scholarly journals Separating Clinical and Subclinical Depression by Big Data Informed Structural Vulnerability Index and Its impact on Cognition: ENIGMA Dot Product

2021 ◽  
Author(s):  
Peter Kochunov ◽  
Yizhou Ma ◽  
Kathryn S Hatch ◽  
Lianne Schmaal ◽  
Neda Jahanshad ◽  
...  
Keyword(s):  
Big Data ◽  
Depressive Symptoms ◽  
Brain Imaging ◽  
Cognitive Performance ◽  
Meta Analysis ◽  
Vulnerability Index ◽  
Imaging Genetics ◽  
Cognitive Tests ◽  
Correlation Pattern ◽  
Dot Product

Big Data neuroimaging collaborations including Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) integrated worldwide data to identify regional brain deficits in major depressive disorder (MDD). We evaluated the sensitivity of translating ENIGMA-defined MDD deficit patterns to the individual level. We treated ENIGMA MDD deficit patterns as a vector to gauge the similarity between individual and MDD patterns by calculating ENIGMA dot product (EDP). We analyzed the sensitivity and specificity of EDP in separating subjects with (1) subclinical depressive symptoms without a diagnosis of MDD, (2) single episode MDD, (3) recurrent MDD, and (4) controls free of neuropsychiatric disorders. We compared EDP to the Quantile Regression Index (QRI; a linear alternative to the brain age metric) and the global gray matter thickness and subcortical volumes and fractional anisotropy (FA) of water diffusion. We performed this analysis in a large epidemiological sample of UK Biobank (UKBB) participants (N=17,053/19,265 M/F). Group-average increases in depressive symptoms from controls to recurrent MDD was mirrored by EDP (r2=0.85), followed by FA (r2=0.81) and QRI (r2=0.56). Subjects with MDD showed worse performance on cognitive tests than controls with deficits observed for 3 out of 9 cognitive tests administered by the UKBB. We calculated correlations of EDP and other brain indices with measures of cognitive performance in controls. The correlation pattern between EDP and cognition in controls was similar (r2=0.75) to the pattern of cognitive differences in MDD. This suggests that the elevation in EDP, even in controls, is associated with cognitive performance - specifically in the MDD-affected domains. That specificity was missing for QRI, FA or other brain imaging indices. In summary, translating anatomically informed meta-analytic indices of similarity using a linear vector approach led to better sensitivity to depressive symptoms and cognitive patterns than whole-brain imaging measurements or an index of accelerated aging.

scholarly journals Data-driven analysis shows robust links between fatigue and depression in early multiple sclerosis

2022 ◽  
Author(s):  
Yuan Ting Chang ◽  
Patrick K.A. Kearns ◽  
Alan Carson ◽  
David Gillespie ◽  
Rozanna Meijboom ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Depressive Symptoms ◽  
Sleep Quality ◽  
Brain Imaging ◽  
Cognitive Performance ◽  
Subjective Sleep Quality ◽  
Fatigue Severity ◽  
Relapsing Remitting Multiple Sclerosis ◽  
Structural Brain ◽  
Structural Brain Imaging

Fatigue is common and disabling in multiple sclerosis, yet its mechanisms are poorly understood. In particular, overlap in measures of fatigue and depression complicates interpretation. A clearer understanding of relationships between fatigue and key clinical, neuropsychiatric and imaging variables including depression could yield clinically relevant mechanistic insight. We applied a data-driven multivariate network approach to quantify relationships between fatigue and other variables in early multiple sclerosis. Data were collected from Scottish patients with newly diagnosed, immunotherapy-naive, relapsing-remitting multiple sclerosis at baseline and month 12 follow-up in FutureMS, a nationally representative multicentre cohort. Subjective fatigue was assessed using the validated Fatigue Severity Scale. Detailed phenotyping included measures assessing physical disability, affective disorders, objective cognitive performance, subjective sleep quality, and structural brain imaging. Bivariate correlations between fatigue and other variables were calculated. Network analysis was then conducted to estimate partial correlations between variables, after accounting for all other included variables. Secondary networks included individual depressive symptoms, to control for overlapping symptom items in measures of fatigue and depression. Data from 322 participants at baseline, and 323 at month 12, were included. At baseline, 49.5% of the cohort reported clinically significant fatigue. Bivariate correlations confirmed that fatigue severity was significantly correlated with all included measures of physical disability, affective disturbance (anxiety and depression), cognitive performance (processing speed and memory/attention), and sleep quality, but not with structural brain imaging variables including normalized lesion and grey matter volumes. In the network analysis, fatigue showed strong correlations with depression, followed by Expanded Disability Status Scale. Weak connections with walking speed, subjective sleep quality and anxiety were identified. After separately controlling for measurement of tiredness in our measure of depression, some key depressive symptoms (anhedonia, subjective concentration deficits, subjectively altered speed of movement, and appetite) remained linked to fatigue. Conversely, fatigue was not linked to objective cognitive performance, white matter lesion volume, or grey matter volumes (cortical, subcortical or thalamic). Results were consistent at baseline and month 12. Depression was identified as the most central variable in the networks. Correlation stability coefficients and bootstrapped confidence intervals of the edge weights supported stability of the estimated networks. Our findings support robust links between subjective fatigue and depression in early relapsing-remitting multiple sclerosis, despite absence of links between fatigue and either objective cognitive performance, or structural brain imaging variables. Depression, including specific depressive symptoms, could be a key target of treatment and research in multiple sclerosis-related fatigue.

