Causal impacts of smoking on pain conditions and the mediating pathways: a mendelian randomization study.

Smoking is a risk factor for multiple diseases. We performed mendelian randomization (MR) analyses to investigate the causal association of smoking initiation on pain conditions and the potential mediating pathways. Genetic associated with smoking initiation at the genome-wide significance level were selected as instrumental variables. Genetic associations with 10 pain conditions were derived from the FinnGen and UK Biobank study. Multivariable MR analysis was conducted to explore the mediation effects of depression, insomnia and sedentary behavior. A series of sensitivity analyses were conducted to assess the stability of our research findings. Genetic liability to smoking initiation was associated with an increased risk of angina pectoris, dorsalgia, low back pain, pain in limb, pain in joint, pain in thoracic spine and sciatica in both FinnGen and UK Biobank study. These causal associations were largely mediated by major depression (2.9- 39.5%), sedentary behavior (13.0- 31.2%), insomnia (10.3- 33.1%) and combination of all three mediators (30.2- 65.3%). The effects of smoking on outcomes were partly attenuated after adjusting for depression, sedentary behavior and insomnia respectively, and the direct effect of smoking initiation on pain was diminished toward null after adjusting for combined three mediators. These results were robust to sensitivity analyses. Our findings illustrated the causal effect of smoking and a broad range of pain conditions, and major depression, sedentary behavior and insomnia mediate many of these associations.

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.

Sleep duration and heart failure risk: Insights from a Mendelian Randomization Study.

To investigate the causal relationship between sleep duration and heart failure (HF) in a European population. We focused on the continuous sleep duration of 460,099 European individuals as our primary exposure. Genome-wide significant single nucleotide polymorphisms (SNPs, n = 9851,867) linked to continuous sleep duration were adopted as instrumental variables. The outcome of interest was based on HF events in a European cohort (n = 977,323; with 930,014 controls and 47,309 cases). We employed a two-sample Mendelian randomization (MR) approach to infer causality between sleep duration and the incidence of HF. For validation purposes, an additional cohort of 336,965 European individuals diagnosed with insomnia was selected as a secondary exposure group. Using its SNPs, a subsequent two-sample MR analysis was conducted with the HF cohort to further corroborate our initial findings. Employing the MR methodology, we selected 57 SNPs that are associated with sleep duration, and 24 SNPs that are associated with insomnia as instrumental variables. We discerned a substantial association between genetically inferred sleep duration and HF risk (odds ratio: 0.61; 95% confidence interval: 0.47-0.78, P < .0001). Our subsequent analysis highlighted a pronounced increased HF risk associated with insomnia (odds ratio: 1.54; 95% confidence interval: 1.08-2.17, P < .02). These conclusions were further bolstered by consistent results from sensitivity analyses. Our study suggests a causal linkage between sleep duration and the onset risk of HF in the European population. Notably, shorter sleep durations were associated with a heightened risk of HF.

Causal relationship between insomnia and thyroid disease: A bidirectional Mendelian randomization study.

OBJECTIVE: Some correlations between thyroid disorders and insomnia have been found in previous studies; however, the causal relationship between them is unclear. The aim of this study was to investigate the causal relationship between insomnia and five thyroid disorders (hyperthyroidism, hypothyroidism, thyroiditis, thyroid nodules, and thyroid cancer). METHODS: We assessed the causal relationship between insomnia and thyroid disorders using inverse variance weighted, weighted median, and Mendelian randomization (MR)-Egger analyses in MR analyses and then used inverse MR analyses to assess the causal relationship between thyroid disorders and insomnia. RESULTS: MR analysis showed that insomnia did not increase the risk of hyperthyroidism, hypothyroidism, thyroiditis, thyroid nodules, and thyroid cancer. However, reverse MR analysis showed that thyroid cancer increased the risk of insomnia (OR = 1.01, 95%CI: 1.00-1.02, p = .01), and the other four thyroid disorders had no direct causal relationship with insomnia. Sensitivity analyses indicated that the results were robust and no pleiotropy or heterogeneity was detected. CONCLUSION: This study did not find evidence of a bidirectional causal relationship between genetically predicted insomnia and hyperthyroidism, hypothyroidism, thyroiditis, and thyroid nodules. However, we found that although insomnia does not increase the risk of thyroid cancer, thyroid cancer does increase the risk of insomnia.

