Prospective biomarkers of major depressive disorder: a systematic review and meta-analysis

AbstractLeading biological hypotheses propose that biological changes may underlie major depressive disorder onset and relapse/recurrence. Here, we investigate if there is prospective evidence for biomarkers derived from leading theories. We focus on neuroimaging, gastrointestinal factors, immunology, neurotrophic factors, neurotransmitters, hormones, and oxidative stress. Searches were performed in Pubmed, Embase and PsychInfo for articles published up to 06/2019. References and citations of included articles were screened to identify additional articles. Inclusion criteria were having an MDD diagnosis as outcome, a biomarker as predictor, and prospective design search terms were formulated accordingly. PRISMA guidelines were applied. Meta-analyses were performed using a random effect model when three or more comparable studies were identified, using a random effect model. Our search resulted in 67,464 articles, of which 75 prospective articles were identified on: Neuroimaging (N = 24), Gastrointestinal factors (N = 1), Immunology (N = 8), Neurotrophic (N = 2), Neurotransmitters (N = 1), Hormones (N = 39), Oxidative stress (N = 1). Meta-analyses on brain volumes and immunology markers were not significant. Only cortisol (N = 19, OR = 1.294, p = 0.024) showed a predictive effect on onset/relapse/recurrence of MDD, but not on time until MDD onset/relapse/recurrence. However, this effect disappeared when studies including participants with a baseline clinical diagnosis were removed from the analyses. Other studies were too heterogeneous to compare. Thus, there is a lack of evidence for leading biological theories for onset and maintenance of depression. Only cortisol was identified as potential predictor for MDD, but results are influenced by the disease state. High-quality (prospective) studies on MDD are needed to disentangle the etiology and maintenance of MDD.

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Brain grey matter abnormalities in medication-free patients with major depressive disorder: a meta-analysis

Psychological Medicine ◽

10.1017/s0033291714000518 ◽

2014 ◽

Vol 44 (14) ◽

pp. 2927-2937 ◽

Cited By ~ 94

Author(s):

Y.-J. Zhao ◽

M.-Y. Du ◽

X.-Q. Huang ◽

S. Lui ◽

Z.-Q. Chen ◽

...

Keyword(s):

Major Depressive Disorder ◽

Depressive Disorder ◽

Anterior Cingulate Cortex ◽

Grey Matter ◽

Meta Analysis ◽

Anterior Cingulate ◽

Healthy Controls ◽

Major Depressive ◽

Meta Regression ◽

Meta Analyses

BackgroundBecause cerebral morphological abnormalities in major depressive disorder (MDD) may be modulated by antidepressant treatment, inclusion of medicated patients may have biased previous meta-analyses of voxel-based morphometry (VBM) studies. A meta-analysis of VBM studies on medication-free MDD patients should be able to distinguish the morphological features of the disease itself from those of treatment.MethodA systematic search was conducted for the relevant studies. Effect-size signed differential mapping was applied to analyse the grey matter differences between all medication-free MDD patients and healthy controls. Meta-regression was used to explore the effects of demographics and clinical characteristics.ResultsA total of 14 datasets comprising 400 medication-free MDD patients and 424 healthy controls met the inclusion criteria. The pooled meta-analysis and subgroup meta-analyses showed robustly reduced grey matter in prefrontal and limbic regions in MDD. Increased right thalamus volume was only seen in first-episode medication-naive patients, and increased grey matter in the bilateral anterior cingulate cortex only in medication wash-out patients. In meta-regression analyses the percentage of female patients in each study was negatively correlated with reduced grey matter in the right hippocampus.ConclusionsBy excluding interference from medication effects, the present study identified grey matter reduction in the prefrontal–limbic network in MDD. The subgroup meta-analysis results suggest that an increased right thalamus volume might be a trait directly related to MDD, while an increased anterior cingulate cortex volume might be an effect of medication. The meta-regression results perhaps reveal the structural underpinning of the sex differences in epidemiological and clinical aspects of MDD.

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History and Spread of Viruses (COVID-19) and Associated Demographic and Clinical Parameters – A systematic review and meta-analysis

Indian Journal of Community Health ◽

10.47203/ijch.2021.v33i01.003 ◽

2021 ◽

Vol 33 (1) ◽

pp. 9-24

Author(s):

Swambhavi Awasthi ◽

Sunil Sharma ◽

Saurav Attri ◽

Sakshi Malik Attri ◽

Rajesh Sharawat ◽

...

