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OBJECTIVE - Early life stress (ELS) is associated with increased risk for the development of major depressive disorder (MDD) in adulthood; however, the degree to which ELS is associated with an early onset of MDD (ie, during childhood or adolescence) is not known. In this meta-analysis, we estimated the associations between ELS and the risk for onset of MDD before age 18 years. In addition, we examined the associations between eight specific forms of ELS (ie, sexual abuse, physical abuse, poverty, physical illness/injury, death of a family member, domestic violence, natural disaster, and emotional abuse) and risk for youth-onset MDD.
METHOD - We conducted a systematic search in scientific databases for studies that assessed both ELS and the presence or absence of MDD before age 18 years. We identified 62 journal articles with a total of 44,066 unique participants. We assessed study quality using the Newcastle-Ottawa Scale. When heterogeneous effect sizes were detected, we tested whether demographic and/or methodological factors moderated the association between ELS and MDD.
RESULTS - Using a random-effects meta-analysis, we found that individuals who experienced ELS were more likely to develop MDD before the age of 18 years than were individuals without a history of ELS (odds ratio = 2.50; 95% confidence interval 2.08, 3.00). Separate meta-analyses revealed a range of associations with MDD: whereas some types of ELS (eg, poverty) were not associated with MDD, other types (eg, emotional abuse) were associated more strongly with MDD than was ELS considered more broadly.
CONCLUSION - These findings provide important evidence that the adverse effect of ELS on MDD risk manifests early in development, prior to adulthood, and varies by type of ELS.
Copyright © 2019 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.
OBJECTIVE - Several studies have found associations between a diagnosis or symptoms of major depressive disorder and markers of cellular aging and dysfunction. These investigations, however, are predominantly cross-sectional and focus on adults. In the present study, we used a prospective longitudinal design to test the cross-sectional association between depressive symptoms in adolescents and telomere length (TL) as well as mitochondrial DNA copy number (mtDNA-cn).
METHOD - A total of 121 adolescents (mean age = 11.38 years, SD = 1.03; 39% male adolescents and 61% female adolescents) were followed for approximately 2 years. At baseline and follow-up, participants provided saliva for DNA extraction, from which measures of TL and mtDNA-cn were obtained. Depressive symptoms were obtained via the Children's Depression Inventory.
RESULTS - There was no association between depressive symptoms and markers of cellular aging at baseline; however, depressive symptoms at baseline predicted higher rates of telomere erosion (β = -0.201, p = .016) and greater increases in mtDNA-cn (β = 0.190, p = .012) over the follow-up period. Markers of cellular aging at baseline did not predict subsequent changes in depressive symptoms. Furthermore, including the number of stressful life events did not alter these patterns of findings.
CONCLUSION - These results indicate that depressive symptoms precede changes in cellular aging and dysfunction, rather than the reverse.
Copyright © 2019 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.
The stress response system is disrupted in individuals with major depressive disorder (MDD) as well as in those at elevated risk for developing MDD. We examined whether DNA methylation (DNAm) levels of CpG sites within HPA-axis genes predict the onset of MDD. Seventy-seven girls, approximately half (n = 37) of whom were at familial risk for MDD, were followed longitudinally. Saliva samples were taken in adolescence (M age = 13.06 years [SD = 1.52]) when participants had no current or past MDD diagnosis. Diagnostic interviews were administered approximately every 18 months until the first onset of MDD or early adulthood (M age of last follow-up = 19.23 years [SD = 2.69]). We quantified DNAm in saliva samples using the Illumina EPIC chip and examined CpG sites within six key HPA-axis genes (NR3C1, NR3C2, CRH, CRHR1, CRHR2, FKBP5) alongside 59 genotypes for tagging SNPs capturing cis genetic variability. DNAm levels within CpG sites in NR3C1, CRH, CRHR1, and CRHR2 were associated with risk for MDD across adolescence and young adulthood. To rule out the possibility that findings were merely due to the contribution of genetic variability, we re-analyzed the data controlling for cis genetic variation within these candidate genes. Importantly, methylation levels in these CpG sites continued to significantly predict the onset of MDD, suggesting that variation in the epigenome, independent of proximal genetic variants, prospectively predicts the onset of MDD. These findings suggest that variation in the HPA axis at the level of the methylome may predict the development of MDD.