Mendelian randomization of individual sleep traits associated with major depressive disorder.

BACKGROUND: Observational studies have shown that individual sleep traits habits are potential risk factors for major depression. However, it is not known whether there is a causal relationship between individual sleep traits habits such as continuous sleep duration, short sleep duration, short sleep duration, insomnia, nap during the day, snoring, and major depression. In this study, Mendelian randomization (MR) was used to predict major depressive disorder (MDD) in individuals sleep traits habits. METHODS: Data were obtained from the genome-wide association study (GWAS). Nine MR analysis methods were used: Inverse Variance Weighted (IVW) [fixed effects/multiplicative random effects], simple mode, simple mode, weighted mode, simple median, weighted median, penalised weighted median, and MR-Egger, MR Egger (bootstrap). IVW was used as the main analysis method for the MR analysis of two samples, and the other methods were used as supplements. RESULTS: The results obtained through the IVW method supported a causal relationship between sleep duration and decreased risk of MDD (odds ratio, ORivw: 0.998; 95 % CI: 0.996-0.999, P<0.001). Two-Sample MR, results showed that short sleep duration has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.179; 95 % CI: 1.108-1.255, P<0.001). However, there were no sufficient evidence supported that long sleep duration has a causal effect on the decreased risk of MDD (odds ratio, ORivw: 0.991; 95 % CI: 0.924-1.062, P = 0.793). A significant causal relationship between insomnia and increased risk of MDD was observed (OR: 1.233; 95 % CI: 1.214-1.253, P<0.001). Interestingly, our study also found that daytime napping has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.519; 95 % CI: 1.376-1.678, P<0.001). The present results did not show a significant causal relationship between snoring and the risk of MDD (ORivw: 1.000; 95 % CI: 0.998-1.002, P = 0.906). Obstructive sleep apnea (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) and morning person (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) have no causal effect on the increased risk of MDD. LIMITATIONS: The study could not ascertain whether there were genetic differences among different ethnicities, nations, and regions, as it only included participants of European ancestry. CONCLUSIONS: In summary, our research provides genetic evidence for the relationship between individual sleep traits (short sleep duration, insomnia, daytime napping) and the increased risk of MDD. Interventions targeting lifestyle factors may reduce the risk of MDD.

Exploring Causal Links Between Gut Microbiota and Geriatric Syndromes: A Two-Sample Mendelian Randomization Analysis.

Background: Both observational studies and clinical trials have demonstrated a link between the gut microbiota and the geriatric syndrome. Nevertheless, the exact nature of this relationship, particularly concerning causality, remains elusive. Mendelian randomization (MR) is a method of inference based on genetic variation to assess the causal relationship between an exposure and an outcome. In this study, we conducted a two-sample Mendelian randomization (TSMR) study to fully reveal the potential genetic causal effects of gut microbiota on geriatric syndromes. Methods: This study used data from genome wide association studies (GWAS) to investigate causal relationships between the gut microbiota and geriatric syndromes, including frailty, Parkinson's disease (PD), delirium, insomnia, and depression. The primary causal relationships were evaluated using the inverse-variance weighted method, MR Egger, simple mode, weighted mode and weighted median. To assess the robustness of the results, horizontal pleiotropy was examined through MR-Egger intercept and MR-presso methods. Heterogeneity was assessed using Cochran's Q test, and sensitivity was evaluated via the leave-one-out method. Results: We identified 41 probable causal relationships between gut microbiota and five geriatric syndrome-associated illnesses using the inverse-variance weighted method. Frailty showed five positive and two negative causal relationships, while PD revealed three positive and four negative causal connections. Delirium showed three positive and two negative causal relationships. Similarly, insomnia demonstrated nine positive and two negative causal connections, while depression presented nine positive and two negative causal relationships. Conclusions: Using the TSMR method and data from the public GWAS database and, we observed associations between specific microbiota groups and geriatric syndromes. These findings suggest a potential role of gut microbiota in the development of geriatric syndromes, providing valuable insights for further research into the causal relationship between gut microbiota and these syndromes.

