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PubMed2025

Exploring the causal relationship between plasma proteins and postherpetic neuralgia: a Mendelian randomization study.

BACKGROUND: The proteome represents a valuable resource for identifying therapeutic targets and clarifying disease mechanisms in neurological disorders. This study investigated potential causal relationships between plasma proteins and postherpetic neuralgia (PHN). METHODS: We conducted a two-sample Mendelian randomization (MR) analysis using genome-wide association study (GWAS) summary statistics from the Decode Genetics dataset (4,907 plasma proteins) and the FinnGen database (490 PHN cases and 435,371 controls). Instrumental variables (IVs) were selected based on relevance, independence, and exclusivity. Causal associations were assessed using inverse-variance weighted (IVW), MR-Egger regression, simple mode, weighted mode, and weighted median methods. Sensitivity analyses, including leave-one-out tests, evaluated result robustness, while colocalization analysis examined shared causal variants between traits. RESULTS: Eight plasma proteins showed significant associations with PHN (PFDR < 0.05). Higher levels of ATRN, PIANP, and CD48 correlated with increased PHN risk, whereas elevated KIR2DL5A, GPI, SEMG2, EIF4B, and HFE2 levels were associated with reduced risk. Sensitivity analyses supported these findings and excluded genetic pleiotropy as a major confounding factor. Colocalization analysis did not detect shared causal variants (PPH4 < 0.8). CONCLUSION: These results suggest a potential causal role for eight plasma proteins in PHN pathogenesis. While these proteins may serve as biomarkers or therapeutic candidates, further validation is required. This study advances understanding of PHN pathophysiology and supports future investigations into diagnostic and therapeutic strategies.

Mendelian randomization↗

PubMed2004

Effects of grouping and attention on the perception of causality.

Beyond perceiving patterns of motion in simple dynamic displays, we can also perceive higher level properties, such as causality, as when we see one object collide with another object. Although causality is a seemingly high-level property, its perception--like the perception of faces or speech--often appears to be automatic, irresistible, and driven by highly constrained and stimulus-driven rules. Here, in an exploration of such rules, we demonstrate that perceptual grouping and attention can influence the both perception of causality in ambiguous displays. We first report several types of grouping effects, based on connectedness, proximity, and common motion. We further suggest that such grouping effects are mediated by the allocation of attention, and we directly demonstrate that causal perception can be strengthened or attenuated on the basis of where observers are attending, independent of fixation. Like Michotte, we find that the perception of causality is mediated by strict visual rules. Beyond Michotte, we find that these rules operate not only over discrete objects, but also over perceptual groups, constrained by the allocation of attention.

Attention↗

PubMed2005

Causal impressions: predicting when, not just whether.

In 1739, David Hume established the so-called cues to causality--environmental cues that are important to the inference of causality. Although this descriptive account has been corroborated experimentally, it has not been established why these cues are useful, except that they may reflect statistical regularities in the environment. One of the cues to causality, covariation, helps predict whether an effect will occur, but not its time of occurrence. In the present study, evidence is provided that spatial and temporal contiguity improve an observer's ability to predict when an effect will occur, thus complementing the utility of covariation as a predictor of whether an effect will occur. While observing Michotte's (1946/1963) launching effect, participants showed greater accuracy and precision in their predictions of the onset of movement by the launched object when there was spatial and temporal contiguity. Furthermore, when auditory cues that bridged a delayed launch were included, causal ratings and predictability were similarly affected. These results suggest that the everyday inference of causality relies on our ability to predict whether and when an effect will occur.

Cognition↗

PubMed2003

Human causality judgments and response rates on DRL and DRH schedules of reinforcement.

The effect of various relationships between a response (an investment made in the context of a game) and an outcome (a return on the investment) on judgments of the causal effectiveness of the response was examined. In Experiment 1, response rates and causal judgments were higher for a differential-reinforcement-of-high-rate (DRH) schedule relative to a variable-ratio (VR) schedule with the same probability of outcome following a response. Response rates were also higher for a DRH than for a variable-interval schedule matched for reinforcement rate. In Experiment 2, response rates and causal judgments were lower for a differential-reinforcement-of-low-rate schedule relative to a VR schedule with the same probability of outcome following a response. These results corroborate the view that schedules are a determinant of both response rates and causal judgments, and that few current theories of causal judgment explicitly predict this pattern of results.

Adolescent↗

PubMed2000

The role of causal discourse structure in narrative writing.

