Metabolomics in Sleep, Insomnia and Sleep Apnea

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.

Mechanism of Panax notoginseng saponins in improving cognitive impairment induced by chronic sleep deprivation based on the integrative analysis of serum metabolomics and network pharmacology

ETHNOPHARMACOLOGICAL RELEVANCE

Panax notoginseng saponin (PNS) has a variety of biological activities, such as improvement of myocardial ischemia, improvement of learning and memory, hypolipidemia, and immunomodulation. However, its protective mechanism on the central nervous system (CNS) is not clear.

AIM OF THE STUDY

The present study initially evaluated the possible mechanism of PNS to improve cognitive dysfunction due to chronic sleep deprivation (CSD).

MATERIALS AND METHODS

In the present study, we used a modified multi-platform aquatic environment sleep deprivation method to induce a cognitively impaired rat model, and explored the mechanism of action of PNS by integrating serum metabolomics and network pharmacology, which was further verified by molecular docking and experiments.

RESULTS

The results showed that PNS significantly shortened the escape latency, increased the target quadrant time and the number of traversing platforms, and attenuated the inflammatory damage in the hippocampal Cornu Ammonis 1 (CA1) region in CSD rats. The non-targeted metabolomics results indicated that 35 biomarkers significantly altered following PNS therapy intervention, with metabolic pathways enriched for the effects of One carbon pool by folate, Riboflavin metabolism, Glycerophospholipid metabolism, Sphingolipid metabolism, Glycerolipid metabolism, Arachidonic acid metabolism, and Tryptophan metabolism. In addition, network pharmacology identified 234 potential targets for PNS intervention in CSD with cognitive impairment. Metabolite-response-enzyme-gene network was constructed by MetaScape and matched with the network pharmacology results to identify a total of five shared targets (LPL, GPAM, HSD11B1, HSD11B2, and SULT2A1) and two metabolic pathways (Sphingolipid metabolism and Steroid hormone biosynthesis). The results of molecular docking revealed that the five active ingredients had good binding ability with the five core targets. qPCR analysis confirmed the ability of PNS to modulate the above five targets.

CONCLUSIONS

The combination of metabolomics and network analysis provides a scientific basis for promoting the clinical application of PNS in cognitive impairment.

Appraising the role of biotics and fermented foods in gut microbiota modulation and sleep regulation

Sleep disturbances are increasingly prevalent, significantly impacting physical and mental health. Recent research reveals a bidirectional relationship between gut microbiota and sleep, mediated through the microbiota-gut-brain axis. This review examines the role of gut microbiota in sleep physiology and explores how biotics, including probiotics, prebiotics, synbiotics, postbiotics, and fermented foods, can enhance sleep quality. Drawing from animal and human studies, we discuss neurobiological mechanisms by which biotics may influence sleep, including modulation of neurotransmitters, immune responses, and hormonal regulation. Key microbial metabolites, such as short-chain fatty acids, are highlighted for their role in supporting sleep-related neurochemical processes. Additionally, this review presents dietary strategies and food processing technologies, like fermentation, as innovative approaches for sleep enhancement. Although promising, the available research has limitations, including small sample sizes, variability in biotic strains and dosages, and reliance on subjective sleep assessments. This review underscores the need for standardized protocols, objective assessments such as polysomnography, and personalized biotic interventions. Emerging findings highlight the therapeutic potential of gut microbiota modulation for sleep improvement, though further large-scale human trials are essential to refine strain selection, dosage, and formulation. This interdisciplinary exploration seeks to advance food-based interventions and holistic strategies for managing sleep disorders and improving quality of life.

Untargeted metabolome atlas for sleep-related phenotypes in the Hispanic community health study/study of Latinos

BACKGROUND

Sleep is essential to maintaining health and wellbeing of individuals, influencing a variety of outcomes from mental health to cardiometabolic disease. This study aims to assess the relationships between various sleep-related phenotypes and blood metabolites.

METHODS

Utilising data from the Hispanic Community Health Study/Study of Latinos, we performed association analyses between 40 sleep-related phenotypes, grouped in several domains (sleep disordered breathing (SDB), sleep duration, sleep timing, self-reported insomnia symptoms, excessive daytime sleepiness (EDS), and heart rate during sleep), and 768 metabolites measured via untargeted metabolomics profiling. Network analysis was employed to visualise and interpret the associations between sleep phenotypes and metabolites.

FINDINGS

The patterns of statistically significant associations between sleep phenotypes and metabolites differed by superpathways, and highlighted subpathways of interest for future studies. For example, primary bile acid metabolism showed the highest cumulative percentage of statistically significant associations across all sleep phenotype domains except for SDB and EDS phenotypes. Several metabolites were associated with multiple sleep phenotypes, from a few domains. Glycochenodeoxycholate, vanillyl mandelate (VMA) and 1-stearoyl-2-oleoyl-GPE (18:0/18:1) were associated with the highest number of sleep phenotypes, while pregnenolone sulfate was associated with all sleep phenotype domains except for sleep duration. N-lactoyl amino acids such as N-lactoyl phenylalanine (lac-Phe), were associated with sleep duration, SDB, sleep timing and heart rate during sleep.

INTERPRETATION

This atlas of sleep-metabolite associations will facilitate hypothesis generation and further study of the metabolic underpinnings of sleep health.

FUNDING

R01HL161012, R35HL135818, R01AG80598.

Linking Gut Microbiota, Oral Microbiota, and Serum Metabolites in Insomnia Disorder: A Preliminary Study

Purpose

Despite recent findings suggesting an altered gut microbiota in those suffering from insomnia disorder (ID), research into the gut microbiota, oral microbiota, serum metabolites, and their interactions in patients with ID is sparse.

Patients and Methods

We collected a total of 114 fecal samples, 133 oral cavity samples and 20 serum samples to characterize the gut microbiota, oral microbiota and serum metabolites in a cohort of 76 ID patients (IDs) and 59 well-matched healthy controls (HCs). We assessed the microbiota as potentially biomarkers for ID for ID by 16S rDNA sequencing and elucidated the interactions involving gut microbiota, oral microbiota and serum metabolites in ID in conjunction with untargeted metabolomics.

Results

Gut and oral microbiota of IDs were dysbiotic. Gut and oral microbial biomarkers could be used to differentiate IDs from HCs. Eleven significantly altered serum metabolites, including adenosine, phenol, and phenol sulfate, differed significantly between groups. In multi-omics analyses, adenosine showed a positive correlation with genus_Lachnospira (p=0.029) and total sleep time (p=0.016). Additionally, phenol and phenol sulphate had a negative correlation with genus_Coprococcus (p=0.0059; p=0.0059) and a positive correlation with Pittsburgh Sleep Quality Index (p=0.006; p=0.006) and Insomnia Severity Index (p=0.021; p=0.021).

Conclusion

Microbiota and serum metabolite changes in IDs are strongly correlated with clinical parameters, implying mechanistic links between altered bacteria, serum metabolites and ID. This study offers novel perspective into the interaction among gut microbiota, oral microbiota, and serum metabolites for ID.

The beneficial effects of modafinil administration on repeat mild traumatic brain injury (RmTBI) pathology in adolescent male rats are not dependent upon the orexinergic system

The sleep-wake cycle plays an influential role in the development and progression of repeat mild traumatic brain injury (RmTBI)-related pathology. Therefore, we first aimed to manipulate the sleep-wake cycle post-RmTBI using modafinil, a wake-promoting substance used for the treatment of narcolepsy. We hypothesized that modafinil would exacerbate RmTBI-induced deficits. Chronic behavioural analyses were completed along with a 27-plex serum cytokine array, metabolomic and proteomic analyses of cerebrospinal fluid (CSF), as well as immunohistochemical staining in structures important for sleep/wake cycles, to examine orexin, melanin-concentrating hormone, tyrosine hydroxylase, and choline acetyltransferase, in the lateral hypothalamus, locus coeruleus, and basal forebrain, respectively. Contrary to expectation, modafinil administration attenuated behavioural deficits, metabolomic changes, and neuropathological modifications. Therefore, the second aim was to determine if the beneficial effects of modafinil treatment were driven by the orexinergic system. The same experimental protocol was used; however, RmTBI rats received chronic orexin-A administration instead of modafinil. Orexin-A administration produced drastically different outcomes, exacerbating anxiety-related and motor deficits, while also significantly disrupting their metabolomic and neuropathological profiles. These results suggest that the beneficial effects of modafinil administration post-RmTBI, work independently of its wake-promoting properties, as activation of the orexinergic wake-promoting system with orexin-A was detrimental. Overall, these findings highlight the complexity of sleep-wake changes in the injured brain and showcase the potential of the arousal and sleep systems in its treatment.

Genetic evidence for the causal impact of insomnia on gastrointestinal diseases and the mediating effects of adiposity traits

BACKGROUND AND AIM

Insomnia has been implicated in gastrointestinal diseases (GIs), but the causal effect between insomnia and GIs and underlying mechanisms remain unknown.

METHODS

By using the released summary-level data, we conducted a two-step Mendelian randomization (MR) analysis to examine the relationship between insomnia and four GIs and estimate the mediating role of candidate mediators. The first step was to investigate the causal association between insomnia and GIs using univariable MR analysis. The second step was to estimate the mediation proportion of selected mediators in these associations using multivariable MR analysis. Subsequently, results from different datasets were combined using the fixed-effect meta-analysis.