Keyword(s):

Meta Analysis ◽

Random Effect ◽

Random Effect Model ◽

Fixed Effect Model ◽

Primary Objective ◽

Asymptomatic Patients ◽

Effect Model ◽

Co Morbidity ◽

The Common ◽

Meta Analyses

COVID-19 made a huge impact on the world due to its rapid transmission and no treatments being available for it. The virus affected more people and spread to various countries than what was predicted when COVID-19 initially began spreading. There have been numerous pandemics and epidemics in the 21st century yet COVID-19 has affected more people and spread widely. The primary objective of the study was to explore history, spread and associated parameters of existing viruses especially COVID-19. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was followed for a systematic search to identify eligible published articles. Clinical data, regarding COVID-19 patients, was obtained from previously published articles. The main cause of COVID-19 spreading rapidly was noted to be due to a high percentage of asymptomatic patients, transmission being air-borne, and the lack of knowledge and preventative measures being implemented when the virus began spreading. The common co-morbidity that found in patients was Diabetes Mellitus, Hypertension, and Coronary Heart Disease. The common symptoms, found through the Meta-analysis, that the patients faced included cough (55.4%), fever (68.4%), fatigue (20.3%), and shortness of breath (18.1%). The proportion of asymptotic positive cases was measured 58.3% (95%CI: 24.7% – 87.9%) while mortality proportion was found to be 6.7% (fixed-effect model) and 13.4% (random-effect model). The Meta-analysis indicated that a higher percentage of males were affected by COVID-19 than females and more patients are found to be asymptomatic. Moreover, the mortality rate of patients that have had COVID-19 was found to be low.

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A Bayesian Model-Averaged Meta-Analysis of the Power Pose Effect with Informed and Default Priors: The Case of Felt Power

10.31222/osf.io/heamz ◽

2017 ◽

Author(s):

Quentin Frederik Gronau ◽

Sara van Erp ◽

Daniel W. Heck ◽

Joseph Cesario ◽

Kai Jonas ◽

...

Keyword(s):

Bayesian Model ◽

Bayesian Model Averaging ◽

Meta Analysis ◽

Random Effect ◽

Random Effect Model ◽

Model Averaging ◽

Fixed Effect Model ◽

Body Postures ◽

Effect Model ◽

Meta Analyses

Carney, Cuddy, and Yap (2010) found that --compared to participants who adopted constrictive body postures-- participants who adopted expansive body postures reported feeling more powerful, showed an increase in testosterone and a decrease in cortisol, and displayed anincreased tolerance for risk. However, these power pose effects have recently come under considerable scrutiny. Here we present a Bayesian meta-analysis of six preregistered studies from this special issue, focusing on the effect of power posing on felt power. Our analysisimproves on standard classical meta-analyses in several ways. First and foremost, we considered only preregistered studies, eliminating concerns about publication bias. Second, the Bayesian approach enables us to quantify evidence for both the alternative and the null hypothesis. Third, we use Bayesian model-averaging to account for the uncertainty with respect to the choice for a fixed-effect model or a random-effect model. Fourth, based on a literature review we obtained an empirically informed prior distribution for the between-studyheterogeneity of effect sizes. This empirically informed prior can serve as a default choice not only for the investigation of the power pose effect, but for effects in the field of psychology more generally. For effect size, we considered a default and an informed prior. Our meta-analysis yields very strong evidence for an effect of power posing on felt power. However, when the analysis is restricted to participants unfamiliar with the effect, the meta-analysis yields evidence that is only moderate.

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The clinical utility of combinatorial pharmacogenomic testing for patients with depression: a meta-analysis

Pharmacogenomics ◽

10.2217/pgs-2019-0157 ◽

2020 ◽

Vol 21 (8) ◽

pp. 559-569 ◽

Cited By ~ 1

Author(s):

Lisa Brown ◽

Oliver Vranjkovic ◽

James Li ◽

Kunbo Yu ◽

Talal Al Habbab ◽

...

