Widespread sleep deprivation is a continuing public health problem in the United States and worldwide affecting adolescents and adults. Acute sleep deprivation results in decrements in spatial memory and cognitive impairments. The hippocampus is vulnerable to acute sleep deprivation with changes in gene expression, cell signaling, and protein synthesis. Sleep deprivation also has long lasting effects on memory and performance that persist after recovery sleep, as seen in behavioral studies from invertebrates to humans. Although previous research has shown that acute sleep deprivation impacts gene expression, the extent to which sleep deprivation affects gene regulation remains unknown. Using an unbiased deep RNA sequencing approach, we investigated the effects of acute sleep deprivation on gene expression in the hippocampus. We identified 1,146 genes that were significantly dysregulated following sleep deprivation with 507 genes upregulated and 639 genes downregulated, including protein coding genes and long non-coding RNAs not previously identified as impacted by sleep deprivation. Notably, genes significantly upregulated after sleep deprivation were associated with RNA splicing and the nucleus. In contrast, downregulated genes were associated with cell adhesion, dendritic localization, the synapse, and postsynaptic membrane. Furthermore, we found through independent experiments analyzing a subset of genes that three hours of recovery sleep following acute sleep deprivation was sufficient to normalize mRNA abundance for most genes, although exceptions occurred for some genes that may affect RNA splicing or transcription. These results clearly demonstrate that sleep deprivation differentially regulates gene expression on multiple transcriptomic levels to impact hippocampal function.

Bipolar disorder (BD) has been previously associated with premature mortality and aging, including acceleration of epigenetic aging. Suicide attempts (SA) are greatly elevated in BD and are associated with decreased lifespan, biological aging, and poorer clinical outcomes. We investigated the relationship between GrimAge, an epigenetic clock trained on time-to-death and associated with mortality and lifespan, and SA in two independent cohorts of BD individuals (discovery cohort - controls (n = 50), BD individuals with (n = 77, BD/SA) and without (n = 67, BD/non-SA) lifetime history of SA; replication cohort - BD/SA (n = 48) and BD/non-SA (n = 47)). An acceleration index for the GrimAge clock (GrimAgeAccel) was computed from blood DNA methylation (DNAm) and compared between groups with multiple general linear models. Differences in epigenetic aging from the discovery cohort were validated in the independent replication cohort. In the discovery cohort, controls, BD/non-SA, and BD/SA significantly differed on GrimAgeAccel (F = 5.424, p = 0.005), with the highest GrimAgeAccel in BD/SA (p = 0.004, BD/SA vs. controls). Within the BD individuals, BD/non-SA and BD/SA differed on GrimAgeAccel in both cohorts (p = 0.008) after covariate adjustment. Finally, DNAm-based surrogates revealed possible involvement of plasminogen activator inhibitor 1, leptin, and smoking pack-years in driving accelerated epigenetic aging. These findings pair with existing evidence that not only BD, but also SA, may be associated with an accelerated biological aging and provide putative biological mechanisms for morbidity and premature mortality in this population.

Suicide attempt (SA) risk is elevated in individuals with bipolar disorder (BD), and DNA methylation patterns may serve as possible biomarkers of SA. We conducted epigenome-wide association studies (EWAS) of blood DNA methylation associated with BD and SA. DNA methylation was measured at >700,000 positions in a discovery cohort ofn = 84 adults with BD with a history of SA (BD/SA),n = 79 adults with BD without history of SA (BD/non-SA), andn = 76 non-psychiatric controls (CON). EWAS revealed six differentially methylated positions (DMPs) and seven differentially methylated regions (DMRs) between BD/SA and BD/non-SA, with multiple immune-related genes implicated. There were no epigenome-wide significant differences when BD/SA and BD/non-SA were each compared to CON, and patterns suggested that epigenetics differentiating BD/SA from BD/non-SA do not differentiate BD/non-SA from CON. Weighted gene co-methylation network analysis and trait enrichment analysis of the BD/SA vs. BD/non-SA contrast further corroborated immune system involvement, while gene ontology analysis implicated calcium signalling. In an independent replication cohort ofn = 48 BD/SA andn = 47 BD/non-SA, fold changes at the discovery cohort’s significant sites showed moderate correlation across cohorts and agreement on direction. In both cohorts, classification accuracy for SA history among individuals with BD was highest when methylation at the significant CpG sites as well as information from clinical interviews were combined, with an AUC of 88.8% (CI = 83.8–93.8%) and 82.1% (CI = 73.6–90.5%) for the combined epigenetic-clinical classifier in the discovery and replication cohorts, respectively. Our results provide novel insight to the role of immune system functioning in SA and BD and also suggest that integrating information from multiple levels of analysis holds promise to improve risk assessment for SA in adults with BD.