The circadian timing system drives the cyclic processes observed in most physiological processes including sleep/wake and metabolic function. The mammalian circadian system comprises a master clock located in the hypothalamic suprachiasmatic nuclei (SCN) and peripheral clocks found in most body tissues. For optimal functioning correct temporal coordination between the central SCN clock and peripheral clocks is maintained via feedback/feed forward neuroendocrine and autonomic mechanisms. The environmental light/dark cycle is the primary time cue synchronising the human circadian timing system to 24 h. Recent research has demonstrated links between circadian clocks and metabolism, and between sleep deprivation/sleep restriction, circadian desynchrony and metabolic disorders. Our current studies aim to investigate the mechanisms underlying these interactions between circadian timing, sleep and metabolism. Measuring the human circadian timing system has traditionally relied on assessment of circadian rhythms driven by the central SCN clock, such as melatonin, cortisol and core body temperature. Of these SCN-driven rhythms, the timing of the melatonin rhythm is considered the most reliable marker of circadian phase and numerous studies have used the melatonin profile to assess circadian rhythmicity and phase in healthy and diseased individuals in laboratory and field studies. Studying circadian regulation of metabolism and assessing the relative importance of photic and non-photic time cues (e.g. food, exercise, sleep/wake behaviour) for entrainment, however, also requires reliable markers of peripheral clocks in humans. For example, it might be that food is a major entrainer of peripheral clocks in humans, as has been demonstrated in animals.Early studies reported clock gene expression in peripheral blood cells and buccal tissue. Gene expression in peripheral blood mononuclear cells (PBMCs) shows 24 h rhythms which are driven by the circadian clock1 and can be phase shifted by appropriately timed light2. Our recent data show that the core clock mechanism in peripheral leucocytes is compromised during acute sleep deprivation3. During one night of total sleep deprivation expression of the clock gene BMAL1 was suppressed and the heat shock gene HSPA1B expression was induced. Some clock gene rhythms showed reduced amplitude during sleep deprivation (CRY1, CLOCK, DBP) while other high-amplitude clock gene rhythms (e.g. PER1-3, REV-ERBα) remained unaffected. For metabolism-clock studies, serial sampling of human adipose tissue offers promise. We have recently demonstrated robust 24 h rhythms in gene expression in this metabolically active tissue in three experimental groups: lean, obese-non-diabetic and obese-Type 2 diabetic groups4. Nocturnal plasma melatonin concentrations were significantly higher in obese-non-diabetic subjects compared to weight-matched Type 2 diabetic subjects (p < 0.01) and lean controls (p < 0.05), whereas there was no difference in the amplitude or timing of leptin rhythms between the three experimental groups5. Elucidation of the mechanisms linking metabolic disease and circadian clock misalignment, however, will require a global “systems” approach in order to identify the metabolites, genes and proteins driving endogenous circadian rhythms and how factors such as sleep/wake, light/dark, food and posture impact on these. Metabolomics is the untargeted investigation of small molecule metabolite profiles that provides a novel and powerful tool, which may provide a better representation of functional phenotype than changes in DNA, RNA and proteins. We have recently established an untargeted liquid chromatography-mass spectrometric (LC-MS) method to measure metabolite rhythms in human plasma6. In healthy volunteers, a total of 1069 metabolite features were detected and 203 (19%) showed significant time of day variation. Of these, 34 metabolites were identified using a combination of accurate mass, tandem MS, and online database searches. These metabolites include corticosteroids, bilirubin, amino acids, acylcarnitines, and lysophospholipids. Defining time of day variation in the human metabolome, in addition to increasing our understanding of daily metabolic pathways, will be crucial for the future applied use of metabolomics in the detection and treatment of human disease.