Identification of human plasma metabolites exhibiting time-of-day variation using an untargeted liquid chromatography-mass spectrometry metabolomic approach

Decoding the nexus: branched-chain amino acids and their connection with sleep, circadian rhythms, and cardiometabolic health

The sleep-wake cycle stands as an integrative process essential for sustaining optimal brain function and, either directly or indirectly, overall body health, encompassing metabolic and cardiovascular well-being. Given the heightened metabolic activity of the brain, there exists a considerable demand for nutrients in comparison to other organs. Among these, the branched-chain amino acids, comprising leucine, isoleucine, and valine, display distinctive significance, from their contribution to protein structure to their involvement in overall metabolism, especially in cerebral processes. Among the first amino acids that are released into circulation post-food intake, branched-chain amino acids assume a pivotal role in the regulation of protein synthesis, modulating insulin secretion and the amino acid sensing pathway of target of rapamycin. Branched-chain amino acids are key players in influencing the brain's uptake of monoamine precursors, competing for a shared transporter. Beyond their involvement in protein synthesis, these amino acids contribute to the metabolic cycles of γ-aminobutyric acid and glutamate, as well as energy metabolism. Notably, they impact GABAergic neurons and the excitation/inhibition balance. The rhythmicity of branched-chain amino acids in plasma concentrations, observed over a 24-hour cycle and conserved in rodent models, is under circadian clock control. The mechanisms underlying those rhythms and the physiological consequences of their disruption are not fully understood. Disturbed sleep, obesity, diabetes, and cardiovascular diseases can elevate branched-chain amino acid concentrations or modify their oscillatory dynamics. The mechanisms driving these effects are currently the focal point of ongoing research efforts, since normalizing branched-chain amino acid levels has the ability to alleviate the severity of these pathologies. In this context, the Drosophila model, though underutilized, holds promise in shedding new light on these mechanisms. Initial findings indicate its potential to introduce novel concepts, particularly in elucidating the intricate connections between the circadian clock, sleep/wake, and metabolism. Consequently, the use and transport of branched-chain amino acids emerge as critical components and orchestrators in the web of interactions across multiple organs throughout the sleep/wake cycle. They could represent one of the so far elusive mechanisms connecting sleep patterns to metabolic and cardiovascular health, paving the way for potential therapeutic interventions.

Glucose Challenge Uncovers Temporal Fungibility of Metabolic Homeostasis over a day:night cycle

Rhythmicity is a cornerstone of behavioral and biological processes, especially metabolism, yet the mechanisms behind metabolite cycling remain elusive. This study uncovers a robust oscillation in key metabolite pathways downstream of glucose in humans. A purpose-built 13C6-glucose isotope tracing platform was used to sample Drosophila every 4h and probe these pathways, revealing a striking peak in biosynthesis shortly after lights-on in wild-type flies. A hyperactive mutant (fumin) demonstrates increased Krebs cycle labelling and dawn-specific glycolysis labelling. Surprisingly, neither underlying feeding rhythms nor the presence of food availability explain the rhythmicity of glucose processing across genotypes, suggesting a robust internal mechanism for metabolic control of glucose processing. These results align with clinical data highlighting detrimental effects of mistimed energy intake. Our approach offers a unique insight into the dynamic range of daily metabolic processing and provides a mechanistic foundation for exploring circadian metabolic homeostasis in disease contexts.

Assessing the influence of sleep and sampling time on metabolites in oral fluid: implications for metabolomics studies

INTRODUCTION

The human salivary metabolome is a rich source of information for metabolomics studies. Among other influences, individual differences in sleep-wake history and time of day may affect the metabolome.

OBJECTIVES

We aimed to characterize the influence of a single night of sleep deprivation compared to sufficient sleep on the metabolites present in oral fluid and to assess the implications of sampling time points for the design of metabolomics studies.

METHODS

Oral fluid specimens of 13 healthy young males were obtained in Salivette® devices at regular intervals in both a control condition (repeated 8-hour sleep) and a sleep deprivation condition (total sleep deprivation of 8 h, recovery sleep of 8 h) and their metabolic contents compared in a semi-targeted metabolomics approach.

RESULTS

Analysis of variance results showed factor 'time' (i.e., sampling time point) representing the major influencer (median 9.24%, range 3.02-42.91%), surpassing the intervention of sleep deprivation (median 1.81%, range 0.19-12.46%). In addition, we found about 10% of all metabolic features to have significantly changed in at least one time point after a night of sleep deprivation when compared to 8 h of sleep.

CONCLUSION

The majority of significant alterations in metabolites' abundances were found when sampled in the morning hours, which can lead to subsequent misinterpretations of experimental effects in metabolomics studies. Beyond applying a within-subject design with identical sample collection times, we highly recommend monitoring participants' sleep-wake schedules prior to and during experiments, even if the study focus is not sleep-related (e.g., via actigraphy).

Challenges in the Metabolomics-Based Biomarker Validation Pipeline

As end-products of the intersection between the genome and environmental influences, metabolites represent a promising approach to the discovery of novel biomarkers for diseases. However, many potential biomarker candidates identified by metabolomics studies fail to progress beyond analytical validation for routine implementation in clinics. Awareness of the challenges present can facilitate the development and advancement of innovative strategies that allow improved and more efficient applications of metabolite-based markers in clinical settings. This minireview provides a comprehensive summary of the pre-analytical factors, required analytical validation studies, and kit development challenges that must be resolved before the successful translation of novel metabolite biomarkers originating from research. We discuss the necessity for strict protocols for sample collection, storage, and the regulatory requirements to be fulfilled for a bioanalytical method to be considered as analytically validated. We focus especially on the blood as a biological matrix and liquid chromatography coupled with tandem mass spectrometry as the analytical platform for biomarker validation. Furthermore, we examine the challenges of developing a commercially viable metabolomics kit for distribution. To bridge the gap between the research lab and clinical implementation and utility of relevant metabolites, the understanding of the translational challenges for a biomarker panel is crucial for more efficient development of metabolomics-based precision medicine.

Serum metabolic alterations in peritoneal dialysis patients with excessive daytime sleepiness

Excessive daytime sleepiness (EDS) is associated with quality of life and all-cause mortality in the end-stage renal disease population. This study aims to identify biomarkers and reveal the underlying mechanisms of EDS in peritoneal dialysis (PD) patients. A total of 48 nondiabetic continuous ambulatory peritoneal dialysis patients were assigned to the EDS group and the non-EDS group according to the Epworth Sleepiness Scale (ESS). Ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) was used to identify the differential metabolites. Twenty-seven (male/female, 15/12; age, 60.1 ± 16.2 years) PD patients with ESS ≥ 10 were assigned to the EDS group, while twenty-one (male/female, 13/8; age, 57.9 ± 10.1 years) PD patients with ESS < 10 were defined as the non-EDS group. With UHPLC-Q-TOF/MS, 39 metabolites with significant differences between the two groups were found, 9 of which had good correlations with disease severity and were further classified into amino acid, lipid and organic acid metabolism. A total of 103 overlapping target proteins of the differential metabolites and EDS were found. Then, the EDS-metabolite-target network and the protein-protein interaction network were constructed. The metabolomics approach integrated with network pharmacology provides new insights into the early diagnosis and mechanisms of EDS in PD patients.

