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

Abstract

Current methods for screening and detecting delirium are not practical in clinical settings. We previously showed that a simplified EEG with bispectral electroencephalography (BSEEG) algorithm can detect delirium in elderly inpatients. In this study, we performed a post-hoc BSEEG data analysis using larger sample size and performed topological data analysis to improve the BSEEG method. Data from 274 subjects included in the previous study were analyzed as a 1st cohort. Subjects were enrolled at the University of Iowa Hospitals and Clinics (UIHC) between January 30, 2016, and October 30, 2017. A second cohort with 265 subjects was recruited between January 16, 2019, and August 19, 2019. The BSEEG score was calculated as a power ratio between low frequency to high frequency using our newly developed algorithm. Additionally, Topological data analysis (TDA) score was calculated by applying TDA to our EEG data. The BSEEG score and TDA score were compared between those patients with delirium and without delirium. Among the 274 subjects from the first cohort, 102 were categorized as delirious. Among the 206 subjects from the second cohort, 42 were categorized as delirious. The areas under the curve (AUCs) based on BSEEG score were 0.72 (1st cohort, Fp1-A1), 0.76 (1st cohort, Fp2-A2), and 0.67 (2nd cohort). AUCs from TDA were much higher at 0.82 (1st cohort, Fp1-A1), 0.84 (1st cohort, Fp2-A2), and 0.78 (2nd cohort). When sensitivity was set to be 0.80, the TDA drastically improved specificity to 0.66 (1st cohort, Fp1-A1), 0.72 (1st cohort, Fp2-A2), and 0.62 (2nd cohort), compared to 0.48 (1st cohort, Fp1-A1), 0.54 (1st cohort, Fp2-A2), and 0.46 (2nd cohort) with BSEEG. BSEEG has the potential to detect delirium, and TDA is helpful to improve the performance.

View details for DOI 10.1038/s41598-020-79391-y

View details for PubMedID 33431928

View details for PubMedCentralID PMC7801387

Abstract

It has been suggested that aging and inflammation play key roles in the development of delirium. In the present study, we investigated the differences of the DNAm patterns in the TNF gene between patients with delirium and without. The data and samples derived from previous and ongoing cohort studies were analyzed. DNAm levels of the TNF gene were analyzed using the Illumina EPIC array genome-wide method and pyrosequencing method. Correlations between age and DNAm levels of each CpG were calculated. Several CpG in the TNF gene in blood showed negative correlation between their DNAm and age in delirium cases both with the EPIC array and by the pyrosequencing method. However, there was no CpG that had significant correlation between their DNAm and age regardless of delirium status among buccal samples. On the other hand, among peripheral blood mononuclear cells samples, it was found that several CpG showed negative correlation between their DNAm and age in delirium cases. The evidence of DNAm change in the TNF gene among delirious subjects was demonstrated.

View details for DOI 10.1016/j.neurobiolaging.2021.05.005

View details for PubMedID 34192631

Abstract

Detecting delirium is important to identify patients with a high risk of poor outcomes. Although many different kinds of screening instruments for delirium exist, there is no solid consensus about which methods are the most effective. In addition, it is important to find the most useful tools in predicting outcomes such as mortality.Retrospective cohort study.University of Iowa Hospitals and Clinics.A total of 1,125 adult inpatients (mean age = 67.7; median age = 69).Post hoc analyses were performed based on existing data from the Confusion Assessment Method for Intensive Care Unit (CAM-ICU), Delirium Rating Scale-Revised-98 (DRS), and the Delirium Observation Screening Scale (DOSS). Correlation among these scales and relationships between 365-day mortality and each scale were evaluated.A positive result on the CAM-ICU ("CAM-ICU positive") was associated with higher DRS and DOSS scores. A DRS score = 9/10 was the best cutoff to detect CAM-ICU positive, and DOSS = 2/3 was the best cutoff to detect CAM-ICU positive. CAM-ICU positive was associated with high 365-day mortality. DRS score = 9/10 and DOSS score = 0/1 were found to differentiate mortality risk the most significantly. Higher DRS and DOSS scores significantly coincided with a decrease in a patient's survival rate at 365 days.The best DRS and DOSS cutoff scores to differentiate 365-day mortality risk were lower than those commonly used to detect delirium in the literature. New cutoff scores for the DRS and DOSS might be useful in differentiating risk of mortality among hospital patients.

View details for DOI 10.1111/jgs.16815

View details for PubMedID 32905636

Abstract

Most of the animal studies using inflammation-induced cognitive change have relied on behavioral testing without objective and biologically solid methods to quantify the severity of cognitive disturbances. We have developed a bispectral EEG (BSEEG) method using a novel algorithm in clinical study. This method effectively differentiates between patients with and without delirium, and predict long-term mortality. In the present study, we aimed to apply our bispectral EEG (BSEEG) method, which can detect patients with delirium, to a mouse model of delirium with systemic inflammation induced by lipopolysaccharides (LPS) injection. We recorded EEG after LPS injection using wildtype early adulthood mice (2~3-month-old) and aged mice (18-19-month-old). Animal EEG recordings were converted for power spectral density to calculate BSEEG score using the similar BSEEG algorithm previously developed for our human study. The BSEEG score was relatively stable and slightly high during the day. Alternatively, the BSEEG score was erratic and low in average during the night. LPS injection increased the BSEEG score dose-dependently and diminished the diurnal changes. The mean BSEEG score increased much more in the aged mice group as dosage increased. Our results suggest that BSEEG method can objectively "quantify" level of neuro-Inflammation induced by systemic inflammation (LPS), and that this BSEEG method can be useful as a model of delirium in mice.

View details for DOI 10.1016/j.jpsychires.2020.12.036

View details for PubMedID 33360427