scholarly journals Caffeine and Cognitive Functions in Sports: A Systematic Review and Meta-Analysis

Nutrients ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 868
Author(s):  
Jorge Lorenzo Calvo ◽  
Xueyin Fei ◽  
Raúl Domínguez ◽  
Helios Pareja-Galeano
Keyword(s):  
Systematic Review ◽  
Reaction Time ◽  
Cognitive Performance ◽  
Cognitive Functions ◽  
Web Of Science ◽  
Meta Analysis ◽  
Caffeine Intake ◽  
Inclusion Criteria ◽  
Research Protocols ◽  
The Relationship

Cognitive functions are essential in any form of exercise. Recently, interest has mounted in addressing the relationship between caffeine intake and cognitive performance during sports practice. This review examines this relationship through a structured search of the databases Medline/PubMed and Web of Science for relevant articles published in English from August 1999 to March 2020. The study followed PRISMA guidelines. Inclusion criteria were defined according to the PICOS model. The identified records reported on randomized cross-over studies in which caffeine intake (as drinks, capsules, energy bars, or gum) was compared to an identical placebo situation. There were no filters on participants’ training level, gender, or age. For the systematic review, 13 studies examining the impacts of caffeine on objective measures of cognitive performance or self-reported cognitive performance were selected. Five of these studies were also subjected to meta-analysis. After pooling data in the meta-analysis, the significant impacts of caffeine only emerged on attention, accuracy, and speed. The results of the 13 studies, nevertheless, suggest that the intake of a low/moderate dose of caffeine before and/or during exercise can improve self-reported energy, mood, and cognitive functions, such as attention; it may also improve simple reaction time, choice reaction time, memory, or fatigue, however, this may depend on the research protocols.

scholarly journals Effects of n-3 Polyunsaturated Fatty Acid Supplementation in the Prevention and Treatment of Depressive Disorders—A Systematic Review and Meta-Analysis

Nutrients ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 1070
Author(s):  
Maike Wolters ◽  
Annkathrin von der Haar ◽  
Ann-Kristin Baalmann ◽  
Maike Wellbrock ◽  
Thomas L. Heise ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Treatment Duration ◽  
Depressive Disorders ◽  
Meta Analysis ◽  
Pufa Supplementation ◽  
Depressive Symptomology ◽  
Beneficial Effects ◽  
Randomized Controlled ◽  
Significant Difference

N-3 polyunsaturated fatty acids (PUFAs) have been suggested to affect depressive disorders. This review aims to determine the effect of n-3 PUFAs on depressive symptoms in people with or without diagnosed depression. Medline, PsycINFO, and Cochrane CENTRAL databases were searched for randomized controlled trials (RCTs) assessing the association between n-3 PUFAs and depressive symptoms or disorders as outcomes. A random-effects meta-analysis of standardized mean difference (SMD) with 95% confidence intervals (CI) was performed. Twenty-five studies (7682 participants) were included. Our meta-analysis (20 studies) indicated that n-3 PUFA supplementation lowered depressive symptomology as compared with placebo: SMD = −0.34, 95% CI: −0.55, −0.12, I2 = 86%, n = 5836, but a possible publication bias cannot be ruled out. Subgroup analyses indicated no statistically significant difference by treatment duration of <12 vs. ≥12 weeks, presence of comorbidity, or severity of depressive symptoms. Nevertheless, beneficial effects were seen in the subgroups of studies with longer treatment duration and with no depression and mild to moderate depression. Subgroup analysis by eicosapentaenoic acid (EPA) dosage revealed differences in favor of the lower EPA dosage. Sensitivity analysis including studies with low risk of bias seems to confirm the overall result. Supplementation of n-3 PUFA appears to have a modest beneficial effect on depressive symptomology, although the quality of evidence is still insufficient.