Daily fluctuation of colonic microbiome in response to nutrient substrates in a pig model

Studies on rodents indicate the daily oscillations of the gut microbiota have biological implications for host. However, the responses of fluctuating gut microbes to the dynamic nutrient substrates are not fully clear. In the study, we found that the feed intake, nutrient substrates, microbiota and metabolites in the colon underwent asynchronous oscillation within a day. Short-chain fatty acids (SCFAs) including acetate, propionate, butyrate and valerate peaked during T24 ~ T27 (Timepoint 24, 12:00 pm, T27, 03:00 am) whereas branched SCFAs isobutyrate and isovalerate peaked during T09 ~ T12. Further extended local similarity analysis (eLSA) revealed that the fluctuation of feed intake dynamically correlated with the colonic carbon substrates which further influenced the oscillation of sugar metabolites and acetate, propionate, butyrate and valerate with a certain time shift. The relative abundance of primary degrader Ruminococcaceae taxa was highly related to the dynamics of the carbon substrates whereas the fluctuations of secondary degraders Lactobacillaceae and Streptococcaceae taxa were highly correlated with the sugar metabolites. Meanwhile, colonic nitrogen substrates were correlated with branched amino acids and the branched SCFAs. Furthermore, we validated the evolution of gut microbes under different carbohydrate and protein combinations by using an in vitro fermentation experiment. The study pictured the dynamics of the micro-ecological environment within a day which highlights the implications of the temporal dimension in studies related to the gut microbiota. Feed intake, more precisely substrate intake, is highly correlated with microbial evolution, which makes it possible to develop chronotherapies targeting the gut microbiota through nutrition intervention.

Daily rhythms of diabetogenic factors in men: role of type 2 diabetes and body weight

Obesity is a major cause of type 2 diabetes. Transition from obesity to type 2 diabetes manifests in the dysregulation of hormones controlling glucose homeostasis and inflammation. As metabolism is a dynamic process that changes across 24 h, we assessed diurnal rhythmicity in a panel of 10 diabetes-related hormones. Plasma hormones were analysed every 2 h over 24 h in a controlled laboratory study with hourly isocaloric drinks during wake. To separate effects of body mass from type 2 diabetes, we recruited three groups of middle-aged men: an overweight (OW) group with type 2 diabetes and two control groups (lean and OW). Average daily concentrations of glucose, triacylglycerol and all the hormones except visfatin were significantly higher in the OW group compared to the lean group (P < 0.001). In type 2 diabetes, glucose, insulin, C-peptide, glucose-dependent insulinotropic peptide and glucagon-like peptide-1 increased further (P < 0.05), whereas triacylglycerol, ghrelin and plasminogen activator inhibitor-1 concentrations were significantly lower compared to the OW group (P < 0.001). Insulin, C-peptide, glucose-dependent insulinotropic peptide and leptin exhibited significant diurnal rhythms in all study groups (P < 0.05). Other hormones were only rhythmic in 1 or 2 groups. In every group, hormones associated with glucose regulation (insulin, C-peptide, glucose-dependent insulinotropic peptide, ghrelin and plasminogen activator inhibitor-1), triacylglycerol and glucose peaked in the afternoon, whereas glucagon and hormones associated with appetite and inflammation peaked at night. Thus being OW with or without type 2 diabetes significantly affected hormone concentrations but did not affect the timing of the hormonal rhythms.

The circadian clock is required for rhythmic lipid transport in Drosophila in interaction with diet and photic condition

Modern lifestyle is often at odds with endogenously driven rhythmicity, which can lead to circadian disruption and metabolic syndrome. One signature for circadian disruption is a reduced or altered metabolite cycling in the circulating tissue reflecting the current metabolic status. Drosophila is a well-established model in chronobiology, but day-time dependent variations of transport metabolites in the fly circulation are poorly characterized. Here, we sampled fly hemolymph throughout the day and analyzed diacylglycerols (DGs), phosphoethanolamines (PEs) and phosphocholines (PCs) using LC-MS. In wild-type flies kept on sugar-only medium under a light-dark cycle, all transport lipid species showed a synchronized bimodal oscillation pattern with maxima at the beginning and end of the light phase which were impaired in period01 clock mutants. In wild-type flies under constant dark conditions, the oscillation became monophasic with a maximum in the middle of the subjective day. In strong support of clock-driven oscillations, levels of the targeted lipids peaked once in the middle of the light phase under time-restricted feeding independent of the time of food intake. When wild-type flies were reared on full standard medium, the rhythmic alterations of hemolymph lipid levels were greatly attenuated. Our data suggest that the circadian clock aligns daily oscillations of DGs, PEs, and PCs in the hemolymph to the anabolic siesta phase, with a strong influence of light on phase and modality.

Metabolic Basis of Circadian Dysfunction in Parkinson's Disease

Parkinson's disease (PD) is one of the most common neurodegenerative disorders. The management of PD is a challenging aspect for general physicians and neurologists. It is characterized by the progressive loss of dopaminergic neurons. Impaired α-synuclein secretion and dopamine release may cause mitochondrial dysfunction and perturb energy metabolism, subsequently altering the activity and survival of dopaminergic neurons, thus perpetuating the neurodegenerative process in PD. While the etiology of PD remains multifactorial, emerging research indicates a crucial role of circadian dysfunction in its pathogenesis. Researchers have revealed that circadian dysfunction and sleep disorders are common among PD subjects and disruption of circadian rhythms can increase the risk of PD. Hence, understanding the findings of circadian biology from translational research in PD is important for reducing the risk of neurodegeneration and for improving the quality of life. In this review, we discuss the intricate relationship between circadian dysfunction in cellular metabolism and PD by summarizing the evidence from animal models and human studies. Understanding the metabolic basis of circadian dysfunction in PD may shed light on novel therapeutic approaches to restore circadian rhythm, preserve dopaminergic function, and ameliorate disease progression. Further investigation into the complex interplay between circadian rhythm and PD pathogenesis is essential for the development of targeted therapies and interventions to alleviate the burden of this debilitating neurodegenerative disorder.

Modulation of sleep by trafficking of lipids through the Drosophila blood-brain barrier

Endocytosis through Drosophila glia is a significant determinant of sleep amount and occurs preferentially during sleep in glia of the blood-brain barrier (BBB). To identify metabolites whose trafficking is mediated by sleep-dependent endocytosis, we conducted metabolomic analysis of flies that have increased sleep due to a block in glial endocytosis. We report that acylcarnitines, fatty acids conjugated to carnitine to promote their transport, accumulate in heads of these animals. In parallel, to identify transporters and receptors whose loss contributes to the sleep phenotype caused by blocked endocytosis, we screened genes enriched in barrier glia for effects on sleep. We find that knockdown of lipid transporters LRP1&2 or of carnitine transporters ORCT1&2 increases sleep. In support of the idea that the block in endocytosis affects trafficking through specific transporters, knockdown of LRP or ORCT transporters also increases acylcarnitines in heads. We propose that lipid species, such as acylcarnitines, are trafficked through the BBB via sleep-dependent endocytosis, and their accumulation reflects an increased need for sleep.

Detection and analysis of chiral molecules as disease biomarkers

The chirality of small metabolic molecules is important in controlling physiological processes and indicating the health status of humans. Abnormal enantiomeric ratios of chiral molecules in biofluids and tissues occur in many diseases, including cancers and kidney and brain diseases. Thus, chiral small molecules are promising biomarkers for disease diagnosis, prognosis, adverse drug-effect monitoring, pharmacodynamic studies and personalized medicine. However, it remains difficult to achieve cost-effective and reliable analysis of small chiral molecules in clinical procedures, in part owing to their large variety and low concentration. In this Review, we describe current and emerging techniques that detect and quantify small-molecule enantiomers and their biological importance.

Short-Term Stability of Serum and Liver Extracts for Untargeted Metabolomics and Lipidomics

Thermal reactions can significantly alter the metabolomic and lipidomic content of biofluids and tissues during storage. In this study, we investigated the stability of polar metabolites and complex lipids in dry human serum and mouse liver extracts over a three-day period under various temperature conditions. Specifically, we tested temperatures of -80 °C (freezer), -24 °C (freezer), -0.5 °C (polystyrene box with gel-based ice packs), +5 °C (refrigerator), +23 °C (laboratory, room temperature), and +30 °C (thermostat) to simulate the time between sample extraction and analysis, shipping dry extracts to different labs as an alternative to dry ice, and document the impact of higher temperatures on sample integrity. The extracts were analyzed using five fast liquid chromatography-mass spectrometry (LC-MS) methods to screen polar metabolites and complex lipids, and over 600 metabolites were annotated in serum and liver extracts. We found that storing dry extracts at -24 °C and partially at -0.5 °C provided comparable results to -80 °C (reference condition). However, increasing the storage temperatures led to significant changes in oxidized triacylglycerols, phospholipids, and fatty acids within three days. Polar metabolites were mainly affected at storage temperatures of +23 °C and +30 °C.

