Diurnal preference and depressive symptomatology: a meta-analysis.
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ABSTRACT:
SUBMITTER: Norbury R
PROVIDER: S-EPMC8184740 | biostudies-literature | 2021 Jun
REPOSITORIES: biostudies-literature
Publications
Diurnal preference and depressive symptomatology: a meta-analysis.
Scientific reports 20210607 1
Eveningness, a preference for later sleep and rise times, has been associated with a number of negative outcomes in terms of both physical and mental health. A large body of evidence links eveningness to Major Depressive Disorder (MDD). However, to date, evidence quantifying this association is limited. The current meta-analysis included 43 effect sizes from a total 27,996 participants. Using a random-effects model it was demonstrated that eveningness is associated with a small effect size (Fish ...[more]
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Project description:ImportanceMorning diurnal preference is associated with reduced risk of major depressive disorder (MDD); however, causality in this association is uncertain.ObjectiveTo examine the association of genetically proxied morning diurnal preference with depression risk using mendelian randomization.Design, setting, and participantsThis 2-sample mendelian randomization study used summary-level genetic associations with diurnal preference and MDD. Up to 340 genetic loci associated with diurnal preference in a meta-analysis of the UK Biobank and 23andMe cohorts were considered as genetic proxies for diurnal preference. The effect size of these variants was scaled using genetic associations with accelerometer-based measurement of sleep midpoint. Genetic associations with MDD were obtained from a meta-analysis of genome-wide association studies data from the Psychiatric Genomics Consortium and UK Biobank. The inverse-variance weighted method was used to estimate the association of genetically proxied morning diurnal preference, corresponding to a 1-hour earlier sleep midpoint, with MDD risk.ExposuresMorning diurnal preference scaled to a 1-hour earlier, objectively measured sleep midpoint.Main outcomes and measuresRisk of MDD, including self-reported and clinically diagnosed cases, as ascertained in meta-analyses of genome-wide association studies.ResultsA total of 697 828 individuals (all of European ancestry) were in the UK Biobank and 23andMe cohorts; 85 502 in the UK Biobank had measurements of the sleep midpoint. A further 170 756 individuals with MDD and 329 443 control participants (all of European ancestry) were in the Psychiatric Genomics Consortium and UK Biobank data. Genetically proxied earlier diurnal preference was associated with a 23% lower risk of depression (odds ratio [OR] per 1-hour earlier sleep midpoint, 0.77 [95% CI, 0.63-0.94]; P = .01). This association was similar when restricting analysis to individuals with MDD as stringently defined by the Psychiatric Genomics Consortium (OR, 0.73 [95% CI, 0.54-1.00]; P = .05) but not statistically significant when defined by hospital-based billing codes in the UK Biobank (OR, 0.64 [95% CI, 0.39-1.06]; P = .08). Sensitivity analyses examining potential bias due to pleiotropy or reverse causality showed similar findings (eg, intercept [SE], 0.00 [0.001]; P = .66 by Egger intercept test).Conclusions and relevanceThe results of this mendelian randomization study support a protective association of earlier diurnal preference with risk of MDD and provide estimates contextualized to an objective sleep timing measure. Further investigation in the form of randomized clinical trials may be warranted.
| S-EPMC8156187 | biostudies-literature
Project description:The rhythm of human life is governed by diurnal cycles, as a result of endogenous circadian processes evolved to maximize biological fitness. Even complex aspects of daily life, such as affective states, exhibit systematic diurnal patterns which in turn influence behaviour. As a result, previous research has identified population-level diurnal patterns in affective preference for music. By analysing audio features from over two billion music streaming events on Spotify, we find that the music people listen to divides into five distinct time blocks corresponding to morning, afternoon, evening, night and late night/early morning. By integrating an artificial neural network with Spotify's API, we show a general awareness of diurnal preference in playlists, which is not present to the same extent for individual tracks. Our results demonstrate how music intertwines with our daily lives and highlight how even something as individual as musical preference is influenced by underlying diurnal patterns.