RESULTS

Univariable MR analysis provided strong evidence for the causal effects of insomnia on four GIs after Bonferroni correction for multiple comparisons, including peptic ulcer disease (PUD) (odds ratio [OR] = 1.15, 95% interval confidence [CI] = 1.10-1.20, P = 1.83 × 10-9), gastroesophageal reflux (GORD) (OR = 1.19, 95% CI = 1.16-1.22, P = 5.95 × 10-42), irritable bowel syndrome (IBS) (OR = 1.18, 95% CI = 1.15-1.22, P = 8.69 × 10-25), and inflammatory bowel disease (IBD) (OR = 1.09, 95% CI = 1.03-1.05, P = 3.46 × 10-3). In the mediation analysis, body mass index (BMI) and waist-to-hip ratio (WHR) were selected as mediators in the association between insomnia and PUD (BMI: mediation proportion [95% CI]: 13.61% [7.64%-20.70%]; WHR: 8.74% [5.50%-12.44%]) and GORD (BMI: 11.82% [5.94%-18.74%]; WHR: 7.68% [4.73%-11.12%]).

CONCLUSIONS

Our findings suggest that genetically instrumented insomnia has causal effects on PUD, GORD, IBS, and IBD, respectively. Adiposity traits partially mediated the associations between insomnia and GIs. Further clinical studies are warranted to evaluate the protective effect of insomnia treatment on GIs.

Integrated gut microbiome and metabolomic analyses elucidate the therapeutic mechanisms of Suanzaoren decoction in insomnia and depression models

Insomnia and depression are psychiatric disorders linked to substantial health burdens. The gut microbiome and metabolomic pathways are increasingly recognized as key contributors to these conditions' pathophysiology. Suanzaoren Decoction (SZRD), a traditional Chinese herbal formulation, has demonstrated significant therapeutic benefits for both insomnia and depression. This study aims to elucidate the mechanistic effects of SZRD on insomnia and depression by integrating gut microbiome and metabolomic analyses and to assess the differential impacts of SZRD dosages. Using ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS), we identified 66 chemical constituents within SZRD. Behavioral assays indicated that low-dose SZRD (LSZRD) significantly ameliorated insomnia symptoms in rat models, whereas high-dose SZRD (HSZRD) markedly improved depressive behaviors. 16S rRNA sequencing revealed that SZRD modulated gut microbiome dysbiosis induced by insomnia and depression, characterized by an increased abundance of short-chain fatty acid (SCFA)-producing genera. Metabolomic profiling demonstrated reduced plasma amino acid metabolites and disrupted γ-aminobutyric acid (GABA) and L-glutamic acid metabolism in the hippocampus of affected rats. SZRD administration restored fecal SCFA levels and ameliorated metabolic imbalances in both plasma and hippocampal tissues. These findings underscore the pivotal role of gut microbiome modulation and metabolic regulation in the therapeutic effects of SZRD, providing a scientific basis for its use in treating insomnia and depression.

Characteristics of gut flora in children who go to bed early versus late

Investigating the characteristics of the gut flora in children who go to bed early versus late. The study sample consisted of 88 healthy children aged 2-14 years, with an equal number of boys and girls. The researchers collected faecal samples from all participants and sequenced the genome of their gut flora. Findings indicate that beta diversity was statistically significant at the genus level for both the early and late sleeper groups (P = 0.045). Furthermore, alpha diversity indicators, including Simpson's index (P = 0.0011) and Shannon's index (P = 0.0013), exhibited higher values at the genus level. The differences observed in terms of species diversity, abundance, and metabolic pathways offer potential avenues for implementing pharmacological interventions aimed at addressing sleep disorders in children.

Metabolic Characteristics of Gut Microbiota and Insomnia: Evidence from a Mendelian Randomization Analysis

Insomnia is a common sleep disorder that significantly impacts individuals' sleep quality and daily life. Recent studies have suggested that gut microbiota may influence sleep through various metabolic pathways. This study aims to explore the causal relationships between the abundance of gut microbiota metabolic pathways and insomnia using Mendelian randomization (MR) analysis. This two-sample MR study used genetic data from the OpenGWAS database (205 gut bacterial pathway abundance) and the FinnGen database (insomnia-related data). We identified single nucleotide polymorphisms (SNPs) associated with gut bacterial pathway abundance as instrumental variables (IVs) and ensured their validity through stringent selection criteria and quality control measures. The primary analysis employed the inverse variance-weighted (IVW) method, supplemented by other MR methods, to estimate causal effects. The MR analysis revealed significant positive causal effects of specific carbohydrate, amino acid, and nucleotide metabolism pathways on insomnia. Key pathways, such as gluconeogenesis pathway (GLUCONEO.PWY) and TCA cycle VII acetate producers (PWY.7254), showed positive associations with insomnia (B > 0, p < 0.05). Conversely, pathways like hexitol fermentation to lactate, formate, ethanol and acetate pathway (P461.PWY) exhibited negative causal effects (B < 0, p < 0.05). Multivariable MR analysis confirmed the independent causal effects of these pathways (p < 0.05). Sensitivity analyses indicated no significant pleiotropy or heterogeneity, ensuring the robustness of the results. This study identifies specific gut microbiota metabolic pathways that play critical roles in the development of insomnia. These findings provide new insights into the biological mechanisms underlying insomnia and suggest potential targets for therapeutic interventions. Future research should further validate these causal relationships and explore how modulating gut microbiota or its metabolic products can effectively improve insomnia symptoms, leading to more personalized and precise treatment strategies.

Longitudinal associations of an exposome score with serum metabolites from childhood to adolescence

Environmental and lifestyle factors, including air pollution, impaired diet, and low physical activity, have been associated with cardiometabolic risk factors in childhood and adolescence. However, environmental and lifestyle exposures do not exert their physiological effects in isolation. This study investigated associations between an exposome score to measure the impact of multiple exposures, including diet, physical activity, sleep duration, air pollution, and socioeconomic status, and serum metabolites measured using LC-MS and NMR, compared to the individual components of the score. A general population of 504 children aged 6-9 years at baseline was followed up for eight years. Data were analysed with linear mixed-effects models using the R software. The exposome score was associated with 31 metabolites, of which 12 metabolites were not associated with any individual exposure category. These findings highlight the value of a composite score to predict metabolic changes associated with multiple environmental and lifestyle exposures since childhood.

Knowledge, attitude and practice towards insomnia and sleep hygiene among patients with chronic insomnia in Northwest China in 2023: a cross-sectional survey

OBJECTIVES

To investigate the knowledge, attitude and practice (KAP) towards insomnia and sleep hygiene among patients with chronic insomnia.

DESIGN

Web-based cross-sectional survey.

SETTING

Shaanxi Provincial People's Hospital (northwest China) between January 2023 and May 2023.

PARTICIPANTS

Patients with chronic insomnia.

PRIMARY AND SECONDARY OUTCOME MEASURES

Demographic characteristics and KAP towards insomnia and sleep hygiene were collected by distributing a questionnaire developed by the authors.

RESULTS

A total of 613 people participated in this study, with a Mean Knowledge Score of 7.63±2.56 (total score of 12), a Mean Attitude Score of 48.39±6.643 (total score of 70) and a Mean Practice Score of 42.37±8.592 (total score of 70). Knowledge was significantly correlated with attitude (r=0.447, p<0.001) and practice (r=0.327, p<0.001), and attitude was significantly correlated with practice (r=0.486, p<0.001). Multivariable logistic regression showed that higher knowledge (OR=1.181 (1.062-1.314), p=0.002) and better attitude (OR=1.171 (1.124-1.221), p<0.001) were independently associated with good practice. According to the structural equation modelling analysis, knowledge directly influenced practice (β=0.457, p=<0.001) and attitude (β=1.160, p=<0.001), while attitude influenced practice (β=0.550, p=<0.001).

CONCLUSION

The KAP towards insomnia and sleep hygiene among patients with chronic insomnia in Northwest China in 2023 was moderate, with better practice showing signs of being influenced by better knowledge and more positive attitudes.

Sleep deprivation causes gut dysbiosis impacting on systemic metabolomics leading to premature ovarian insufficiency in adolescent mice

Rationale: Currently, there are occasional reports of health problems caused by sleep deprivation (SD). However, to date, there remains a lack of in-depth research regarding the effects of SD on the growth and development of oocytes in females. The present work aimed to investigate whether SD influences ovarian folliculogenesis in adolescent female mice. Methods: Using a dedicated device, SD conditions were established in 3-week old female mice (a critical stage of follicular development) for 6 weeks and gut microbiota and systemic metabolomics were analyzed. Analyses were related to parameters of folliculogenesis and reproductive performance of SD females. Results: We found that the gut microbiota and systemic metabolomics were severely altered in SD females and that these were associated with parameters of premature ovarian insufficiency (POI). These included increased granulosa cell apoptosis, reduced numbers of primordial follicles (PmFs), correlation with decreased AMH, E2, and increased LH in blood serum, and a parallel increased number of growing follicles and changes in protein expression compatible with PmF activation. SD also reduced oocyte maturation and reproductive performance. Notably, fecal microbial transplantation from SD females into normal females induced POI parameters in the latter while niacinamide (NAM) supplementation alleviated such symptoms in SD females. Conclusion: Gut microbiota and alterations in systemic metabolomics caused by SD induced POI features in juvenile females that could be counteracted with NAM supplementation.