Structural elucidation of 3-nitrophenylhydrazine derivatives of tricarboxylic acid cycle acids and optimization of their fragmentation to boost sensitivity in liquid chromatography-mass spectrometry

Carboxylic acids participate in many metabolic pathways including tricarboxylic acid (TCA) cycle. Therefore, there have been ongoing attempts to develop sensitive liquid chromatography-mass spectrometry methods over the last decades. Derivatization of the carboxylic acids with 3-nitrophenylhydrazine presents a well-established methodology, and yet the derivatized species of polycarboxylic acids and their fragmentation in collision-induced dissociation have not been fully studied before. In our study, we elucidated how annotation of most abundant 3-nitrophenylhydrazine derivatives and optimization of their fragmentation in multiple reaction monitoring can boost the sensitivity, especially for polycarboxylic acids. Finally, the optimized liquid chromatography-tandem mass spectrometry method allowed for low detection limits ranging from 10 pM for 2-oxoglutaric acid to 800 pM for pyruvic acid. All TCA carboxylates were quantified in 20 µL of human plasma and the targeted method was validated in the same matrix. The same methodology with a modified gradient elution was also applied to untargeted screening of fatty acids by using high-resolution mass spectrometry enabling identification of 29 medium- to long-chain fatty acids in human plasma. The TCA carboxylates were also quantified in 10⁵ of C2C12 mouse myuotube cells grown under different treatments to proof applicability of the methodology to biological studies in a wider sense. However, unfortunately all the TCA carboxylates were also found in the derivatized blanks in substantial amounts, which prevents from using the methodology for quantification of the carboxylates in less than 10⁵ cells.

Multi-Omics Reveal Interplay between Circadian Dysfunction and Type2 Diabetes

Type 2 diabetes is one of the leading threats to human health in the 21st century. It is a metabolic disorder characterized by a dysregulated glucose metabolism resulting from impaired insulin secretion or insulin resistance. More recently, accumulated epidemiological and animal model studies have confirmed that circadian dysfunction caused by shift work, late meal timing, and sleep loss leads to type 2 diabetes. Circadian rhythms, 24-h endogenous biological oscillations, are a fundamental feature of nearly all organisms and control many physiological and cellular functions. In mammals, light synchronizes brain clocks and feeding is a main stimulus that synchronizes the peripheral clocks in metabolic tissues, such as liver, pancreas, muscles, and adipose tissues. Circadian arrhythmia causes the loss of synchrony of the clocks of these metabolic tissues and leads to an impaired pancreas β-cell metabolism coupled with altered insulin secretion. In addition to these, gut microbes and circadian rhythms are intertwined via metabolic regulation. Omics approaches play a significant role in unraveling how a disrupted circadian metabolism causes type 2 diabetes. In the present review, we emphasize the discoveries of several genes, proteins, and metabolites that contribute to the emergence of type 2 diabetes mellitus (T2D). The implications of these discoveries for comprehending the circadian clock network in T2D may lead to new therapeutic solutions.

Circadian orchestration of host and gut microbiota in infection

Circadian rhythms are present in almost every organism and regulate multiple aspects of biological and physiological processes (e.g. metabolism, immune responses, and microbial exposure). There exists a bidirectional circadian interaction between the host and its gut microbiota, and potential circadian orchestration of both host and gut microbiota in response to invading pathogens. In this review, we summarize what is known about these intestinal microbial oscillations and the relationships between host circadian clocks and various infectious agents (bacteria, fungi, parasites, and viruses), and discuss how host circadian clocks prime the immune system to fight pathogen infections as well as the direct effects of circadian clocks on viral activity (e.g. SARS-CoV-2 entry and replication). Finally, we consider strategies employed to realign normal circadian rhythmicity for host health, such as chronotherapy, dietary intervention, good sleep hygiene, and gut microbiota-targeted therapy. We propose that targeting circadian rhythmicity may provide therapeutic opportunities for the treatment of infectious diseases.

Metabolomics in pediatric lower respiratory tract infections and sepsis: a literature review

Lower respiratory tract infections (LRTIs) are a leading cause of morbidity and mortality in children. The ability of healthcare providers to diagnose and prognose LRTIs in the pediatric population remains a challenge, as children can present with similar clinical features regardless of the underlying pathogen or ultimate severity. Metabolomics, the large-scale analysis of metabolites and metabolic pathways offers new tools and insights that may aid in diagnosing and predicting the outcomes of LRTIs in children. This review highlights the latest literature on the clinical utility of metabolomics in providing care for children with bronchiolitis, pneumonia, COVID-19, and sepsis. IMPACT: This article summarizes current metabolomics approaches to diagnosing and predicting the course of pediatric lower respiratory infections. This article highlights the limitations to current metabolomics research and highlights future directions for the field.

Metabolomic profiles in night shift workers: A cross-sectional study on hospital female nurses

Background and aim

Shift work, especially including night shifts, has been found associated with several diseases, including obesity, diabetes, cancers, and cardiovascular, mental, gastrointestinal and sleep disorders. Metabolomics (an omics-based methodology) may shed light on early biological alterations underlying these associations. We thus aimed to evaluate the effect of night shift work (NSW) on serum metabolites in a sample of hospital female nurses.

Methods

We recruited 46 nurses currently working in NSW in Milan (Italy), matched to 51 colleagues not employed in night shifts. Participants filled in a questionnaire on demographics, lifestyle habits, personal and family health history and work, and donated a blood sample. The metabolome was evaluated through a validated targeted approach measuring 188 metabolites. Only metabolites with at least 50% observations above the detection limit were considered, after standardization and log-transformation. Associations between each metabolite and NSW were assessed applying Tobit regression models and Random Forest, a machine-learning algorithm.

Results

When comparing current vs. never night shifters, we observed lower levels of 21 glycerophospholipids and 6 sphingolipids, and higher levels of serotonin (+171.0%, 95%CI: 49.1-392.7), aspartic acid (+155.8%, 95%CI: 40.8-364.7), and taurine (+182.1%, 95%CI: 67.6-374.9). The latter was higher in former vs. never night shifters too (+208.8%, 95%CI: 69.2-463.3). Tobit regression comparing ever (i.e., current + former) and never night shifters returned similar results. Years worked in night shifts did not seem to affect metabolite levels. The Random-Forest algorithm confirmed taurine and aspartic acid among the most important variables in discriminating current vs. never night shifters.

Conclusions

This study, although based on a small sample size, shows altered levels of some metabolites in night shift workers. If confirmed, our results may shed light on early biological alterations that might be related to adverse health effects of NSW.

Dynamic behavior of cell-free mitochondrial DNA in human saliva

Mitochondria contain their own genome that can be released in multiple biofluids such as blood and cerebrospinal fluid, as cell-free mitochondrial DNA (cf-mtDNA). In clinical studies, blood cf-mtDNA predicts mortality and higher cf-mtDNA levels are associated with mental and physical stress. However, the dynamics of cf-mtDNA has not been defined, and whether it can be measured non-invasively like other neuroendocrine markers in saliva has not been examined. Here we report cf-mtDNA in human saliva and establish its natural within-person dynamic behavior across multiple weeks. In a small proof-of-principle cohort of healthy adults, we first develop an approach to rapidly quantify salivary cf-mtDNA without DNA isolation, and demonstrate the existence of salivary cf-mtDNA. We then deploy this approach to perform an intensive repeated-measures analysis of two healthy men studied at 4 daily timepoints over 53-60 consecutive days (n = 212-220 observations each) with parallel measures of steroid hormones, self-reported daily mood, and health-related behaviors. Salivary cf-mtDNA exhibited a robust awakening response reaching up to two orders of magnitude 30-45 min after awakening, varied from day-to-day, and moderately correlated with the cortisol awakening response. In exploratory analyses, no consistent association with self-reported daily mood/health-related behaviors were found, although this requires further examination in future studies. Dynamic variation in cf-mtDNA was inversely related with salivary interleukin 6 (IL-6), inconsistent with a pro-inflammatory effect of salivary cf-mtDNA. The highly dynamic behavior of salivary cf-mtDNA opens the door to non-invasive studies examining the relevance of mtDNA signaling in relation to human health.

