Metformin use history and genome-wide DNA methylation profile: potential molecular mechanism for aging and longevity.

BACKGROUND: Metformin, a commonly prescribed anti-diabetic medication, has repeatedly been shown to hinder aging in pre-clinical models and to be associated with lower mortality for humans. It is, however, not well understood how metformin can potentially prolong lifespan from a biological standpoint. We hypothesized that metformin's potential mechanism of action for longevity is through its epigenetic modifications. METHODS: To test our hypothesis, we conducted a post-hoc analysis of available genome-wide DNA methylation (DNAm) data obtained from whole blood collected from inpatients with and without a history of metformin use. We assessed the methylation profile of 171 patients (first run) and only among 63 diabetic patients (second run) and compared the DNAm rates between metformin users and nonusers. RESULTS: Enrichment analysis from the Kyoto Encyclopedia of Genes and Genome (KEGG) showed pathways relevant to metformin's mechanism of action, such as longevity, AMPK, and inflammatory pathways. We also identified several pathways related to delirium whose risk factor is aging. Moreover, top hits from the Gene Ontology (GO) included HIF-1α pathways. However, no individual CpG site showed genome-wide statistical significance (p < 5E-08). CONCLUSION: This study may elucidate metformin's potential role in longevity through epigenetic modifications and other possible mechanisms of action.

DNA methylation in the TNF-alpha gene decreases along with aging among delirium inpatients.

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.

New Cutoff Scores for Delirium Screening Tools to Predict Patient Mortality.

BACKGROUND/OBJECTIVES: 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. DESIGN: Retrospective cohort study. SETTING: University of Iowa Hospitals and Clinics. PARTICIPANTS: A total of 1,125 adult inpatients (mean age = 67.7; median age = 69). MEASUREMENTS: 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. RESULTS: 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. CONCLUSION: 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.

Evaluation of point-of-care thumb-size bispectral electroencephalography device to quantify delirium severity and predict mortality.

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.