The differential pattern of associations between nighttime sleep disturbances with dimensions of daytime sleepiness in community-dwelling older adults, the Yilan study, Taiwan.

BACKGROUND: The association between nighttime sleep disturbance and daytime sleepiness remains unclear. This study aimed to examine the relationships between various domains of nighttime sleep disturbance, daytime sleepiness, and their specific dimensions. METHODS: This was a community-based cross-sectional study. The participants were adults aged 65 years and older from Yilan City, Taiwan. Daytime sleepiness (DS) was defined using the Epworth Sleepiness Scale (ESS) with scores ≥ 11. The ESS dimensions were further examined using exploratory factor analysis. The highest 15% factor scores for each factor were defined as factor-specific DS. Various domains of nighttime sleep disturbance were assessed using the Pittsburgh Sleep Quality Index. Logistic regression analysis was used to examine the independent relationships among various nighttime sleep disturbances, ESS, and its dimensions. RESULTS: Of the 2585 participants, a total of 59.0% were women. Two factors were identified by exploratory factor analysis and were designated as 'passive factor' and 'active factor'. Multiple logistic regression analyses elucidated that short sleep duration was a common risk indicator for ESS-defined (odds ratio (OR): 2.01; 95% confidence interval (CI): 1.43-2.83), passive factor-defined (OR: 2.23, 95% CI: 1.65-3.00), and active factor-defined DS (OR: 1.47, 95% CI: 1.07-2.00). Hypnotic use was associated with a lower risk of both ESS-defined (OR: 0.66, 95% CI: 0.47-0.92) and passive factor-defined DS (OR:0.69, 95% CI: 0.52-0.92). Bathroom use (OR: 1.41, 95% CI: 1.04-1.91), coughing or snoring (OR: 2.14, 95% CI: 1.01-4.56), and sleep efficiency (OR: 0.42; 95% CI: 0.31-0.57) were uniquely associated with active factor-defined DS. CONCLUSION: Two factors were identified in the ESS, revealing factor-specific correlates of DS. Specifically, ESS- and passive factor-defined DS shared similar correlates. In contrast, some correlates seem unique to active-factor-defined DS.

Sex difference in the association between excessive daytime sleepiness and health-related quality of life in community-dwelling older adults: The Yilan study, Taiwan.

OBJECTIVES: The association between excessive daytime sleepiness and health-related quality of life among older adults and at-risk individuals remains unclear. This study examined relationships between excessive daytime sleepiness and unfavorable health-related quality of life and explored the moderating effect of sex. STUDY DESIGN: This was a community-based study of adults aged 65 years or more. Excessive daytime sleepiness was defined as a score exceeding 10 on the Epworth Sleepiness Scale. Multiple logistic regression analyses were used to examine the relationships between excessive daytime sleepiness and health-related quality of life. The moderating effect of sex was examined by testing interaction terms. MAIN OUTCOME MEASURES: Health-related quality of life was measured using the Short Form 12 Health Survey, which includes a physical component summary and a mental component summary. Unfavorable health-related quality of life was defined as the lowest tertile of the scores for both components. RESULTS: In total, 3788 individuals participated. After controlling for covariates, older adults with excessive daytime sleepiness did not have an unfavorable physical component summary but were more likely to have an unfavorable mental component summary (odds ratio 1.96; 95 % confidence interval 1.47-2.61). When stratified by sex, excessive daytime sleepiness was associated with a poor physical component summary in men (odds ratio 1.77, 95 % confidence interval 1.00-3.13) but not in women. CONCLUSIONS: Excessive daytime sleepiness was associated with a poor mental component summary in both sexes; however, the association with a poor physical component summary was specific to men.

Prevalence, dimensions, and correlates of excessive daytime sleepiness in community-dwelling older adults: the Yilan study, Taiwan.

BACKGROUND: Daytime sleepiness is an important health problem. However, the dimensionality of the Epworth Sleepiness Scale (ESS) in older adults remains unclear. This study aimed to determine the prevalence of ESS-defined excessive daytime sleepiness in older adults. Furthermore, the dimensionality of ESS and its respective correlates were also compared. MATERIALS AND METHODS: This is a community-based survey in which community-dwelling older adults aged ≥ 65 years participated. Excessive daytime sleepiness was assessed using the ESS and was defined as an ESS score of > 10. Exploratory factor analysis was performed to identify the ESS factors. Multiple logistic regression analysis was used to examine the independent correlates of the ESS-defined and factor-specific correlates of excessive daytime sleepiness. RESULTS: In total, 3978 older adults participated in this study. The mean age was 76.6 ± 6.7 years, with 53.8% ≥ 75 years, and 57.1% were female. The prevalence of ESS-defined excessive daytime sleepiness was 16.0%. An exploratory factor analysis revealed two factors in the ESS, which were designated as 'passive' and 'active' according to the soporific levels of ESS items loaded in each factor. Multiple logistic regression showed that male, illiteracy, depression, disability, short sleep duration and no exposure to hypnotics were risk indicators for ESS-defined excessive daytime sleepiness. However, the correlates for passive and active factor-defined excessive daytime sleepiness differ in pattern, especially in variables related to education, exercise, mental health, and sleep. CONCLUSIONS: The prevalence of ESS-defined excessive daytime sleepiness is high, and its correlates vary among older adults. This study also suggests a dual ESS structure in community-dwelling older adults.

Daytime sleepiness is prevalent in older adults.The Epworth Sleepiness Scale (ESS) has dual constructs in older adults.Correlates for excessive daytime sleepiness vary by constructs of the ESS.

Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference.

Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.

Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Exploring the genetics of lithium response in bipolar disorders.

BACKGROUND: Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N = 2064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. RESULTS: We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. CONCLUSIONS: Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.