| S-EPMC8580447 | biostudies-literature
Project description:Background and Objectives: Depressive symptoms are prominent in both major depressive disorder (MDD) and bipolar disorder (BD). However, comparative research on the network structure of depressive symptoms in these two diagnostic groups has been limited. This study aims to compare the network structure of depressive symptoms in MDD and BD, providing a deeper understanding of the depressive symptomatology of each disorder. Materials and Methods: The Zung Self-Rating Depressive Scale, a 20-item questionnaire, was administered to assess the depressive symptoms in individuals with MDD (n = 322) and BD (n = 516). A network analysis was conducted using exploratory graph analysis (EGA), and the network structure was analyzed using regularized partial correlation models. To validate the dimensionality of the Zung SDS, principal component analysis (PCA) was adopted. Centrality measures of the depressive symptoms within each group were assessed, followed by a network comparison test between the two groups. Results: In both diagnostic groups, the network analysis revealed four distinct categories, aligning closely with the PCA results. "Depressed affect" emerged as the most central symptom in both MDD and BD. Furthermore, non-core symptoms, "Personal devaluation" in MDD and "Confusion" in BD, displayed strong centrality. The network comparison test did not reveal significant differences in the network structure between MDD and BD. Conclusions: The absence of significant differences in the network structures between MDD and BD suggests that the underlying mechanisms of depressive symptoms may be similar across these disorders. The identified central symptoms, including "Depressed affect", in both disorders and the distinct non-core symptoms in each highlight the complexity of the depressive symptomatology. Future research should focus on validating these symptoms as therapeutic targets and incorporate various methodologies, including non-metric dimension reduction techniques or canonical analysis.
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Project description:EPIC array data were generated from 2 MDD case control cohorts. EWAS was performed in each cohort, followed by meta-analysis between the 2 cohort. Cohort 1: A total of 191 blood samples from 112 patients with MDD was collected up till the interim analysis (wave 1 samples) from an observational clinical study OBSERVEMDD0001 (ClinicalTrials.gov Identifier: NCT02489305) compared to 32 healthy controls; Cohort 2: The MDD cases (N = 359) were drawn from the Molecular Biomarkers of Antidepressant Response study compared to 68 healthy controls.
2022-11-03 | GSE198904 | GEO
Project description:BackgroundAffective disorders are a debilitating and very prevalent problem throughout the world. Often these are associated with the onset of comorbidities or a consequence of chronic diseases. Anxiety and depression are associated with poor social and personal relationships, compromised health. We aimed to synthesize evidence from studies measuring the impact of a health literacy (HL) intervention on the improvement of affective disorders.MethodsFor this systematic review and meta-analysis, we searched PubMed/MEDLINE, Embase, Web of Science, Ibecs, Cuiden, Scielo, Science Direct and Dialnet for exclusively randomized controlled trial studies (RCTs) published between 1 Jan 2011, and 31 May 2022. The search terms employed were "health literacy," "health knowledge," "anxiety," "anxiety disorder," "depression," "depressive disorder," and "adult." The risk of bias assessment was performed using the Cochrane Collaboration Revised Risk of Bias tool (RoB2). We conducted random-effects meta-analyses and explored heterogeneity using meta-regression and a stratified survey.ResultsOf 2,863 citations found through the initial screening, 350 records were screened by the title and abstract for their themes and relevance. Finally, nine studies complied with the inclusion criteria for the meta-analysis. 66.66% of studies (n = 6) were rated as having a low risk of bias and 33.33% (n = 3) were judged to raise some concerns. The health literacy interventions were associated with -1.378 reduction in depression and anxiety questionnaires scores [95% CI (-1.850, -0.906)]. Low mood disorder scores are associated with better mental health and wellbeing.ConclusionOur findings demonstrate that an HL intervention in relation to the symptoms associated with affective disorders improves the emotional state of patients in PHC, with a moderately positive effect in reducing depression and anxiety.