All writers produce text content and ideally connect it together according to discourse conventions. We investigate whether a particularly strong discourse convention, the need for causal coherence in narratives, can predict the kind of text writers will produce. Causality has been found to be a significant discourse factor in reading comprehension and hence can be expected to determine also what writers produce during composition. In Experiment 1, writers composed short continuations at various points throughout a simple narrative, whereas in Experiment 2, writers composed continuations to complete several narratives. The results indicate that causality indeed plays a major role in composition. Writers tend to produce new text in such a way that it is causally connected to the prior text. Furthermore, writers favored causal relations of necessity or of necessity and sufficiency while largely avoiding relations of sufficiency alone, which suggests a general discourse constraint to be maximally informative (e.g., Grice, 1975).

Communication↗

PubMed1989

Acquisition context and the use of causal rules.

Judgmental asymmetries in using causal knowledge (e.g., for prediction or diagnosis) have been attributed to the inherent directionality of causal knowledge. The present study examines the effect of acquisition context--representations used for initial instruction, and the type of judgement required during acquisition--on judgments using causal rules. In contrast to traditional concept formation research, this paradigm examined the development of procedures for using rules, rather than rule induction. College-student subjects learned to use causal rules describing digital logic gates, receiving instruction with either verbal rules or truth tables, and practicing either predicting or verifying logic-gate outputs. After 200 trials of practice with each rule, subjects were transferred to the untrained judgment task. Transfer was strongly asymmetrical. Subjects trained to make prediction judgments were slowed substantially by transfer to the verification task, while subjects trained to make verification judgments had little difficulty with transfer to the prediction task. Truth-table representations resulted in superior performance, especially for verification judgments. Contrary to prediction, verification judgments always required more time. The results demonstrate that acquisition context may be partly responsible for judgmental asymmetries, and imply that examining conditions of acquisition is important for understanding how causal knowledge is used.

Humans↗

PubMed1990

An on-line assessment of causal reasoning during comprehension.

Fletcher and Bloom (1988) have argued that as readers read narratives, clause by clause, they repeatedly focus their attention on the last preceding clause that contains antecedents but no consequences in the text. This strategy allows them to discover a causal path linking the text's opening to its final outcome while minimizing the number of times long-term memory must be searched for missing antecedents or consequences. In order to test this hypothesis, we examined the reading times of 25 subjects for each clause of eight simple narrative texts. The results show that: (1) causal links between clauses that co-occur in short-term memory (as predicted by the strategy) increase the time required to read the second clause; (2) potential causal links between clauses that never co-occur in short-term memory (again as predicted by the strategy) have no effect on reading time; and (3) reinstatement searches are initiated at the end of sentences that are causally unrelated to the contents of short-term memory or that contain clauses that satisfy goals no longer in short-term memory. These results support the claim that subjects engage in a form of causal reasoning when they read simple narrative texts.

Attention↗

PubMed1992

[Causality and disease].

The interpretation of the causal relations in the beginning of a disease offers a central problem in medicine. It obtains a special interest with the increasing significance of the chronic diseases. The handling of this problem cannot depend on the experience of the every day life. It must take in consideration the general aspects of the causality as they are the topic of modern physics and biology as well as of philosophy. In the principle acknowledgement of the principle of causality a change from a deterministic monocausal to a more complex thinking takes place considering a complex of conditions followed by a field of possibilities of effects. Special interest needs the differentiation between the description and the interpretation of causal relations that means between ontological and epistemological thinking. The causal relation in medicine depends on the same principles as in physics and in biology.

Chronic Disease↗

PubMed2004

Methodologic implications of the Precautionary Principle: causal criteria.

Applying the Precautionary Principle to public health requires a re-evaluation of the methods of inference currently used to make claims about disease causation from epidemiologic and other forms of scientific evidence. In current thinking, a well-established, near-certain causal relationship implies highly consistent statistically significant results across many different studies, large relative risk estimates, extensive understanding of biological mechanisms and dose-response relationships, positive prevention trial results, a clear temporal relationship between cause and effect, and other conditions spelled out in terms of the widely-used causal criteria. The Precautionary Principle, however, states that preventive measures are to be taken when cause and effect relationships are not fully established scientifically. What evidentiary conditions, as reflected in the causal criteria, will be certain enough to warrant precautionary preventive action? This paper argues that minimum evidentiary requirements for causation need to be articulated if the Precautionary Principle is to be successfully incorporated into public health practice. Two precautionary changes to criteria-based methods of causal inference are examined: reducing the number of criteria and weakening the rules of inference accompanying the criteria. Such changes point in the direction of identifying minimum evidentiary conditions, but would be premature without better understanding how well current methods of causal inference work.

Environmental Pollutants↗

PubMed1991

Practical implications of modes of statistical inference for causal effects and the critical role of the assignment mechanism.