Investigating the Link between Circadian Clock Gene Expressions, Chronotype, Insomnia, and Daytime Sleepiness in Patients with Obstructive Sleep Apnea.

INTRODUCTION: This study aimed to investigate the relationship between obstructive sleep apnea (OSA), circadian rhythms, and individual sleep-wake preferences, as measured by chronotype, and to assess the association between circadian clock gene expression and subjective sleep-related variables. METHODS: A total of 184 individuals were recruited, underwent polysomnography (PSG), and completed questionnaires including a chronotype questionnaire (CQ), insomnia severity index (ISI), and Epworth sleepiness scale (ESS). Blood samples were collected in the evening before and morning after PSG. Gene expression analysis included BMAL1, CLOCK, PER1, CRY1, NPAS2, and NR1D1. RESULTS: In the OSA group, the subjective amplitude (AM score of CQ) positively correlated with all circadian clock genes in the morning (R ≥ 0.230 and p < 0.05 for each one), while the morningness-eveningness (ME score of CQ) was only associated with the evening BMAL1 level (R = 0.192; p = 0.044). In healthy controls, insomnia severity correlated with evening expression of BMAL1, PER1, and CRY1. CONCLUSIONS: The findings highlight the complex interplay between OSA, circadian rhythms, and sleep-related variables, suggesting potential determinants of morning chronotype in OSA and implicating disrupted circadian clock function in subjective feelings of energy throughout the day. Further research is warranted to elucidate underlying mechanisms and guide personalized management strategies.

Insomnia and sleep duration for kidney function: Mendelian randomization study.

OBJECTIVES: Extensive researches highlight the detrimental impact of sleep disorders such as insomnia and insufficient sleep duration on kidney function. However, establishing a clear causal relationship between insomnia, sleep duration, and kidney function remains challenging. This study aims to estimate this relationship using Mendelian randomization (MR). METHODS: Independent genetic variants strongly associated with insomnia (N = 462,341) and sleep duration (N = 460,099) were selected as instrumental variables from corresponding genome-wide association studies (GWAS). Kidney function parameters, including serum creatinine, estimated glomerular filtration rate by cystatin C (eGFRcys), acute renal failure (ARF), chronic renal failure (CRF), kidney injury molecule-1, neutrophil gelatinase associated lipocalin, microalbuminuria, cystatin C, and ß2 microglobulin, were derived from GWAS databases. A two-sample MR study was conducted to assess the causal relationship between sleep disorders and kidney function, and multivariable MR was used to identify potential mediators. The inverse-variance weighted was used as the primary estimate. RESULTS: MR analysis found robust evidence indicating that insomnia and short sleep duration were associated with an increased risk of elevated serum creatinine, regardless of adjusting for obesity. Causal links between sleep duration and eGFRcys or cystatin C were also identified. While genetically predicted insomnia and sleep duration were found to potentially impact ARF, CRF, microalbuminuria, and ß2 microglobulin, the p-values in multivariable MR analysis became nonsignificant. No pleiotropy was detected. CONCLUSIONS: This study demonstrates a causal impact of insomnia on the risk of elevated serum creatinine and a positive effect of sleep duration on serum creatinine, eGFRcys, and cystatin C. Our findings also suggest their potential indirect effects on ARF, CRF, microalbuminuria, and ß2 microglobulin mediated by obesity.

[A Mendelian randomization study on the relationship between insomnia and osteoporosis].

