Development and Internal Validation of a Novel Model to Identify Inflammatory Biomarkers of a Response to Escitalopram in Patients With Major Depressive Disorder

Objective: The aim of our study was to identify immune- and inflammation-related factors with clinical utility to predict the clinical efficacy of treatment for depression.Study Design: This was a follow-up study. Participants who met the entry criteria were administered with escitalopram (5–10 mg/day) as an initial treatment. Self-evaluation and observer valuations were arranged at the end of weeks 0, 4, 8, and 12, with blood samples collected at baseline and during weeks 2 and 12. Multivariable logistic regression analysis was then carried out by incorporating three cytokines selected by the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. Internal validation was estimated using the bootstrap method with 1,000 repetitions.Results: A total of 85 patients with Major Depressive Disorder (MDD), including 62 responders and 23 non-responders, were analyzed. Monocyte chemoattractant protein-1 (MCP-1), vascular cell adhesion molecule-1 (VCAM-1), and lipocalin-2 were selected by the LASSO regression model. The area under the curve (AUC) from the logistic model was 0.811 and was confirmed as 0.7887 following bootstrapping validation.Conclusions: We established and validated a good prediction model to facilitate the individualized prediction of escitalopram treatment for MDD and created a personalized approach to treatment for patients with depression.

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Remission Rates, Time to Remission, and Related Factors in Adolescents with Major Depressive Disorder

10.5152/eurjther.2021.20081 ◽

2021 ◽

Vol 27 (3) ◽

pp. 219-223

Author(s):

Zehra Topal ◽

◽

Yusuf Ozturk ◽

Nuran Demir ◽

Oznur Adiguzel ◽

...

Keyword(s):

Major Depressive Disorder ◽

Depressive Disorder ◽

Major Depressive ◽

Related Factors ◽

Remission Rates

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Disparities in COVID-19 infection, hospitalisation and death in people with schizophrenia, bipolar disorder, and major depressive disorder: a cohort study of the UK Biobank

Molecular Psychiatry ◽

10.1038/s41380-021-01344-2 ◽

2021 ◽

Author(s):

Lamiece Hassan ◽

Niels Peek ◽

Karina Lovell ◽

Andre F. Carvalho ◽

Marco Solmi ◽

...

Keyword(s):

Bipolar Disorder ◽

Major Depressive Disorder ◽

Cohort Study ◽

Depressive Disorder ◽

Sociodemographic Factors ◽

Vulnerable Groups ◽

Multivariable Logistic Regression Analysis ◽

Uk Biobank ◽

Major Depressive ◽

The Uk

AbstractPeople with severe mental illness (SMI; including schizophrenia/psychosis, bipolar disorder (BD), major depressive disorder (MDD)) experience large disparities in physical health. Emerging evidence suggests this group experiences higher risks of infection and death from COVID-19, although the full extent of these disparities are not yet established. We investigated COVID-19 related infection, hospitalisation and mortality among people with SMI in the UK Biobank (UKB) cohort study. Overall, 447,296 participants from UKB (schizophrenia/psychosis = 1925, BD = 1483 and MDD = 41,448, non-SMI = 402,440) were linked with healthcare and death records. Multivariable logistic regression analysis was used to examine differences in COVID-19 outcomes by diagnosis, controlling for sociodemographic factors and comorbidities. In unadjusted analyses, higher odds of COVID-19 mortality were seen among people with schizophrenia/psychosis (odds ratio [OR] 4.84, 95% confidence interval [CI] 3.00–7.34), BD (OR 3.76, 95% CI 2.00–6.35), and MDD (OR 1.99, 95% CI 1.69–2.33) compared to people with no SMI. Higher odds of infection and hospitalisation were also seen across all SMI groups, particularly among people with schizophrenia/psychosis (OR 1.61, 95% CI 1.32–1.96; OR 3.47, 95% CI 2.47–4.72) and BD (OR 1.48, 95% CI 1.16–1.85; OR 3.31, 95% CI 2.22–4.73). In fully adjusted models, mortality and hospitalisation odds remained significantly higher among all SMI groups, though infection odds remained significantly higher only for MDD. People with schizophrenia/psychosis, BD and MDD have higher risks of COVID-19 infection, hospitalisation and mortality. Only a proportion of these disparities were accounted for by pre-existing demographic characteristics or comorbidities. Vaccination and preventive measures should be prioritised in these particularly vulnerable groups.

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Promoter Hypomethylation of miR-124 Gene Is Associated With Major Depressive Disorder

Frontiers in Molecular Neuroscience ◽

10.3389/fnmol.2021.771103 ◽

2021 ◽

Vol 14 ◽

Author(s):

Duan Zeng ◽

Shen He ◽

Nan Zhao ◽

Manji Hu ◽

Jie Gao ◽

...

Keyword(s):

Major Depressive Disorder ◽

Depressive Disorder ◽

Antidepressant Treatment ◽

Cpg Islands ◽

Healthy Controls ◽

Lasso Regression ◽

Bonferroni Correction ◽

Major Depressive ◽

Cpg Sites ◽

Significant Difference

Based on our previous studies and other evidence, miR-124 is an important biomarker and therapeutic target for major depressive disorder (MDD). The aim of this study was to clarify the role of miR-124 methylation in MDD and antidepressant effects from the perspective of epigenetics. MethylTarget™ was used to detect methylation levels of the three miR-124 precursor genes (MIR124-1, MIR124-2, and MIR124-3) in 33 pre- and post-treatment MDD patients and 33 healthy controls. A total of 11 cytosine-phosphate-guanine (CpG) islands in the three miR-124 precursor genes, including 222 CpG sites, were detected. All CpG islands were hypomethylated in MDD patients when compared to healthy controls and seven CpG regions were still identified with a statistically significant difference after Bonferroni correction. In addition, 137 of 222 CpG sites were found a statistical difference between MDD patients and controls, and 40 CpG sites were still statistically significant after Bonferroni correction. After performing the LASSO regression model, seven biomarkers with differential methylation among 40 CpG sites were identified. Mean methylation score was lower in MDD patients (z = −5.84, p = 5.16E-9). The AUC value reached 0.917 (95% CI: 0.854–0.981) to discriminate MDD and controls. No changes in methylation of the three miR-124 precursor genes were found in MDD patients following antidepressant treatment. The methylation of miR-124 could be a promising diagnostic biomarker for MDD.

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