Association Between Hypnotics and Dementia: A Mini Narrative Review.

OBJECTIVE: This narrative review aims to provide a comprehensive assessment of the existing literature on the relationship between hypnotics and dementia, considering both potential link and inconclusive or lack of association. METHODS: Data from studies that investigate the association between hypnotic medications and dementia were reviewed. Studies included both cohort studies and systematic reviews, participants with various type of dementia and hypnotics including benzodiazepines (BZDs) and Z-drugs (ZDs). RESULTS: The existing literatures presents conflicting evidence regarding the association between hypnotics, including BZDs and ZDs, and the risk of dementia. Some studies suggest a potential link between prolonged use of hypnotics and an increased risk of dementia. However, other studies indicate inconclusive or lacking evidence regarding this association. Factors such as study design, sample characteristics, and control of confounding variables contribute to the variability in findings. CONCLUSION: The relationship between hypnotics and dementia remains complex and controversial. While some studies suggest a potential association, others find inconclusive or conflicting evidence. Future research should focus on addressing methodological limitations, considering classifying dementia subtypes, and try to adjust medication lag time.

Association between weekend catch-up sleep and the risk of prediabetes and diabetes: A cross-sectional study using KNHANES.

BACKGROUND: The objectives of this cross-sectional study were to explore the relationship between weekend catch-up sleep (WCUS) and the risk of prediabetes/diabetes and to assess how this risk varies based on WCUS duration, using a large population sample in South Korea. METHODS: Data were sourced from the 2021 Korea National Health and Nutrition Examination Survey, involving 2472 subjects aged 30 years and above, employed, and not using blood glucose-lowering medications. Prediabetes/diabetes risk was examined based on the presence of WCUS. Participants were categorized into four groups by WCUS duration (< 1, ≥ 1 and < 2, ≥ 2 and < 3, and ≥ 3 h) to evaluate the prediabetes/diabetes risk across varying WCUS durations. RESULTS: No significant difference in prediabetes/diabetes risk was observed between the WCUS and non-WCUS groups. In subgroup analysis, a WCUS duration of 1 to 2 h was related to a lower odds ratio of prediabetes (aOR = 0.618, 95% CI = 0.382-0.999), while 3 h or more was associated with a higher odds ratio of diabetes (aOR = 3.098, 95% CI = 1.561-6.149). CONCLUSIONS: In individuals who experience insufficient sleep during weekdays and manage to achieve the optimal average sleep duration of 1 to 2 h of WCUS, WCUS was associated with improved blood glucose regulation. However, compensating for excessive weekday sleep deprivation with WCUS of 3 h or more was associated with impaired blood glucose regulation.

Prolactin Level Changes according to Atypical Antipsychotics Use: A Study Based on Clinical Data Warehouse.

Objective: : Antipsychotic drugs are known as the major cause of non-neoplastic hyperprolactinemia. This study aimed to investigate the levels of serum prolactin depending on the use of antipsychotic drugs in patients through the Clinical Data Warehouse (CDW). Methods: : We conducted a cohort search in the CDW application and got 260 patients' medical records diagnosed with schizophrenia, schizotypal and delusional disorders, manic episodes, and bipolar affective disorders who were taking one of risperidone, blonanserin, amisulpride, and olanzapine. After that, we reviewed the medical data and used the ANCOVA analysis and the post hoc test to compare serum prolactin levels among four antipsychotic drug groups. Results: : Among the 117 subjects included in the analysis, the mean serum prolactin level was 64.6 ± 54.6 ng/ml. Serum prolactin levels were significantly higher in subjects taking risperidone or amisulpride compared to blonanserin and olanzapine. The female subjects who took blonanserin, olanzapine, and risperidone had significantly higher prolactin levels, but there was no difference in serum prolactin levels between sex in the subjects who took amisulpride. Conclusion: : This study suggests the need for regular monitoring of serum prolactin levels in patients who are taking antipsychotics, especially in female patients. And we showed that there is a possibility to conduct more effective and simpler big data research using the CDW. Further studies on the subjects with controlled confounding variables and larger sample groups are needed.

Narcolepsy risk loci outline role of T cell autoimmunity and infectious triggers in narcolepsy.