Objective: To explore the relationship between insomnia and osteoporosis. Methods: Mendelian randomization (MR) analysis were used in this study. The single nucleotide polymorphisms (SNPs) related to insomnia from genome-wide association analysis research data were selected as the instrumental variables by using inverse variance weighted (IVW), MR-Egger regression, weighted median method, maximum likelihood, penalized weighted median estimator, and Mendelian randomization robust adjusted profile score (MR-RAPS) to determine the causal relationship between insomnia and osteoporosis. Odds ratio (OR) and 95% confidence interval (CI) values were used to evaluate the association between insomnia and osteoporosis. Cochran's Q-test was used to detect heterogeneity of SNPs, MR-Egger regression was used to test for level pleiotropy, and the leave-one-out method was used to test sensitivity, MR pleiotropy residual sum and outlier (MR-PRESSO) method and radial MR were used to detect erroneous outliers. Results: The screening criteria were set based on the three major assumptions of MR; finally, 31 SNPs were included in the MR analysis. The results of MR causal effect analysis using the IVW method showed that insomnia increased the risk of osteoporosis by about 0.7% (OR=1.007, 95%CI 1.001-1.014, P=0.044); heterogeneity testing showed heterogeneity between SNPs (Q=57.91, P<0.001); and the MR- Egger intercept test did not indicate horizontal pleiotropy in this study (intercept value=3.807×10-5, P=0.888). Leave-one-out method showed that no single SNP had a significant impact on the overall results. No abnormal SNP was detected according to the MR-PRESSO results (P=0.059), and radial MR did not detect any outliers. Conclusion: Mendelian randomization analysis showed that insomnia can increase the risk of osteoporosis.

Impact of negative emotions and insomnia on sepsis: A mediation Mendelian randomization study.

BACKGROUND: Negative emotions and insomnia (NEI) can lead to inflammation, which is a characteristic of sepsis. However, the interaction among NEI and sepsis has not yet been proven. Therefore, Mendelian mediation was used to explore this relationship in this study. METHODS: The genetic correlation NEI and sepsis was assessed by via linkage disequilibrium scores (LDSC). A two-sample Mendelian randomization (MR) study design was performed to examine the causal association between NEI and sepsis using the inverse variance weighted (IVW) method. The reliability of the results was estimated by weighted median and MR-Egger methods, but heterogeneity was evaluated via Radial and Cochran's Q tests. Biases in gene polymorphisms were checked by MR-Egger regression and MR-PRESSO. Mendelian mediation analyses were applied to quantify the intermediary effect and proportional contribution. RESULTS: A genetic link between sepsis and depression was determined via LDSC analysis. The relationship between depression and sepsis was revealed through MR analysis [odds ratio (OR) = 1.21, 95 % confidence interval (CI) = 1.08-1.36, p = 1.07 × 10-3)]. The results were not influenced by heterogeneity or pleiotropy biases. Chitinase 3 Like 1 (CHI3L1) was a mediator with a mediation effect size of 0.12. The ratio of the intermediated effect to total effect was 10.31 %. CONCLUSION: CHI3L1 is a key factor which mediates the interaction between NEI and sepsis.

Mendelian randomization highlights sleep disturbances mediated the effect of depression on chronic pain.

INTRODUCTION: Depression and chronic pain are significant contributors to the global burden of disease. Previous research has revealed complex relationships between these two conditions, which may be influenced by sleep quality. However, observational studies have limitations, including confounding factors and reverse causation. This study aims to explore the mediating effects of sleep on the relationship between depression and chronic pain using Mendelian randomization (MR). METHODS: We conducted a two-step, two-sample MR study using mediation analysis. We obtained major depressive disorder (MDD) Genome-Wide Association Studdies (GWAS) data from Wray et al.'s GWAS meta-analysis. Phenotypic data related to sleep were collected from the UK Biobank. Chronic pain data were obtained from the Finnish database. RESULTS: MR analysis revealed significant genetic associations between MDD and chronic localized pain [IVW: odds ratio (OR) = 1.26, 95% confidence interval (CI) = 1.16-1.38, p = 2.52 × 10-7] as well as fibromyalgia (IVW: OR = 2.17, 95% CI = 1.34-3.52, p = .002). Genetic susceptibility for MDD was also associated with insomnia (IVW: OR = 1.10, 95% CI = 1.06-1.13, p = 3.57 × 10-8) and self-reported short sleep duration (IVW: OR = 1.03, 95% CI = 1.00-1.06, p = .047). The mediating effects of insomnia and fibromyalgia on the pathway from depression to chronic regional pain were 1.04 and 1.03, respectively, with mediation proportions of 12.8% and 15.2%. Insomnia mediated the pathway between depression and fibromyalgia with an effect of 1.12, accounting for 15.2% of the total effect. CONCLUSION: This two-step MR analysis strengthens the evidence of genetic predictive associations between depression and chronic pain, highlighting the mediating roles of insomnia and short sleep duration. It further elucidates the specific roles of distinct sleep disorders, differentiating insomnia and short sleep duration from other sleep-related phenotypes.