The Diurnal Blood Metabolome and Effects of Vitamin D Supplementation: A Randomised Crossover Trial in Postmenopausal Women

A way to maintain an adequate vitamin D status is through supplementation. Demonstration of blood-metabolome rhythmicity of vitamin D3 post-dosing effects is lacking in the pharmaco-metabonomics area. Thus, the overall aim of this study was to investigate the diurnal changes in the blood metabolome and how these are affected by vitamin D3 supplementation. The study was conducted as a crossover study, and the treatment included 200 µg (8000 IU) of vitamin D3 as compared with placebo with a washout period of at least 10 days. The participants were postmenopausal women aged 60−80 years (N = 29) with vitamin D insufficiency (serum 25-hydroxyvitamin D < 50 nmol/L) but otherwise healthy. During the intervention day, blood samples were taken at 0 h, 2 h, 4 h, 6 h, 8 h, 10 h, 12 h, and 24 h, and plasma was analysed by proton nuclear magnetic resonance (NMR) spectroscopy as a metabolomics approach. In general, diurnal effects were identified for the majority of the 20 quantified metabolites, and hierarchical cluster analysis revealed a change in the overall plasma metabolome around 12 AM (6 h after intervention), suggesting that the diurnal rhythm is reflected in two diurnal plasma metabolomes; a morning metabolome (8−12 AM) and an afternoon/evening metabolome (2−8 PM). Overall, the effect of vitamin D supplementation on the blood metabolome was minor, with no effect on the diurnal rhythm. However, a significant effect of the vitamin D supplementation on plasma acetone levels was identified. Collectively, our findings reveal an influence of diurnal rhythm on the plasma metabolome, while vitamin D supplementation appears to have minor influence on fluctuations in the plasma metabolome.

An Overview of the Latest Metabolomics Studies on Atopic Eczema with New Directions for Study

Atopic eczema (AE) is an inflammatory skin disorder affecting approximately 20% of children worldwide and early onset can lead to asthma and allergies. Currently, the mechanisms of the disease are not fully understood. Metabolomics, the analysis of small molecules in the skin produced by the host and microbes, opens a window to observe the mechanisms of the disease which then may lead to new drug targets for AE treatment. Here, we review the latest advances in AE metabolomics, highlighting both the lipid and non-lipid molecules, along with reviewing the metabolites currently known to reside in the skin.

Circadian rhythm of lipid metabolism

Lipids comprise a diverse group of metabolites that are indispensable as energy storage molecules, cellular membrane components and mediators of inter- and intra-cellular signaling processes. Lipid homeostasis plays a crucial role in maintaining metabolic health in mammals including human beings. A growing body of evidence suggests that the circadian clock system ensures temporal orchestration of lipid homeostasis, and that perturbation of such diurnal regulation leads to the development of metabolic disorders comprising obesity and type 2 diabetes. In view of the emerging role of circadian regulation in maintaining lipid homeostasis, in this review, we summarize the current knowledge on lipid metabolic pathways controlled by the mammalian circadian system. Furthermore, we review the emerging connection between the development of human metabolic diseases and changes in lipid metabolites that belong to major classes of lipids. Finally, we highlight the mechanisms underlying circadian organization of lipid metabolic rhythms upon the physiological situation, and the consequences of circadian clock dysfunction for dysregulation of lipid metabolism.

Assessment of Plasma-Endogenous Opioid Neuropeptide Levels and Psychometric Properties of Non-Suicidal Self-Injury in Adolescents

OBJECTIVE

Non-suicidal self-injury (NSSI) is one of the most common mental health problems and growing public-health issues, coupled with a significant population-level burden among adolescents in both developed and developing countries. We aimed to assess the role of endogenous opioid system-emotion regulation circuitry in NSSI through measurement of plasma beta-endorphin (β-EP), met-enkephalin (MENK) levels, and determination of psychometric features of Turkish adolescent subjects.

METHOD

In this research, we measured plasma β-EP and MENK levels of 49 adolescents with NSSI and 39 control subjects without NSSI between the ages of 12-18 years. All adolescent subjects were observed in the outpatient clinic, and their clinical and sociodemographic characteristics were examined. All subjects were assessed using the Brief Symptom Inventory (BSI) and Inventory of Statements About Self Injury (ISAS).

RESULTS

Plasma β-EP levels were statistically lower in adolescents with NSSI than control group, whereas there was no statistically significant difference in MENK levels. β-EP levels showed a negative correlation with depression severity. The data obtained from BSI and ISAS were not found to be associated with both β-EP and MENK levels, while subscale scores exhibited versatile correlations.

CONCLUSION

Our findings supported the salient role of β-EP in NSSI behavior. Also, decreased plasma β-EP could be assessed as a reliable indicator for NSSI. However, it is possible that measurement of basal plasma levels of neuropeptides might also bring many confounders and could cause bias. Therefore, repeated measurements of plasma-endogenous opioid neuropeptides in a time-dependent manner-concomitant to engage of NSSI behavior-might give more reliable results.

The Impact of Meal Timing on Risk of Weight Gain and Development of Obesity: a Review of the Current Evidence and Opportunities for Dietary Intervention

PURPOSE OF REVIEW

The aim of this short review is to provide an updated commentary on the current literature examining the impact of meal timing on obesity and weight gain in adults. The potential mechanisms, including novel and emerging factors, behind timing of food intake across the 24-h period in the development of obesity, and dietary strategies manipulating meal timing to ameliorate weight gain are also explored.

RECENT FINDINGS

Dietary patterns that feature meal timing outside of the regular daytime hours can contribute to circadian disruption as food is metabolised in opposition to internal daily rhythms and can feedback on the timekeeping mechanisms setting these rhythms. Epidemiological evidence examining the impact of late meal timing patterns is beginning to suggest that eating at night increases the risk of weight gain over time. Mechanisms contributing to this include changes to the efficiency of metabolism across the day, and dysregulation of appetite hormone and gut microbiota by mis-timed meals. When meals are eaten, in relation to the time of day, is increasingly considered of importance when implementing dietary change in order to address the growing burden of obesity, although further research is required in order to determine optimal patterns.

Circadian lipid and hepatic protein rhythms shift with a phase response curve different than melatonin

While studies suggest that light and feeding patterns can reset circadian rhythms in various metabolites, whether these shifts follow a predictable pattern is unknown. We describe the first phase response curves (PRC) for lipids and hepatic proteins in response to combined light and food stimuli. The timing of plasma rhythms was assessed by constant routine before and after exposure to a combined 6.5-hour blue light exposure and standard meal schedule, which was systematically varied by ~20° between in0000dividuals. We find that the rhythms shift according to a PRC, with generally greater shifts for lipids and liver proteins than for melatonin. PRC timing varies relative to the stimulus, with albumin and triglyceride PRCs peaking at a time similar to melatonin whereas the cholesterol and high-density lipoprotein PRCs are offset by ~12 h. These data have important implications for treating circadian misalignment in shiftworkers who consume meals and are exposed to light around the clock.

Presence of human breast cancer xenograft changes the diurnal profile of amino acids in mice

Human xenografts are extremely useful models to study the biology of human cancers and the effects of novel potential therapies. Deregulation of metabolism, including changes in amino acids (AAs), is a common characteristic of many human neoplasms. Plasma AAs undergo daily variations, driven by circadian endogenous and exogenous factors. We compared AAs concentration in triple negative breast cancer MDA-MB-231 cells and MCF10A non-tumorigenic immortalized breast epithelial cells. We also measured plasma AAs in mice bearing xenograft MDA-MB-231 and compared their levels with non-tumor-bearing control animals over 24 h. In vitro studies revealed that most of AAs were significantly different in MDA-MB-231 cells when compared with MCF10A. Plasma concentrations of 15 AAs were higher in cancer cells, two were lower and four were observed to shift across 24 h. In the in vivo setting, analysis showed that 12 out of 20 AAs varied significantly between tumor-bearing and non-tumor bearing mice. Noticeably, these metabolites peaked in the dark phase in non-tumor bearing mice, which corresponds to the active time of these animals. Conversely, in tumor-bearing mice, the peak time occurred during the light phase. In the early period of the light phase, these AAs were significantly higher in tumor-bearing animals, yet significantly lower in the middle of the light phase when compared with controls. This pilot study highlights the importance of well controlled experiments in studies involving plasma AAs in human breast cancer xenografts, in addition to emphasizing the need for more precise examination of exometabolomic changes using multiple time points.

