EFFECTS OF SLEEP DEPRIVATION ON CIRCADIAN FLUCTUATIONS OF 54,000 BIOMARKERS

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In a review of 61 studies with 2,000 depressed (Bipolar Disorder and Major Depression) patients during the past three decades, one night of total sleep deprivation completely reversed the depressive symptoms in roughly 50% of patients (Wu et al. 1990). However, the mechanism of action is unknown and the duration of the antidepressant effects are short-term. Treatment resistant depressed patients are currently being recruited (IRB Protocol # 2001-1616) to undergo sleep deprivation and possible examination of gene expression in lymphocytes. Lymphocytes are a peripheral, renewable, accessible tissue compared to brain yet lymphocytes express a large number of neuronal-related genes (Vawter, M.P., unpublished results). Lymphocyte gene expression is modulated by cytokines, hormones, medications or neurotransmitters released into circulation. Lymphocytes may respond in a circadian manner such as seen in CLOCK gene cycles, and as a surrogate probe for gene expression in the brain (Mill et al. 2002). A convergence of data from microarray studies, quantitative trait locus analysis, and mutagenesis screens demonstrates the pervasiveness of circadian regulation in multiple tissues. The importance of maintaining the internal temporal homeostasis regulated by the cellular circadian system is shown when mutations in genes coding for core components of the clock disrupt homeostatis and can result in disease, including cancer and disturbances to the sleep/wake cycle (Lowrey and Takahashi, 2004). Lymphocyte gene expression profiling has been associated with bipolar disorder (Washizuka et al. 2005), major depression (Rocc et al. 2002), schizophrenia (Nadri et al. 2002, Kipnis et al. 2004), and personality traits (Czermak et al. 2004). Data generated from the current bipolar subjects will be compared to a control group of healthy subjects. A control population, however, has never been examined in a sleep deprivation paradigm for biomarker expression. This protocol involves a 48 hour time course where blood samples from healthy donors will be collected before and during a single night of sleep deprivation. Collection during the first 24 hour period will enable a baseline expression pattern for a normal circadian rhythm to be defined for each individual. The following 24 hour period will demonstrate the effect of sleep deprivation on this expression pattern. Understanding the molecular profile of this response in healthy controls will be fundamental to understanding the efficacy of sleep deprivation treatment in psychiatric disorders. We propose to test a series of hypotheses regarding the gene expression patterns of circulating lymphocytes. We will determine the expression patterns on an Affymetrics GeneChip microarray containing 54,000 sequences using funding from a NIH R21 grant. A subset of these sequences have been shown to be sensitive to phenotypic differences in a case-control comparison involving post-mortem brain (Vawter et al. 2004). Potential biomarkers for other phenotypes or environmental conditions such as sleep deprivation could be discovered using the same approach. The collection of the control subjects is funded by the GCRC CReFF award. First, we hypothesize that a normal circadian pattern will result in control subjects without sleep deprivation. We would expect the overall pattern to be similar to that found in a larger study with healthy individuals containing only one time piont (Whitney et al. 2003). To characterize this pattern over time, samples will be taken for 24 hours before an overnight sleep deprivation session. The diurnal variation seen throughout a 24 hour cycle will determine normal gene expression in circulating lymphocytes without sleep deprivation. Second, we hypothesize that the effect of sleep deprivation on control subjects' gene expression patterns will show shifts in those genes regulating circadian rhythm (e.g. CLOCK, PER, NPAS2 & BMAL1, Bunney et al. 2000). Consistent global changes may also occur and those trends will further help elucidate the mechanism of sleep deprivation. Comparisons will be made for the same subject before and during the sleep deprivation. This design will ensure that differences found can reliably be attributed to the effect of sleep deprivation on the lymphocyte gene expression. Third, we hypothesize that the data collected from the control subjects will be significantly different compared to depressed subjects collected in a similar experiment (IRB Protocol # 2001-1616). The differences can inform as to the potentially novel mechanism that is involved with sleep deprivation and the key to its effectiveness in eliminating the symptoms associated with depression. Only with a control population to use as a reference for the depressed subjects can the mechanism be clarified for these psychiatric disorders. Additionally, a small set of genes (e.g. APOBEC3B, ADSS, ATM, CLC, CTBP1, DATF1, CXCL1 & S100A9, Tsuang et al. 2005) in lymphocytes could be used as a diagnostic tool for psychiatric disorders. Determining the circadian variation inherent within a population will help to isolate the most stable candidate genes for future study. If a robust gene expression difference between populations can be determined, then a more objective diagnostic test could be developed. Fourth, we hypothesize that there will be some overlap in the peripheral lymphocyte gene expression and neural expression derived from post mortem brain samples. Data collected through the Conte center within the department will be compared to the lymphocyte gene expression of the current study. The expression differences found between the brains of depressed and control subjects can be compared to the differences seen in the blood. Stable similarities of these expression differences between central and peripheral systems can be thought of as a biological probe. The use of lymphocytes as a biological probe for neuronal activity has been discussed previously (Gladkevich et al. 2004). Establishing a reliable, cheap peripheral system of detection for differences within the brain may have many potential applications in neuroscience. Fifth, we hypothesize that there will be a difference in biomarker expression between subjects who respond positively to the sleep deprivation and those who do not, according to the psychological surveys. We expect to find no significant difference for the control subjects, but decreased symptomology in roughly 50% of the depressed subjects. Correlating subject's response with the gene expression patterns will define a biomarker expression pattern for the subjects who respond to the sleep deprivation. This pattern may be instrumental in targeting the use of sleep deprivation therapy specifically to those who are likely to respond. If this approach proves an efficient screening tool, then pharmacogentic applications could follow. Understanding the mechanism of sleep deprivation, developing a diagnostic tool and discovering subpopulations likely to respond to a particular treatment is the promise for future implementation of this approach.