BackgroundPsychiatric traits have been associated with intracerebral hemorrhage (ICH) in observational studies, although their causal relationships remain uncertain. We used Mendelian randomization analyses to infer causality between psychiatric traits and ICH.MethodsWe collected data from genome-wide association studies of ICH (n = 361,194) and eight psychiatric traits among Europeans, including mood swings (n = 451,619), major depressive disorder (n = 480,359), attention-deficit/hyperactivity disorder (n = 53,293), anxiety (n = 459,560), insomnia (n = 462,341), schizophrenia (n = 77,096), neuroticism (n = 374,323), and bipolar disorder (n = 51,710). We performed a series of bidirectional two-sample Mendelian randomization and related sensitivity analyses. A Bonferroni corrected threshold of p < 0.00625 (0.05/8) was considered to be significant, and p < 0.05 was considered suggestive of evidence for a potential association.ResultsMendelian randomization analyses revealed suggestive positive causality of mood swings on ICH (odds ratio = 1.006, 95% confidence interval = 1.001–1.012, p = 0.046), and the result was consistent after sensitivity analysis. However, major depressive disorder (p = 0.415), attention-deficit/hyperactivity disorder (p = 0.456), anxiety (p = 0.664), insomnia (p = 0.699), schizophrenia (p = 0.799), neuroticism (p = 0.140), and bipolar disorder (p = 0.443) are not significantly associated with the incidence of ICH. In the reverse Mendelian randomization analyses, no causal effects of ICH on mood swings (p = 0.565), major depressive disorder (p = 0.630), attention-deficit/hyperactivity disorder (p = 0.346), anxiety (p = 0.266), insomnia (p = 0.102), schizophrenia (p = 0.463), neuroticism (p = 0.261), or bipolar disorder (p = 0.985) were found.ConclusionOur study revealed that mood swings are suggestively causal of ICH and increase the risk of ICH. These results suggest the clinical significance of controlling mood swings for ICH prevention.

Background: Patients with acute ischemic stroke (AIS) caused by large vessel occlusions who are successfully recanalized may still have a poor prognosis. Transcranial Doppler (TCD) and quantitative electroencephalography (QEEG) were used to assess cerebral blood flow and metabolism, with the goal of identifying patients with severe neurological deficits and poor prognosis at an early stage. Methods: We prospectively recruited AIS patients with large vessel occlusions with successful recanalization after endovascular treatment and assessed their prognosis at 90 days using the modified Rankin Scale (mRS) score. All patients’ clinical Information, Glasgow Coma Scale (GCS), and National Institute of Health Stroke Scale (NIHSS) scores were recorded. TCD-QEEG was used to evaluate the brain functioning of AIS patients. Results:Thirty-seven patients (63±11.7 years; 24 males) were studied, and 18 patients had a poor prognosis at 90 days which mRS >3. Multivariable analyses showed that TCD indicators ofUPI (pulsatility index of unaffected side) (odds ratio [OR] 1.076, 95% confidence interval [CI] 1.001–1.157, p=0.048), QEEG indicators of pairwise derived brain symmetry index (pdBSI) (OR 3.041, 95%CI 1.040–8.897, p=0.042), and NIHSS score (OR 1.638, 95%CI 1.071–2.504, p=0.023) were independent predictors of clinical outcomes. The area under the ROC curve for the model combining UPI, pdBSI, and NIHSS scores was 0.980, demonstrating superior predictive accuracy than any single variable. Conclusions: The combination of TCD, QEEG, and NIHSS scores demonstrated the best prognostic assessment accuracy by assessing cerebral blood flow, metabolism, and neurological function in patients with AIS after revascularization.