Nutrient timing and metabolic regulation symposium review from "Novel dietary approaches to appetite regulation, health and performance (2021)"

Daily (circadian) rhythms coordinate our physiology and behaviour with regular environmental changes. Molecular clocks in peripheral tissues (e.g. liver, skeletal muscle and adipose) give rise to rhythms in macronutrient metabolism, appetite regulation and the components of energy balance such that our bodies can align the periodic delivery of nutrients with ongoing metabolic requirements. The timing of meals both in absolute terms (i.e. relative to clock time) and in relative terms (i.e. relative to other daily events) is therefore relevant to metabolism and health. Experimental manipulation of feeding–fasting cycles can advance understanding of the effect of absolute and relative timing of meals on metabolism and health. Such studies have extended the overnight fast by regular breakfast omission and revealed that morning fasting can alter the metabolic response to subsequent meals later in the day, whilst also eliciting compensatory behavioural responses (i.e. reduced physical activity). Similarly, restricting energy intake via alternate‐day fasting also has the potential to elicit a compensatory reduction in physical activity, and so can undermine weight‐loss efforts (i.e. to preserve body fat stores). Interrupting the usual overnight fast (and therefore also the usual sleep cycle) by nocturnal feeding has also been examined and further research is needed to understand the importance of this period for either nutritional intervention or nutritional withdrawal. In summary, it is important for dietary guidelines for human health to consider nutrient timing (i.e. when we eat) alongside the conventional focus on nutrient quantity and nutrient quality (i.e. how much we eat and what we eat).

Metabolic Impairment in Coronary Artery Disease: Elevated Serum Acylcarnitines Under the Spotlights

Coronary artery disease (CAD) remains the leading cause of death worldwide. Expanding patients' metabolic phenotyping beyond clinical chemistry investigations could lead to earlier recognition of disease onset and better prevention strategies. Additionally, metabolic phenotyping, at the molecular species level, contributes to unravel the roles of metabolites in disease development. In this cross-sectional study, we investigated clinically healthy individuals (n = 116, 65% male, 70.8 ± 8.7 years) and patients with CAD (n = 54, 91% male, 67.0 ± 11.5 years) of the COmPLETE study. We applied a high-coverage quantitative liquid chromatography-mass spectrometry approach to acquire a comprehensive profile of serum acylcarnitines, free carnitine and branched-chain amino acids (BCAAs), as markers of mitochondrial health and energy homeostasis. Multivariable linear regression analyses, adjusted for confounders, were conducted to assess associations between metabolites and CAD phenotype. In total, 20 short-, medium- and long-chain acylcarnitine species, along with L-carnitine, valine and isoleucine were found to be significantly (adjusted p ≤ 0.05) and positively associated with CAD. For 17 acylcarnitine species, associations became stronger as the number of affected coronary arteries increased. This implies that circulating acylcarnitine levels reflect CAD severity and might play a role in future patients' stratification strategies. Altogether, CAD is characterized by elevated serum acylcarnitine and BCAA levels, which indicates mitochondrial imbalance between fatty acid and glucose oxidation.

Rapid and reversible control of human metabolism by individual sleep states

Sleep is crucial to restore body functions and metabolism across nearly all tissues and cells, and sleep restriction is linked to various metabolic dysfunctions in humans. Using exhaled breath analysis by secondary electrospray ionization high-resolution mass spectrometry, we measured the human exhaled metabolome at 10-s resolution across a night of sleep in combination with conventional polysomnography. Our subsequent analysis of almost 2,000 metabolite features demonstrates rapid, reversible control of major metabolic pathways by the individual vigilance states. Within this framework, whereas a switch to wake reduces fatty acid oxidation, a switch to slow-wave sleep increases it, and the transition to rapid eye movement sleep results in elevation of tricarboxylic acid (TCA) cycle intermediates. Thus, in addition to daily regulation of metabolism, there exists a surprising and complex underlying orchestration across sleep and wake. Both likely play an important role in optimizing metabolic circuits for human performance and health.

Multi-omics driven predictions of response to acute phase combination antidepressant therapy: a machine learning approach with cross-trial replication

Combination antidepressant pharmacotherapies are frequently used to treat major depressive disorder (MDD). However, there is no evidence that machine learning approaches combining multi-omics measures (e.g., genomics and plasma metabolomics) can achieve clinically meaningful predictions of outcomes to combination pharmacotherapy. This study examined data from 264 MDD outpatients treated with citalopram or escitalopram in the Mayo Clinic Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) and 111 MDD outpatients treated with combination pharmacotherapies in the Combined Medications to Enhance Outcomes of Antidepressant Therapy (CO-MED) study to predict response to combination antidepressant therapies. To assess whether metabolomics with functionally validated single-nucleotide polymorphisms (SNPs) improves predictability over metabolomics alone, models were trained/tested with and without SNPs. Models trained with PGRN-AMPS' and CO-MED's escitalopram/citalopram patients predicted response in CO-MED's combination pharmacotherapy patients with accuracies of 76.6% (p < 0.01; AUC: 0.85) without and 77.5% (p < 0.01; AUC: 0.86) with SNPs. Then, models trained solely with PGRN-AMPS' escitalopram/citalopram patients predicted response in CO-MED's combination pharmacotherapy patients with accuracies of 75.3% (p < 0.05; AUC: 0.84) without and 77.5% (p < 0.01; AUC: 0.86) with SNPs, demonstrating cross-trial replication of predictions. Plasma hydroxylated sphingomyelins were prominent predictors of treatment outcomes. To explore the relationship between SNPs and hydroxylated sphingomyelins, we conducted multi-omics integration network analysis. Sphingomyelins clustered with SNPs and metabolites related to monoamine neurotransmission, suggesting a potential functional relationship. These results suggest that integrating specific metabolites and SNPs achieves accurate predictions of treatment response across classes of antidepressants. Finally, these results motivate functional investigation into how sphingomyelins might influence MDD pathophysiology, antidepressant response, or both.

Clinical lipidomics: realizing the potential of lipid profiling

Dysregulation of lipid metabolism plays a major role in the etiology and sequelae of inflammatory disorders, cardiometabolic and neurological diseases, and several forms of cancer. Recent advances in lipidomic methodology allow comprehensive lipidomic profiling of clinically relevant biological samples, enabling researchers to associate lipid species and metabolic pathways with disease onset and progression. The resulting data serve not only to advance our fundamental knowledge of the underlying disease process but also to develop risk assessment models to assist in the diagnosis and management of disease. Currently, clinical applications of in-depth lipidomic profiling are largely limited to the use of research-based protocols in the analysis of population or clinical sample sets. However, we foresee the development of purpose-built clinical platforms designed for continuous operation and clinical integration-assisting health care providers with disease risk assessment, diagnosis, and monitoring. Herein, we review the current state of clinical lipidomics, including the use of research-based techniques and platforms in the analysis of clinical samples as well as assays already available to clinicians. With a primary focus on MS-based strategies, we examine instrumentation, analysis techniques, statistical models, prospective design of clinical platforms, and the possible pathways toward implementation of clinical lipidomics.