scholarly journals Systematic review and meta-analysis of the prevalence of depressive symptoms, dysthymia and major depressive disorders among homeless people

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e040061
Author(s):  
Getinet Ayano ◽  
Asmare Belete ◽  
Bereket Duko ◽  
Light Tsegay ◽  
Berihun Assefa Dachew
Keyword(s):  
Systematic Review ◽  
Depressive Symptoms ◽  
Depressive Disorders ◽  
Meta Analysis ◽  
Random Effect ◽  
Homeless People ◽  
Sensitivity Analyses ◽  
Prevalence Rates ◽  
Major Depressive ◽  
Major Depressive Disorders

ObjectivesTo assess the global prevalence estimates of depressive symptoms, dysthymia and major depressive disorders (MDDs) among homeless people.DesignSystematic review and meta-analysis.Data sourcesDatabases including PubMed, Scopus and Web of Science were systematically searched up to February 2020 to identify relevant studies that have reported data on the prevalence of depressive symptoms, dysthymia and MDDs among homeless people.Eligibility criteriaOriginal epidemiological studies written in English that addressed the prevalence of depressive problems among homeless people.Data extraction and synthesisA random-effect meta-analysis was performed to pool the prevalence estimated from individual studies. Subgroup and sensitivity analyses were employed to compare the prevalence across the groups as well as to identify the source of heterogeneities. The Joanna Briggs Institute’s quality assessment checklist was used to measure the study quality. Cochran’s Q and the I2 test were used to assess heterogeneity between the studies.ResultsForty publications, including 17 215 participants, were included in the final analysis. This meta-analysis demonstrated considerably higher prevalence rates of depressive symptoms 46.72% (95% CI 37.77% to 55.90%), dysthymia 8.25% (95% CI 4.79% to 11.86%), as well as MDDs 26.24% (95% CI 21.02% to 32.22%) among homeless people. Our subgroup analysis showed that the prevalence of depressive symptoms was high among younger homeless people (<25 years of age), whereas the prevalence of MDD was high among older homeless people (>50 years of age) when compared with adults (25–50 years).ConclusionThis review showed that nearly half, one-fourth and one-tenth of homeless people are suffering from depressive symptoms, dysthymia and MDDs, respectively, which are notably higher than the reported prevalence rates in the general population. The findings suggest the need for appropriate mental health prevention and treatment strategies for this population group.

Combined healthy lifestyle and depressive symptoms: a meta-analysis of observational studies

2021 ◽  
Author(s):  
Xiaowen Wang ◽  
Ahmed Arafa ◽  
Keyang Liu ◽  
Ehab S Eshak ◽  
Yonghua Hu ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Observational Studies ◽  
Healthy Lifestyle ◽  
Meta Analysis

scholarly journals Long-term outcomes of psychological treatment for posttraumatic stress disorder: a systematic review and meta-analysis

2021 ◽  
pp. 1-11
Author(s):  
Maxi Weber ◽  
Sarah Schumacher ◽  
Wiebke Hannig ◽  
Jürgen Barth ◽  
Annett Lotzin ◽  
...  
Keyword(s):  
Systematic Review ◽  
Depressive Symptoms ◽  
Stress Disorder ◽  
Psychological Treatment ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Long Term Outcomes ◽  
Psychological Treatments

Abstract Several types of psychological treatment for posttraumatic stress disorder (PTSD) are considered well established and effective, but evidence of their long-term efficacy is limited. This systematic review and meta-analysis aimed to investigate the long-term outcomes across psychological treatments for PTSD. MEDLINE, Cochrane Library, PTSDpubs, PsycINFO, PSYNDEX, and related articles were searched for randomized controlled trials with at least 12 months of follow-up. Twenty-two studies (N = 2638) met inclusion criteria, and 43 comparisons of cognitive behavioral therapy (CBT) were available at follow-up. Active treatments for PTSD yielded large effect sizes from pretest to follow-up and a small controlled effect size compared with non-directive control groups at follow-up. Trauma-focused treatment (TFT) and non-TFT showed large improvements from pretest to follow-up, and effect sizes did not significantly differ from each other. Active treatments for comorbid depressive symptoms revealed small to medium effect sizes at follow-up, and improved PTSD and depressive symptoms remained stable from treatment end to follow-up. Military personnel, low proportion of female patients, and self-rated PTSD measures were associated with decreased effect sizes for PTSD at follow-up. The findings suggest that CBT for PTSD is efficacious in the long term. Future studies are needed to determine the lasting efficacy of other psychological treatments and to confirm benefits beyond 12-month follow-up.

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