Recent Research Trends and Key Topics in Sleep and Genetics from 2002 to 2022

Sleep is a fundamental biological process that is conserved across a wide range of organisms from invertebrates to vertebrates, but the pathobiology and molecular mechanisms of sleep are still not fully understood. There was a strong interest in the genetics of sleep. In the 1930s, Geyer conducted a twin study in children and first showed that genetic factors were involved in the regulation of sleep. Since then, numerous high-quality studies on gene expression profiling indicate that there is a shared genetic basis for sleep across different species (1, 2). In other words, there is a belief that the mechanism responsible for sleep is evolutionarily conserved and that similar genetic pathways are involved in regulating sleep across different organisms. Nowadays, various new programs and techniques have been developed, leading to breakthroughs in the understanding of sleep function, circadian rhythms, and pathological mechanisms of sleep-related diseases (3–5).

However, the molecular and pathobiology mechanisms of sleep and sleep-related diseases are quite complex and least understood phenomena for a long time. Genetic analysis of sleep has only become a significant discipline in the past decade, with the focus expanding to drosophila, zebrafish, and worms. With the help of genetics, many sleep-related problems have been solved, for example, the identification of loci related to various sleep disorders such as obstructive sleep apnea (OSA), major depressive disorder (MDD), and insomnia disorder. As genetic technologies continue to develop, genes will be a powerful tool in solving these problems.

In this study, we utilized bibliometric citation analysis, which is widely employed to map and analyze the performance of specific fields, to gain insights into the temporal trends in the field of sleep quality and associated genes. It provides valuable predictions about the progress and development of specific fields based on factors such as publication volume and citation frequency (6, 7). The published studies have played a significant role in advancing specific research fields (8). To recognize the significance of the sleep and genetics topic and the effectiveness of bibliometric analysis, we conducted an analysis of publications related to this theme. Our objective was to assist researchers to identify the current trends and hot spots in this field, both in the past and future and to provide a comprehensive understanding of the evolution of this field.

In our study, bibliometric mapping was used to visualize the development of sleep quality and associated genes research from 2002 to 2022. Our findings revealed a continuous increase in scientific output in the field of genetics and sleep over the past two decades. The ranking of publication numbers of countries, universities, authors, and journals helped researchers to search for cooperations, to seek positions, or to publish their works conveniently. Analyzing the collaborative relationships among different countries/regions and institutions can also reflect the academic exchange in this field. Recent advancements in sleep research studies have been facilitated by experimental techniques such as genome-wide association studies (GWAS) analysis. Additionally, newly emergent research hot spots, including obstructive sleep apnea, circadian clock, and circadian genes, were indicated by keyword burst detection. However, despite the substantial amount of research in this area, there was a lack of studies focusing on predicting and clarifying current research hot topics and frontiers. To address this gap, we cataloged the attributes of existing studies and analyzed the results of cluster labeling and burst detection techniques to develop a nuanced understanding of the current state of research and identify promising avenues for future exploration in this field.

GWAS, which is the study of related single nucleotide polymorphisms (SNPs) for a given phenotype with large human populations, have been applied in different sleep subtypes since 2015, especially in sleep duration research studies. SNPs near PAX8 gene, responsible for regulating thyroid-specific genes, were identified in multiple GWAS studies on self-reported and objective sleep duration (9–12). Mutations in this gene were found to potentially increase sleep duration by 2–3 min (13, 14). Vaccinia-related kinase 2 (VRK2), associated with schizophrenia (15), was another gene that had been robustly replicated in the previous GWAS (10). GWAS helped scientists identify lots of new intriguing loci related to sleep such as DRD2, SLC6A3, or GABRR1 in the neuron system (11), but more efforts are needed as few novel loci from GWAS are strongly replicated (14).

Apart from SNPs, epigenetic processes including DNA methylation (DNAm), which means the methyl modification of cytosine by DNA methyltransferase, have been implicated in influencing sleep (16). The loss of DNAm of differentially methylated positions showed an association with insufficient sleep in a cross-sectional genome-wide analysis (17). Circadian clock genes were reported to be regulated by DNAm. For example, the expression level of Per1 was increased during perinatal development by demethylating within the SCN (18), while Cry2 showed significantly increased methylation in older mice (19). Moreover, researchers have reported that the methylation level of some genes may correlate with sleep disorders. Forkhead Box P3 (FOXP3) and endothelial nitric oxide synthase (eNOS) gene DNAm levels have been suggested to play a crucial role in pediatric OSA (20). Moreover, DNAm modules in MAPT, which is a key regulator of Tau proteins in the brain, were implicated in sleep duration in children (21). However, there is still an ongoing debate in this area. A meta-analysis in 2022 showed DNA methylation, at birth or in childhood, was not associated with sleep (22). Consequently, there is an urgent need for epigenome-wide association studies to validate the reliability of specific epigenetic alterations in relation to sleep.

