Abstract

To investigate the relationship between history of anti-inflammatory medication use and delirium risk, as well as long-term mortality.In this retrospective cohort study, subjects recruited between January 2016 and March 2020 were analyzed. Information about anti-inflammatory medication use history including aspirin, NSAIDs, glucosamine, and other anti-inflammatory drugs, was collected. Logistic regression analysis investigated the relationship between anti-inflammatory medications and delirium. Log-rank analysis and cox proportional hazards model investigated the relationship between anti-inflammatory medications and one-year mortality.The data from 1274 subjects were analyzed. The prevalence of delirium was significantly lower in subjects with NSAIDs usage (23.0%) than in those without NSAIDs usage (35.0%) (p < 0.001). Logistic regression analysis controlling for age, sex, dementia status, and hospitalization department showed that the risk of delirium tended to be reduced by a history of NSAIDs use (OR, 0.76 [95% CI, 0.55 to 1.03]). The one-year mortality in the subjects with NSAIDs (survival rate, 0.879 [95% CI, 0.845 to 0.906]) was significantly higher than in the subjects without NSAIDs (survival rate, 0.776 [95% CI, 0.746 to 0.803]) (p < 0.001). A history of NSAIDs use associated with the decreased risk of one-year mortality even after adjustment for age, sex, Charlson Comorbidity Index, delirium status, and hospitalization department (HR, 0.70 [95% CI, 0.51 to 0.96]).This study suggested that NSAIDs usage was associated with decreased delirium prevalence and lower one-year mortality. The potential benefit of NSAIDs on delirium risk and mortality were shown.

View details for DOI 10.1016/j.jpsychores.2023.111212

View details for PubMedID 36963165

Abstract

Delirium is dangerous and a predictor of poor patient outcomes. We have previously reported the utility of the bispectral EEG (BSEEG) with a novel algorithm for the detection of delirium and prediction of patient outcomes including mortality. The present study employed a normalized BSEEG (nBSEEG) score to integrate the previous cohorts to combine their data to investigate the prediction of patient outcomes. We also aimed to test if the BSEEG method can be applicable regardless of age, and independent of delirium motor subtypes.We calculated nBSEEG score from raw BSEEG data in each cohort and classified patients into BSEEG-positive and BSEEG-negative groups. We used log-rank test and Cox proportional hazards models to predict 90-day and 1-year outcomes for the BSEEG-positive and -negative groups in all subjects and motor subgroups.A total of 1,077 subjects, the BSEEG-positive group showed significantly higher 90-day (hazard ratio 1.33 [95% CI 1.16-1.52] and 1-year (hazard ratio 1.22 [95% CI 1.06-1.40] mortality rates than the negative group after adjustment for covariates such as age, sex, CCI, and delirium status. Among patients with different motor subtypes of delirium, the hypoactive group showed significantly higher 90-day (hazard ratio 1.41 [95% CI 1.12-1.76] and 1-year mortality rates (hazard ratio 1.32 [95% CI 1.05-1.67], which remained significant after adjustment for the same covariates.We found that the BSEEG method is capable of capturing patients at high mortality risk.

View details for DOI 10.1016/j.jagp.2023.03.002

View details for PubMedID 37003894

View details for Web of Science ID 000935831100003

View details for Web of Science ID 000892356700006

Abstract

AIMS: There is no previous study demonstrating the differences of genome-wide DNA methylation (DNAm) profiles between patients with and without postoperative delirium (POD). We aimed to discover epigenetic (DNAm) markers that are associated with POD in blood obtained from patients before and after neurosurgery.METHODS: Pre- and post-surgical blood DNA samples from 37 patients, including 10 POD cases, were analyzed using the Illumina EPIC array genome-wide platform. We examined DNAm differences in blood from patients with and without POD. Enrichment analysis with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes terms were also conducted.RESULTS: When POD cases were tested for DNAm change before and after surgery, enrichment analyses showed many relevant signals with statistical significance in immune response related-pathways and inflammatory cytokine related-pathways such as "cellular response to cytokine stimulus", "regulation of immune system process", "regulation of cell activation", and "regulation of cytokine production". Furthermore, after excluding the potential effect of common factors related to surgery and anesthesia between POD cases and non-POD controls, the enrichment analyses showed significant signals such as "immune response" and "T cell activation", which are same pathways previously identified from an independent non-surgical inpatient cohort.CONCLUSIONS: Our first genome-wide DNAm investigation of POD showed promising signals related to immune response, inflammatory response and other relevant signals considered to be associated with delirium pathophysiology. Our data supports the hypothesis that epigenetics are playing an important role in pathophysiological mechanism of delirium and suggest the potential usefulness of epigenetics based biomarker of POD. This article is protected by copyright. All rights reserved.

