Dr Namrata Chowdhury

Patients with liver cirrhosis can develop hyperammonemia and hepatic encephalopathy (HE), accompanied by pronounced daytime sleepiness. Previous studies with healthy volunteers show that experimental increase in blood ammonium levels increases sleepiness and slows the waking EEG. As ammonium increases adenosine levels in vitro, and adenosine is a known regulator of sleep/wake homeostasis, we hypothesized that the sleepiness-inducing effect of ammonium is mediated by adenosine. Eight adult male Wistar rats were fed with an ammonium-enriched diet for 4 weeks; eight rats on standard diet served as controls. Each animal was implanted with electroencephalography/electromyography (EEG/EMG) electrodes and a microdialysis probe. Sleep EEG recording and cerebral microdialysis were carried out at baseline and after 6 hours of sleep deprivation. Adenosine and metabolite levels were measured by HPLC and targeted LC/MS metabolomics, respectively. Baseline adenosine and metabolite levels (12 of 16 amino acids, taurine, t4-hydroxy-proline and acetylcarnitine) were lower in hyperammonemic animals, while putrescine was higher. After sleep deprivation, hyperammonemic animals exhibited a larger increase in adenosine levels, and a number of metabolites showed a different time-course in the two groups. In both groups the recovery period was characterized by a significant decrease in wakefulness/increase in NREM and REM sleep. However, while control animals exhibited a gradual compensatory effect, hyperammonemic animals showed a significantly shorter recovery phase. In conclusion, the adenosine/metabolite/EEG response to sleep deprivation was modulated by hyperammonemia, suggesting that ammonia affects homeostatic sleep regulation and its metabolic correlates.

Misalignment between internal circadian rhythmicity and externally imposed behavioral schedules, such as occurs in shift workers, has been implicated in elevated risk of metabolic disorders. To determine underlying mechanisms, it is esse ntial to assess whether and how peripheral clocks are disturbed during shift work and to what extent this is linked to the central suprachiasmatic nuclei (SCN) pacemaker and/or misaligned behavioral time cues. Investigating rhythms in circulating metabolites as biomarkers of peripheral clock distur- bances may offer new insight s. We evaluated the impact of misaligned sleep/wake and feeding/fasting cycles on circulating metabolites using a targeted metabolomics approach. Sequential plasma samples obtained during a 24-h constant routine that followed a 3-d simulated night-s hift schedule, compared with a simulated day-shift schedule, we re analyzed for 132 circulating metabolites. Nearly half of these metabolites showed a 24-h rhyth- micity under constant routine following either or both simulated shift schedules. However, while tradition al markers of the circadian clock in the SCN — melatonin, cortisol, and PER3 expression — maintained a stable phase alignment after both schedules, only a few metabo- lites did the same. Many showed reversed rhythms, lost their rhythms, or showed rhythmicity only under constant routine fol- lowing the night-shift schedule. Here, 95% of the metabolites with a 24-h rhythmicity showed rhythms that were driven by behavior- al time cues externally imposed during the preceding simulated shift schedule rather than being driven by the central SCN circa- dian clock. Characterization of these metabolite rhythms will pro- vide insight into the underlying mechanisms linking shift work and metabolic disorders

Background: Metabolic abnormalities have long been predicted in Huntington’s disease (HD) but remain poorly characterized. Chronobiological dysregulation has been described in HD and may include abnormalities in circadian-driven metabolism. Objective: Here we investigated metabolite profiles in the transgenic sheep model of HD (OVT73) at presymptomatic ages. Our goal was to understand changes to the metabolome as well as potential metabolite rhythm changes associated with HD. Methods: We used targeted liquid chromatography mass spectrometry (LC-MS) metabolomics to analyze metabolites in plasma samples taken from female HD transgenic and normal (control) sheep aged 5 and 7 years. Samples were taken hourly across a 27-h period. The resulting dataset was investigated by machine learning and chronobiological analysis. Results: The metabolic profiles of HD and control sheep were separable by machine learning at both ages. We found both absolute and rhythmic differences in metabolites in HD compared to control sheep at 5 years of age. An increase in both the number of disturbed metabolites and the magnitude of change of acrophase (the time at which the rhythms peak) was seen in samples from 7-year-old HD compared to control sheep. There were striking similarities between the dysregulated metabolites identified in HD sheep and human patients (notably of phosphatidylcholines, amino acids, urea, and threonine). Conclusion: This work provides the first integrated analysis of changes in metabolism and circadian rhythmicity of metabolites in a large animal model of presymptomatic HD.

Metabolic rhythms include rapid, ultradian (hourly) dynamics, but it is unclear what their relationship to circadian metabolic rhythms is, and what role meal timing plays in coordinating these ultradian rhythms in metabolism. Here, we characterised widespread ultradian rhythms under ad libitum feeding conditions in the plasma metabolome of the vole, the gold standard animal model for behavioural ultradian rhythms, naturally expressing ~2-hour foraging rhythms throughout the day and night. These ultradian metabolite rhythms co-expressed with diurnal 24-hour rhythms in the same metabolites and did not align with food intake patterns. Specifically, under light-dark entrained conditions we showed twice daily entrainment of phase and period of ultradian behavioural rhythms associated by phase adjustment of the ultradian cycle around the light-dark and dark-light transitions. These ultradian activity patterns also drove an ultradian feeding pattern. We used a unique approach to map this behavioural activity/feeding status to high temporal resolution (every 90 minutes) measures of plasma metabolite profiles across the 24-hour light-dark cycle. A total of 148 known metabolites were detected in vole plasma. Supervised, discriminant analysis did not group metabolite concentration by feeding status, instead, unsupervised clustering of metabolite time courses revealed clusters of metabolites that exhibited significant ultradian rhythms with periods different from the feeding cycle. Two clusters with dissimilar ultradian dynamics, one lipid-enriched (period = 3.4 h) and one amino acid-enriched (period = 4.1 h), both showed co-expression with diurnal cycles. A third cluster solely comprised of glycerophospholipids (specifically ether-linked phosphatidylcholines) and expressed an 11.9 h ultradian rhythm without co-expressed diurnal rhythmicity. Our findings show coordinated co-expression of diurnal metabolic rhythms with rapid dynamics in feeding and metabolism. These findings reveal that ultradian rhythms are integral to biological timing of metabolic regulation, and will be important in interpreting the impact of circadian desynchrony and meal timing on metabolic rhythms.

Parkinson’s disease (PD) is a chronic disorder that presents a range of premotor signs, such as sleep disturbances and cognitive decline, which are key non-motor features of the disease. Increasing evidence of a possible association between sleep disruption and the neurodegenerative process suggests that sleep impairment could produce a detectable metabolic signature on the disease. In order to integrate neurocognitive and metabolic parameters, we performed untargeted and targeted metabolic profiling of the rotenone PD model in a chronic sleep restriction (SR) (6 h/day for 21 days) condition. We found that SR combined with PD altered several behavioural (reversal of locomotor activity impairment; cognitive impairment; delay of rest-activity rhythm) and metabolic parameters (branched-chain amino acids, tryptophan pathway, phenylalanine, and lipoproteins, pointing to mitochondrial impairment). If combined, our results bring a plethora of parameters that represents reliable early-phase PD biomarkers which can easily be measured and could be translated to human studies.