Narcolepsy type 1 (NT1) is caused by a loss of hypocretin/orexin transmission. Risk factors include pandemic 2009 H1N1 influenza A infection and immunization with Pandemrix®. Here, we dissect disease mechanisms and interactions with environmental triggers in a multi-ethnic sample of 6,073 cases and 84,856 controls. We fine-mapped GWAS signals within HLA (DQ0602, DQB1*03:01 and DPB1*04:02) and discovered seven novel associations (CD207, NAB1, IKZF4-ERBB3, CTSC, DENND1B, SIRPG, PRF1). Significant signals at TRA and DQB1*06:02 loci were found in 245 vaccination-related cases, who also shared polygenic risk. T cell receptor associations in NT1 modulated TRAJ*24, TRAJ*28 and TRBV*4-2 chain-usage. Partitioned heritability and immune cell enrichment analyses found genetic signals to be driven by dendritic and helper T cells. Lastly comorbidity analysis using data from FinnGen, suggests shared effects between NT1 and other autoimmune diseases. NT1 genetic variants shape autoimmunity and response to environmental triggers, including influenza A infection and immunization with Pandemrix®.

Narcolepsy is associated with an increased risk of HLA-related autoimmune diseases: Evidence from a nationwide healthcare system data in South Korea.

STUDY OBJECTIVES: To determine the incidence rate of narcolepsy in South Korea and closely examine the relationship between narcolepsy, which is believed to be an autoimmune response, and other systemic autoimmune diseases. METHODS: We examined data from the South Korean nationwide health insurance claims database from 2010 to 2019. Our study included patients with narcolepsy as well as age- and sex-matched controls without narcolepsy. We estimated the incidence of narcolepsy and the odds ratio of narcolepsy and associated autoimmune comorbidities in South Korea. RESULTS: We identified 8710 patients with narcolepsy (59.8% men and 40.2% women). The incidence of narcolepsy was 0.05%. Patients with narcolepsy were at a significantly high risk of ankylosing spondylitis, rheumatoid arthritis, and Sjögren's syndrome, which diseases are known to be related to human leukocyte antigen (HLA) genes. CONCLUSIONS: Narcolepsy is closely related to systemic autoimmune diseases, particularly those related to HLA genes.

Does panic disorder increase the risk of cardiovascular diseases in diabetics?: A nationwide population-based study.

BACKGROUND: Several studies have suggested a link between panic disorder (PD) and cardiovascular disease (CVD). However, the extent to which PD confers risk for CVD is still unclear, particularly in diabetics, a group showing high risk for CVD. METHODS: A nationwide population-based cohort of 1,624,718 patients with type 2 diabetes were selected from the National Health Screening Program database covering the years 2009 to 2012. The subjects were divided into two groups: those without panic disorder (non-PD group, n = 1,618,263) and those with newly diagnosed PD (PD-group, n = 6455). Follow-up of subjects for up to 10 years was conducted for evaluation of the incidences of myocardial infarction (MI), stroke, and death. RESULTS: After adjusting for the baseline covariates and diabetes mellitus (DM)-related variables, no difference in the future risk of MI and stroke was observed between the non-PD group and the PD group. Compared with the non-PD group, the PD group showed an increase in the future risk of death. [adjusted hazard ratio (aHR) = 1.120, 95 % confidence interval (CI): 1.039-1.206]. In contrast to the population aged <40 and > 65 years, in the age group of 40-64 years a significantly higher risk of stroke was observed in the PD group compared with the non-PD group (aHR = 1.352, 95%CI: 1.136-1.610). LIMITATION: The diagnoses were based on the diagnostic codes of the claim data. CONCLUSION: The current findings suggested that PD might not contribute to the risk of future MI and stroke in diabetics who have already been at risk of various cardiovascular complications.

Association Between Diabetic Retinopathy and Insomnia Risk: A Nationwide Population-Based Study.

Background: Previous studies have suggested a close link between sleep disturbances and diabetic retinopathy (DR). However, to date, no confirmatory findings have been reported. We aimed to explore the risk of insomnia in DR by considering demographic factors and diabetes mellitus (DM)-related variables. Methods: A nationwide population-based cohort of 2,206,619 patients with type 2 diabetes from the Korean National Insurance Service Database was followed up for insomnia incidence. DR, non-proliferative DR (NPDR), and proliferative DR (PDR) were defined according to ICD-10 codes. The interactive effects of sex, age, and DM-related variables were analyzed to evaluate their impact on insomnia risk in DR. Results: Compared with the non-DR group, insomnia risk was increased in the DR [(adjusted hazard ratio (aHR): 1.125, 95% confidence interval (CI):1.108-1.142), NPDR (aHR:1.117, 95% CI:1.099-1.134), and PDR (aHR:1.205, 95% CI: 1.156-1.256), even after controlling for comorbidities, lifestyle factors, and DM-related variables. The men and youngest age groups (<40 years) were most vulnerable to insomnia risk. Sex, age, DM duration, and chronic kidney disease (CKD) status exerted interactive effects with DR status in increasing the insomnia risk. In the PDR group, sex, age, DM duration, insulin therapy status, and CKD status exerted interactive effects that increased the risk of insomnia. Conclusion: Insomnia risk is significantly higher in patients with DR, and clinical attention is warranted.