Comparative analysis of gut microbiota in children with obstructive sleep apnea: assessing the efficacy of 16S rRNA gene sequencing in metabolic function prediction based on weight status

Background

Analyzing bacterial microbiomes consistently using next-generation sequencing (NGS) is challenging due to the diversity of synthetic platforms for 16S rRNA genes and their analytical pipelines. This study compares the efficacy of full-length (V1-V9 hypervariable regions) and partial-length (V3-V4 hypervariable regions) sequencing of synthetic 16S rRNA genes from human gut microbiomes, with a focus on childhood obesity.

Methods

In this observational and comparative study, we explored the differences between these two sequencing methods in taxonomic categorization and weight status prediction among twelve children with obstructive sleep apnea.

Results

The full-length NGS method by Pacbio® identified 118 genera and 248 species in the V1-V9 regions, all with a 0% unclassified rate. In contrast, the partial-length NGS method by Illumina® detected 142 genera (with a 39% unclassified rate) and 6 species (with a 99% unclassified rate) in the V3-V4 regions. These approaches showed marked differences in gut microbiome composition and functional predictions. The full-length method distinguished between obese and non-obese children using the Firmicutes/Bacteroidetes ratio, a known obesity marker (p = 0.046), whereas the partial-length method was less conclusive (p = 0.075). Additionally, out of 73 metabolic pathways identified through full-length sequencing, 35 (48%) were associated with level 1 metabolism, compared to 28 of 61 pathways (46%) identified through the partial-length method. The full-length NGS also highlighted complex associations between body mass index z-score, three bacterial species (Bacteroides ovatus, Bifidobacterium pseudocatenulatum, and Streptococcus parasanguinis ATCC 15912), and 17 metabolic pathways. Both sequencing techniques revealed relationships between gut microbiota composition and OSA-related parameters, with full-length sequencing offering more comprehensive insights into associated metabolic pathways than the V3-V4 technique.

Conclusion

These findings highlight disparities in NGS-based assessments, emphasizing the value of full-length NGS with amplicon sequence variant analysis for clinical gut microbiome research. They underscore the importance of considering methodological differences in future meta-analyses.

Machine learning methods for adult OSAHS risk prediction

BACKGROUND

Obstructive sleep apnea hypopnea syndrome (OSAHS) is a common disease that can cause multiple organ damage in the whole body. Our aim was to use machine learning (ML) to build an independent polysomnography (PSG) model to analyze risk factors and predict OSAHS.

MATERIALS AND METHODS

Clinical data of 2064 snoring patients who underwent physical examination in the Health Management Center of the First Affiliated Hospital of Shanxi Medical University from July 2018 to July 2023 were retrospectively collected, involving 24 characteristic variables. Then they were randomly divided into training group and verification group according to the ratio of 7:3. By analyzing the importance of these features, it was concluded that LDL-C, Cr, common carotid artery plaque, A1c and BMI made major contributions to OSAHS. Moreover, five kinds of machine learning algorithm models such as logistic regression, support vector machine, Boosting, Random Forest and MLP were further established, and cross validation was used to adjust the model hyperparameters to determine the final prediction model. We compared the accuracy, Precision, Recall rate, F1-score and AUC indexes of the model, and finally obtained that MLP was the optimal model with an accuracy of 85.80%, Precision of 0.89, Recall of 0.75, F1-score of 0.82, and AUC of 0.938.

CONCLUSION

We established the risk prediction model of OSAHS using ML method, and proved that the MLP model performed best among the five ML models. This predictive model helps to identify patients with OSAHS and provide early, personalized diagnosis and treatment options.

Untargeted Metabolome Atlas for Sleep Phenotypes in the Hispanic Community Health Study/Study of Latinos

Sleep is essential to maintaining health and wellbeing of individuals, influencing a variety of outcomes from mental health to cardiometabolic disease. This study aims to assess the relationships between various sleep phenotypes and blood metabolites. Utilizing data from the Hispanic Community Health Study/Study of Latinos, we performed association analyses between 40 sleep phenotypes, grouped in several domains (i.e., sleep disordered breathing (SDB), sleep duration, timing, insomnia symptoms, and heart rate during sleep), and 768 metabolites measured via untargeted metabolomics profiling. Network analysis was employed to visualize and interpret the associations between sleep phenotypes and metabolites. The patterns of statistically significant associations between sleep phenotypes and metabolites differed by superpathways, and highlighted subpathways of interest for future studies. For example, some xenobiotic metabolites were associated with sleep duration and heart rate phenotypes (e.g. 1H-indole-7-acetic acid, 4-allylphenol sulfate), while ketone bodies and fatty acid metabolism metabolites were associated with sleep timing measures (e.g. 3-hydroxybutyrate (BHBA), 3-hydroxyhexanoylcarnitine (1)). Heart rate phenotypes had the overall largest number of detected metabolite associations. Many of these associations were shared with both SDB and with sleep timing phenotypes, while SDB phenotypes shared relatively few metabolite associations with sleep duration measures. A number of metabolites were associated with multiple sleep phenotypes, from a few domains. The amino acids vanillylmandelate (VMA) and 1-carboxyethylisoleucine were associated with the greatest number of sleep phenotypes, from all domains other than insomnia. This atlas of sleep-metabolite associations will facilitate hypothesis generation and further study of the metabolic underpinnings of sleep health.

Targeted metabolomics-based understanding of the sleep disturbances in drug-naïve patients with schizophrenia

BACKGROUND

Sleep disturbances are a common occurrence in patients with schizophrenia, yet the underlying pathogenesis remain poorly understood. Here, we performed a targeted metabolomics-based approach to explore the potential biological mechanisms contributing to sleep disturbances in schizophrenia.

METHODS

Plasma samples from 59 drug-naïve patients with schizophrenia and 36 healthy controls were subjected to liquid chromatography-mass spectrometry (LC-MS) targeted metabolomics analysis, allowing for the quantification and profiling of 271 metabolites. Sleep quality and clinical symptoms were assessed using the Pittsburgh Sleep Quality Index (PSQI) and the Positive and Negative Symptom Scale (PANSS), respectively. Partial correlation analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) model were used to identify metabolites specifically associated with sleep disturbances in drug-naïve schizophrenia.

RESULTS

16 characteristic metabolites were observed significantly associated with sleep disturbances in drug-naïve patients with schizophrenia. Furthermore, the glycerophospholipid metabolism (Impact: 0.138, p<0.001), the butanoate metabolism (Impact: 0.032, p=0.008), and the sphingolipid metabolism (Impact: 0.270, p=0.104) were identified as metabolic pathways associated with sleep disturbances in drug-naïve patients with schizophrenia.

CONCLUSIONS

Our study identified 16 characteristic metabolites (mainly lipids) and 3 metabolic pathways related to sleep disturbances in drug-naïve schizophrenia. The detection of these distinct metabolites provide valuable insights into the underlying biological mechanisms associated with sleep disturbances in schizophrenia.

Microbiota Metabolite Profiles and Dietary Intake in Older Individuals with Insomnia of Short vs. Normal Sleep Duration

Recent evidence suggests that the gut microbiota plays a role in insomnia pathogenesis. This study compared the dietary habits and microbiota metabolites of older adults with insomnia of short vs. normal sleep duration (ISSD and INSD, respectively). Data collection included sleep assessment through actigraphy, dietary analysis using the Food Frequency Questionnaire, and metabolomic profiling of stool samples. The results show that ISSD individuals had higher body mass index and a greater prevalence of hypertension. Significant dietary differences were observed, with the normal sleep group consuming more kilocalories per day and specific aromatic amino acids (AAAs) phenylalanine and tyrosine and branch-chain amino acid (BCAA) valine per protein content than the short sleep group. Moreover, metabolomic analysis identified elevated levels of the eight microbiota metabolites, benzophenone, pyrogallol, 5-aminopental, butyl acrylate, kojic acid, deoxycholic acid (DCA), trans-anethole, and 5-carboxyvanillic acid, in the short compared to the normal sleep group. The study contributes to the understanding of the potential role of dietary and microbial factors in insomnia, particularly in the context of sleep duration, and opens avenues for targeted dietary interventions and gut microbiota modulation as potential therapeutic approaches for treating insomnia.

Relationship Between Insomnia and Continued Outpatient Treatment in Psychiatric Patients

Purpose

Sleep plays an essential role in maintaining both physical and mental well-being. Many patients in psychiatric outpatient settings complain of insomnia. However, the causal relationship between insomnia and depressive symptoms in all mental illnesses remains unclear. Moreover, research on insomnia and the continuation of outpatient treatment is lacking. We hypothesize a high correlation between depression and insomnia among patients with diverse mental illnesses. Additionally, we posit that insomnia significantly influences the continuity of outpatient visits. To this end, we evaluated insomnia and depression symptoms in psychiatric patients both at their initial visit and one year later. We also examined factors related to insomnia at the outset and factors associated with the ongoing utilization of outpatient treatment.

Patients and Methods

The participants of the study consisted of patients who made their first visit to the outpatient department of psychiatry and neurology at Showa University East Hospital between June 1, 2021, and March 31, 2023, and who continued attending the outpatient clinic for one year. Clinical characteristics were assessed using the Self-rating Depression Scale (SDS) and the Athens Insomnia Scale (AIS).

Results

The study's findings were collected from a cohort of 1106 patients and revealed that more than 70% experienced insomnia at the time of their initial visit. In total 137 patients continued to receive outpatient treatment for one year, and their AIS scores improved from 9 points to 5 points. A multivariate analysis revealed that the SDS items of depressed mood and insomnia were confounding factors influencing AIS improvement.