The significant public health burden associated with late-life depression (LLD) is magnified by the high rates of recurrence. In this manuscript, we review what is known about recurrence risk factors, conceptualize recurrence within a model of homeostatic disequilibrium, and discuss the potential significance and challenges of new research into LLD recurrence. The proposed model is anchored in the allostatic load theory of stress. We review the allostatic response characterized by neural changes in network function and connectivity and physiologic changes in the hypothalamic-pituitary-adrenal axis, autonomic nervous system, immune system, and circadian rhythm. We discuss the role of neural networks' instability following treatment response as a source of downstream disequilibrium, triggering and/or amplifying abnormal stress response, cognitive dysfunction and behavioral changes, ultimately precipitating a full-blown recurrent episode of depression. We propose strategies to identify and capture early change points that signal recurrence risk through mobile technology to collect ecologically measured symptoms, accompanied by automated algorithms that monitor for state shifts (persistent worsening) and variance shifts (increased variability) relative to a patient's baseline. Identifying such change points in relevant sensor data could potentially provide an automated tool that could alert clinicians to at-risk individuals or relevant symptom changes even in a large practice.
Published by Elsevier Inc.
Major depression is a common and severe psychiatric disorder with a highly polygenic genetic architecture. Genome-wide association studies have successfully identified multiple independent genetic loci that harbour variants associated with major depression, but the exact causal genes and biological mechanisms are largely unknown. Tissue-specific network approaches may identify molecular mechanisms underlying major depression and provide a biological substrate for integrative analyses. We provide a framework for the identification of individual risk genes and gene co-expression networks using genome-wide association summary statistics and gene expression information across multiple human brain tissues and whole blood. We developed a novel gene-based method called eMAGMA that leverages tissue-specific eQTL information to identify 99 biologically plausible risk genes associated with major depression, of which 58 are novel. Among these novel associations is Complement Factor 4A (C4A), recently implicated in schizophrenia through its role in synaptic pruning during postnatal development. Major depression risk genes were enriched in gene co-expression modules in multiple brain tissues and the implicated gene modules contained genes involved in synaptic signalling, neuronal development, and cell transport pathways. Modules enriched with major depression signals were strongly preserved across brain tissues, but were weakly preserved in whole blood, highlighting the importance of using disease-relevant tissues in genetic studies of psychiatric traits. We identified tissue-specific genes and gene co-expression networks associated with major depression. Our novel analytical framework can be used to gain fundamental insights into the functioning of the nervous system in major depression and other brain-related traits.
This article reviews the interactions of estrogen changes and psychosocial stress in contributing to vulnerability to major depressive disorder (MDD) in women. Estrogen modulates brain networks and processes related to changes in stress response, cognition, and emotional dysregulation that are core characteristics of MDD. Synergistic effects of estrogen on cognitive and emotional function, particularly during psychosocial stress, may underlie the association of ovarian hormone fluctuation and depression in women. We propose a model of estrogen effects on multiple brain systems that interface with stress-related emotional and cognitive processes implicated in MDD and discuss possible mechanisms through which reproductive events and changes in estrogen may contribute to MDD risk in women with other concurrent risk factors.
BACKGROUND - Major depressive disorder (MDD) is one of the most prevalent and debilitating psychiatric disorders. Cognitive complaints are commonly reported in MDD and cognitive impairment is a criterion item for MDD diagnosis. As cognitive processes are increasingly understood as the consequences of distributed interactions between brain regions, a network-based approach may provide novel information about the neurobiological basis of cognitive deficits in MDD.
METHODS - 51 Depressed (MDD, n = 23) and non-depressed (control, n = 28) adult participants completed neuropsychological testing and resting-state fMRI (rsfMRI). Cognitive domain scores (processing speed, working memory, episodic memory, and executive function) were calculated. Anatomical regions of interests were entered as seeds for functional connectivity analyses in: default mode (DMN), salience, and executive control (ECN) networks. Partial correlations controlling for age and sex were conducted for cognitive domain scores and functional connectivity in clusters with significant differences between groups.
RESULTS - Significant rsfMRI differences between groups were identified in multiple clusters in the DMN and ECN. Greater positive connectivity within the ECN and between ECN and DMN regions was associated with poorer episodic memory performance in the Non-Depressed group but better performance in the MDD group. Greater connectivity within the DMN was associated with better episodic and working memory performance in the Non-Depressed group but worse performance in the MDD group.
CONCLUSIONS - These results provide evidence that cognitive performance in MDD may be associated with aberrant functional connectivity in cognitive networks and suggest patterns of alternate brain function that may support cognitive processes in MDD.
Copyright © 2018 Elsevier Ltd. All rights reserved.