Maternal Plasma Metabolic Profile Demarcates a Role for Neuroinflammation in Non-Typical Development of Children

Maternal and cord plasma metabolomics were used to elucidate biological pathways associated with increased diagnosis risk for autism spectrum disorders (ASD). Metabolome-wide associations were assessed in both maternal and umbilical cord plasma in relation to diagnoses of ASD and other non-typical development (Non-TD) compared to typical development (TD) in the Markers of Autism risk in Babies: Learning Early Signs (MARBLES) cohort study of children born to mothers who already have at least one child with ASD. Analyses were stratified by sample matrix type, machine mode, and annotation confidence level. Dimensionality reduction techniques were used [i.e, principal component analysis (PCA) and random subset weighted quantile sum regression (WQSRS)] to minimize the high multiple comparison burden. With WQSRS, a metabolite mixture obtained from the negative mode of maternal plasma decreased the odds of Non-TD compared to TD. These metabolites, all related to the prostaglandin pathway, underscored the relevance of neuroinflammation status. No other significant findings were observed. Dimensionality reduction strategies provided confirming evidence that a set of maternal plasma metabolites are important in distinguishing Non-TD compared to TD diagnosis. A lower risk for Non-TD was linked to anti-inflammatory elements, thereby linking neuroinflammation to detrimental brain function consistent with studies ranging from neurodevelopment to neurodegeneration.

Identification of a Preliminary Plasma Metabolome-based Biomarker for Circadian Phase in Humans

Measuring individual circadian phase is important to diagnose and treat circadian rhythm sleep-wake disorders and circadian misalignment, inform chronotherapy, and advance circadian science. Initial findings using blood transcriptomics to predict the circadian phase marker dim-light melatonin onset (DLMO) show promise. Alternatively, there are limited attempts using metabolomics to predict DLMO and no known omics-based biomarkers predict dim-light melatonin offset (DLMOff). We analyzed the human plasma metabolome during adequate and insufficient sleep to predict DLMO and DLMOff using one blood sample. Sixteen (8 male/8 female) healthy participants aged 22.4 ± 4.8 years (mean ± SD) completed an in-laboratory study with 3 baseline days (9 h sleep opportunity/night), followed by a randomized cross-over protocol with 9-h adequate sleep and 5-h insufficient sleep conditions, each lasting 5 days. Blood was collected hourly during the final 24 h of each condition to independently determine DLMO and DLMOff. Blood samples collected every 4 h were analyzed by untargeted metabolomics and were randomly split into training (68%) and test (32%) sets for biomarker analyses. DLMO and DLMOff biomarker models were developed using partial least squares regression in the training set followed by performance assessments using the test set. At baseline, the DLMOff model showed the highest performance (0.91 R2 and 1.1 ± 1.1 h median absolute error ± interquartile range [MdAE ± IQR]), with significantly (p < 0.01) lower prediction error versus the DLMO model. When all conditions (baseline, 9 h, and 5 h) were included in performance analyses, the DLMO (0.60 R2; 2.2 ± 2.8 h MdAE; 44% of the samples with an error under 2 h) and DLMOff (0.62 R2; 1.8 ± 2.6 h MdAE; 51% of the samples with an error under 2 h) models were not statistically different. These findings show promise for metabolomics-based biomarkers of circadian phase and highlight the need to test biomarkers that predict multiple circadian phase markers under different physiological conditions.

Tick-Tock Consider the Clock: The Influence of Circadian and External Cycles on Time of Day Variation in the Human Metabolome-A Review

The past decade has seen a large influx of work investigating time of day variation in different human biofluid and tissue metabolomes. The driver of this daily variation can be endogenous circadian rhythms driven by the central and/or peripheral clocks, or exogenous diurnal rhythms driven by behavioural and environmental cycles, which manifest as regular 24 h cycles of metabolite concentrations. This review, of all published studies to date, establishes the extent of daily variation with regard to the number and identity of 'rhythmic' metabolites observed in blood, saliva, urine, breath, and skeletal muscle. The probable sources driving such variation, in addition to what metabolite classes are most susceptible in adhering to or uncoupling from such cycles is described in addition to a compiled list of common rhythmic metabolites. The reviewed studies show that the metabolome undergoes significant time of day variation, primarily observed for amino acids and multiple lipid classes. Such 24 h rhythms, driven by various factors discussed herein, are an additional source of intra/inter-individual variation and are thus highly pertinent to all studies applying untargeted and targeted metabolomics platforms, particularly for the construction of biomarker panels. The potential implications are discussed alongside proposed minimum reporting criteria suggested to acknowledge time of day variation as a potential influence of results and to facilitate improved reproducibility.

Screening of lipid metabolism biomarkers in patients with coronary heart disease via ultra-performance liquid chromatography-high resolution mass spectrometry

Coronary heart disease (CHD) has a high mortality worldwide. This study aimed to screen lipid metabolism biomarkers in patients with coronary heart disease via ultra-performance liquid chromatography-high resolution mass spectrometry. Extraction and reconstitution solvents, liquid chromatographic and mass spectrometry conditions were optimized to detect more plasma lipid metabolites. In this study, the chromatographic and mass spectra characteristics of lipid metabolites were summarized. A total of 316 lipid metabolites were annotated via diagnostic fragment ion filtration, nitrogen rule filtration, and neutral loss filtration. Glycerophospholipid metabolism and sphingolipid metabolism were revealed as the main lipid disorders of CHD. This study provides a novel insight for high-throughput detection of lipid metabolites in plasma and provides a further understanding of the occurrence of CHD, which can provide valuable suggestions for the prevention of CHD.

Stability of amino acids and related amines in human serum under different preprocessing and pre-storage conditions based on iTRAQ®-LC-MS/MS

Amino acid analysis or metabonomics requires large-scale sample collection, which makes sample storage a critical consideration. However, functional amino acids are often neglected in metabolite stability studies because of the difficulty in detecting and accurately quantifying them with most analysis methods. Here, we investigated the stability of amino acids and related amines in human serum following different preprocessing and pre-storage procedures. Serum samples were collected and subjected to three storage conditions; cold storage (4°C), room temperature storage (22°C), and freezing (−80°C). The concentration of amino acids and related amines were quantified using iTRAQ^®-LC-MS/MS with isobaric tagging reagents. Approximately 54.84%, 58.06%, and 48.39% of detectable and target analytes were altered at the 4°C condition, 22°C condition, and when subjected to freeze-thaw cycles, respectively. Some amino acids which are unstable and relatively stable were found. Our study provides detailed amino acid profiles in human serum and suggests pre-treatment measures that could be taken to improve stability.

Summary: We investigated the stability of amino acids in serum samples that underwent prolonged storage at 4°C and 22°C, and repeated freeze-thaw cycles at −80°C using stable isotope iTRAQ labeling and liquid chromatography tandem mass spectrometry.

Metabolic Profiling Indicates Diversity in the Metabolic Physiologies Associated With Maternal Postpartum Depressive Symptoms

Background: Postpartum depression (PPD) is a devastating disease requiring improvements in diagnosis and prevention. Blood metabolomics identifies biological markers discriminatory between women with and those without antenatal depressive symptoms. Whether this cutting-edge method can be applied to postpartum depressive symptoms merits further investigation. Methods: As a substudy within the Biology, Affect, Stress, Imagine and Cognition Study, 24 women with PPD symptom (PPDS) assessment at 6 weeks postpartum were included. Controls were selected as having a score of ≤ 6 and PPDS cases as ≥12 on the Edinburgh Postnatal Depression Scale. Blood plasma was collected at 10 weeks postpartum and analyzed with gas chromatography-mass spectrometry metabolomics. Results: Variations of metabolomic profiles within the PPDS samples were identified. One cluster showed altered kidney function, whereas the other, a metabolic syndrome profile, both previously associated with depression. Five metabolites (glycerol, threonine, 2-hydroxybutanoic acid, erythritol, and phenylalanine) showed higher abundance among women with PPDSs, indicating perturbations in the serine/threonine and glycerol lipid metabolism, suggesting oxidative stress conditions. Conclusions: Alterations in certain metabolites were associated with depressive pathophysiology postpartum, whereas diversity in PPDS physiologies was revealed. Hence, plasma metabolic profiling could be considered in diagnosis and pathophysiological investigation of PPD toward providing clues for treatment. Future studies require standardization of various subgroups with respect to symptom onset, lifestyle, and comorbidities.