Conclusion

Given that 70% of patients complained of insomnia at the time of their first visit and that sleep improved in many of the 12.4% of patients who continued to receive outpatient treatment for at least one year, the results suggest that sleep status is an important determinant of whether a patient continues to attend outpatient clinics.

An integrated liver, hippocampus and serum metabolomics based on UPLC-Q-TOF-MS revealed the therapeutical mechanism of Ziziphi Spinosae Semen in p-chlorophenylalanine-induced insomnia rats

Ziziphi Spinosae Semen (ZSS), a well-known herbal medicine for treating insomnia, is popular in not only China but also in Europe, India and Iran. However, its underlying mechanisms remain unclear. In this work, taking the targeted organs of insomnia, the liver and hippocampus, as the objects, a combination metabolomics based on ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was established to illustrate the abnormality of metabolic characteristics of the liver, hippocampus and serum of p-chlorophenylalanine (PCPA)-induced insomnia rats and to demonstrate the mechanism of ZSS in treating insomnia. The results showed that ZSS could restore the brain cell morphology, decrease the degree of hepatocyte necrosis and regulate the disturbance of neurotransmitters and hormones in insomnia rats. In terms of metabolomics, a total of 33 liver metabolites, 25 hippocampal metabolites and 18 serum metabolites were finally selected as the potential biomarkers and an important pathway of phenylalanine, tyrosine and tryptophan biosynthesis was common in three tissues in PCPA rats. Meanwhile, ZSS significantly reversed the levels of 23 liver metabolites, 15 hippocampal metabolites and 5 serum metabolites. The present study demonstrates the actions of ZSS in treating insomnia by enhancing both cerebral and hepatic functions.

Metabolomic profiles of sleep-disordered breathing are associated with hypertension and diabetes mellitus development

Sleep-disordered breathing (SDB) is a prevalent disorder characterized by recurrent episodic upper airway obstruction. Using data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we apply principal component analysis (PCA) to seven SDB-related measures. We estimate the associations of the top two SDB PCs with serum levels of 617 metabolites, in both single-metabolite analysis, and a joint penalized regression analysis. The discovery analysis includes 3299 individuals, with validation in a separate dataset of 1522 individuals. Five metabolite associations with SDB PCs are discovered and replicated. SDB PC1, characterized by frequent respiratory events common in older and male adults, is associated with pregnanolone and progesterone-related sulfated metabolites. SDB PC2, characterized by short respiratory event length and self-reported restless sleep, enriched in young adults, is associated with sphingomyelins. Metabolite risk scores (MRSs), representing metabolite signatures associated with the two SDB PCs, are associated with 6-year incident hypertension and diabetes. These MRSs have the potential to serve as biomarkers for SDB, guiding risk stratification and treatment decisions.

Pathways of sleep disturbances in juvenile idiopathic arthritis and recommendations for clinical management approaches: A critical review

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease affecting young people. It has a profound impact on their physical, mental and social lives, leading to long-term disability. With the growing awareness of the importance of sleep in all areas of functioning in young people, an emerging literature has drawn attention to the role of sleep in the pathogenesis of JIA. Sleep disturbances in children and adolescents with JIA arise from a wide range of symptoms and pathways, leading to a vicious cycle that exacerbates subclinical inflammation, symptoms and disease progression. Putative factors contributing to sleep disturbances include chronic inflammation, JIA-associated sleep disorders, JIA symptoms (e.g. pain), psychological comorbidities and potential circadian disruption, which may be exacerbated by the transition to adolescence. Here, we review these pathways and advocate key strategies and alternatives for sleep management in young people with JIA in clinical settings. We identify gaps in knowledge and suggest future directions to improve our understanding of JIA sleep disorders, including clinical trials investigating potential strategies to improve sleep health in this young population.

Daytime Sleepiness, Apnea, Neuroimaging Correlates and Cortisol Dysregulation in a Memory Clinic Cohort

BACKGROUND

Sleep disturbances as well as cortisol hypersecretion are increasingly acknowledged as risk factors for Alzheimer's disease (AD). However, the mechanisms underlying the association, and the interplay with cortisol abnormalities, remain unclear.

OBJECTIVES

This study aims to identify how self-reported sleep disturbances are associated with structural brain measures and diurnal cortisol dysregulation among memory clinic patients.

DESIGN

A cross-sectional study performed at Karolinska University Hospital Memory Clinic, Sweden.

PARTICIPANTS

The study was based on 146 memory clinic patients diagnosed with either subjective cognitive impairment or mild cognitive impairment.

MEASUREMENTS

Self-reported sleep was measured using the Karolinska Sleep Questionnaire. MRI or CT was used to quantify structural brain measures using four visual rating scales (Scheltens, Pasquier, Koedam, and Fazekas scales), and salivary cortisol was sampled to measure diurnal cortisol patterns through measures of cortisol immediately after awakening, cortisol awakening response, bedtime cortisol, total cortisol from awakening to bedtime, and the AM/PM cortisol ratio.

RESULTS

Increased sleep apnea index (OR=1.20, 95% CI=1.04:1.39, p=0.015) was associated with greater odds of posterior brain atrophy, measured by the Koedam visual rating scale, and reduced awakening cortisol (β=-0.03, 95% CI=-0.07:0.00, p=0.045). Increased daytime sleepiness was associated with both reduced awakening cortisol (β=-0.03, 95% CI=-0.06:0.00, p=0.025) and a reduced AM/PM cortisol ratio (β=-0.04, CI=-0.08:-0.01, p= 0.021).

CONCLUSION

In a memory clinic cohort self-reported sleep disturbances are associated with both worse structural brain tissue integrity and altered diurnal cortisol profiles. These findings may add insights into possible mechanisms behind sleep disturbances in aging with subjective and cognitive impairment.

[Carbonyl stress in menopausal women with insomnia]

OBJECTIVE

To assess the level of advanced oxidation protein products (AOPP) and advanced glycation end products (AGEs) in menopausal women with insomnia.

MATERIAL AND METHODS

One hundred and thirty-six menopausal women were examined. After collecting medical history, general clinical examination, examination by a gynecologist and identifying the presence and nature of sleep disorders, the subjects were divided into 4 groups: 1 - control/perimenopause (n=21); 2 - insomnia/perimenopause (n=34); 3 - control/postmenopause (n=31); 4 - insomnia/postmenopause (n=50). The content of AOPP and the level of AGEs were determined using enzyme immunoassay.

RESULTS

A high percentage of menopausal women with insomnia have carbonyl stress values above the confidence interval (AGEs - 49.2% of women, AOPP - 55.2%). The insomnia in perimenopause is associated with high levels of AGEs (4533.10 [3834.09; 5098] ng/ml, p=0.039) and AOPP (28.92 [22.27; 40] nmol/L, p=0.002) as compared to controls (3685.87 [3376.11; 4318] ng/ml and 19.8 [16.85; 23.97] nmol/L, respectively). There are no significant differences in the studied parameters in postmenopause with insomnia.

CONCLUSION

Insomnia in perimenopause is a provoking factor for the development of free radical pathology and is associated with the formation of carbonyl stress, and in postmenopause it does not make significant changes in metabolic pathways involving carbonyl compounds.

Genetic study of the causal effect of lipid profiles on insomnia risk: a Mendelian randomization trial

OBJECTIVES

In response to the controversy surrounding observational studies of the association between lipid profiles and the risk of insomnia, the aim of this study was to analyze lipid profiles, including triglycerides (TG), apolipoprotein A-1 (ApoA-1), apolipoprotein B (ApoB) and lipoprotein A (LPA), in a European population to further assess the causal relationship between these lipid types and insomnia.

MATERIALS AND METHODS

This study explores the causal effect of lipid profiles on insomnia based on a genome-wide association study (GWAS)-derived public dataset using two-sample and multivariate Mendelian randomization (MVMR) analysis. The main MR analyses used inverse variance weighting (IVW) odds ratio (OR), and the sensitivity analyses included weighted median (WM) and MR‒Egger.

RESULTS

Both MR and MVMR showed that lowering ApoA-1 and LPA levels had causal effects on the risk of insomnia [MR: per 10 units, ApoA-1: OR: 0.7546, 95% CI: 0.6075-0.9372, P = 0.011; LPA: OR: 0.8392, 95% CI: 0.7202-0.9778, P = 0.025; MVMR: per 10 units, ApoA-1: OR: 0.7600, 95% CI: 0.6362-0.9079, P = 0.002; LPA, OR: 0.903, 95% CI: 0.8283-0.9845, P = 0.021]. There were no causal effects of TG or ApoB on insomnia (all P > 0.05). The MR‒Egger intercept test, funnel plot, and IVW methods all suggested an absence of strong directional pleiotropy, and leave-one-out permutation analysis did not detect any single single-nucleotide polymorphism that had a strong influence on the results.

CONCLUSION

Elevated levels of ApoA-1 and LPA were independently and causally associated with the risk of insomnia, suggesting that elevated ApoA-1 and LPA levels may contribute to a reduced risk of insomnia.