Mediation Effect of the Coping Strategies on the Relation Between Stress and Sleep Quality.

OBJECTIVE: Recently data has been accumulated regarding the role of coping strategies in the relationship between stress and sleep quality. Therefore, we set out to identify the mediating effects of coping strategies between stress and sleep quality. METHODS: A online-based cross-sectional study was performed using the Perceived Stress Scale-10, the Pittsburgh Sleep Quality Index, and a simplification of the 60-item Coping Orientation to Problems Experienced (Brief COPE) inventory in the nonclinical adult sample. The 24 items of Brief COPE were categorized into four factors (social support, problem solving, avoidance, positive thinking). Then, we used the PROCESS macro to conduct the multiple mediation analysis for the four coping styles as potential mediators in the relationship between stress and sleep quality, and an additional subgroup analysis was examined to identify a gender difference for the mediation effect. RESULTS: As a group, four coping styles mediated significantly the association between perceived stress and poor sleep quality. And avoidance has maintained its significance thought all regression analyses. Finally, this results remained as same in the females. CONCLUSION: The effect of perceived stress on poor sleep quality was mediated by coping strategies, especially by avoidance. Thus, further research should consider the coping styles of individuals to reduce the influence of stress on sleep quality.

Proteomic biomarkers of Kleine-Levin syndrome.

STUDY OBJECTIVES: Kleine-Levin syndrome (KLS) is characterized by relapsing-remitting episodes of hypersomnia, cognitive impairment, and behavioral disturbances. We quantified cerebrospinal fluid (CSF) and serum proteins in KLS cases and controls. METHODS: SomaScan was used to profile 1133 CSF proteins in 30 KLS cases and 134 controls, while 1109 serum proteins were profiled in serum from 26 cases and 65 controls. CSF and serum proteins were both measured in seven cases. Univariate and multivariate analyses were used to find differentially expressed proteins (DEPs). Pathway and tissue enrichment analyses (TEAs) were performed on DEPs. RESULTS: Univariate analyses found 28 and 141 proteins differentially expressed in CSF and serum, respectively (false discovery rate <0.1%). Upregulated CSF proteins included IL-34, IL-27, TGF-b, IGF-1, and osteonectin, while DKK4 and vWF were downregulated. Pathway analyses revealed microglial alterations and disrupted blood-brain barrier permeability. Serum profiles show upregulation of Src-family kinases (SFKs), proteins implicated in cellular growth, motility, and activation. TEA analysis of up- and downregulated proteins revealed changes in brain proteins (p < 6 × 10-5), notably from the pons, medulla, and midbrain. A multivariate machine-learning classifier performed robustly, achieving a receiver operating curve area under the curve of 0.90 (95% confidence interval [CI] = 0.78-1.0, p = 0.0006) in CSF and 1.0 (95% CI = 1.0-1.0, p = 0.0002) in serum in validation cohorts, with some commonality across tissues, as the model trained on serum sample also discriminated CSF samples of controls versus KLS cases. CONCLUSIONS: Our study identifies proteomic KLS biomarkers with diagnostic potential and provides insight into biological mechanisms that will guide future research in KLS.

Suicide Risk in Patients With Diabetes Varies by the Duration of Diabetes: The Korea National Health and Nutrition Examination Survey (2019).