Causal inference in an important topic and one that is now attracting serious attention of statisticians. Although there exist recent discussions concerning the general definition of causal effects and a substantial literature on specific techniques for the analysis of data in randomized and nonrandomized studies, there has been relatively little discussion of modes of statistical inference for causal effects. This presentation briefly describes and contrasts four basic modes of statistical inference for causal effects, emphasizes the common underlying causal framework with a posited assignment mechanism, and describes practical implications in the context of an example involving the effects of switching from a name-band to a generic drug. A fundamental conclusion is that in such nonrandomized studies, sensitivity of inference to the assignment mechanism is the dominant issue, and it cannot be avoided by changing modes of inference, for instance, by changing from randomization-based to Bayesian methods.

Bayes Theorem↗

PubMedDate not supplied

A causal model of positive health practices: the relationship between approach and replication.

This study supports the position that causal models developed a priori preclude replication with varied samples. Based on a critique of a study of positive health practices among adults (Muhlenkamp & Sayles, 1986), a causal model of positive health practices for adolescents was developed a priori from a theoretical formulation. Using data from a sample of 165 adolescents who responded to the Personal Lifestyle Questionnaire, the Rosenberg Self-Esteem Scale, Part 2 of the Personal Resource Questionnaire which measures a social support system, and a demographic data sheet, the intercorrelations among the study variables were analyzed using correlation coefficients. The causal model was then tested with the adolescent data using the LISREL VI program. The results showed a relatively good fit of the model to the data via a number of indicators. The model was then applied to data published from adults (Muhlenkamp & Sayles) using the LISREL VI program. The results indicated that there was a relatively poor fit of the model to the adult data, thus demonstrating the problem of replicating causal models with varied samples when the correct approach to causal modeling is used. The discussion focuses on theoretical and methodological reasons for the findings.

Adolescent↗

PubMedDate not supplied

On the prevalence of causal search in illness situations.

The prevalence of causal search was examined in two samples, one of chronically ill patients, the other of acutely ill patients. In contrast to the assumption that causal search occurs in important or unexpected life events, the results indicated that such a search was reported by only about half of 296 long-term diabetic, hypertensive, and arthritic patients and 83 newly diagnosed myocardial infarction patients. Moreover, in both samples, affect and expectancies for the future were better for those who had not engaged in causal search. Further research to examine the questions used to elicit causal responses and to test the assumption that causal thinking takes place is suggested.

Acute Disease↗

PubMed1987

Taking account of time lags in causal models.

Although it takes time for a cause to exert an effect, causal models often fail to allow adequately for time lags. In particular, causal models that contain cross-sectional relations (i.e., relations between values of 2 variables at the same time) are unsatisfactory because they omit the values of variables at prior times, they omit effects that variables can have on themselves, and they fail to specify the length of the causal interval that is being studied. These omissions can produce severe biases in estimates of the size of causal effects. Longitudinal models also can fail to take account of time lags properly, and this too can lead to severely biased estimates. The discussion illustrates the biases that can occur in both cross-sectional and longitudinal models, introduces the latent longitudinal approach to causal modeling, and shows how latent longitudinal models can be used to reduce bias by taking account of time lags even when data are available for only 1 point in time.

Child↗

PubMed1974

Assessment of causal prophylactic activity in Plasmodium berghei yoelii and its value for the development of new antimalarial drugs.

The causal prophylactic activity of several reference and experimental antimalarial compounds was assessed in sporozoite-induced infections of NMRI mice with Plasmodium berghei yoelii (strain 17X). The animals were inoculated with 10 000 sporozoites per mouse and treated once 2-4 hours later. The test system has proved to be very suitable in experiments involving more than 3 000 mice. The infection rate in 448 untreated controls was 97.3%. Lowering the sporozoite content of the inoculum to 1 000 or 100 sporozoites markedly reduced the rate (65.1% and 32.7%). In experiments with primaquine the causal prophylactic activity was also influenced by the time of drug administration before or after sporozoite inoculation. No causal prophylactic effect was demonstrable with quinine, chloroquine, amodiaquine, amopyroquine, RC-12, or B 505. Primaquine was active, but pamaquine and pentaquine were only sporadically active. The pre-erythrocytic stages of P. b. yoelii were only slightly sensitive to dapsone, sulfadiazine, and sulformethoxine; they were 10-100 times more susceptible to proguanil, cycloguanil, and pyrimethamine. The experimental 6-aminoquinolines NI 147/36, NI 187/82, and BA 138/111 and the 7-chlorolincomycin derivative U 24729 were also studied. Experiments in which curative activity against blood-induced infections of P. b. yoelii was evaluated showed that the causal prophylactics act more specifically against the pre-erythrocytic than against the erythrocytic forms. This specificity was most pronounced among the DHFR-inhibitors, whose outstanding activity may be explained by the fact that the rate of multiplication of the pre-erythrocytic forms of P. b. yoelii is greater than that of other plasmodia used hitherto; it is also greater than the rate shown by the malaria parasites of man and that of the erythrocytic forms of P. b. yoelii itself. We believe that this feature will render P. b. yoelii very useful for determination of the causal prophylactic activity of new compounds, but it may also overrate the potency of drugs that interfere with nucleic acid biosynthesis.