Mass spectrum oriented metabolomics for evaluating the efficacy and discovering the metabolic mechanism of Naoling Pian for insomnia

Insomnia is an accompanying symptom of many diseases and is closely associated with neurodegenerative diseases. Naoling Pian (NLP) is a patented Chinese medicine mainly used to treat insomnia. To evaluate the sedative and hypnotic effects of NLP and its modulatory effects on biological metabolites and metabolic pathways, rats with p-chlorophenylalanine (PCPA)-induced insomnia were given different doses of NLP by oral gavage for seven days. Diazepam (DZP) served as a positive control. Behavior was measured using the open field test, and neurotransmitter levels in the brain tissue related to sleep were measured using ELISA. The metabolic profiles and biomarkers of PCPA-induced insomnia in rats before and after NLP administration were analyzed using UPLC-Q/TOF-MS combined with multivariate data analysis. The results showed that the levels of 5-hydroxytryptamine, gamma-aminobutyric acid, norepinephrine, and dopamine in the brain tissue were significantly recovered in the NLP treatment groups, demonstrating similar or even superior therapeutic effects compared to the DZP group. The behavior of the PCPA-model rats partially recovered to normal levels after seven days of treatment. Metabolomics identified 30 metabolites in the urine as potential biomarkers of insomnia, and NLP significantly altered 25 of these, involving 21 metabolic pathways. NLP has a remarkable effect on insomnia, the therapeutic effects of which may be largely due to the rectification of metabolic disturbances. This is the first study of the sedative and hypnotic effects of NLP from a metabolomic perspective.

The Effects of Different Types of Sleep Disorder on Colorectal Cancer: A Nationwide Population-Based Cohort Study

The impact of sleep disorders (SDs), particularly sleep apnea (SA), on the development of colorectal cancer (CRC) has been the subject of significant research. However, the potential contribution of other SDs to the incidence of CRC remains unexplored. The objective of this study was to examine the effects of SDs on the risk of developing CRC. This study assessed CRC risk among individuals diagnosed with SDs compared with age- and sex-matched unaffected individuals. A longitudinal, nationwide, population-based cohort study was conducted using data from the Taiwan National Health Insurance Research Database (NHIRD) encompassing 177,707 individuals diagnosed with SDs and 177,707 matched controls. Cox proportional hazard regression analysis was used to determine the relative increased risk of CRC in individuals with SDs and specific subgroups of SDs. The CRC incidences were 1.32-fold higher (95% CI 1.23-1.42) in the overall SD cohort, 1.17-fold higher (95% CI 0.82-1.68) in the SA cohort, 1.42-fold higher (95% CI 1.31-1.55) in the insomnia cohort, 1.27-fold higher (95% CI 1.17-1.38) in the sleep disturbance cohort, and 1.00-fold higher (95% CI 0.77-1.29) in the other SD cohort, after adjusting for age, sex, and comorbidities.

Integrating animal experiments, mass spectrometry and network-based approach to reveal the sleep-improving effects of Ziziphi Spinosae Semen and γ-aminobutyric acid mixture

BACKGROUND

Ziziphi Spinosae Semen (ZSS) is a plant widely used as medicine and food in Asian countries due to its numerous health benefits. γ-aminobutyric acid (GABA), a non-proteinaceous amino acid, is one of the major inhibitory neurotransmitters with a relaxant function. In this study, a system pharmacology approach was employed to assess the effects of a mixture composed of ZSS and GABA (ZSSG) on sleep improvement.

METHODS

Mice were divided into five groups (n = 10) and received either no treatment, sodium pentobarbital, or sodium barbital with diazepam or ZSSG. The effects of ZSSG on sleep quality were evaluated in mice, and differential metabolites associated with sleep were identified among the control, ZSS, GABA, and ZSSG groups. Additionally, network-based ingredient-insomnia proximity analysis was applied to explore the major ingredients.

RESULTS

ZSSG significantly improved sleep quality by decreasing sleep latency and prolonging sleep duration in sodium pentobarbital-induced sleeping mouse model (P < 0.05). ZSSG significantly enhanced the brain content of GABA in mice. Furthermore, ZSSG also significantly decreased sleep latency-induced by sodium barbital in mice (P < 0.05). Metabolic analysis revealed significant differences in 10 metabolites between ZSSG group and the groups administering ZSS or GABA. Lastly, using the network-based ingredient screening model, we discovered potential four active ingredients and three pairwise ingredient combinations with synergistic effect on insomnia from ZSSG among 85 ingredients identified by UPLC-Q/TOF-MS. Also, we have constructed an online computation platform.

CONCLUSION

Our data demonstrated that ZSSG improved the sleeping quality of mice and helped to balance metabolic disorders-associated with sleep disorders. Moreover, based on the network-based prediction method, the four potential active ingredients in ZSSG could serve as quality markers-associated with insomnia. The network-based framework may open up a new avenue for the discovery of active ingredients of herbal medicine for treating complex chronic diseases or symptoms, such as insomnia.

Cerebrospinal fluid lipidomic fingerprint of obstructive sleep apnoea in Alzheimer's disease

BACKGROUND

Obstructive sleep apnoea (OSA) has a high prevalence in patients with Alzheimer's disease (AD). Both conditions have been shown to be associated with lipid dysregulation. However, the relationship between OSA severity and alterations in lipid metabolism in the brains of patients with AD has yet to be fully elucidated. In this context, we examined the cerebrospinal fluid (CSF) lipidome of patients with suspected OSA to identify potential diagnostic biomarkers and to provide insights into the pathophysiological mechanisms underlying the effect of OSA on AD.

METHODS

The study included 91 consecutive AD patients who underwent overnight polysomnography (PSG) to diagnose severe OSA (apnoea-hypopnea index ≥ 30/h). The next morning, CSF samples were collected and analysed by liquid chromatography coupled to mass spectrometry in an LC-ESI-QTOF-MS/MS platform.

RESULTS

The CSF levels of 11 lipid species were significantly different between AD patients with (N = 38) and without (N = 58) severe OSA. Five lipids (including oxidized triglyceride OxTG(57:2) and four unknown lipids) were significantly correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Our analyses revealed a 4-lipid signature (including oxidized ceramide OxCer(40:6) and three unknown lipids) that provided an accuracy of 0.80 (95% CI: 0.71-0.89) in the detection of severe OSA. These lipids increased the discriminative power of the STOP-Bang questionnaire in terms of the area under the curve (AUC) from 0.61 (0.50-0.74) to 0.85 (0.71-0.93).

CONCLUSIONS

Our results reveal a CSF lipidomic fingerprint that allows the identification of AD patients with severe OSA. Our findings suggest that an increase in central nervous system lipoxidation may be the principal mechanism underlying the association between OSA and AD.

Emerging role of metabolomics for biomarker discovery in obstructive sleep apnea

Obstructive sleep apnea (OSA) is characterized by the complete or partial blockage of the upper airway passage during sleep which causes repetitive breaks in sleep and may result in excessive daytime sleepiness. OSA has been linked to various metabolic disorders and chronic health conditions, such as obesity, diabetes, hypertension, and depression. Profiling of alterations in metabolites and their regulation in OSA has been hypothesized to be an effective approach for early diagnosis and prognosis of OSA. Several studies have characterized metabolic fingerprints associated with sleep disorders. There is a lack of understanding of metabolite contents and their alterations in OSA that may help to identify specific biomarkers. The information provided in this review will help update new methodologies and interventions of high throughput advanced molecular/metabolomics tools which may clarify the metabolic aspects and mechanisms for improved management and treatment of OSA.

Branched-chain amino acids and sleep: a population-derived study of Australian children aged 11-12 years and their parents

Micronutrients, particularly amino acids, are thought to play an important role in sleep regulation and maintenance. While tryptophan is a known predictor of sleep, less is known about branched-chain amino acids (BCAAs), which compete with tryptophan for transport across the blood-brain barrier. The aim of this study was to determine the association between BCAAs and actigraphy-derived sleep duration, timing and efficiency, and self-reported trouble sleeping. This study examined data on children and adults collected as part of the Child Health CheckPoint study. Linear mixed models, adjusted for geographic clustering, were used to determine the association between BCAAs and sleep characteristics. Complete-case analysis was conducted for 741 children aged 11-12 years old (51% females) and 941parents (87% mothers). While BCAAs were significantly associated with children's sleep duration, timing and self-reported trouble sleeping, no associations were observed in adults, in fully adjusted models. In children, higher levels of BCAAs are associated with shorter sleep duration, delayed sleep timing, and more frequent reports of trouble sleeping.

Metabolomic Profiles of Sleep-Disordered Breathing are Associated with Hypertension and Diabetes Mellitus Development: the HCHS/SOL

Sleep-disordered breathing (SDB) is a prevalent disorder characterized by recurrent episodic upper airway obstruction. In a dataset from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we applied principal component analysis (PCA) on seven measures characterizing SDB-associated respiratory events. We estimated the association of the top two SDB PCs with serum levels of 617 metabolites, in both single-metabolite analysis, and a joint, penalized regression analysis using the least absolute shrinkage and selection operator (LASSO). Discovery analysis included n = 3,299 HCHS/SOL individuals; associations were validated in a separate dataset of n = 1,522 HCHS/SOL individuals. Seven metabolite associations with SDB PCs were discovered and replicated. Metabolite risk scores (MRSs) developed based on LASSO association results and representing metabolite signatures associated with the two SDB PCs were associated with 6-year incident hypertension and incident diabetes. MRSs have the potential to serve as biomarkers for SDB, guiding risk stratification and treatment decisions.