| S-EPMC9948257 | biostudies-literature
Project description:Burnout syndrome is has been associated with mental health problems such as depression, anxiety, and stress. Given this fact, some teachers implement various coping strategies for emotional control that are not always functional to mitigate such difficulties. Accordingly, this study aimed to identify different burnout profiles that vary in the levels of the three underlying dimensions: depersonalization (DE), emotional exhaustion (EE), and personal accomplishment (PA). Further, this study aimed to examine whether there are significant differences in depressive symptomatology, coping strategies, and the quality of interpersonal relationships at school between teachers with varying burnout profiles. The Maslach Burnout Inventory (MBI), Zung Self-Rating Depression Scale (SDS), Coping with Stress Questionnaire, and a questionnaire that measured sociodemographic characteristics were administered to 215 teachers (men: 42.8%) who were recruited from various secondary schools. Cluster analysis identified three different burnout profiles: groups of teachers with a predominance of (a) low levels of EE and high levels of PA, (b) high levels of EE and DE, and (c) low levels of DE and PA. The results revealed that there were significant differences in coping strategies, depressive symptomatology, and the quality of interpersonal relationships at school between teachers with different burnout profiles. These results have important implications for educational professionals. Specifically, the findings underscore the need for prevention and intervention programs that enhance teachers' emotional skills, especially their ability to cope with exhaustion. These skills will alleviate their depression and consequently offer both teachers and students a conducive learning environment.
| S-EPMC7142211 | biostudies-literature
Project description:BackgroundAnhedonia and depressed mood are considered the cardinal symptoms of major depressive disorder. These are the first 2 items of the Patient Health Questionnaire (PHQ)-9 and comprise the ultrabrief PHQ-2 used for prescreening depressive symptomatology. The prescreening performance of alternative PHQ-9 item pairings is rarely compared with that of the PHQ-2.ObjectiveThis study aims to use machine learning (ML) with the PHQ-9 items to identify and validate the most predictive 2-item depressive symptomatology ultrabrief questionnaire and to test the generalizability of the best pairings found on the primary data set, with 6 external data sets from different populations to validate their use as prescreening instruments.MethodsAll 36 possible PHQ-9 item pairings (each yielding scores of 0-6) were investigated using ML-based methods with logistic regression models. Their performances were evaluated based on the classification of depressive symptomatology, defined as PHQ-9 scores ≥10. This gave each pairing an equal opportunity and avoided any bias in item pairing selection.ResultsThe ML-based PHQ-9 items 2 and 4 (phq2&4), the depressed mood and low-energy item pairing, and PHQ-9 items 2 and 8 (phq2&8), the depressed mood and psychomotor retardation or agitation item pairing, were found to be the best on the primary data set training split. They generalized well on the primary data set test split with area under the curves (AUCs) of 0.954 and 0.946, respectively, compared with an AUC of 0.942 for the PHQ-2. The phq2&4 had a higher AUC than the PHQ-2 on all 6 external data sets, and the phq2&8 had a higher AUC than the PHQ-2 on 3 data sets. The phq2&4 had the highest Youden index (an unweighted average of sensitivity and specificity) on 2 external data sets, and the phq2&8 had the highest Youden index on another 2. The PHQ-2≥2 cutoff also had the highest Youden index on 2 external data sets, joint highest with the phq2&4 on 1, but its performance fluctuated the most. The PHQ-2≥3 cutoff had the highest Youden index on 1 external data set. The sensitivity and specificity achieved by the phq2&4 and phq2&8 were more evenly balanced than the PHQ-2≥2 and ≥3 cutoffs.ConclusionsThe PHQ-2 did not prove to be a more effective prescreening instrument when compared with other PHQ-9 item pairings. Evaluating all item pairings showed that, compared with alternative partner items, the anhedonia item underperformed alongside the depressed mood item. This suggests that the inclusion of anhedonia as a core symptom of depression and its presence in ultrabrief questionnaires may be incompatible with the empirical evidence. The use of the PHQ-2 to prescreen for depressive symptomatology could result in a greater number of misclassifications than alternative item pairings.
