Significant role of gene-gene interactions of clock genes in mood disorder

Sex-specific associations between circadian-related genes and depression in UK Biobank participants highlight links to glucose metabolism, inflammation and neuroplasticity pathways

Depressive disorders have increased in global prevalence, making improved management of these disorders a public health priority. Prior research has linked circadian clock genes to depression, either through direct interactions with mood-related pathways in the brain or by modulating the phase of circadian rhythms. Using machine learning and statistical techniques, we explored associations between 157,347 SNP variants from 51 circadian-related genes and depression scores from the patient health questionnaire 9 (PHQ-9) in 99,939 UK Biobank participants. Our results highlight multiple pathways linking the circadian system to mood, including metabolic, monoamine, immune, and stress-related pathways. Notably, genes regulating glucose metabolism and inflammation (GSK3B, LEP, RORA, and NOCT) were prominent factors in females, in addition to DELEC1 and USP46, two genes of unknown function. In contrast, FBXL3 and DRD4 emerged as significant risk factors for male depression. We also found epistatic interactions involving RORA, NFIL3, and ZBTB20 as either risk or protective factors for depression, underscoring the importance of transcription factors (ZBTB20, NFIL3) and hormone receptors (RORA) in depression etiology. Understanding the complex, sex-specific links between circadian genes and mood disorders will facilitate the development of therapeutic interventions and enhance the efficacy of multi-target treatments for depression.

The circadian rhythm: A new target of natural products that can protect against diseases of the metabolic system, cardiovascular system, and nervous system

BACKGROUND

The treatment of metabolic system, cardiovascular system, and nervous system diseases remains to be explored. In the internal environment of organisms, the metabolism of substances such as carbohydrates, lipids and proteins (including biohormones and enzymes) exhibit a certain circadian rhythm to maintain the energy supply and material cycle needed for the normal activities of organisms. As a key factor for the health of organisms, the circadian rhythm can be disrupted by pathological conditions, and this disruption accelerates the progression of diseases and results in a vicious cycle. The current treatments targeting the circadian rhythm for the treatment of metabolic system, cardiovascular system, and nervous system diseases have certain limitations, and the identification of safer and more effective circadian rhythm regulators is needed.

AIM OF THE REVIEW

To systematically assess the possibility of using the biological clock as a natural product target for disease intervention, this work reviews a range of evidence on the potential effectiveness of natural products targeting the circadian rhythm to protect against diseases of the metabolic system, cardiovascular system, and nervous system. This manuscript focuses on how natural products restore normal function by affecting the amplitude of the expression of circadian factors, sleep/wake cycles and the structure of the gut microbiota.

KEY SCIENTIFIC CONCEPTS OF THE REVIEW

This work proposes that the circadian rhythm, which is regulated by the amplitude of the expression of circadian rhythm-related factors and the sleep/wake cycle, is crucial for diseases of the metabolic system, cardiovascular system and nervous system and is a new target for slowing the progression of diseases through the use of natural products. This manuscript provides a reference for the molecular modeling of natural products that target the circadian rhythm and provides a new perspective for the time-targeted action of drugs.

Emerging trends and hot spots of sleep and genetic research: a bibliometric analysis of publications from 2002 to 2022 in the field

Background

Sleep is an important biological process and has been linked to many diseases; however, very little is known about which and how genes control and regulate sleep. Although technology has seen significant development, this issue has still not been adequately resolved. Therefore, we conducted a bibliometric analysis to assess the progress in research on sleep quality and associated genes over the past 2 decades. Through our statistical data and discussions, we aimed to provide researchers with better research directions and ideas, thus promoting the advancement of this field.

Methods

On December 29, 2022, we utilized bibliometric techniques, such as co-cited and cluster analysis and keyword co-occurrence, using tools such as CiteSpace, VOSviewer, and the Online Analysis Platform of Literature Metrology (http://bibliometric.com/), to conduct a thorough examination of the relevant publications extracted from the Web of Science Core Collection (WoSCC). Our analysis aimed to identify the emerging trends and hot spots in this field while also predicting their potential development in future.

Results

Cluster analysis of the co-cited literature revealed the most popular terms relating to sleep quality and associated genes in the manner of cluster labels; these included genome-wide association studies (GWAS), circadian rhythms, obstructive sleep apnea (OSA), DNA methylation, and depression. Keyword burst detection suggested that obstructive sleep apnea, circadian clock, circadian genes, and polygenic risk score were newly emergent research hot spots.

Conclusion

Based on this bibliometric analysis of the publications in the last 20 years, a comprehensive analysis of the literature clarified the contributions, changes in research hot spots, and evolution of research techniques regarding sleep quality and associated genes. This research can provide medical staff and researchers with revelations into future directions of the study on the pathological mechanisms of sleep-related diseases.