Keyword(s):

Patient Outcomes ◽

Clinical Utility ◽

Meta Analysis ◽

Random Effect ◽

Random Effect Model ◽

Relative Risk Ratio ◽

Symptom Improvement ◽

Test Results ◽

Major Depressive ◽

Effect Model

Aim: To perform a meta-analysis of prospective, two-arm studies examining the clinical utility of using the combinatorial pharmacogenomic test, GeneSight Psychotropic, to inform treatment decisions for patients with major depressive disorder (MDD). Patients & methods: The pooled mean effect of symptom improvement and pooled relative risk ratio (RR) of response and remission were calculated using a random effect model. Results: Overall, 1556 patients were included from four studies, with outcomes evaluated at week 8 or week 10. Patient outcomes were significantly improved for patients with MDD whose care was guided by the combinatorial pharmacogenomic test results compared with unguided care (symptom improvement Δ = 10.08%, 95% CI: 1.67–18.50; p = 0.019; response RR = 1.40, 95% CI: 1.17–1.67; p < 0.001; remission RR = 1.49, 95% CI: 1.17–1.89; p = 0.001). Conclusion: GeneSight Psychotropic guided care improves outcomes among patients with MDD.

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Metabolic syndrome in antipsychotic-naïve patients with first-episode psychosis: a systematic review and meta-analysis

Psychological Medicine ◽

10.1017/s0033291721002853 ◽

2021 ◽

pp. 1-14

Author(s):

Nathalia Garrido-Torres ◽

Idalino Rocha-Gonzalez ◽

Luis Alameda ◽

Aurora Rodriguez-Gangoso ◽

Ana Vilches ◽

...

Keyword(s):

Systematic Review ◽

Metabolic Syndrome ◽

Meta Analysis ◽

Random Effect ◽

Random Effect Model ◽

First Episode ◽

Effect Model ◽

Caucasian Origin ◽

Drug Naïve ◽

Meta Analyses

Abstract Background It is unclear what the prevalence of metabolic syndrome (MetS) in drug-naïve first-episode of psychosis (FEP) is, as previous meta-analyses were conducted in minimally exposed or drug-naïve FEP patients with psychotic disorder at any stage of the disease; thus, a meta-analysis examining MetS in naïve FEP compared with the general population is needed. Methods Studies on individuals with FEP defined as drug-naïve (0 days exposure to antipsychotics) were included to conduct a systematic review. A meta-analysis of proportions for the prevalence of MetS in antipsychotic-naïve patients was performed. Prevalence estimates and 95% CI were calculated using a random-effect model. Subgroup analyses and meta-regressions to identify sources and the amount of heterogeneity were also conducted. Results The search yielded 4143 articles. After the removal of duplicates, 2473 abstracts and titles were screened. At the full-text stage, 112 were screened, 18 articles were included in a systematic review and 13 articles in the main statistical analysis. The prevalence of MetS in naïve (0 days) FEP is 13.2% (95% CI 8.7–19.0). Ethnicity accounted for 3% of the heterogeneity between studies, and diagnostic criteria used for MetS accounted for 7%. When compared with controls matched by sex and age, the odds ratio is 2.52 (95% CI 1.29–5.07; p = 0.007). Conclusions Our findings of increased rates of MetS in naïve FEP patients suggest that we are underestimating cardiovascular risk in this population, especially in those of non-Caucasian origin. Our findings support that altered metabolic parameters in FEPs are not exclusively due to antipsychotic treatments.

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Dose-Response Relationship in Selective Serotonin and Norepinephrine Reuptake Inhibitors in the Treatment of Major Depressive Disorder: A Meta-Analysis and Network Meta-Analysis of Randomized Controlled Trials

Psychotherapy and Psychosomatics ◽

10.1159/000520554 ◽

2021 ◽

pp. 1-10

Author(s):

Lena Rink ◽

Anne Adams ◽

Cora Braun ◽

Tom Bschor ◽

Kathrin Kuhr ◽

...