Metabolic profiles of saliva in male mouse models of chronic sleep disorders induced by psychophysiological stress

Disordered sleep is a global social problem and an established significant risk factor for psychological and metabolic diseases. We profiled non-targeted metabolites in saliva from mouse models of chronic sleep disorder (CSD). We identified 288 and 55 metabolites using CE-FTMS and LC-TOFMS, respectively, among which concentrations of 58 (CE-FTMS) and three (LC-TOFMS) were significantly changed by CSD. Pathway analysis revealed that CSD significantly suppressed glycine, serine and threonine metabolism. Arginine and proline metabolic pathways were among those that were both upregulated and downregulated. Pathways of alanine, aspartate and glutamate metabolism, genetic information processing, and the TCA cycle tended to be downregulated, whereas histidine metabolism tended to be upregulated in mice with CSD. Pyruvate, lactate, malate, succinate and the glycemic amino acids alanine, glycine, methionine, proline, and threonine were significantly decreased, whereas 3-hydroxybutyric and 2-hydroxybutyric acids associated with ketosis were significantly increased, suggesting abnormal glucose metabolism in mice with CSD. Increases in the metabolites histamine and kynurenic acid that are associated with the central nervous system- and decreased glycine, might be associated with sleep dysregulation and impaired cognitive dysfunction in mice with CSD. Our findings suggested that profiling salivary metabolites could be a useful strategy for diagnosing CSD.

Metabolomic approach for obstructive sleep apnea in adults: a systematic review

Obstructive Sleep Apnea (OSA) corresponds to episodes of complete or partial upper airway obstruction during sleep. The gold standard for diagnosing OSA is polysomnography; however, metabolomics is an innovative and highly sensitive method that seeks to identify and quantify small molecules in biological systems. Identify the metabolites most frequently associated with obstructive sleep apnea in adults. The search for articles was conducted between October 2020 and August 2021, in electronic databases, such as MEDLINE/PubMed, Scielo, Embase, and Cochrane, through the combination of descriptors: obstructive sleep apnea, metabolomic, adult. This systematic review included all cross-sectional studies published, including human patients aged 18 years or older, of both genders who underwent type I or II polysomnography and metabolomics study. The search strategy selected 3697 surveys, and 4 of them were selected to be a part of this systematic review. Based on the analyzed surveys, it was found that all of them were able to diagnose OSA, reaching a sensitivity of 75-97%, and specificity that ranged from 72 to 100%; besides differentiating patients with OSA (severe, moderate, and mild) from simple snorers with a mean sensitivity of 77.2% and specificity of 66.25%. These findings suggest that, in addition to being used as a screening and diagnostic strategy for OSA, metabolomics has the potential to be used for severity stratification and to monitor the disease's progression.

Sleep disorders affect cognitive function in adults: an overview of systematic reviews and meta-analyses

Sleep disorders frequently result in poor memory, attention deficits, as well as a worse prognosis for neurodegenerative changes, such as Alzheimer's disease. The purpose of this study is to investigate the impact of sleep disorders on cognition. We screened four databases for all meta-analyses and systematic reviews from the establishment through March 2022. We have carried out quality evaluation and review the eligible systematic reviews. Evidence grading and quality assessment were performed on 22 eligible articles. Sleep deprivation primarily affects simple attention, complex attention, and working memory in cognition and alertness. The moderate-to-high-quality evidence proves optimal sleep time as 7-8 h. Sleep time outside this range increases the risk of impaired executive function, non-verbal memory, and working memory. Sleep-related breathing disorders is more likely to cause mild cognitive impairment and affects several cognitive domains. In older adults, insomnia primarily affects working memory, episodic memory, inhibitory control, cognitive flexibility, problem-solving, operational ability, perceptual function, alertness, and complex attention, and maintaining sensitivity. Sleep disturbances significantly impair cognitive function, and early detection and intervention may be critical steps in reducing poor prognosis. A simple neuropsychological memory test could be used to screen people with sleep disorders for cognitive impairment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-022-00439-9.

Treatment of insomnia based on the mechanism of pathophysiology by acupuncture combined with herbal medicine: A review

Insomnia is a sleep disorder which severely affects patients mood, quality of life and social functioning, serves as a trigger or risk factor to a variety of diseases such as depression, cardiovascular and cerebrovascular diseases, obesity and diabetes, and even increases the risk of suicide, and has become an increasingly widespread concern worldwide. Considerable research on insomnia has been conducted in modern medicine in recent years and encouraging results have been achieved in the fields of genetics and neurobiology. Unfortunately, however, the pathogenesis of insomnia remains elusive to modern medicine, and pharmacological treatment of insomnia has been regarded as conventional. However, in the course of treatment, pharmacological treatment itself is increasingly being questioned due to potential dependence and drug resistance and is now being replaced by cognitive behavior therapy as the first-line treatment. As an important component of complementary and alternative medicine, traditional Chinese medicine, especially non-pharmacological treatment methods such as acupuncture, is gaining increasing attention worldwide. In this article, we discuss the combination of traditional Chinese medicine, acupuncture, and medicine to treat insomnia based on neurobiology in the context of modern medicine.

Predicting insomnia severity using structure-function coupling in female chronic insomnia patients

Functional connectivity between brain regions is constrained by the underlying structural pathways. However, how this structure-function coupling is disrupted in female patients with insomnia disorder is unclear. This study examines if the whole-brain pattern of structure-function coupling could be used to predict unseen female patients' insomnia severity index. Resting-state functional MRI and diffusion-weighted imaging were performed in 82 female participants with chronic insomnia. Structure-function coupling was computed using the Spearman rank correlations between structural and functional connectivity profiles. Using relevance vector regression approach and 10-fold cross-validation, we predicted the individuals' insomnia severity index using the pattern of whole-brain structure-function coupling. Finally, we extracted the contribution of each regional coupling to the prediction model. The pattern of structure-function coupling could be used to significantly predict unseen individuals' insomnia severity index scores (r = 0.29, permutation P < 0.001; mean absolute error (MAE) = 4.59, permutation P < 0.001). Moreover, the brain regions with high functional hierarchy, including regions in the default mode network, mainly displayed negative contribution weights, while the regions with lower functional hierarchy, including occipital regions and the precentral gyrus, mainly displayed positive contribution weights. This is the first study to demonstrate an association between structure-function coupling and the insomnia severity index in females with insomnia disorder. Importantly, our data suggest that insomnia severity is associated with a reduction in structure-function coupling in higher-order brain regions and an increase in structure-function coupling in lower-order brain regions.

SREBP modulates the NADP+/NADPH cycle to control night sleep in Drosophila

Sleep behavior is conserved throughout evolution, and sleep disturbances are a frequent comorbidity of neuropsychiatric disorders. However, the molecular basis underlying sleep dysfunctions in neurological diseases remains elusive. Using a model for neurodevelopmental disorders (NDDs), the Drosophila Cytoplasmic FMR1 interacting protein haploinsufficiency (Cyfip^85.1/+), we identify a mechanism modulating sleep homeostasis. We show that increased activity of the sterol regulatory element-binding protein (SREBP) in Cyfip^85.1/+ flies induces an increase in the transcription of wakefulness-associated genes, such as the malic enzyme (Men), causing a disturbance in the daily NADP⁺/NADPH ratio oscillations and reducing sleep pressure at the night-time onset. Reduction in SREBP or Men activity in Cyfip^85.1/+ flies enhances the NADP⁺/NADPH ratio and rescues the sleep deficits, indicating that SREBP and Men are causative for the sleep deficits in Cyfip heterozygous flies. This work suggests modulation of the SREBP metabolic axis as a new avenue worth exploring for its therapeutic potential in sleep disorders.

Enhanced intrathalamic morphological connectivity in patients with chronic insomnia

This study aimed to systematically investigate abnormal morphological connectivity in subregions of the thalamus and examine the clinical relevance of this connectivity in patients with chronic insomnia. One hundred and two patients with chronic insomnia (aged 45.50 [34.75 ~ 58.00] years; 24 men, 78 women) and one hundred and one healthy controls (aged 45.00 [34.00 ~ 55.00] years; 32 men, 69 women) were recruited. Intrathalamic and thalamocortical morphological connectivity in the thalamic subregions defined in the Human Brainnetome Atlas were computed and compared between the two groups. Spearman's correlation was used to estimate the association between thalamic morphological connectivity alterations and clinical variables. Compared with the control group, the insomnia group exhibited higher intrathalamic mean morphological connectivity than the control group, though no alterations in thalamocortical morphological connectivity were observed. However, no correlation was found between altered intrathalamic morphological connectivity and behavioral scales. In addition, alterations in morphological connectivity among thalamic subregions were found mainly in the left medial premotor thalamus, left medial prefrontal thalamus, and left sensory thalamus; however, these results were no longer significant after correction. Our findings suggest increased intrathalamic morphological connectivity in patients with chronic insomnia, thus enriching the understanding of morphological connectivity at the individual level and providing new perspectives for clinical interventions and diagnostic imaging.