Whole Person Modeling: a transdisciplinary approach to mental health research

The growing global burden of mental illness has prompted calls for innovative research strategies. Theoretical models of mental health include complex contributions of biological, psychosocial, experiential, and other environmental influences. Accordingly, neuropsychiatric research has self-organized into largely isolated disciplines working to decode each individual contribution. However, research directly modeling objective biological measurements in combination with cognitive, psychological, demographic, or other environmental measurements is only now beginning to proliferate. This review aims to (1) to describe the landscape of modern mental health research and current movement towards integrative study, (2) to provide a concrete framework for quantitative integrative research, which we call Whole Person Modeling, (3) to explore existing and emerging techniques and methods used in Whole Person Modeling, and (4) to discuss our observations about the scarcity, potential value, and untested aspects of highly transdisciplinary research in general. Whole Person Modeling studies have the potential to provide a better understanding of multilevel phenomena, deliver more accurate diagnostic and prognostic tests to aid in clinical decision making, and test long standing theoretical models of mental illness. Some current barriers to progress include challenges with interdisciplinary communication and collaboration, systemic cultural barriers to transdisciplinary career paths, technical challenges in model specification, bias, and data harmonization, and gaps in transdisciplinary educational programs. We hope to ease anxiety in the field surrounding the often mysterious and intimidating world of transdisciplinary, data-driven mental health research and provide a useful orientation for students or highly specialized researchers who are new to this area.

A Predictive Model of Risk Factors for Conversion From Major Depressive Disorder to Bipolar Disorder Based on Clinical Characteristics and Circadian Rhythm Gene Polymorphisms

BACKGROUND

Bipolar disorder (BD) is easy to be misdiagnosed as major depressive disorder (MDD), which may contribute to a delay in treatment and affect prognosis. Circadian rhythm dysfunction is significantly associated with conversion from MDD to BD. So far, there has been no study that has revealed a relationship between circadian rhythm gene polymorphism and MDD-to-BD conversion. Furthermore, the prediction of MDD-to-BD conversion has not been made by integrating multidimensional data. The study combined clinical and genetic factors to establish a predictive model through machine learning (ML) for MDD-to-BD conversion.

METHOD

By following up for 5 years, 70 patients with MDD and 68 patients with BD were included in this study at last. Single nucleotide polymorphisms (SNPs) of the circadian rhythm genes were selected for detection. The R software was used to operate feature screening and establish a predictive model. The predictive model was established by logistic regression, which was performed by four evaluation methods.

RESULTS

It was found that age of onset was a risk factor for MDD-to-BD conversion. The younger the age of onset, the higher the risk of BD. Furthermore, suicide attempts and the number of hospitalizations were associated with MDD-to-BD conversion. Eleven circadian rhythm gene polymorphisms were associated with MDD-to-BD conversion by feature screening. These factors were used to establish two models, and 4 evaluation methods proved that the model with clinical characteristics and SNPs had the better predictive ability.

CONCLUSION

The risk factors for MDD-to-BD conversion have been found, and a predictive model has been established, with a specific guiding significance for clinical diagnosis.

Biological, Psychological, and Social Determinants of Depression: A Review of Recent Literature

Depression is one of the leading causes of disability, and, if left unmanaged, it can increase the risk for suicide. The evidence base on the determinants of depression is fragmented, which makes the interpretation of the results across studies difficult. The objective of this study is to conduct a thorough synthesis of the literature assessing the biological, psychological, and social determinants of depression in order to piece together the puzzle of the key factors that are related to this condition. Titles and abstracts published between 2017 and 2020 were identified in PubMed, as well as Medline, Scopus, and PsycInfo. Key words relating to biological, social, and psychological determinants as well as depression were applied to the databases, and the screening and data charting of the documents took place. We included 470 documents in this literature review. The findings showed that there are a plethora of risk and protective factors (relating to biological, psychological, and social determinants) that are related to depression; these determinants are interlinked and influence depression outcomes through a web of causation. In this paper, we describe and present the vast, fragmented, and complex literature related to this topic. This review may be used to guide practice, public health efforts, policy, and research related to mental health and, specifically, depression.

Circadian Rhythms in Mood Disorders

Altered behavioral rhythms are a fundamental diagnostic feature of mood disorders. Patients report worse subjective sleep and objective measures confirm this, implicating a role for circadian rhythm disruptions in mood disorder pathophysiology. Molecular clock gene mutations are associated with increased risk of mood disorder diagnosis and/or severity of symptoms, and mouse models of clock gene mutations have abnormal mood-related behaviors. The mechanism by which circadian rhythms contribute to mood disorders remains unknown, however, circadian rhythms regulate and are regulated by various biological systems that are abnormal in mood disorders and this interaction is theorized to be a key component of mood disorder pathophysiology. A growing body of evidence has begun defining how the interaction of circadian and neurotransmitter systems influences mood and behavior, including the role of current antidepressants and mood stabilizers. Additionally, the hypothalamus-pituitary-adrenal (HPA) axis interacts with both circadian and monoaminergic systems and may facilitate the contribution of environmental stressors to mood disorder pathophysiology. The central role of circadian rhythms in mood disorders has led to the development of chronotherapeutics, which are treatments designed specifically to target circadian rhythm regulators, such as sleep, light, and melatonin, to produce an antidepressant response.