Genomic correlation, shared loci, and causal relationship between insomnia and psoriasis: a large-scale genome-wide cross-trait analysis.

Psoriasis and insomnia have co-morbidities, however, their common genetic basis is still unclear. We analyzed psoriasis and insomnia with summary statistics from genome-wide association studies. We first quantified overall genetic correlations, then ascertained multiple effector loci and expression-trait associations, and lastly, we analyzed the causal effects between psoriasis and insomnia. A prevalent genetic link between psoriasis and insomnia was found, four pleiotropic loci affecting psoriasis and insomnia were identified, and 154 genes were shared, indicating a genetic link between psoriasis and insomnia. Yet, there is no causal relationship between psoriasis and insomnia by two-sample Mendelian randomization. We discovered a genetic connection between insomnia and psoriasis driven by biological pleiotropy and unrelated to causation. Cross-trait analysis indicates a common genetic basis for psoriasis and insomnia. The results of this study highlight the importance of sleep management in the pathogenesis of psoriasis.

Kinesin binding as a shared pathway underlying the genetic basis of male factor infertility and insomnia.

OBJECTIVE: To study whether male factor infertility and insomnia share genetic risk variants and identify any molecular, cellular, and biologic interactions between these traits. DESIGN: The in silico study was performed. Two lists of genetic variants were manually curated through a literature review, one of those associated with male factor infertility and the other with insomnia. Genes were assigned to these variants to compose male factor infertility-associated (454 genes) and insomnia-associated (921 genes) gene lists. SETTING: Not applicable. PATIENT(S): Not applicable. INTERVENTION(S): Not applicable. MAIN OUTCOME MEASURE(S): Enrichment of biologic pathways and protein-protein interaction analysis. RESULT(S): Twenty-eight genes were common to both lists, representing a greater overlap than would be expected by chance. In the 28 genes contained in the intersection list, there was a significant enrichment of pathways related to kinesin binding. A protein-protein interaction analysis using the intersection list as input retrieved 25 nodes and indicated that two of them were kinesin-related proteins (PLEKHM2 and KCL1). CONCLUSION(S): The shared male factor infertility and insomnia genes, and the biologic pathways highlighted in this study, suggest that further functional investigations into the interplay between fertility and sleep are warranted.

Impact of insomnia on ovarian cancer risk and survival: a Mendelian randomization study.

BACKGROUND: Insomnia is the most common sleep disorder in patients with epithelial ovarian cancer (EOC). We investigated the causal association between genetically predicted insomnia and EOC risk and survival through a two-sample Mendelian randomization (MR) study. METHODS: Insomnia was proxied using genetic variants identified in a genome-wide association study (GWAS) meta-analysis of UK Biobank and 23andMe. Using genetic associations with EOC risk and overall survival from the Ovarian Cancer Association Consortium (OCAC) GWAS in 66,450 women (over 11,000 cases with clinical follow-up), we performed Iterative Mendelian Randomization and Pleiotropy (IMRP) analysis followed by a set of sensitivity analyses. Genetic associations with survival and response to treatment in ovarian cancer study of The Cancer Genome Atlas (TCGA) were estimated controlling for chemotherapy and clinical factors. FINDINGS: Insomnia was associated with higher risk of endometrioid EOC (OR = 1.60, 95% CI 1.05-2.45) and lower risk of high-grade serous EOC (HGSOC) and clear cell EOC (OR = 0.79 and 0.48, 95% CI 0.63-1.00 and 0.27-0.86, respectively). In survival analysis, insomnia was associated with shorter survival of invasive EOC (OR = 1.45, 95% CI 1.13-1.87) and HGSOC (OR = 1.4, 95% CI 1.04-1.89), which was attenuated after adjustment for body mass index and reproductive age. Insomnia was associated with reduced survival in TCGA HGSOC cases who received standard chemotherapy (OR = 2.48, 95% CI 1.13-5.42), but was attenuated after adjustment for clinical factors. INTERPRETATION: This study supports the impact of insomnia on EOC risk and survival, suggesting treatments targeting insomnia could be pivotal for prevention and improving patient survival. FUNDING: National Institutes of Health, National Cancer Institute. Full funding details are provided in acknowledgments.