OBJECTIVE: The objectives of this study were to investigate the suicide risk in diabetes patients and evaluate the variations in suicide risk by the duration of diabetes using a large population sample in South Korea. METHODS: Data from 6,296 adults in the 2019 Korea National Health and Nutrition Examination Survey were included. The suicidal ideation, suicide plans, and suicidal behavior of diabetes patients were compared to the general population. After classifying the patients into ≤1 year, 2 to 9 years, and ≥10 years of diabetes duration, we evaluated the relationship between the duration of diabetes and the suicide risk. RESULTS: Diabetes patients had higher prevalences of suicidal ideation (9.1%, p<0.001) and suicide plans (3.6%, p<0.001) than the general population. After adjusting for potential confounding factors, suicide plans (adjusted odds ratio [aOR]=2.926, 95% confidence interval [CI]=1.325-6.463) were significantly associated with diabetes. In the 2 to 9 years group of diabetes patients, we found an increase in the risk of suicidal ideation (aOR=2.035, 95% CI=1.129-3.670), suicide plans (aOR=3.507, 95% CI=1.538-7.996), and suicidal behavior (aOR=7.130, 95% CI=2.035-24.978) after adjusting for the covariates. However, no increases in suicide risk were observed ≤1 year and ≥10 years after diabetes diagnosis. CONCLUSION: In adults, diabetes is associated with an increase in suicide risk. Suicide risk in diabetes patients showed an inverted U-shaped depending upon the duration of diabetes.

Differential characteristics of repeated polysomnography and multiple sleep latency test parameters in narcolepsy type 1 and type 2 patients: a longitudinal retrospective study.

PURPOSE: Narcolepsy is a chronic disorder and its phenotype is dichotomized into narcolepsy type 1 (NT1) and narcolepsy type 2 (NT2). The clinical course and pathophysiological mechanisms of these two clinical entities and their differences are not adequately defined. This study aimed to explore the differential longitudinal patterns of polysomnography (PSG) and multiple sleep latency test (MSLT) in NT1 and NT2. METHODS: In this retrospective study demographic characteristics, PSG, and MSLT parameters at baseline and follow-up were compared between NT1 and NT2 patients. Patients with both follow-up MSLT and PSG were selected for sub-group analysis. Baseline and follow-up MSLT and PSG parameters were compared. RESULTS: Of 55 patients with narcolepsy, mean follow-up periods were 7.4 ± 3.5 years for NT1 and 5.5 ± 2.9 for NT2. Demographic data showed increased body mass index and prevalence of sleep paralysis in NT1. Baseline PSG characteristics between NT1 and NT2 showed decreased sleep latency (p = 0.016) and REM latency (p = 0.046) in NT1 group when compared with NT2. Nocturnal SOREMP on PSG was more prevalent in NT1 (p = 0.017), and half of NT2 patients with nocturnal SOREMP on PSG changed their diagnoses to NT1. On follow-up PSG, NT1 displayed reductions in sleep stage N2 (p = 0.006) and N3 (p = 0.048), while wake after sleep onset (WASO) (p = 0.023) and apnea-hypopnea index (AHI) (p = 0.007) were significantly increased. CONCLUSION: Differential MSLT and PSG characteristics of NT1 and NT2 in at baseline and follow-up indicate that NT1 and NT2 are distinct disease phenotypes, and that they present with a contrasting course of disease.

Kleine-Levin syndrome is associated with birth difficulties and genetic variants in the TRANK1 gene loci.

Kleine-Levin syndrome (KLS) is a rare disorder characterized by severe episodic hypersomnia, with cognitive impairment accompanied by apathy or disinhibition. Pathophysiology is unknown, although imaging studies indicate decreased activity in hypothalamic/thalamic areas during episodes. Familial occurrence is increased, and risk is associated with reports of a difficult birth. We conducted a worldwide case-control genome-wide association study in 673 KLS cases collected over 14 y, and ethnically matched 15,341 control individuals. We found a strong genome-wide significant association (rs71947865, Odds Ratio [OR] = 1.48, P = 8.6 × 10-9) within the 3'region of TRANK1 gene locus, previously associated with bipolar disorder and schizophrenia. Strikingly, KLS cases with rs71947865 variant had significantly increased reports of a difficult birth. As perinatal outcomes have dramatically improved over the last 40 y, we further stratified our sample by birth years and found that recent cases had a significantly reduced rs71947865 association. While the rs71947865 association did not replicate in the entire follow-up sample of 171 KLS cases, rs71947865 was significantly associated with KLS in the subset follow-up sample of 59 KLS cases who reported birth difficulties (OR = 1.54, P = 0.01). Genetic liability of KLS as explained by polygenic risk scores was increased (pseudo R2 = 0.15; P < 2.0 × 10-22 at P = 0.5 threshold) in the follow-up sample. Pathway analysis of genetic associations identified enrichment of circadian regulation pathway genes in KLS cases. Our results suggest links between KLS, circadian regulation, and bipolar disorder, and indicate that the TRANK1 polymorphisms in conjunction with reported birth difficulties may predispose to KLS.