Circadian rhythms, which serve as an endogenous time clock, are present in a wide range of living organisms (23). The neuronal network and molecular mechanisms of circadian rhythms were well studied. The core regulatory loop of circadian rhythms was controlled by the transcription factors brain and muscle ARNT-like protein 1 (BMAL1) and circadian locomotor output cycles kaput (CLOCK), which promoted the expression of period and cryptochrome genes (Per1, Per2, Cry1, and Cry2). Consequently, the accumulation of heterodimer PER/CRY inhibited their own transcription, forming a self-regulatory feedback loop. This network regulated the expression of countless other genes and was vital for cell physiology and metabolism (24, 25). Recently, some research studies showed these circadian clock genes had multiple functions outside the suprachiasmatic nucleus (SCN), a major core brain region that controls timekeeping, to influence sleep (26). For example, sleep deprivation for 6 h increased the expression of per1 in forebrain lysates (26) and the expression of per2 in the whole brain, liver, and kidney but not in SCN (27). Moreover, the expression of Bmal1 in the skeletal muscle was essential and capable of effectively regulating the total amount of sleep (28). As for Cry1 and Cry2, double knockout mice showed increased non-rapid eye movement (non-REM) sleep (29). The molecular mechanism of circadian genes in regulating sleep is still under investigation.

Obstructive sleep apnea (OSA), which is caused by recurrent episodes of upper airway collapse and obstruction during sleep, is a prevalent sleep-disordered breathing (30). It often manifests through symptoms such as loud snoring, nocturnal awakenings, and excessive daytime sleepiness. The prevalence of moderate OSA in the general population ranged from 9 to 38%, with a higher occurrence among men (30). There are many risk factors that affect the OSA, including unmodifiable risk factors like sex, age, and race, and modifiable risk factors such as obesity, endocrine disorders, or obstruction (31). The genetic etiology of OSA was little known. Previous studies using different methods, such as genetic expression analysis and Mendelian randomization analysis, found some genes may be associated with OSA such as PCNA, PSMC6 (32), LEPR, MMP-9, and GABBR1 (33). Recently, one GWAS study of OSA using FinnGen found high genetic correlations between OSA and obesity (34). Another twin study showed OSA also had a common genetic background with hypertriglyceridemia (35). Moreover, genetic analyses also showed patients with OSA have higher C-reactive protein and tumor necrosis factor-alpha levels (36) and were susceptible to diseases such as atrial fibrillation (37), but the mechanism of these associations was not clear.

Sleep disorders were associated with a higher risk of developing depressed and suicidal thoughts in those with major depressive disorder (MDD). MDD could be influenced by genetic factors, with a heritability of 40–50% based on twin studies. New research studies indicate that depression and sleep disorders share pathogenesis. According to a study conducted by Ma et al., circadian rhythm disturbances might contribute to depression (38). Park et al. utilized a non-parametric model-free0000000000 multivariate dimensionality reduction (MDR) approach and found that circadian genes, TIMELESS rs4630333 and CSNK1E rs135745, were significantly associated with MDD and bipolar disorder (39). Moreover, genetic variations in adenosine metabolism were associated with depression, sleep, and attention disturbances. MyD88, essential for microglial activation, affected microglial homeostasis functions and lowered the serotonergic neuronal output, leading to insomnia and depressive behavior.

Sleep-related disorders are complex phenotypes influenced by both genetic and environmental factors, leading to significant individual variations (40). In contrast, common genetic-related diseases such as albinism and hemophilia are less affected by environmental factors and are easier to study. Genes involved in the regulation of sleep-related disorders are complex, and genetic research in this area is still in its early stages. Many questions remain unanswered. Many other diseases are often associated with sleep-related disorders. Studying the genes related to sleep-related disorders greatly aids in understanding the mechanisms of other diseases, such as mental illnesses and binge eating disorder (BED) (41), which are closely linked to sleep disorders. Unlike other diseases, sleep-related disorders do not affect specific organs, making them more challenging to study (3).

Although many genes related to sleep disorders have been identified through existing technological means, it is difficult to replicate the genes obtained in different laboratories, and many genes cannot be validated. Furthermore, because sleep-related disorders also exhibit environmental susceptibility, it is important to take into account regional and ethnic differences when conducting genetic association analyses (40).

In conclusion, bibliometric analysis offered an objective and quantitative method for assessing publication performance between countries, researchers, and research institutions. Our results showed considerable interest in the field of sleep quality and associated genes research in recent years, particularly the study of GWAS, circadian rhythms, OSA, and depression. The relationship between genes and sleep disorders has gained increasing attention. Recent literature has gradually revealed the specific mechanisms involved, providing potential avenues for prevention, treatment, and intervention of sleep disorders.

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

YT: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Visualization, Writing—original draft. YQ: Data curation, Software, Writing—original draft. SC: Conceptualization, Software, Validation, Writing—original draft. TX: Data curation, Writing—review and editing. JL: Formal analysis, Writing—review and editing. DS: Supervision, Writing—review and editing. WY: Supervision, Writing—review and editing. XC: Funding acquisition, Writing—review and editing.