Keyword(s):

Major Depressive Disorder ◽

Depressive Disorder ◽

Dose Response ◽

Meta Analysis ◽

Response Relationship ◽

Dose Response Relationship ◽

Major Depressive ◽

Meta Analyses ◽

Higher Doses ◽

Norepinephrine Reuptake

Introduction: Selective serotonin and norepinephrine reuptake inhibitors (SNRI) are among the most prescribed antidepressants, and dose escalation is a frequently applied strategy after non-response to an initially prescribed dose. Objective: This meta-analysis aimed to find evidence of a dose-response relationship or to the contrary in direct comparisons of different SNRI doses in patients with major depressive disorder. Methods: A systematic literature search for RCTs comparing at least two doses of SNRIs was carried out in CENTRAL, PubMed, PsycINFO, and EMBASE. Doses were classified as high, medium, and low according to manufacturers’ product monographs and analyses at the level of SNRIs as a group and for single substances, accompanied by sensitivity network meta-analyses (Prospero CRD42018081031). Results: From 2,070 studies screened, we included 26 studies with a total of 10,242 patients. Comparisons of medium versus low and high versus medium doses resulted in clinically and statistically non-significant standardized mean differences of –0.06 (–0.16 to 0.04) and –0.06 (–0.16 to 0.03) in favor of higher doses. In the analyses of single substances, no statistically significant results emerged, and many contrasts yielded very small effect sizes. Dropouts due to side effects tended to be more frequent with higher doses. Heterogeneity was low. Network meta-analyses of direct comparisons supported the findings, as did a risk of bias analysis. Conclusion: Based on the lack of positive evidence for a dose-response relationship in SNRIs as a group and in single SNRIs, we recommend prescribing medium doses. In case of insufficient response, we do not recommend increasing the dose of SNRIs.

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A Bayesian Model-Averaged Meta-Analysis of the Power Pose Effect with Informed and Default Priors: The Case of Felt Power

10.31234/osf.io/9z8ch ◽

2017 ◽

Author(s):

Quentin Frederik Gronau ◽

Sara van Erp ◽

Daniel W. Heck ◽

Joseph Cesario ◽

Kai Jonas ◽

...

Keyword(s):

Bayesian Model ◽

Bayesian Model Averaging ◽

Meta Analysis ◽

Random Effect ◽

Random Effect Model ◽

Model Averaging ◽

Fixed Effect Model ◽

Body Postures ◽

Effect Model ◽

Meta Analyses

Carney, Cuddy, and Yap (2010) found that --compared to participants who adopted constrictive body postures-- participants who adopted expansive body postures reported feeling more powerful, showed an increase in testosterone and a decrease in cortisol, and displayed an increased tolerance for risk. However, these power pose effects have recently come under considerable scrutiny. Here we present a Bayesian meta-analysis of six preregistered studies from this special issue, focusing on the effect of power posing on felt power. Our analysis improves on standard classical meta-analyses in several ways. First and foremost, we considered only preregistered studies, eliminating concerns about publication bias. Second, the Bayesian approach enables us to quantify evidence for both the alternative and the null hypothesis. Third, we use Bayesian model-averaging to account for the uncertainty with respect to the choice for a fixed-effect model or a random-effect model. Fourth, based on a literature review we obtained an empirically informed prior distribution for the between-study heterogeneity of effect sizes. This empirically informed prior can serve as a default choice not only for the investigation of the power pose effect, but for effects in the field of psychology more generally. For effect size, we considered a default and an informed prior. Our meta-analysis yields very strong evidence for an effect of power posing on felt power. However, when the analysis is restricted to participants unfamiliar with the effect, the meta-analysis yields evidence that is only moderate.

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Metabolic syndrome and the incidence of lung cancer: a meta-analysis of cohort studies

Diabetology & Metabolic Syndrome ◽

10.1186/s13098-020-00598-0 ◽

2020 ◽

Vol 12 (1) ◽

Author(s):

Li Qiao ◽

Deliang Ma ◽

Hui Lv ◽

Ding Shi ◽

Min Fei ◽

...

Keyword(s):