Predictors of 1-year rehospitalization in inpatients with bipolar I disorder treated with atypical antipsychotics.

Bipolar disorder (BPD) is debilitating disorder, and patients can experience multiple relapses and subsequent hospitalizations. Since pharmacotherapy is the mainstay of treatment for patients with BPD, investigations on the effects of atypical antipsychotics (AAP) on reducing rehospitalization risk are crucial. The objective of study is to explore predictors of 1-year rehospitalization in patients with bipolar I disorder treated with AAP. A retrospective chart review on inpatients with bipolar I disorder was conducted. All participants were followed up for 1 year, and they were subdivided into three AAP treatment groups (olanzapine, risperidone, and quetiapine group). Kaplan-Meier survival analysis was implemented to detect time to rehospitalization due to any mood episodes within 1 year after discharge. Cox proportional regression model was adopted to find predictors of 1-year hospitalization in patients who experienced rehospitalization. One hundred thirty-eight participants were included in the study, and a 1-year rehospitalization rate was 18.1%. Time to rehospitalization did not differ between three AAP treatment groups. Predictors of rehospitalization due to any episode within 1 year were family history of depression and number of previous admission. Our findings can be conducive to understanding prognosis, and predicting rehospitalization risk in patients with BPD on AAP.

Factors associated with poor sleep quality in the Korean general population: Providing information from the Korean version of the Pittsburgh Sleep Quality Index.

BACKGROUND: Recently, studies have been conducted to address the research gap in the understanding of poor-quality sleep and its relationship to health outcomes, through the evaluation of sleep quality. The aim of this study was to provide information regarding poor sleep quality based on a nationwide general population sample in Korea. METHODS: We conducted a cross-sectional study using data from a nationwide sample of 165,193 individuals (males: 44%) aged 19 years or older from the 2018 Korea Community Health Survey. The age range of the participants was 19-107 years (mean: 55.3 ± 17.5). The Korean version of the Pittsburgh Sleep Quality Index (PSQI) was used for assessing sleep quality. Poor sleep quality was defined as a total PSQI score of >5. RESULTS: The overall prevalence of poor sleepers was 41.0% (males: 35.6%; females: 46.2%). Poor sociodemographic status (illiteracy, low income, and unemployment), poor health behaviors (smoking, high-risk drinking, diabetes, hypertension, non-participation in walking, and obesity), and poor mental health (perceived poor health status, stress, depressive symptoms, and subjective cognitive decline) were all associated with poor sleep quality in both males and females. LIMITATIONS: As this study relies on self-reported and cross-sectional data, causal inferences cannot be made. CONCLUSIONS: Poor sleep quality is highly prevalent in females. In addition, poor socio-demographic status, poor health behaviors, and poor mental health were associated with poor sleep quality. The mechanisms underlying sex differences in sleep quality remain to be elucidated, and further studies are required to address this.

Risk Factors for Serious Suicide Attempts with High Medical Severity.

OBJECTIVES: his study investigated the risk factors leading to serious suicide attempts with high medical severity. METHODS: Nine hundred and eighty-two patients who visited the emergency room after attempting suicide were divided into two groups: suicide attempters with high medical severity (25.3%) and those with low medical severity (74.7%). Demographic variables, clinical characteristics, and factors related to each suicide attempt were compared between the two groups. Multivariate logistic regression analysis was conducted to investigate risk factors for high medical severity in patients' current suicide attempts. RESULTS: The results show that suicide attempters with high medical severity had more severe depression and psychological disturbances such as agitation, intense emotions, and self-reproach. Suicide attempters with high medical severity also had more serious risk factors for suicide such as repetitive/intense/continuous thoughts of suicide, suicidal planning, and a stronger wish to die. School/work problems and physical illnesses were related to high medical severity with more lethal methods. Logistic regression demonstrated that school/work problems, total risk rating, severity of suicidal ideation, and agitation were risks for more serious suicide attempts, whereas more frequent lifetime suicide attempts were a protective factor. CONCLUSION: This study demonstrates that suicide attempters with high medical severity had more severe psychopathologies and risk factors related to suicidal behavior than those with low medical severity.

Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy.