No causal association between insomnia and bladder cancer: a bidirectional two-sample Mendelian randomization study.

BACKGROUND: Previous observational studies have indicated a potential link between insomnia and bladder cancer, yet the underlying causal relationship remains uncertain. The current study employed a bidirectional two-sample Mendelian randomization (MR) analysis to investigate this association. METHODS: A two-sample MR analysis was conducted utilizing publicly available summary data from genome-wide association studies (GWAS) on insomnia and bladder cancer. Various regression methods including the inverse variance weighted (IVW), weighted median, MR-Egger, weighted mode, and simple mode methods were employed for the MR analysis. The presence of pleiotropy and heterogeneity in the MR results was also assessed. Furthermore, additional sensitivity tests were performed to mitigate potential biases. RESULTS: No significant causal relationship was detected between insomnia and bladder cancer using IVW method (OR = 0.761, 95% CI 0.996-1.005; P = 0.76). Similarly, the IVW model did not reveal any causal effect of bladder cancer on the risk of insomnia (OR = 1.47, 95% CI 0.772-2.799; P = 0.24). Consistent results were obtained from the other four methods employed. There was no evidence of horizontal pleiotropy or heterogeneity in our MR analysis (P > 0.05). The sensitivity analyses further supported the reliability of the estimated causal effects. CONCLUSIONS: This study presents no evidence for a causal relationship between insomnia and bladder cancer.

Causal associations between sleep traits and age at natural menopause: A Mendelian randomization study.

Observational studies have revealed that several sleep traits can impact ovarian function in women. However, there is no evidence suggesting associations between sleep traits and age at natural menopause (ANM). The objective of this study was to investigate the causal relationship between sleep traits (insomnia, sleep duration, daytime sleepiness) and ANM from the perspective of genetic variation. We selected the single-nucleotide polymorphisms from large-scale genome-wide association studies as instrumental variables and conducted a two-sample Mendelian randomization (MR) analysis on these single-nucleotide polymorphisms, including inverse variance weighting, MR-Egger, weighted median, simple mode and weighted mode. The Steiger test was employed to verify the correct causal directionality. The robustness of the MR analysis was examined through Cochran's Q test, horizontal pleiotropy test, and leave-one-out analysis. The results indicated that insomnia was causally associated with ANM (inverse variance weighting: ß = -0.982; 95% CI: -1.852 to -0.111, P = .027), with other analyses confirming the robustness of this finding. Steiger test and reverse MR Analysis validated the absence of a reverse causal association between the two. However, sleep duration and daytime sleepiness did not exhibit a causal effect on ANM. In summary, this study provides initial evidence that insomnia can contribute to an earlier onset of ANM. Nevertheless, further clinical studies are needed to elucidate these findings.

The role of accelerometer-derived sleep traits on glycated haemoglobin and glucose levels: a Mendelian randomization study.

Self-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be 'objective' measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics.

Sleep regulation and host genetics.

Due to the multifactorial and complex nature of rest, we focus on phenotypes related to sleep. Sleep regulation is a multifactorial process. In this chapter, we focus on those phenotypes inherent to sleep that are highly prevalent in the population, and that can be modulated by lifestyle, such as sleep quality and duration, insomnia, restless leg syndrome and daytime sleepiness. We, therefore, leave in the background those phenotypes that constitute infrequent pathologies or for which the current level of scientific evidence does not favour the implementation of practical approaches of this type. Similarly, the regulation of sleep quality is intimately linked to the regulation of the circadian rhythm. Although this relationship is discussed in the sections that require it, the in-depth study of circadian rhythm regulation at the molecular level deserves a separate chapter, and this is how it is dealt with in this volume.

Tai Chi compared with cognitive behavioral therapy and the reversal of systemic, cellular and genomic markers of inflammation in breast cancer survivors with insomnia: A randomized clinical trial.