Loss of function in the Drosophila clock gene period results in altered intermediary lipid metabolism and increased susceptibility to starvation

The fruit fly Drosophila is a prime model in circadian research, but still little is known about its circadian regulation of metabolism. Daily rhythmicity in levels of several metabolites has been found, but knowledge about hydrophobic metabolites is limited. We here compared metabolite levels including lipids between period01 (per01) clock mutants and Canton-S wildtype (WTCS) flies in an isogenic and non-isogenic background using LC-MS. In the non-isogenic background, metabolites with differing levels comprised essential amino acids, kynurenines, pterinates, glycero(phospho)lipids, and fatty acid esters. Notably, detectable diacylglycerols (DAG) and acylcarnitines (AC), involved in lipid metabolism, showed lower levels in per01 mutants. Most of these differences disappeared in the isogenic background, yet the level differences for AC as well as DAG were consistent for fly bodies. AC levels were dependent on the time of day in WTCS in phase with food consumption under LD conditions, while DAGs showed weak daily oscillations. Two short-chain ACs continued to cycle even in constant darkness. per01 mutants in LD showed no or very weak diel AC oscillations out of phase with feeding activity. The low levels of DAGs and ACs in per01 did not correlate with lower total food consumption, body mass or weight. Clock mutant flies showed higher sensitivity to starvation independent of their background-dependent activity level. Our results suggest that neither feeding, energy storage nor mobilisation is significantly affected in per01 mutants, but point towards impaired mitochondrial activity, supported by upregulation of the mitochondrial stress marker 4EBP in the clock mutants.

Day-night rhythm of skeletal muscle metabolism is disturbed in older, metabolically compromised individuals

OBJECTIVE

Skeletal muscle mitochondrial function and energy metabolism displays day-night rhythmicity in healthy, young individuals. Twenty-four-hour rhythmicity of metabolism has been implicated in the etiology of age-related metabolic disorders. Whether day-night rhythmicity in skeletal muscle mitochondrial function and energy metabolism is altered in older, metabolically comprised humans remains unknown.

METHODS

Twelve male overweight volunteers with impaired glucose tolerance and insulin sensitivity stayed in a metabolic research unit for 2 days under free living conditions with regular meals. Indirect calorimetry was performed at 5 time points (8 AM, 1 PM, 6 PM, 11 PM, 4 AM), followed by a muscle biopsy. Mitochondrial oxidative capacity was measured in permeabilized muscle fibers using high-resolution respirometry.

RESULTS

Mitochondrial oxidative capacity did not display rhythmicity. The expression of circadian core clock genes BMAL1 and REV-ERBα showed a clear day-night rhythm (p < 0.001), peaking at the end of the waking period. Remarkably, the repressor clock gene PER2 did not show rhythmicity, whereas PER1 and PER3 were strongly rhythmic (p < 0.001). On the whole-body level, resting energy expenditure was highest in the late evening (p < 0.001). Respiratory exchange ratio did not decrease during the night, indicating metabolic inflexibility.

CONCLUSIONS

Mitochondrial oxidative capacity does not show a day-night rhythm in older, overweight participants with impaired glucose tolerance and insulin sensitivity. In addition, gene expression of PER2 in skeletal muscle indicates that rhythmicity of the negative feedback loop of the molecular clock is disturbed. CLINICALTRIALS.

GOV ID

NCT03733743.

Crosstalk between circadian rhythms and the microbiota

Circadian rhythms influence daily molecular oscillations in gene/protein expression and aspects of biology and physiology, including behaviour, body temperature and sleep–wake cycles. These circadian rhythms have been associated with a number of metabolic, immune and microbial changes that correlate with health and susceptibility to disease, including infection. While light is the main inducer of circadian rhythms, other factors, including the microbiota, can have important effects on peripheral rhythms. The microbiota have been of significant interest to many investigators over the past decade, with the development of molecular techniques to identify large numbers of species and their function. These studies have shown microbial associations with disease susceptibility, and some of these have demonstrated that alterations in microbiota cause disease. Microbial circadian oscillations impact host metabolism and immunity directly and indirectly. Interestingly, microbial oscillations also regulate host circadian rhythms, and the host circadian rhythms in turn modulate microbial composition. Thus, it is of considerable interest and importance to understand the crosstalk between circadian rhythms and microbiota and especially the microbial influences on the host. In this review, we aim to discuss the role of circadian microbial oscillations and how they influence host immunity. In addition, we discuss how host circadian rhythms can also modulate microbial rhythms. We also discuss potential connections between microbes and circadian rhythms and how these may be used therapeutically to maximize clinical success.

Time-restricted feeding mice a high-fat diet induces a unique lipidomic profile

Time-restricted feeding (TRF) can reduce adiposity and lessen the co-morbidities of obesity. Mice consuming obesogenic high-fat (HF) diets develop insulin resistance and hepatic steatosis, but have elevated indices of long-chain polyunsaturated fatty acids (LCPUFA) that may be beneficial. While TRF impacts lipid metabolism, scant data exist regarding the impact of TRF upon lipidomic composition of tissues. We (1) tested the hypothesis that TRF of a HF diet elevates LCPUFA indices while preventing insulin resistance and hepatic steatosis and (2) determined the impact of TRF upon the lipidome in plasma, liver, and adipose tissue. For 12 weeks, male, adult mice were fed a control diet ad libitum, a HF diet ad libitum (HF-AL), or a HF diet with TRF, 12 hours during the dark phase (HF-TRF). HF-TRF prevented insulin resistance and hepatic steatosis resulting from by HF-AL treatment. TRF-blocked plasma increases in LCPUFA induced by HF-AL treatment but elevated concentrations of triacylglycerols and non-esterified saturated fatty acids. Analysis of the hepatic lipidome demonstrated that TRF did not elevate LCPUFA while reducing steatosis. However, TRF created (1) a separate hepatic lipid signature for triacylglycerols, phosphatidylcholine, and phosphatidylethanolamine species and (2) modified gene and protein expression consistent with reduced fatty acid synthesis and restoration of diurnal gene signaling. TRF increased the saturated fatty acid content in visceral adipose tissue. In summary, TRF of a HF diet alters the lipidomic profile of plasma, liver, and adipose tissue, creating a third distinct lipid metabolic state indicative of positive metabolic adaptations following HF intake.

Metabolomics Pilot Study Identifies Desynchronization of 24-H Rhythms and Distinct Intra-patient Variability Patterns in Critical Illness: A Preliminary Report

Background: Synchronized circadian rhythms play a key role in coordinating physiologic health. Desynchronized circadian rhythms may predispose individuals to disease or be indicative of underlying disease. Intensive care unit (ICU) patients likely experience desynchronized circadian rhythms due to disruptive environmental conditions in the ICU and underlying pathophysiology. This observational pilot study was undertaken to determine if 24-h rhythms are altered in ICU patients relative to healthy controls by profiling 24-h rhythms in vital signs and plasma metabolites.

Methods: We monitored daily rhythms in 5 healthy controls and 5 ICU patients for 24 h. Heart rate and blood pressure were measured every 30 min, temperature was measured every hour, and blood was sampled for mass spectrometry-based plasma metabolomics every 4 h. Bedside sound levels were measured every minute. Twenty-four hours rhythms were evaluated in vitals and putatively identified plasma metabolites individually and in each group using the cosinor method.

Results: ICU patient rooms were significantly louder than healthy controls' rooms and average noise levels were above EPA recommendations. Healthy controls generally had significant 24-h rhythms individually and as a group. While a few ICU patients had significant 24-h rhythms in isolated variables, no significant rhythms were identified in ICU patients as a group, except in cortisol. This indicates a lack of coherence in phases and amplitudes among ICU patients. Finally, principal component analysis of metabolic profiles showed surprising patterns in plasma sample clustering. Each ICU patient's samples were clearly discernable in individual clusters, separate from a single cluster of healthy controls.