Lung Cancer ◽

Metabolic Syndrome ◽

Cohort Studies ◽

Smoking Status ◽

Meta Analysis ◽

Random Effect ◽

Random Effect Model ◽

Current Evidence ◽

Effect Model ◽

Meta Analyses

Abstract Background Metabolic syndrome (MetS) has been related to the pathogenesis of variety categories of cancers. This meta-analysis aimed to determine the association between MetS and the incidence of lung cancer. Methods Relevant cohort studies were identified by search of PubMed, Embase, and Cochrane’s Library databases. Cochrane’s Q test and I2 statistic were used to analyze the heterogeneity. Random-effect model which incorporates the potential heterogeneity was used for the meta-analysis. Results Five cohort studies with 188,970 participants were included. A total of 1,295 lung cancer cases occurred during follow-up. Meta-analyses showed that neither MetS defined by the revised NCEP-ATP III criteria (hazard ratio [HR]: 0.94, 95% confidence interval [CI]: 0.84 to 1.05, p = 0.25; I2 = 0) nor the IDF criteria (HR: 0.82, 95% CI: 0.61 to 1.11, p = 0.20; I2 = 0) was associated with an affected risk of lung cancer. Subgroup analyses showed consistent results in women and in men, in studies performed in Asian and non-Asian countries, and in prospective and retrospective cohorts (p all > 0.05). Meta-analysis limited to studies with the adjustment of smoking status also showed similar results (HR: 0.91, 95% CI: 0.80 to 1.05, p = 0.21; I2 = 0). No publication bias was detected based on the Egger regression test (p = 0.32). Conclusions Current evidence from cohort studies does not support that MetS is an independent risk factor for the incidence of lung cancer.

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Are men dying more than women by COVID-19?

10.1101/2020.07.06.20147629 ◽

2020 ◽

Author(s):

Thaise Pinto de Melo ◽

Delvan Alves Silva ◽

Alexandre Naime Barbosa

Keyword(s):

Death Rate ◽

Meta Analysis ◽

Random Effect ◽

Random Effect Model ◽

Well Being ◽

Death Rates ◽

Effect Model ◽

Public Data ◽

Health Organization ◽

Meta Analyses

We aimed to clarify if the infection and death rate by COVID-19 differ among gender in the top 50 countries with the highest death rates. Also, we investigated if secondary variables such as HDI, number of hospital beds, average age, temperature, percentage of elderly, smoker and obesity are contributing to the variability observed among countries. Meta-analyses and meta-regressions approaches were applied to official public data reported by the Word Health Organization and governments until May, 2020. A random effect model was used for the meta-analysis and heterogeneity was calculated by I2 statistic. There was not significative difference between men and women to be infected by COVID-19 (P = 0.42), though a significative difference was observed for death rate (P < 0.0001). High heterogeneity was observed among countries. For both infection and death rates this variability was mainly explained by the HDI (42.3% and 54.2%), average age (40.9% and 40.3%) and temperature (30.1% and 39.3%). Man are dying more than women around the word by COVID-19. Countries with highest HDI present less difference between sexes. These results reinforce that public politics promoting social isolation, health care and general well-being of the population are key factors in combating COVID-19.

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Quantitative Assessment of the Association between Genetic Variants in MicroRNAs and Colorectal Cancer Risk

BioMed Research International ◽

10.1155/2015/276410 ◽

2015 ◽

Vol 2015 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Xiao-Xu Liu ◽

Meng Wang ◽

Dan Xu ◽

Jian-Hai Yang ◽

Hua-Feng Kang ◽

...

Keyword(s):

Colorectal Cancer ◽

Genetic Variants ◽

Meta Analysis ◽

Random Effect ◽

Random Effect Model ◽

Population Based ◽

Effect Model ◽

High Risk Factor ◽

Rs11614913 Polymorphism ◽

Meta Analyses

Background. The associations between polymorphisms in microRNAs and the susceptibility of colorectal cancer (CRC) were inconsistent in previous studies. This study aims to quantify the strength of the correlation between the four common polymorphisms among microRNAs (hsa-mir-146a rs2910164, hsa-mir-149 rs2292832, hsa-mir-196a2 rs11614913, and hsa-mir-499 rs3746444) and CRC risk.Methods. We searched PubMed, Web of Knowledge, and CNKI to find relevant studies. The combined odds ratio (OR) with 95% confidence interval (95% CI) was used to estimate the strength of the association in a fixed or random effect model.Results. 15 studies involving 5,486 CRC patients and 7,184 controls were included. Meta-analyses showed that rs3746444 had association with CRC risk in Caucasians (OR = 0.57, 95% CI = 0.34–0.95). In the subgroup analysis, we found significant associations between rs2910164 and CRC in hospital based studies (OR = 1.24, 95% CI = 1.03–1.49). rs2292832 may be a high risk factor of CRC in population based studied (OR = 1.18, 95% CI = 1.08–1.38).Conclusion. This meta-analysis showed that rs2910164 and rs2292832 may increase the risk of CRC. However, rs11614913 polymorphism may reduce the risk of CRC. rs3746444 may have a decreased risk to CRC in Caucasians.

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