BACKGROUND: Insomnia contributes to inflammation in breast cancer survivors. This study evaluates whether insomnia treatment reverses inflammation in breast cancer survivors with insomnia. METHODS: Participants (n = 90) were randomized to 3 months of Tai Chi (n = 45) or cognitive behavioral therapy for insomnia (CBT-I)(n = 45), and followed for one year post-intervention to 15 month endpoint. Our previous report found that Tai Chi as compared to CBT-I resulted in similar rates of insomnia response and remission over 15 months. Here, we analyze changes in plasma C-reactive protein and pro- and anti-inflammatory cytokines, Toll-like receptor (TLR)-4 stimulated monocyte production of interleukin (IL)-6 and tumor necrosis factor-α (TNF), and cellular pro-inflammatory and anti-viral gene expression (Conserved Transcriptional Response to Adversity RNA profile; CTRA) over 15 months. RESULTS: Insomnia treatment resulted in decreases in the TLR-4 stimulated monocyte production of IL-6, TNF, and their co-expression, as well as decreases in the CTRA profile, decreases inflammatory gene transcripts, and increases in anti-viral gene transcripts over 15 months (all P's < 0.01). In addition, as compared to CBT-I, Tai Chi resulted in greater decreases in plasma IL-6 (P < 0.05), and greater decreases in TLR-4 activated monocyte production of IL-6 and co-expression of IL-6 and TNF at 15 month endpoint. CBT-I resulted in greater increases in anti-viral gene transcripts. CONCLUSIONS: Administration of either CBT-I or Tai Chi effectively treats insomnia, and shows additional benefits of reducing cellular and genomic markers of inflammation, and increasing anti-viral genomic markers in breast cancer survivors with insomnia. Tai Chi, as compared to CBT-I, yields greater and more durable decreases in systemic- and cellular inflammation. Targeting insomnia might mitigate the risk of inflammation-related co-morbidities in breast cancer survivors.

Potential mechanisms of traditional Chinese medicine in treating insomnia: A network pharmacology, GEO validation, and molecular-docking study.

The purpose of this study is to investigate the potential mechanisms of Chinese herbs for the treatment of insomnia using a combination of data mining, network pharmacology, and molecular-docking validation. All the prescriptions for insomnia treated by the academician Qi Wang from 2020 to 2022 were collected. The Ancient and Modern Medical Case Cloud Platform v2.3 was used to identify high-frequency Chinese medicinal herbs and the core prescription. The Traditional Chinese Medicine Systems Pharmacology and UniProt databases were utilized to predict the effective active components and targets of the core herbs. Insomnia-related targets were collected from 4 databases. The intersecting targets were utilized to build a protein-protein interaction network and conduct gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using the STRING database, Cytoscape software, and clusterProfiler package. Gene chip data (GSE208668) were obtained from the Gene Expression Omnibus database. The limma package was applied to identify differentially expressed genes (DEGs) between insomnia patients and healthy controls. To create a "transcription factor (TF)-miRNA-mRNA" network, the differentially expressed miRNAs were entered into the TransmiR, FunRich, Targetscan, and miRDB databases. Subsequently, the overlapping targets were validated using the DEGs, and further validations were conducted through molecular docking and molecular dynamics simulations. Among the 117 prescriptions, 65 herbs and a core prescription were identified. Network pharmacology and bioinformatics analysis revealed that active components such as ß-sitosterol, stigmasterol, and canadine acted on hub targets, including interleukin-6, caspase-3, and hypoxia-inducible factor-1α. In GSE208668, 6417 DEGs and 7 differentially expressed miRNAs were identified. A "TF-miRNA-mRNA" network was constructed by 4 "TF-miRNA" interaction pairs and 66 "miRNA-mRNA" interaction pairs. Downstream mRNAs exert therapeutic effects on insomnia by regulating circadian rhythm. Molecular-docking analyses demonstrated good docking between core components and hub targets. Molecular dynamics simulation displayed the strong stability of the complex formed by small molecule and target. The core prescription by the academician Qi Wang for treating insomnia, which involves multiple components, targets, and pathways, showed the potential to improve sleep, providing a basis for clinical treatment of insomnia.