Sleep duration, plasma metabolites, and obesity and diabetes: a metabolome-wide association study in US women

Short and long sleep duration are associated with adverse metabolic outcomes, such as obesity and diabetes. We evaluated cross-sectional differences in metabolite levels between women with self-reported habitual short (<7 h), medium (7-8 h), and long (≥9 h) sleep duration to delineate potential underlying biological mechanisms. In total, 210 metabolites were measured via liquid chromatography-mass spectrometry in 9207 women from the Nurses' Health Study (NHS; N = 5027), the NHSII (N = 2368), and the Women's Health Initiative (WHI; N = 2287). Twenty metabolites were consistently (i.e. praw < .05 in ≥2 cohorts) and/or strongly (pFDR < .05 in at least one cohort) associated with short sleep duration after multi-variable adjustment. Specifically, levels of two lysophosphatidylethanolamines, four lysophosphatidylcholines, hydroxyproline and phenylacetylglutamine were higher compared to medium sleep duration, while levels of one diacylglycerol and eleven triacylglycerols (TAGs; all with ≥3 double bonds) were lower. Moreover, enrichment analysis assessing associations of metabolites with short sleep based on biological categories demonstrated significantly increased acylcarnitine levels for short sleep. A metabolite score for short sleep duration based on 12 LASSO-regression selected metabolites was not significantly associated with prevalent and incident obesity and diabetes. Associations of single metabolites with long sleep duration were less robust. However, enrichment analysis demonstrated significant enrichment scores for four lipid classes, all of which (most markedly TAGs) were of opposite sign than the scores for short sleep. Habitual short sleep exhibits a signature on the human plasma metabolome which is different from medium and long sleep. However, we could not detect a direct link of this signature with obesity and diabetes risk.

T cell receptor repertoire as a novel indicator for identification and immune surveillance of patients with severe obstructive sleep apnea

Background

Obstructive sleep apnea (OSA) is the most prevalent sleep disturbance that affects approximately 936 million people worldwide and leads to extensively increased incidence of cardiovascular disease, metabolic syndrome, neurological disorders, and traffic accidents. Severe OSA patients suffer a significantly higher risk of complications and worse comorbidity outcomes. Notwithstanding, with inadequate access to contact diagnosis based on polysomnography (PSG), numerous patients with severe sleep apnea have not been diagnosed, especially during the pandemic. Moreover, how the T cell immunity is impaired in OSA remains largely unknown.

Methods

We primarily investigated the T cell receptor (TCR) repertoires of 50 patients with severe OSA, 23 patients with mild-to-moderate OSA, 23 patients without OSA, and 157 healthy individuals, from their peripheral blood. Firstly, we compared the clinical characteristics, blood cell counts, the ratio of neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), and CD4+/CD8+T cell count between groups. Then, we compared the diversity, clonotypes, unique VJ alleles in patients with different disease severity. Furthermore, by identifying a series of disease-associated amino acid sequences, we employed a repeated hold-out machine learning strategy to explore the optimal algorithm for calculating the TCR repertoire characteristic Index (OSA-TCI). We further confirmed its relation with clinical features by linear regression analysis. Moreover, in followup of severe OSA patients who accepted adherent non-invasive ventilation, we assessed the changes of TCR repertoires, OSA-TCI, ESS, NLR, PLR, and CD4+/CD8+T after therapy.

Results

We found an unexpected increase in diversity and clonotypes in the TCR repertoire of OSA patients. Furthermore, we successfully developed a novel indicator termed OSA-TCI to summarize the unique repertoire alteration, which provided 90% of sensitivity and 87% of specificity in distinguishing severe OSA. In rationalization, OSA-TCI was found correlated to AHI, BMI, hemoglobin, N1, N2 percentage of sleep, snoring, smoking and lowest oxygen saturation, but only independently related to AHI (R = 0.603) and smoking (R = 0.22). Finally, we observed OSA-TCI in the eight severe patients decreased significantly after home noninvasive ventilation for three months during follow-up, consistently in line with the TCR repertoire improvement. In contrast, NLR, PLR, and the ratio of CD4+/CD8+T cell count were found useless to diagnose and therapeutic surveillance of severe OSA.

Conclusions

Our study is the first to unveil the TCR repertoire alteration in OSA, indicates possible insidious autoimmune mechanisms underlying OSA, and suggests that TCR repertoires serve as a convenient peripheral blood biomarker for OSA assessment without long-time contact and facility/instrument occupation. It may shed light on future diagnostic, immunological, pathophysiological, and prognostic research on OSA.

Association between insomnia and absenteeism or presenteeism among Korean employees

Background

In Korea, few studies clarify insomnia and its association and absenteeism or presenteeism. Therefore, this study aims to examine the association between insomnia and absenteeism/presenteeism using the sixth Korean Working Conditions Survey.

Methods

Insomnia was evaluated by the Minimal Insomnia Symptoms Scale (MISS). Absenteeism and presenteeism were assessed by asking if the employee had experienced absence or working despite being ill for the prior 12 months at the point of the survey. Multiple logistic analyses were conducted to explore insomnia and its association with absenteeism and presenteeism.

Results

The odds ratios of insomnia for absenteeism and presenteeism were 3.48 (95% confidence interval [CI]: 2.76-4.39) and 3.68 (95% CI: 3.18-4.26) in the fully adjusted model. As the MISS scores increased, absenteeism and presenteeism showed the increasing trend that odd ratios increased accordingly from the first to the fourth quartile.

Conclusions

This study observed that insomnia was related to both absenteeism and presenteeism among Korean employees.

Identification of metabolic fingerprints in severe obstructive sleep apnea using gas chromatography-Mass spectrometry

Objective: Obstructive sleep apnea (OSA) is considered a major sleep-related breathing problem with an increasing prevalence rate. Retrospective studies have revealed the risk of various comorbidities associated with increased severity of OSA. This study aims to identify novel metabolic biomarkers associated with severe OSA. Methods: In total, 50 cases of OSA patients (49.74 ± 11.87 years) and 30 controls (39.20 ± 3.29 years) were included in the study. According to the polysomnography reports and questionnaire-based assessment, only patients with an apnea-hypopnea index (AHI >30 events/hour) exceeding the threshold representing severe OSA patients were considered for metabolite analysis. Plasma metabolites were analyzed using gas chromatography-mass spectrometry (GC-MS). Results: A total of 92 metabolites were identified in the OSA group compared with the control group after metabolic profiling. Metabolites and their correlated metabolic pathways were significantly altered in OSA patients with respect to controls. The fold-change analysis revealed markers of chronic kidney disease, cardiovascular risk, and oxidative stress-like indoxyl sulfate, 5-hydroxytryptamine, and 5-aminolevulenic acid, respectively, which were significantly upregulated in OSA patients. Conclusion: Identifying these metabolic signatures paves the way to monitor comorbid disease progression due to OSA. Results of this study suggest that blood plasma-based biomarkers may have the potential for disease management.

Multiomics Analysis Reveals Aberrant Metabolism and Immunity Linked Gut Microbiota with Insomnia

Studies have confirmed that insomnia is related to gut microbiota. Previous research suggests that immunity and metabolism are also associated with insomnia. However, to our knowledge, the integration of these factors has not been investigated in insomnia. Here, we explored the correlations across gut microbiota, serum metabolism, and inflammatory factors in insomnia. Our results showed that the composition and structure of gut microbiota and metabolism in insomnia patients were different from healthy controls. Compared to healthy controls, the relative abundances of Lactobacillus, Streptococcus, and Lactobacillus crispatus were significantly increased in insomniacs. There were five metabolic pathways in insomniacs (glycerophospholipid metabolism; glutathione metabolism; nitrogen metabolism; alanine, aspartate, and glutamate metabolism; aminoacyl-tRNA biosynthesis) significantly different between the two groups. Moreover, we found that IL-1β levels were significantly higher in insomnia patients while TNF-α was significantly reduced. We further identified that the changes in the level of IL-1β and TNF-α were associated with some specific bacteria and metabolites, such as Prevotella amnii, Prevotella buccalis, Prevotella timonensis, and Prevotella colorans. Mediation analysis further determined that the immune factors and metabolites could mediate the relationship between gut microbes and insomnia. IMPORTANCE Our study indicated that systematic inflammation and metabolites might be a pathway linking the gut microbiome with insomnia. These findings provide new insights and a better understanding of gut microbiota's role in insomnia as well as potential novel microbiome-related etiologies for insomnia.

Causality of genetically determined metabolites on anxiety disorders: a two-sample Mendelian randomization study

BACKGROUND

Although anxiety disorders are one of the most prevalent mental disorders, their underlying biological mechanisms have not yet been fully elucidated. In recent years, genetically determined metabolites (GDMs) have been used to reveal the biological mechanisms of mental disorders. However, this strategy has not been applied to anxiety disorders. Herein, we explored the causality of GDMs on anxiety disorders through Mendelian randomization study, with the overarching goal of unraveling the biological mechanisms.

METHODS

A two-sample Mendelian randomization (MR) analysis was implemented to assess the causality of GDMs on anxiety disorders. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, whereas four different GWAS datasets of anxiety disorders were the outcomes. Notably, all datasets were acquired from publicly available databases. A genetic instrumental variable (IV) was used to explore the causality between the metabolite and anxiety disorders for each metabolite. The MR Steiger filtering method was implemented to examine the causality between metabolites and anxiety disorders. The standard inverse variance weighted (IVW) method was first used for the causality analysis, followed by three additional MR methods (the MR-Egger, weighted median, and MR-PRESSO (pleiotropy residual sum and outlier) methods) for sensitivity analyses in MR analysis. MR-Egger intercept, and Cochran's Q statistical analysis were used to evaluate possible heterogeneity and pleiotropy. Bonferroni correction was used to determine the causative association features (P < 1.03 × 10^-4). Furthermore, metabolic pathways analysis was performed using the web-based MetaboAnalyst 5.0 software. All statistical analysis were performed in R software. The STROBE-MR checklist for the reporting of MR studies was used in this study.