Conclusions: In this pilot study, ICU patients' 24-h rhythms show significant desynchronization compared to healthy controls. Clustering of plasma metabolic profiles suggests that metabolomics could be used to track individual patients' clinical courses longitudinally. Our results show global disordering of metabolism and the circadian system in ICU patients which should be characterized further in order to determine implications for patient care.

Novel Approaches for Assessing Circadian Rhythmicity in Humans: A Review

The temporal organization of molecular and physiological processes is driven by environmental and behavioral cycles as well as by self-sustained molecular circadian oscillators. Quantification of phase, amplitude, period, and disruption of circadian oscillators is essential for understanding their contribution to sleep-wake disorders, social jet lag, interindividual differences in entrainment, and the development of chrono-therapeutics. Traditionally, assessment of the human circadian system, and the output of the SCN in particular, has required collection of long time series of univariate markers such as melatonin or core body temperature. Data were collected in specialized laboratory protocols designed to control for environmental and behavioral influences on rhythmicity. These protocols are time-consuming, expensive, and not practical for assessing circadian status in patients or in participants in epidemiologic studies. Novel approaches for assessment of circadian parameters of the SCN or peripheral oscillators have been developed. They are based on machine learning or mathematical model-informed analyses of features extracted from 1 or a few samples of high-dimensional data, such as transcriptomes, metabolomes, long-term simultaneous recording of activity, light exposure, skin temperature, and heart rate or in vitro approaches. Here, we review whether these approaches successfully quantify parameters of central and peripheral circadian oscillators as indexed by gold standard markers. Although several approaches perform well under entrained conditions when sleep occurs at night, the methods either perform worse in other conditions such as shift work or they have not been assessed under any conditions other than entrainment and thus we do not yet know how robust they are. Novel approaches for the assessment of circadian parameters hold promise for circadian medicine, chrono-therapeutics, and chrono-epidemiology. There remains a need to validate these approaches against gold standard markers, in individuals of all sexes and ages, in patient populations, and, in particular, under conditions in which behavioral cycles are displaced.

Developing preliminary blood metabolomics-based biomarkers of insufficient sleep in humans

STUDY OBJECTIVE

Identify small molecule biomarkers of insufficient sleep using untargeted plasma metabolomics in humans undergoing experimental insufficient sleep.

METHODS

We conducted a crossover laboratory study where 16 normal-weight participants (eight men; age 22 ± 5 years; body mass index < 25 kg/m2) completed three baseline days (9 hours sleep opportunity per night) followed by 5-day insufficient (5 hours sleep opportunity per night) and adequate (9 hours sleep opportunity per night) sleep conditions. Energy balanced diets were provided during baseline, with ad libitum energy intake provided during the insufficient and adequate sleep conditions. Untargeted plasma metabolomics analyses were performed using blood samples collected every 4 hours across the final 24 hours of each condition. Biomarker models were developed using logistic regression and linear support vector machine (SVM) algorithms.

RESULTS

The top-performing biomarker model was developed by linear SVM modeling, consisted of 65 compounds, and discriminated insufficient versus adequate sleep with 74% overall accuracy and a Matthew's Correlation Coefficient of 0.39. The compounds in the top-performing biomarker model were associated with ATP Binding Cassette Transporters in Lipid Homeostasis, Phospholipid Metabolic Process, Plasma Lipoprotein Remodeling, and sphingolipid metabolism.

CONCLUSION

We identified potential metabolomics-based biomarkers of insufficient sleep in humans. Although our current biomarkers require further development and validation using independent cohorts, they have potential to advance our understanding of the negative consequences of insufficient sleep, improve diagnosis of poor sleep health, and could eventually help identify targets for countermeasures designed to mitigate the negative health consequences of insufficient sleep.

Find the Needle in the Haystack, Then Find It Again: Replication and Validation in the 'Omics Era

Advancements in high-throughput technologies have made it feasible to study thousands of biological pathways simultaneously for a holistic assessment of health and disease risk via ‘omics platforms. A major challenge in ‘omics research revolves around the reproducibility of findings—a feat that hinges upon balancing false-positive associations with generalizability. Given the foundational role of reproducibility in scientific inference, replication and validation of ‘omics findings are cornerstones of this effort. In this narrative review, we define key terms relevant to replication and validation, present issues surrounding each concept with historical and contemporary examples from genomics (the most well-established and upstream ‘omics), discuss special issues and unique considerations for replication and validation in metabolomics (an emerging field and most downstream ‘omics for which best practices remain yet to be established), and make suggestions for future research leveraging multiple ‘omics datasets.

Fasting blood triglycerides vary with circadian phase in both young and older people

Daily rhythms in several physiological processes are important for cardiometabolic health. The lipid panel is used clinically to assess cardiovascular disease risk, but previous attempts to demonstrate circadian variation in lipids have failed to uncouple the endogenous circadian rhythm from the effects of meals and wake duration. Changes in basal lipid levels and dampening of circadian rhythms have been reported with aging, but it is unknown whether aging is also associated with changes in the rhythmic variation of lipids. We measured fasting lipid panels (triglycerides, total cholesterol, high-density lipoprotein, and low-density lipoprotein) in blood at wake time in 21 healthy adults using a specialized laboratory protocol that uncouples sleep-wake and activity-related effects from the endogenous circadian rhythm. Young and older adults exhibited endogenous circadian variations in fasting triglycerides, with both groups peaking in the early biological morning. Young adults also exhibited significant circadian rhythmicity in total cholesterol and low-density lipoprotein, while older adults did not exhibit circadian rhythmicity in any other lipids. These results reveal that triglyceride metabolism may be regulated by the central circadian pacemaker. Moreover, our findings may have clinical implications in assessing cardiovascular risk in shift workers and younger adults, since routine measurement of morning/fasting lipids may not fully and reliably assess triglyceride- and other lipid-related biomarkers of cardiovascular disease risk in these groups.

Circadian and Sleep Metabolomics Across Species

Under normal circadian function, metabolic control is temporally coordinated across tissues and behaviors with a 24-h period. However, circadian disruption results in negative consequences for metabolic homeostasis including energy or redox imbalances. Yet, circadian disruption has become increasingly prevalent within today's society due to many factors including sleep loss. Metabolic consequences of both have been revealed by metabolomics analyses of circadian biology and sleep. Specifically, two primary analytical platforms, mass spectrometry and nuclear magnetic resonance spectroscopy, have been used to study molecular clock and sleep influences on overall metabolic rhythmicity. For example, human studies have demonstrated the prevalence of metabolic rhythms in human biology, as well as pan-metabolome consequences of sleep disruption. However, human studies are limited to peripheral metabolic readouts primarily through minimally invasive procedures. For further tissue- and organism-specific investigations, a number of model systems have been studied, based upon the conserved nature of both the molecular clock and sleep across species. Here we summarize human studies as well as key findings from metabolomics studies using mice, Drosophila, and zebrafish. While informative, a limitation in existing literature is a lack of interpretation regarding dynamic synthesis or catabolism within metabolite pools. To this extent, future work incorporating isotope tracers, specific metabolite reporters, and single-cell metabolomics may provide a means of exploring dynamic activity in pathways of interest.

A Metabolomic Approach for Predicting Diurnal Changes in Cortisol

Introduction: The dysregulation of cortisol secretion has been associated with a number of mental health and mood disorders. However, diagnostics for mental health and mood disorders are behavioral and lack biological contexts. Objectives: The goal of this work is to identify volatile metabolites capable of predicting changes in total urinary cortisol across the diurnal cycle for long-term stress monitoring in psychological disorders. Methods: We applied comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry to sample the urinary volatile metabolome using an untargeted approach across three time points in a single day for 60 subjects. Results: The finalized multiple regression model includes 14 volatile metabolites and 7 interaction terms. A review of the selected metabolites suggests pyrrole, 6-methyl-5-hepten-2-one and 1-iodo-2-methylundecane may originate from endogenous metabolic mechanisms influenced by glucocorticoid signaling mechanisms. Conclusion: This analysis demonstrated the feasibility of using specific volatile metabolites for the prediction of secreted cortisol across time.