Germline Variants and Genetic Interactions of Several EMT Regulatory Genes Increase the Risk of HBV-Related Hepatocellular Carcinoma

Epithelial-mesenchymal transition (EMT) plays an important role in the development of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). We hypothesized that germline variants in the major EMT regulatory genes (SNAIL1, ZEB1, ZEB2, TWIST1) may influence the development of HBV-related HCC. We included 421 cases of HBsAg-positive patients with HCC, 1371 cases of HBsAg-positive subjects without HCC [patients with chronic hepatitis B (CHB) or liver cirrhosis (LC)] and 618 cases of healthy controls in the case-control study. Genotype, allele, and haplotype associations in the major EMT regulatory genes were tested. Environment-gene and gene-gene interactions were analysed using the non-parametric model-free multifactor dimensionality reduction (MDR) method. The SNAIL1rs4647958T>C was associated with a significantly increased risk of both HCC (CT+CC vs. TT: OR=1.559; 95% confidence interval [CI], 1.073-2.264; P=0.020) and CHB+LC (CT+CC vs. TT: OR=1.509; 95% CI, 1.145-1.988; P=0.003). Carriers of the TWIST1rs2285681G>C (genotypes CT+CC) had an increased risk of HCC (CG+CC vs. GG: OR=1.407; 95% CI, 1.065-1.858; P=0.016). The ZEB2rs3806475T>C was associated with significantly increased risk of both HCC (P _recessive =0.001) and CHB+LC (P _recessive<0.001). The CG haplotype of the rs4647958/rs1543442 haplotype block was associated with significant differences between healthy subjects and HCC patients (P=0.0347). Meanwhile, the CT haplotype of the rs2285681/rs2285682 haplotype block was associated with significant differences between CHB+LC and HCC patients (P=0.0123). In MDR analysis, the combination of TWIST1rs2285681, ZEB2rs3806475, SNAIL1rs4647958 exhibited the most significant association with CHB+LC and Health control in the three-locus model. Our results suggest significant single-gene associations and environment-gene/gene-gene interactions of EMT-related genes with HBV-related HCC.

Chronotype and social support among student athletes: impact on depressive symptoms

Previous studies have shown individuals with evening chronotype to have a greater likelihood for depression (self-reported and clinical ratings), especially in young adults. However, the mechanisms for this relationship remain unknown. Low levels of social support may be a plausible mechanism: young adults with evening chronotypes are awake when others are sleeping, which may lead to feelings of isolation or low support. This study examined links between chronotype, depression, and social support in relationship subtypes within a group of university student athletes. Data were obtained from 189 NCAA Division-I student athletes across all sports. Chronotype was assessed with the Circadian Energy Scale and ranged from -2 (definitely morning type) to +2 (definitely evening type). Depressive symptoms were assessed with Center for Epidemiological Studies Depression scale. Social support was assessed with the Multidimensional Scale of Perceived Social Support, which included subscales for Family, Friends, and Significant Other. A subscale for Team was created using the items from the Friends subscale (changing the word "friends" to "teammates"). Regression analyses adjusted for age, sex, and minority status. More evening chronotype was associated with higher reported depressive symptoms (p = .018), lower overall perceived social support (p = .001), and lower perceived social support specifically provided by family (p < .0001), friends (p < .0001), and teammates (p = .014). However, more evening chronotype was associated with higher depressive symptoms for higher, but not lower perceived social support from significant other. Moreover, chronotype-by-support interactions on depressive symptoms were observed; the statistical relationship between chronotype and depression was evident only in those with low (but not high) social support from friends and teammates. These data suggest that having a more evening chronotype may be associated with social isolation, and decreased opportunities for interactions with friends and teammates. This may contribute to the long-standing circadian association seen with depression in college student-athletes. Interventions aimed at increasing university support networks may reduce the impact of depression in students self-identifying with later chronotypes and sleep schedules.