RESULTS

In MR analysis, 85 significant causative relationship GDMs were identified. Among them, 11 metabolites were overlapped in the four different datasets of anxiety disorders. Bonferroni correction showing1-linoleoylglycerophosphoethanolamine (OR_{fixed-effect IVW} = 1.04; 95% CI 1.021-1.06; P_{fixed-effect IVW} = 4.3 × 10^-5) was the most reliable causal metabolite. Our results were robust even without a single SNP because of a "leave-one-out" analysis. The MR-Egger intercept test indicated that genetic pleiotropy had no effect on the results (intercept = - 0.0013, SE = 0.0006, P = 0.06). No heterogeneity was detected by Cochran's Q test (MR-Egger. Q = 7.68, P = 0.742; IVW. Q = 12.12, P = 0.436). A directionality test conducted by MR Steiger confirmed our estimation of potential causal direction (P < 0.001). In addition, two significant pathways, the "primary bile acid biosynthesis" pathway (P = 0.008) and the "valine, leucine, and isoleucine biosynthesis" pathway (P = 0.03), were identified through metabolic pathway analysis.

CONCLUSION

This study provides new insights into the causal effects of GDMs on anxiety disorders by integrating genomics and metabolomics. The metabolites that drive anxiety disorders may be suited to serve as biomarkers and also will help to unravel the biological mechanisms of anxiety disorders.

Salivary Biomarkers Associated with Psychological Alterations in Patients with Diabetes: A Systematic Review

The care of individuals with diabetes needs a holistic perspective, taking into account both the physical disease and the mental health problems that may be associated. Different studies show a higher prevalence of depression or anxiety issues in diabetes patients than in the general population, which is why diabetes can be considered one of the chronic diseases in which psychological care is crucial to maintain quality of life. The objective of this review is to examine the published articles that relate the bidirectional associations between objective and subjective measures of anxiety, depressive symptomatology, stress, sleep quality, and salivary biomarkers in patients with diabetes. For this, a search was carried out in the electronic databases PubMed, Cochrane, and SCOPUS using the keywords "diabetes", "saliva", "sleep", "anxiety", "depression", and "stress" for works published up until May 2022 and limited to the English and Spanish languages. The sample comprised 14 articles, 5 of which analysed the associations between depressive symptomatology and salivary biomarkers in people with diabetes. Among the salivary biomarkers most frequently used to evaluate psychological alterations in persons with diabetes are cortisol and melatonin. Thus, significant changes in the levels of these biomarkers were observed in most studies. Four out of five studies reported a statistically significant relationship between increased salivary cortisol in the evening/midnight or the cortisol awakening response and depressive symptoms. In contrast, lower cortisol levels upon waking in the morning were observed when there was no depression or anxiety. Regarding the association between salivary cortisol values and sleep quality in patients with diabetes, lower morning cortisol values related to prolonged nighttime sleep were common in the analysed studies. Low melatonin concentrations showed a negative correlation with sleep quality. As it is an easy-to-apply and non-invasive method, the measurement of salivary biomarkers can be very useful for predicting psychological alterations in patients with diabetes. Further scientific studies are required to determine the sensitivity of these biological substances acting as biomarkers for detecting sleep disorders and psychological alterations.

Machine Learning and Pathway Analysis-Based Discovery of Metabolomic Markers Relating to Chronic Pain Phenotypes

Recent scientific evidence suggests that chronic pain phenotypes are reflected in metabolomic changes. However, problems associated with chronic pain, such as sleep disorders or obesity, may complicate the metabolome pattern. Such a complex phenotype was investigated to identify common metabolomics markers at the interface of persistent pain, sleep, and obesity in 71 men and 122 women undergoing tertiary pain care. They were examined for patterns in d = 97 metabolomic markers that segregated patients with a relatively benign pain phenotype (low and little bothersome pain) from those with more severe clinical symptoms (high pain intensity, more bothersome pain, and co-occurring problems such as sleep disturbance). Two independent lines of data analysis were pursued. First, a data-driven supervised machine learning-based approach was used to identify the most informative metabolic markers for complex phenotype assignment. This pointed primarily at adenosine monophosphate (AMP), asparagine, deoxycytidine, glucuronic acid, and propionylcarnitine, and secondarily at cysteine and nicotinamide adenine dinucleotide (NAD) as informative for assigning patients to clinical pain phenotypes. After this, a hypothesis-driven analysis of metabolic pathways was performed, including sleep and obesity. In both the first and second line of analysis, three metabolic markers (NAD, AMP, and cysteine) were found to be relevant, including metabolic pathway analysis in obesity, associated with changes in amino acid metabolism, and sleep problems, associated with downregulated methionine metabolism. Taken together, present findings provide evidence that metabolomic changes associated with co-occurring problems may play a role in the development of severe pain. Co-occurring problems may influence each other at the metabolomic level. Because the methionine and glutathione metabolic pathways are physiologically linked, sleep problems appear to be associated with the first metabolic pathway, whereas obesity may be associated with the second.

Proteomics Reveals Molecular Changes in Insomnia Patients with More Dreams

Background

Insomnia is a sleep disorder and the cause of many healthy problems. However, there are few studies on patients with insomnia and dreaminess at present. Therefore, this study is aimed at exploring the pathological molecular mechanisms and potential diagnostic and therapeutic targets related to insomnia patients with more dreams.

Methods

Sleep characteristics of 36 primary insomnia patients with more dreams and 36 well sleeping participants were assessed using polysomnography (PSG) and Pittsburgh Sleep Quality Index (PSQI). Serum samples from 9 insomnia patients and 9 controls were randomly selected for proteomic detection. Differentially expressed proteins (DEPs) between the two groups were identified; enrichment analysis and PPI network were performed. The top 10 most connected proteins in the PPI network were subjected to targeted drug prediction and screened key proteins. Proteins with targeted drugs were recognized as key proteins and subjected to ELISA detection.

Results

Insomnia patients had a distinct REM behavior disorder signature compared with controls. Proteomic sequencing identified 76 DEPs. Enrichment analysis found that DEPs were significantly enriched in the complement and coagulation cascades. Metabolic responses were also activated in insomnia patients. Among the hub proteins screened in the PPI network, APOA1, APOB, F2, and SPARC may be targeted by many herbal medicines and considered as key proteins. ELISA assays validated their differential expression between insomnia and controls.

Conclusion

In this study, we identified the potential key proteins of insomnia patients with more dreams. The pathological process may associate with inflammation and metabolic response. These results provide molecular targets for diagnostic and therapeutic targets. The results of our analysis suggest that the expression changes of key proteins have a good predictive diagnostic role for the occurrence of insomnia with more dreams in patients.

A Clinical Study on the Relationship Among Insomnia, Tongue Diagnosis, and Oral Microbiome

Currently, there is a lack of adequate methods to assess insomnia objectively. This study addresses the usefulness of tongue features and oral microbial profile as a potential diagnostic biomarker of insomnia. One hundred insomniac patients and 20 healthy control subjects were selected. Their demographic and clinical characteristics, as well as the tongue diagnostic indices and oral microbial profile, were examined. Compared to the control group, insomniac patients showed a higher abnormal low-frequency/high-frequency (LF/HF) ratio. In tongue diagnosis, the indices related to lightness of tongue body and tongue coating were higher in the insomniac group vs. the control group. Furthermore, linear discriminant analysis (LDA) of oral microbial population revealed that the relative abundances of Clostridia, Veillonella, Bacillus and Lachnospiraceae were significantly higher in the insomniac patients than the control group. Additionally, the tongue features of the insomniac group exhibited that the non-coating group had a poor sleep condition compared to the thick-coating group, although the difference was insignificant. On the other hand, the oral microbial communities of the insomniac patients revealed greater alpha and beta diversities in the non-coating group vs. the thick-coating group. The alpha and beta diversities were higher in orotype1 than orotype2. Collectively, this study highlighted that the lightness of tongue body and tongue coating as well as oral microbial profiles of SR1, Actinobacteria, Clostridia and Lachnospiraceae_unclassified could be considered potential biomarkers of insomnia.

Assessing the Causal Role of Sleep Traits on Glycated Hemoglobin: A Mendelian Randomization Study

OBJECTIVE

To examine the effects of sleep traits on glycated hemoglobin (HbA1c).

RESEARCH DESIGN AND METHODS

This study triangulated evidence across multivariable regression (MVR) and one- (1SMR) and two-sample Mendelian randomization (2SMR) including sensitivity analyses on the effects of five self-reported sleep traits (i.e., insomnia symptoms [difficulty initiating or maintaining sleep], sleep duration, daytime sleepiness, napping, and chronotype) on HbA1c (in SD units) in adults of European ancestry from the UK Biobank (for MVR and 1SMR analyses) (n = 336,999; mean [SD] age 57 [8] years; 54% female) and in the genome-wide association studies from the Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC) (for 2SMR analysis) (n = 46,368; 53 [11] years; 52% female).

RESULTS

Across MVR, 1SMR, 2SMR, and their sensitivity analyses, we found a higher frequency of insomnia symptoms (usually vs. sometimes or rarely/never) was associated with higher HbA1c (MVR 0.05 SD units [95% CI 0.04-0.06]; 1SMR 0.52 [0.42-0.63]; 2SMR 0.24 [0.11-0.36]). Associations remained, but point estimates were somewhat attenuated after excluding participants with diabetes. For other sleep traits, there was less consistency across methods, with some but not all providing evidence of an effect.

CONCLUSIONS

Our results suggest that frequent insomnia symptoms cause higher HbA1c levels and, by implication, that insomnia has a causal role in type 2 diabetes. These findings could have important implications for developing and evaluating strategies that improve sleep habits to reduce hyperglycemia and prevent diabetes.