A cohort of 288 men who attended the Department of Andrology of Xiangya Hospital (Changsha, China) between June 2017 and June 2023 were recruited, comprising 223 patients with clinically confirmed ED and 65 controls. Detailed demographic, cardiovascular, and ED severity data were collected. Genetic variants associated with ED and parental CVD history were obtained from genome-wide association study (GWAS) summary statistics, and two-sample MR analyses were conducted to evaluate causal effects. Clinically, men with ED were significantly older, exhibited higher body mass index (BMI), and demonstrated lower testosterone levels compared with controls. A trend toward an association between family history of CVD and ED was observed. MR analyses provided robust evidence of causality, with paternal CVD history increasing ED risk and maternal CVD history exerting an even stronger effect. Sensitivity analyses confirmed the stability of these findings without evidence of pleiotropic bias. Collectively, these results indicate that familial genetic susceptibility to CVD independently contributes to the risk of ED. These findings underscore the clinical importance of incorporating family history into ED risk stratification and highlight the need for early screening and preventive strategies in men with a family history of CVD. Proactive management of this high-risk population may mitigate the future burden of ED and its cardiovascular sequelae.

Humans↗

PubMed1999

[A causal model of blood enzyme data and visualization of tissue conditions].

Quantitative diagnostics is an important field in which clinical data are converted into medical information. A variety of approaches to obtain medical diagnoses have been developed and multivariate statistical analysis supports the diagnostic process. Although many clinical data are affected by body conditions such as disease and functional failure, only a few models take this phenomenon into consideration. The correlation between laboratory test results can be understood as a causal relationship between body conditions and clinical test data variations. A multivariate statistical method, factor analysis, expresses a causal relationship between latent variables and observed variables. We developed a causal model for blood enzyme data using factor analysis. The latent variables were assumed to be organ specific regarding 9 enzyme data. This causal model expressed clinical knowledge within blood enzymes and allowed visualization of organ conditions. The visualization of laboratory data is useful to screen patient's pathological states.

Data Interpretation, Statistical↗