Identification of the key genes and pathways involved in B cells in primary Sjögren' s syndrome

Primary Sjögren’ s syndrome (pSS) is a relatively common autoimmune disease, which mainly involves the exocrine glands, causing dry eye, dryness of mouth, fatigue and pain in the joints, thus severely affecting the normal lives of patients. B cell populations are considered to play an important role in their pathogenesis and pSS patients are generally characterized by exhibiting biological signs of B cell activation. Moreover, another important characterized change in the peripheral blood of pSS patients is found to be the decreased number of circulating memory B cells. However, the mechanisms underlying the B cell activation and the decreased level of circulating memory B cells in pSS patients are still unclear. Therefore, we identified key genes and pathways involved in B cells in pSS through a combination of several bioinformatic approaches including Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and weighted gene co-expression network analysis (WGCNA) using gene expression data of pSS patients and controls from an open database Gene Expression Omnibus (GEO). The results may provide some novel insights into the pathogenesis of pSS. Moreover, we constructed and validated a diagnostic model for pSS by using the expression patterns of these key genes, which may assist clinicians in diagnosing pSS.

A new approach for seasonal pattern: is it related to bipolarity dimension? Findings from an Italian multicenter study

OBJECTIVE

The aims of this study were to assess the impact of seasonal pattern on several clinical dimensions in inpatients with a current major depressive episode and to evaluate clinical differences between unipolar and bipolar depression according to seasonal pattern.

METHODS

Study participants were 300 patients affected by major depressive disorder (MDD) or bipolar disorder (BD) currently experiencing a major depressive episode (MDE) and were recruited at three University Medical Centres in Italy. All study subjects completed several evaluation scales for depressive and hypomanic symptoms, quality of life and functioning, impulsiveness, and seasonal pattern.

RESULTS

Several differences between BD with and without seasonal pattern, MDD with and without seasonal pattern but in particular between BD and MDD with seasonal pattern were found. Patients with MDE with seasonal pattern had more frequently received a longitudinal diagnosis of BD.

CONCLUSIONS

A large number of patients with BD and seasonal pattern, but also a considerable number of patients with MDD and seasonal pattern, endorsed manic items during a current MDE. Seasonal pattern should be associated with a concept of bipolarity in mood disorders and not only related to bipolar disorder. A correct identification of seasonal patterns may lead to the implementation of personalised pharmacological treatment approaches.KEY POINTSHigh prevalence of mixed features in mood disorders with seasonal pattern, supporting the need for a dimensional approach to major depressive disorder and bipolar disorder.Significant percentage of patients with a primary diagnosis of major depressive disorder had seasonal pattern.Significant percentage of patients with a primary diagnosis of major depressive disorder reported (hypo)manic symptomatology.

Investigation of gene-gene interactions of clock genes for chronotype in a healthy Korean population

Chronotype is an important moderator of psychiatric illnesses, which seems to be controlled in some part by genetic factors. Clock genes are the most relevant genes for chronotype. In addition to the roles of individual genes, gene-gene interactions of clock genes substantially contribute to chronotype. We investigated genetic associations and gene-gene interactions of the clock genes BHLHB2, CLOCK, CSNK1E, NR1D1, PER1, PER2, PER3, and TIMELESS for chronotype in 1293 healthy Korean individuals. Regression analysis was conducted to find associations between single nucleotide polymorphism (SNP) and chronotype. For gene-gene interaction analyses, the quantitative multifactor dimensionality reduction (QMDR) method, a nonparametric model-free method for quantitative phenotypes, were performed. No individual SNP or haplotype showed a significant association with chronotype by both regression analysis and single-locus model of QMDR. QMDR analysis identified NR1D1 rs2314339 and TIMELESS rs4630333 as the best SNP pairs among two-locus interaction models associated with chronotype (cross-validation consistency [CVC] = 8/10, p = 0.041). For the three-locus interaction model, the SNP combination of NR1D1 rs2314339, TIMELESS rs4630333, and PER3 rs228669 showed the best results (CVC = 4/10, p < 0.001). However, because the mean differences between genotype combinations were minor, the clinical roles of clock gene interactions are unlikely to be critical.

Glymphatic Dysfunction: A Bridge Between Sleep Disturbance and Mood Disorders

Mounting evidence demonstrates a close relationship between sleep disturbance and mood disorders, including major depression disorder (MDD) and bipolar disorder (BD). According to the classical two-process model of sleep regulation, circadian rhythms driven by the light-dark cycle, and sleep homeostasis modulated by the sleep-wake cycle are disrupted in mood disorders. However, the exact mechanism of interaction between sleep and mood disorders remains unclear. Recent discovery of the glymphatic system and its dynamic fluctuation with sleep provide a plausible explanation. The diurnal variation of the glymphatic circulation is dependent on the astrocytic activity and polarization of water channel protein aquaporin-4 (AQP4). Both animal and human studies have reported suppressed glymphatic transport, abnormal astrocytes, and depolarized AQP4 in mood disorders. In this study, the "glymphatic dysfunction" hypothesis which suggests that the dysfunctional glymphatic pathway serves as a bridge between sleep disturbance and mood disorders is proposed.