The effectiveness of cognitive treatments for low back pain, a prevalent and costly condition, are commonly based on the principles of the Cognitive Behavioral Model of Fear of Movement/(Re)injury. In this model, persons with a painful injury/experience who also engage in pain catastrophizing are most likely to avoid activity leading to disability. The validation of this model in patients with acute low back is limited. The purpose of this project was to examine the relationship of perceived disability with variables identified in the Cognitive Behavioral Model of Fear of Movement/(Re)injury such as, pain severity, pain catastrophizing, depression, and exercise in persons with acute low back pain. A multiple linear regression model was used to assess the association of perceived disability with pain severity, pain catastrophizing, depression, and exercise at baseline among subjects with acute low back pain ( = 44) participating in a randomized clinical trial to prevent transition to chronic low back pain. Controlling for age, the overall model was significant for perceived disability ([5, 35] = 14.2; < .001). Higher scores of pain catastrophizing ( = .003) and pain severity ( < .001) were associated with higher perceived disability levels. Exercise and depression were not significantly associated with perceived disability. The use of the Cognitive Behavioral Model of Fear of Movement/(Re)injury in acute LBP patients is appropriate; because this model is commonly used as rationale for the effectiveness of cognitive treatments, these findings have clinical relevance in the treatment of this condition.
© 2018 Springer Publishing Company, LLC.
BACKGROUND - Late-life depression (LLD) has been associated with alterations in intrinsic functional networks, best characterized in the default mode network (DMN), cognitive control network (CCN), and salience network. However, these findings often derive from small samples, and it is not well understood how network findings relate to clinical and cognitive symptomatology.
METHODS - We studied 100 older adults (n = 79 with LLD, n = 21 nondepressed) and collected resting-state functional magnetic resonance imaging, clinical measures of depression, and performance on cognitive tests. We selected canonical network regions for each intrinsic functional network (DMN, CCN, and salience network) as seeds in seed-to-voxel analysis. We compared connectivity between the depressed and nondepressed groups and correlated connectivity with depression severity among depressed subjects. We then investigated whether the observed connectivity findings were associated with greater severity of common neuropsychiatric symptoms or poorer cognitive performance.
RESULTS - LLD was characterized by decreased DMN connectivity to the frontal pole, a CCN region (Wald χ = 22.33, p < .001). No significant group differences in connectivity were found for the CCN or salience network. However, in the LLD group, increased CCN connectivity was associated with increased depression severity (Wald χ > 20.14, p < .001), greater anhedonia (Wald χ = 7.02, p = .008) and fatigue (Wald χ = 6.31, p = .012), and poorer performance on tests of episodic memory (Wald χ > 4.65, p < .031), executive function (Wald χ = 7.18, p = .007), and working memory (Wald χ > 4.29, p < .038).
CONCLUSIONS - LLD is characterized by differences in DMN connectivity, while CCN connectivity is associated with LLD symptomology, including poorer performance in several cognitive domains.
Published by Elsevier Inc.
Substantial work associates late-life depression with hippocampal pathology. However, there is less information about differences in hippocampal subfields and other connected temporal lobe regions and how these regions may be influenced by vascular factors. Individuals aged 60 years or older with and without a DSM-IV diagnosis of Major Depressive Disorder completed clinical assessments and 3 T cranial MRI using a protocol allowing for automated measurement of medial temporal lobe subfield volumes. A subset also completed pseudo-continuous arterial spin labeling, allowing for the measurement of hippocampal cerebral blood flow. In 59 depressed and 21 never-depressed elders (mean age = 66.4 years, SD = 5.8y, range 60-86y), the depressed group did not exhibit statistically significant volumetric differences for the total hippocampus or hippocampal subfields but did exhibit significantly smaller volumes of the perirhinal cortex, specifically in the BA36 region. Additionally, age had a greater effect in the depressed group on volumes of the cornu ammonis, entorhinal cortex, and BA36 region. Finally, both clinical and radiological markers of vascular risk were associated with smaller BA36 volumes, while reduced hippocampal blood flow was associated with smaller hippocampal and cornu ammonis volumes. In conclusion, while we did not observe group differences in hippocampal regions, we observed group differences and an effect of vascular pathology on the BA36 region, part of the perirhinal cortex. This is a critical region exhibiting atrophy in prodromal Alzheimer's disease. Moreover, the observed greater effect of age in the depressed groups is concordant with past longitudinal studies reporting greater hippocampal atrophy in late-life depression.