Animals↗

PubMed1981

Path analysis: a strategy for investigating multivariate causal relationships in communication disorders.

This tutorial paper explains, illustrates, and discusses path analysis, a powerful strategy for examining the plausibility and degree of causal relationships which are postulated to exist among a set of variables. In addition to its strength as a method of theory testing, path analysis is highly compatible with the kind of retrospective research which is so often used to study speech and language pathologies. One of its major advantages is that it allows explicit recognition of multiple, interacting causes of communication disorders and allows the researcher to evaluate the logical consequences of assumptions made about the specific nature of those causal relationships. A summary of the meaning of causal relationships is followed by a presentation of the principles underlying path analysis, as well as an outline of its basic procedures. Also presented is an illustrative example of the application of path analysis to the evaluation of some competing causal theories of a communication disorder. Finally, the general advantages of path analysis and its applicability to the investigation of causal relationships in speech and language pathologies are summarized and discussed.

Humans↗

PubMed1997

[Explanation of interpersonal events: on the significance of balance and causality].

According to Brown and VanKleeck (1989), the perceived causes of interpersonal events are mediated by two kinds of factors: First, the interpersonal verbs used to describe these events carry implicit information with regard to the question of which one of the potential interaction partners has caused the event. Second, explanations of interpersonal events are governed by the principle of balance. For example, positive events are predominantly explained by positive causes, and negative events by negative causes. In addition, the interaction of the two mechanisms also has important consequences concerning the explanation of social events: (1) In balanced triads, an event is ascribed to the interaction partner who is seen as the causally dominant one (according to the implicit causality of the verb that is used to describe the interaction). (2) However, this pattern of data is reversed for unbalanced triads: here, the event is ascribed to the interaction partner who is seen as the causally less dominant one, according to the implicit causality of the verb. The present study addresses the question of whether this attributional shift can be explained in terms of corresponding changes in perceived covariation information. Results indicate that the perception of consensus and distinctiveness indeed correspond to the causal attributions as they are obtained for different kinds of triads. Thus, classical attribution variables are regarded as promising candidates in order to explain these attributional shifts for balanced versus unbalanced events.

Adult↗

PubMed1998

Attribution as a function of agential distance in a causal chain.

The hypothesis that causality and blame will be differently affected by agential distance within a two-step causal chain was tested. A hypothetical medical accident was presented to 360 female college students in India, who gave causality, blame, or punishment judgments about either the proximal agent or the distal agent. The study had a 2 (proximal vs. distal agent) x 2 (high vs. low extenuation) x 2 (mild vs. severe outcome) x 3 (casuality, blame, or punishment judgments) fully crossed, between-subjects factorial design, with 15 participants per cell. In support of the basic hypothesis, more blame and punishment were assigned to the distal agent than to the proximal agent, whereas agential distance did not affect causal attribution. Extenuation was effective on causality and blame judgments only when the outcome was mild, and there was no effect of extenuation on punishment judgments, irrespective of outcome severity.

Adult↗

PubMed2024

BICEP: Bayesian inference for rare genomic variant causality evaluation in pedigrees.

Next-generation sequencing is widely applied to the investigation of pedigree data for gene discovery. However, identifying plausible disease-causing variants within a robust statistical framework is challenging. Here, we introduce BICEP: a Bayesian inference tool for rare variant causality evaluation in pedigree-based cohorts. BICEP calculates the posterior odds that a genomic variant is causal for a phenotype based on the variant cosegregation as well as a priori evidence such as deleteriousness and functional consequence. BICEP can correctly identify causal variants for phenotypes with both Mendelian and complex genetic architectures, outperforming existing methodologies. Additionally, BICEP can correctly down-weight common variants that are unlikely to be involved in phenotypic liability in the context of a pedigree, even if they have reasonable cosegregation patterns. The output metrics from BICEP allow for the quantitative comparison of variant causality within and across pedigrees, which is not possible with existing approaches.

Pedigree↗