Neuroimaging markers of adolescent depression in the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study

Brain-based Sex Differences in Depression: A Systematic Review of Neuroimaging Studies

Major depressive disorder (MDD) is a common psychiatric illness with a wide range of symptoms such as mood decline, loss of interest, and feelings of guilt and worthlessness. Women develop depression more often than men, and the diagnostic criteria for depression mainly rely on female patients' symptoms. By contrast, male depression usually manifests as anger attacks, aggression, substance use, and risk-taking behaviors. Various studies have focused on the neuroimaging findings in psychiatric disorders for a better understanding of their underlying mechanisms. With this review, we aimed to summarize the existing literature on the neuroimaging findings in depression, separated by male and female subjects. A search was conducted on PubMed and Scopus for magnetic resonance imaging (MRI), functional MRI (fMRI), and diffusion tensor imaging (DTI) studies of depression. After screening the search results, 15 MRI, 12 fMRI, and 4 DTI studies were included. Sex differences were mainly reflected in the following regions: 1) total brain, hippocampus, amygdala, habenula, anterior cingulate cortex, and corpus callosum volumes, 2) frontal and temporal gyri functions, along with functions of the caudate nucleus and prefrontal cortex, and 3) frontal fasciculi and frontal projections of corpus callosum microstructural alterations. Our review faces limitations such as small sample sizes and heterogeneity in populations and modalities. But in conclusion, it reflects the possible roles of sex-based hormonal and social factors in the depression pathophysiology.

The Collaborative Study on the Genetics of Alcoholism: Overview

Alcohol use disorders (AUD) are commonly occurring, heritable and polygenic disorders with etiological origins in the brain and the environment. To outline the causes and consequences of alcohol-related milestones, including AUD, and their related psychiatric comorbidities, the Collaborative Study on the Genetics of Alcoholism (COGA) was launched in 1989 with a gene-brain-behavior framework. COGA is a family based, diverse (~25% self-identified African American, ~52% female) sample, including data on 17,878 individuals, ages 7-97 years, in 2246 families of which a proportion are densely affected for AUD. All participants responded to questionnaires (e.g., personality) and the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) which gathers information on psychiatric diagnoses, conditions and related behaviors (e.g., parental monitoring). In addition, 9871 individuals have brain function data from electroencephalogram (EEG) recordings while 12,009 individuals have been genotyped on genome-wide association study (GWAS) arrays. A series of functional genomics studies examine the specific cellular and molecular mechanisms underlying AUD. This overview provides the framework for the development of COGA as a scientific resource in the past three decades, with individual reviews providing in-depth descriptions of data on and discoveries from behavioral and clinical, brain function, genetic and functional genomics data. The value of COGA also resides in its data sharing policies, its efforts to communicate scientific findings to the broader community via a project website and its potential to nurture early career investigators and to generate independent research that has broadened the impact of gene-brain-behavior research into AUD.

Aberrant single-subject morphological brain networks in first-episode, treatment-naive adolescents with major depressive disorder

Background

Neuroimaging-based connectome studies have indicated that major depressive disorder (MDD) is associated with disrupted topological organization of large-scale brain networks. However, the disruptions and their clinical and cognitive relevance are not well established for morphological brain networks in adolescent MDD.

Objective

To investigate the topological alterations of single-subject morphological brain networks in adolescent MDD.

Methods

Twenty-five first-episode, treatment-naive adolescents with MDD and 19 healthy controls (HCs) underwent T1-weighted magnetic resonance imaging and a battery of neuropsychological tests. Single-subject morphological brain networks were constructed separately based on cortical thickness, fractal dimension, gyrification index, and sulcus depth, and topologically characterized by graph-based approaches. Between-group differences were inferred by permutation testing. For significant alterations, partial correlations were used to examine their associations with clinical and neuropsychological variables in the patients. Finally, a support vector machine was used to classify the patients from controls.

Results

Compared with the HCs, the patients exhibited topological alterations only in cortical thickness-based networks characterized by higher nodal centralities in parietal (left primary sensory cortex) but lower nodal centralities in temporal (left parabelt complex, right perirhinal ectorhinal cortex, right area PHT and right ventral visual complex) regions. Moreover, decreased nodal centralities of some temporal regions were correlated with cognitive dysfunction and clinical characteristics of the patients. These results were largely reproducible for binary and weighted network analyses. Finally, topological properties of the cortical thickness-based networks were able to distinguish the MDD adolescents from HCs with 87.6% accuracy.

Conclusion

Adolescent MDD is associated with disrupted topological organization of morphological brain networks, and the disruptions provide potential biomarkers for diagnosing and monitoring the disease.