View details for DOI 10.1111/pcn.13495

View details for PubMedID 36266784

Abstract

OBJECTIVE: No previous study demonstrates the difference in the genome-wide DNA methylation status of post-operative delirium (POD) using human brain tissue obtained from neurosurgery and multiple peripheral tissues such as blood, saliva, and buccal samples from the same individuals. We aimed to identify epigenetic marks of DNA methylation in the brain and peripheral tissues to elucidate the potential pathophysiological mechanism of POD.METHODS: The four tissue types (brain, blood, saliva, buccal) of DNA samples from up to 40 patients, including 11 POD cases, were analyzed using Illumina EPIC array. DNAm differences between patients with and without POD were examined. We also conducted enrichment analysis based on the top DNAm signals.RESULTS: The most different CpG site between control and POD was found at cg16526133 near the ADAMTS9 gene from the brain tissue(p=8.66E-08). However, there are no CpG sites to reach the genome-wide significant level. The enrichment analysis based on the 1000 top hit CpG site (p<0.05) on the four tissues showed several intriguing pathways. In the brain, there are pathways including "positive regulation of glial cell differentiation". Blood samples showed also pathways related to immune function. Besides, both saliva and the buccal sample showed pathways related to circadian rhythm, although these findings were not FDR significant.CONCLUSION: Enrichment analysis found several intriguing pathways related to potential delirium pathophysiology. Present data may further support the role of epigenetics, especially DNA methylation, in the molecular mechanisms of delirium pathogenesis.

View details for DOI 10.1016/j.jpsychires.2022.10.023

View details for PubMedID 36270064

Abstract

There is growing evidence for the role of DNA methylation (DNAm) quantitative trait loci (mQTLs) in the genetics of complex traits, including psychiatric disorders. However, due to extensive linkage disequilibrium (LD) of the genome, it is challenging to identify causal genetic variations that drive DNAm levels by population-based genetic association studies. This limits the utility of mQTLs for fine-mapping risk loci underlying psychiatric disorders identified by genome-wide association studies (GWAS). Here we present INTERACT, a deep learning model that integrates convolutional neural networks with transformer, to predict effects of genetic variations on DNAm levels at CpG sites in the human brain. We show that INTERACT-derived DNAm regulatory variants are not confounded by LD, are concentrated in regulatory genomic regions in the human brain, and are convergent with mQTL evidence from genetic association analysis. We further demonstrate that predicted DNAm regulatory variants are enriched for heritability of brain-related traits and improve polygenic risk prediction for schizophrenia across diverse ancestry samples. Finally, we applied predicted DNAm regulatory variants for fine-mapping schizophrenia GWAS risk loci to identify potential novel risk genes. Our study shows the power of a deep learning approach to identify functional regulatory variants that may elucidate the genetic basis of complex traits.