Analysis of sleep for the diagnosis of sleep disorders such as Type-1 Narcolepsy (T1N) currently requires visual inspection of polysomnography records by trained scoring technicians. Here, we used neural networks in approximately 3,000 normal and abnormal sleep recordings to automate sleep stage scoring, producing a hypnodensity graph-a probability distribution conveying more information than classical hypnograms. Accuracy of sleep stage scoring was validated in 70 subjects assessed by six scorers. The best model performed better than any individual scorer (87% versus consensus). It also reliably scores sleep down to 5 s instead of 30 s scoring epochs. A T1N marker based on unusual sleep stage overlaps achieved a specificity of 96% and a sensitivity of 91%, validated in independent datasets. Addition of HLA-DQB1*06:02 typing increased specificity to 99%. Our method can reduce time spent in sleep clinics and automates T1N diagnosis. It also opens the possibility of diagnosing T1N using home sleep studies.

Erratum to "Prediction of Treatment Response to Donepezil using Automated Hippocampal Subfields Volumes Segmentation in Patients with Mild Alzheimer's Disease".

[This corrects the article on p. 698 in vol. 14.].

A Longitudinal Follow-Up Study on Multiple Sleep Latency Test and Body Mass Index of Patients With Narcolepsy Type 1 in Korea.

STUDY OBJECTIVES: Narcolepsy is a chronic disorder with numerous adverse long-term consequences including increased obesity, high mortality rates, and decreased quality of life. With emerging attention to the long-term course of the disorder and importance of accurate diagnosis, the diagnostic stability of the Multiple Sleep Latency Test (MSLT)-the mostly frequently used test to identify narcolepsy-is often challenged. METHODS: In this study, we compared the baseline and follow-up demographic characteristics and body mass index (BMI) of patients with narcolepsy type 1. Moreover, MSLT results from repeated tests conducted on 48 patients with narcolepsy type 1 were compared, with mean follow-up of approximately 10 years. RESULTS: BMI from the baseline to the follow-up visit was significantly increased in the participants. There were no significantly different parameter changes in MSLT results. CONCLUSIONS: MSLT has good test-retest validity in patients with narcolepsy type 1. Close surveillance for the detection and management of obesity is warranted in clinical settings.

Prediction of Treatment Response to Donepezil using Automated Hippocampal Subfields Volumes Segmentation in Patients with Mild Alzheimer's Disease.

Previous studies reported some relationships between donepezil treatment and hippocampus in Alzheimer's disease (AD). However, due to methodological limitations, their close relationships remain unclear. The aim of this study is to predict treatment response to donepezil by utilizing the automated segmentation of hippocampal subfields volumes (ASHS) in AD. Sixty four AD patients were prescribed with donepezil and were followed up for 24 weeks. Cognitive function was measured to assess whether there was a response from the donepezil treatment. ASHS was implemented on non-responder (NR) and responder (TR) groups, and receiver operator characteristic (ROC) analysis was conducted to evaluate the sensitivity, specificity, and accuracy of hippocampal subfields in predicting response to donepezil. The left total hippocampus and the CA1 area of the NR were significantly smaller than those of the TR group. The ROC curve analysis showed the left CA1 volumes showed highest area under curve (AUC) of 0.85 with a sensitivity of 88.0%, a specificity of 74.0% in predicting treatment response to donepezil treatment. We expect that hippocampal subfields volume measurements that predict treatment responses to current AD drugs will enable more evidence-based, individualized prescription of medications that will lead to more favorable treatment outcomes.

Sleep Problems as Predictors in Attention-Deficit Hyperactivity Disorder: Causal Mechanisms, Consequences and Treatment.

Attention-deficit hyperactivity disorder (ADHD) is notorious for its debilitating consequences and early age of onset. The need for early diagnosis and intervention has frequently been underscored. Previous studies have attempted to clarify the bidirectional relationship between ADHD and sleep problems, proposing a potential role for sleep problems as early predictors of ADHD. Sleep deprivation, sleep-disordered breathing, and circadian rhythm disturbances have been extensively studied, yielding evidence with regard to their induction of ADHD-like symptoms. Genetic-phenotypic differences across individuals regarding the aforementioned sleep problems have been elucidated along with the possible use of these characteristics for early prediction of ADHD. The long-term consequences of sleep problems in individuals with ADHD include obesity, poor academic performance, and disrupted parent-child interactions. Early intervention has been proposed as an approach to preventing these debilitating outcomes of ADHD, with novel treatment approaches ranging from melatonin and light therapy to myofunctional therapy and adjustments of the time point at which school starts.