Efficacy and tolerability of antidepressant drugs in treatment of depression in children and adolescents: a network meta-analysis

OBJECTIVE

To evaluate the efficacy and safety of antidepressants in treatment of depression disorder in children and adolescents by network meta-analysis.

METHODS

Databases of PubMed, Cochrane Library, EMBASE, Web of Science, PsycINFO, CBM, CNKI and Wanfang Data were searched for randomized controlled trials (RCT) related to antidepressants in treatment of children and adolescents with depression from inception to December 2021. Quality assessment and data extraction from the included RCTs were performed. Statistical analyses of efficacy and tolerability were conducted with Stata 15.1 software. Surface under the cumulative ranking (SUCAR) was used to rank the value of the antidepressants.

RESULTS

A total of 33 RCTs were included in 32 articles, involving 6949 patients. There are 13 antidepressants used in total, including amitriptyline, vilazodone, fluoxetine, selegiline, paroxetine, imipramine, desipramine, sertraline, nortriptyline, escitalopram, citalopram, venlafaxine and duloxetine. The results of network meta-analysis showed that the efficacy of duloxetine ( OR=1.95, 95% CI: 1.41-2.69), fluoxetine ( OR=1.73, 95% CI: 1.40-2.14), venlafaxine ( OR=1.37, 95% CI: 1.04-1.80) and escitalopram ( OR=1.48, 95% CI: 1.12-1.95) were significantly higher than that of placebos (all P<0.05); the probability cumulative ranks were duloxetine (87.0%), amitriptyline (83.3%), fluoxetine (79.0%), escitalopram (62.7%), etc. The results showed that the intolerability of patients receiving imipramine ( OR=0.15, 95% CI: 0.08-0.27), sertraline ( OR=0.33, 95% CI: 0.16-0.71), venlafaxine ( OR=0.35, 95% CI: 0.17-0.72), duloxetine ( OR=0.35, 95% CI: 0.17-0.73) and paroxetine ( OR=0.52, 95% CI: 0.30-0.88) were significantly higher than that of placebos (all P<0.05), and the probability cumulative ranks were imipramine (95.7%), sertraline (69.6%), venlafaxine (68.6%), duloxetine (68.2%), etc. Conclusion: Among 13 antidepressants, duloxetine, fluoxetine, escitalopram and venlafaxine are significantly better than placebo in terms of efficacy, but duloxetine and venlafaxine are less well tolerated.

Alcohol and the Adolescent Brain: What We've Learned and Where the Data Are Taking Us

This article is part of a Festschrift commemorating the 50th anniversary of the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Established in 1970, first as part of the National Institute of Mental Health and later as an independent institute of the National Institutes of Health, NIAAA today is the world's largest funding agency for alcohol research. In addition to its own intramural research program, NIAAA supports the entire spectrum of innovative basic, translational, and clinical research to advance the diagnosis, prevention, and treatment of alcohol use disorder and alcohol-related problems. To celebrate the anniversary, NIAAA hosted a 2-day symposium, "Alcohol Across the Lifespan: 50 Years of Evidence-Based Diagnosis, Prevention, and Treatment Research," devoted to key topics within the field of alcohol research. This article is based on Dr. Tapert's presentation at the event. NIAAA Director George F. Koob, Ph.D., serves as editor of the Festschrift.

Chinese Color Nest Project : An accelerated longitudinal brain-mind cohort

The ongoing Chinese Color Nest Project (CCNP) was established to create normative charts for brain structure and function across the human lifespan, and link age-related changes in brain imaging measures to psychological assessments of behavior, cognition, and emotion using an accelerated longitudinal design. In the initial stage, CCNP aims to recruit 1520 healthy individuals (6-90 years), which comprises three phases: developing (devCCNP: 6-18 years, N = 480), maturing (matCCNP: 20-60 years, N = 560) and aging (ageCCNP: 60-84 years, N = 480). In this paper, we present an overview of the devCCNP, including study design, participants, data collection and preliminary findings. The devCCNP has acquired data with three repeated measurements from 2013 to 2017 in Southwest University, Chongqing, China (CCNP-SWU, N = 201). It has been accumulating baseline data since July 2018 and the second wave data since September 2020 in Chinese Academy of Sciences, Beijing, China (CCNP-CAS, N = 168). Each participant in devCCNP was followed up for 2.5 years at 1.25-year intervals. The devCCNP obtained longitudinal neuroimaging, biophysical, social, behavioral and cognitive data via MRI, parent- and self-reported questionnaires, behavioral assessments, and computer tasks. Additionally, data were collected on children's learning, daily life and emotional states during the COVID-19 pandemic in 2020. We address data harmonization across the two sites and demonstrated its promise of characterizing the growth curves for the overall brain morphometry using multi-center longitudinal data. CCNP data will be shared via the National Science Data Bank and requests for further information on collaboration and data sharing are encouraged.