View details for DOI 10.1073/pnas.2206069119

View details for PubMedID 35969790

Abstract

The pathophysiological mechanisms of postoperative delirium (POD) are still not clear, and no reliable biomarker is available to differentiate those with and without POD. Pre- and post-surgery blood from epilepsy subjects undergoing neurosurgery were collected. DNA methylation (DNAm) levels of the TNF gene, IL1B gene, and IL6 gene by the Illumina EPIC array method, and DNAm levels of the TNF gene by pyrosequencing, were analyzed. Blood from 37 subjects were analyzed by the EPIC array method, and blood from 27 subjects were analyzed by pyrosequencing. Several CpGs in the TNF gene in preoperative blood showed a negative correlation between their DNAm and age both in the POD group and in the non-POD group. However, these negative correlations were observed only in the POD group after neurosurgery. Neurosurgery significantly altered DNAm levels at 17 out of 24 CpG sites on the TNF gene, 8 out of 14 CpG sites on the IL1B gene, and 4 out of 14 CpG sites on the IL6 gene. Furthermore, it was found that the Inflammatory Methylation Index (IMI), which was based on the post-surgery DNAm levels at the selected five CpG sites, can be a potential detection tool for delirium with moderate accuracy; area under the curve (AUC) value was 0.84. The moderate accuracy of this IMI was replicated using another cohort from our previous study, in which the AUC was 0.79. Our findings provide further evidence of the potential role of epigenetics and inflammation in the pathophysiology of delirium.

View details for DOI 10.1038/s41398-021-01752-6

View details for PubMedID 34887385

Abstract

BACKGROUND: We have developed the bispectral electroencephalography (BSEEG) method for detection of delirium and prediction of poor outcomes.AIMS: To improve the BSEEG method by introducing a new EEG device.METHOD: In a prospective cohort study, EEG data were obtained and BSEEG scores were calculated. BSEEG scores were filtered on the basis of standard deviation (s.d.) values to exclude signals with high noise. Both non-filtered and s.d.-filtered BSEEG scores were analysed. BSEEG scores were compared with the results of three delirium screening scales: the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), the Delirium Rating Scale-Revised-98 (DRS) and the Delirium Observation Screening Scale (DOSS). Additionally, the 365-day mortalities and the length of stay (LOS) in the hospital were analysed.RESULTS: We enrolled 279 elderly participants and obtained 620 BSEEG recordings; 142 participants were categorised as BSEEG-positive, reflecting slower EEG activity. BSEEG scores were higher in the CAM-ICU-positive group than in the CAM-ICU-negative group. There were significant correlations between BSEEG scores and scores on the DRS and the DOSS. The mortality rate of the BSEEG-positive group was significantly higher than that of the BSEEG-negative group. The LOS of the BSEEG-positive group was longer compared with that of the BSEEG-negative group. BSEEG scores after s.d. filtering showed stronger correlations with delirium screening scores and more significant prediction of mortality.CONCLUSIONS: We confirmed the usefulness of the BSEEG method for detection of delirium and of delirium severity, and prediction of patient outcomes with a new EEG device.

View details for DOI 10.1192/bjp.2021.101

View details for PubMedID 35049468

Abstract

Complications of delirium and dementia increase mortality; however, it is difficult to diagnose delirium accurately, especially among dementia patients. The bispectral electroencephalography score can detect delirium and predict mortality in elderly patients. We aimed to develop an efficient and reliable bispectral electroencephalography device for high-throughput screening. We also hypothesized that bispectral electroencephalography score can predict mortality among dementia patients. A prospective cohort study was conducted between January 2016 and December 2018 to measure bispectral electroencephalography from elderly patients and correlate with outcomes. A total of 502 elderly (55 years old or older) patients with and without dementia were enrolled. For a replication of the utility of bispectral electroencephalography, mortalities between bispectral electroencephalography-positive and bispectral electroencephalography-negative group were compared. In addition, patients with and without dementia status were added to examine the utility of bispectral electroencephalography among dementia patients. The mortality within 180 days in the bispectral electroencephalography-positive group was higher than that of the bispectral electroencephalography-negative group in both the replication and the total cohorts. Mortality of those in the bispectral electroencephalography-positive group showed a dose-dependent increase in both cohorts. When the dementia patients showed bispectral electroencephalography positive, their mortality was significantly higher than those with dementia but who were bispectral electroencephalography-negative. Mortality within 30 days in the bispectral electroencephalography-positive group was significantly higher than that of the bispectral electroencephalography-negative group. The utility of the bispectral electroencephalography to predict mortality among large sample of 502 elderly patients was shown. The bispectral electroencephalography score can predict mortality among elderly patients in general, and even among dementia patients, as soon as 30 days.

View details for DOI 10.1093/braincomms/fcab037

View details for PubMedID 34136808

View details for PubMedCentralID PMC8204260