Epidemiological studies on the association between migraine and Alzheimer’s disease (AD) risk have yielded inconsistent conclusions. We aimed to characterize the phenotypic and genetic relationships between migraine and AD.

To investigate the association between migraine and the risk of AD by analyzing data from a large sample of 404,318 individuals who were initially free from all-cause dementia or cognitive impairment, utilizing the UK Biobank dataset. We employed Cox regression modeling and propensity score matching techniques to examine the relationship between migraine and subsequent occurrences of AD. Additionally, the study utilized Mendelian randomization (MR) analysis to identify the genetic relationship between migraine and the risk of AD.

Migraine patients had a significantly increased risk of developing AD, compared to non-migraine patients (adjusted hazard ratio (HR) = 2.34, 95% confidence interval (CI) = 2.01–0.74, P < 0.001). Moreover, the propensity scores matching analyses found that migraine patients had a significantly higher risk of developing AD compared to non-migraine patients (HR = 1.85, 95%CI = 1,68–2.05, P < 0.001). Additionally, the MR suggested that significant causal effects of migraine on AD risks were observed [odds ratio (OR) = 2.315; 95% confidence interval (CI) = 1.029–5.234; P = 0.002]. Moreover, no evidence supported the causal effects of AD on migraine (OR = 1.000; 95%CI = 0.999–1.006; P = 0.971).

The present study concludes that migraine patients, compared to a matched control group, exhibit an increased risk of developing AD. Moreover, migraine patients exhibit an increased predisposition of genetic susceptibility to AD. These findings hold significant clinical value for early intervention and treatment of migraines to reduce the risk of AD.

Several observational studies have investigated the association of insomnia with psychiatric disorders. Such studies yielded mixed results, and whether these associations are causal remains unclear. Thus, we aimed to identify the causal relationships between insomnia and five major psychiatric disorders.

The analysis was implemented with six genome-wide association studies; one for insomnia and five for psychiatric disorders (attention-deficit/hyperactivity disorder, autism spectrum disorder, major depressive disorder, schizophrenia, and bipolar disorder). A heterogeneity in dependent instrument (HEIDI) approach was used to remove the pleiotropic instruments, Mendelian randomization (MR)-Egger regression was adopted to test the validity of the screened instruments, and bidirectional generalized summary data-based MR was performed to estimate the causal relationships between insomnia and these major psychiatric disorders.

We observed significant causal effects of insomnia on the risk of autism spectrum disorder and bipolar disorder, with odds ratios of 1.739 (95% confidence interval: 1.217–2.486, p = 0.002) and 1.786 (95% confidence interval: 1.396–2.285, p = 4.02 × 10−6), respectively. There was no convincing evidence of reverse causality for insomnia with these two disorders (p = 0.945 and 0.546, respectively). When insomnia was considered as either the exposure or outcome variable, causal estimates for the remaining three psychiatric disorders were not significant.

Our results suggest a causal role of insomnia in autism spectrum disorder and bipolar disorder. Future disease models should include insomnia as a factor for these two disorders to develop effective interventions. More detailed mechanism studies may also be inspired by this causal inference.

Childhood sexual abuse (CSA) is strongly associated with risk for major depression (MD) but the degree to which this association is causal remains uncertain.

We applied structural equation modeling using the Mplus program to 1493 longitudinally assessed female twins from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders.

Our model included (i) retrospective self- and co-twin reports on CSA, (ii) major potentially confounding covariates, (iii) assessment of lifetime history of MD at two separate interviews, and (iv) mood-congruent recall (implemented by allowing current depressive symptoms to predict reporting of CSA). In a model with only measurement error, CSA explained 9.6% of MD. Including four key covariates reduced the variance explained to 5.3%, with the largest effects found for parental loss and low parental warmth. Adding the effect of mood-congruent recall to a final well-fitting model reduced the percentage of variance explained in lifetime MD (LTMD) by CSA to 4.4%. In this model, current depressive symptoms significantly predicted recall of CSA.

In a model correcting for measurement error, confounding and the impact of mood-congruent recall, CSA remains substantially associated with the risk for LTMD in women. These findings strongly suggest, but do not prove, that this association is causal, and are consistent with previous results in this sample using a co-twin control design, but also indicate that more than half of the uncorrected CSA–MD association is probably not causal. Traumatic life experiences contribute substantially to the risk for LTMD.

Social cognition has been identified as a significant construct for schizophrenia research with relevance to diagnosis, assessment, treatment and functional outcome. However, social cognition has not been clearly understood in terms of its relationships with neurocognition and functional outcomes. The present study sought to examine the empirical independence of social cognition and neurocognition; to investigate the possible causal structure among social cognition, neurocognition and psychosocial functioning.

The sample consists of 130 individuals diagnosed with schizophrenia. All participants were recruited as they were admitted to four community-based psychosocial rehabilitation programs. Social cognition, neurocognition and psychosocial functioning were measured at baseline and 12 months. The empirical independence of social cognition and neurocognition was tested using confirmatory factor analysis (CFA) and the possible causal structure among social cognition, neurocognition and psychosocial functioning was investigated using latent difference score (LDS) analysis.

A two-factor model of social cognition and neurocognition fit the data very well, indicating the empirical independence of social cognition, whereas the longitudinal CFA results show that the empirical independence of neurocognition and social cognition is maintained over time. The results of the LDS analysis support a causal model that indicates that neurocognition underlies and is causally primary to social cognition, and that neurocognition and social cognition are causally primary to functional outcome.

Social cognition and neurocognition could have independent and distinct upward causal effects on functional outcome. It is also suggested that the approaches for remediation of neurocognition and social cognition might need to be distinct.