| S-EPMC10623235 | biostudies-literature
Project description:BackgroundMost animals restrict their activity to a specific part of the day, being diurnal, nocturnal or crepuscular. The genetic basis underlying diurnal preference is largely unknown. Under laboratory conditions, Drosophila melanogaster is crepuscular, showing a bi-modal activity profile. However, a survey of strains derived from wild populations indicated that high variability among individuals exists, including flies that are nocturnal.ResultsUsing a highly diverse population, we performed an artificial selection experiment, selecting flies with extreme diurnal or nocturnal preference. After 10 generations, we obtained highly diurnal and nocturnal strains. We used whole-genome expression analysis to identify differentially expressed genes in diurnal, nocturnal and crepuscular (control) flies. Other than one circadian clock gene (pdp1), most differentially expressed genes were associated with either clock output (pdf, to) or input (Rh3, Rh2, msn). This finding was congruent with behavioural experiments indicating that both light masking and the circadian pacemaker are involved in driving nocturnality.ConclusionsOur study demonstrates that genetic variation segregating in wild populations contributes to substantial variation in diurnal preference. We identified candidate genes associated with diurnality/nocturnality, while data emerging from our expression analysis and behavioural experiments suggest that both clock and clock-independent pathways are involved in shaping diurnal preference. The diurnal and nocturnal selection strains provide us with a unique opportunity to understand the genetic architecture of diurnal preference.
| S-EPMC7457780 | biostudies-literature
Project description:Most animals restrict their activity to specific part of the day, being either diurnal, nocturnal, or crepuscular. The genetic basis underlying this diurnal preference is largely unknown. Under laboratory conditions, Drosophila melanogaster is crepuscular, showing a bi-modal activity profile. However, recent experiments in our lab indicated that high variability among individuals exist, particularly in strains that derive from different wild populations. By assembling together flies from various geographical strains, we have generated a highly diverse population whose progeny exhibited extreme diurnal preference, including diurnal and nocturnal flies. We have used this population as a starting point for an artificial selection experiment in which we selected males that show the most extreme diurnal preference and mated them to their sisters. The response to selection was strong, and already after 10 selection cycles we obtained highly diurnal (D) and nocturnal (N) strains. Another strain that was not selected and showed intermediate behaviour (crepuscular) served as a control (C). These strains provide us with a unique opportunity to understand the genetics of diurnal preference.
2020-08-17 | GSE116985 | GEO
Project description:RationaleFalls are common among older adults and may be related to depressive symptoms (DS). With advancing age, there is an onset of chronic conditions, sensory impairments, and activity limitations that are associated with falls and with depressive disorders. Prior cross-sectional studies have observed significant associations between DS and subsequent falls as well as between fractures and subsequent clinical depression and DS.ObjectiveThe directionality of these observed relationship between falls and DS is in need of elaboration given that cross-sectional study designs can yield biased estimates of the DS-falls relationship.MethodsUsing 2006-2010 Health and Retirement Study data, cross-lagged panel structural equation models were used to evaluate associations between falls and DS among 7233 community-dwelling adults ages ≥65. Structural coefficients between falls and DS (in 2006→2008, 2008→2010) were estimated.ResultsA good-fitting model was found: Controlling for baseline (2006) physical functioning, vision, chronic conditions, and social support and neighborhood social cohesion, falls were not associated with subsequent DS, but a 0.5 standard deviation increase in 2006 DS was associated with a 30% increase in fall risk two years later. This DS-falls relationship was no longer significant when use of psychiatric medications, which was positively associated with falls, was included in the model.ConclusionUsing sophisticated methods and a large U.S. sample, we found larger magnitudes of effect in the DS-falls relationship than in prior studies-highlighting the risk of falls for older adults with DS. Medical providers might assess older individuals for DS as well as use of psychotropic medications as part of a broadened falls prevention approach. National guidelines for fall risk assessments as well as quality indicators for fall prevention should include assessment for clinical depression.
| S-EPMC5411980 | biostudies-literature