Search

Identifying significant predictors of behavioral outcomes is of great interest in many psychological studies. Lasso regression, as an alternative to stepwise regression for variable selection, has started gaining traction among psychologists. Yet, further investigation is valuable to fully understand its performance across various psychological data conditions. Using a Monte Carlo simulation and an empirical demonstration, we compared Lasso regression to stepwise regression in typical psychological datasets varying in sample size, predictor size, sparsity, and signal-to-noise ratio. We found that: (1) Lasso regression was more accurate in within-sample selection and yielded more consistent out-of-sample prediction accuracy than stepwise regression; (2) Lasso with a harsher shrinkage parameter was more accurate, parsimonious, and robust to sampling variability than the prediction-optimizing Lasso. Finally, we concluded with cautious notes and recommendations in practice on the application of Lasso regression.

Background: Exposure to environmental pollutants early in life has been associated with increased prevalence and severity of depression in adolescents; however, the neurobiological mechanisms underlying this association are not well understood. In the current longitudinal study, we investigated whether pollution burden in early adolescence (9–13 years) was associated with altered brain activation and connectivity during implicit emotion regulation and changes in depressive symptoms across adolescence. Methods: One hundred forty-five participants (n = 87 female; 9–13 years) provided residential addresses, from which we determined their relative pollution burden at the census tract level, and performed an implicit affective regulation task in the scanner. Participants also completed questionnaires assessing depressive symptoms at 3 time points, each approximately 2 years apart, from which we calculated within-person slopes of depressive symptoms. We conducted whole-brain activation and connectivity analyses to examine whether pollution burden was associated with alterations in brain function during implicit emotion regulation of positively and negatively valenced stimuli and how these effects were related to slopes of depressive symptoms across adolescence. Results: Greater pollution burden was associated with greater bilateral medial prefrontal cortex activation and stronger bilateral medial prefrontal cortex connectivity with regions within the default mode network (e.g., temporoparietal junction, posterior cingulate cortex, precuneus) during implicit regulation of negative emotions, which was associated with greater increases in depressive symptoms across adolescence in those exposed to higher pollution burden. Conclusions: Adolescents living in communities characterized by greater pollution burden showed altered default mode network functioning during implicit regulation of negative emotions that was associated with increases in depressive symptoms across adolescence.

Early life adversity has been posited to influence the pace of structural neurodevelopment. Most research, however, has relied on cross-sectional data, which do not reveal whether the pace of neurodevelopmental change is accelerated or slowed following early exposures. In a birth cohort study that included neuroimaging data obtained at 4.5, 6, and 7.5 years of age (N = 784), we examined associations among a cumulative measure of perinatal adversity relative to resources, nonlinear trajectories of hippocampal and amygdala volume, and children’s subsequent depressive symptoms at 8.5 years of age. Greater adversity was associated with reduced bilateral hippocampal body volume in early childhood, but also to faster growth in the right hippocampal body across childhood. Further, the association between adversity and childhood depressive symptoms was mediated by faster hippocampal body growth. These findings suggest that perinatal adversity is biologically embedded in hippocampal structure development, including an accelerated pace of change in the right hippocampal body that is implicated in children’s psychopathology risk. In addition, our findings suggest that reduced hippocampal volume is not inconsistent with accelerated hippocampal change; these aspects of structural development may typically co-occur, as smaller regional volumes in early childhood were associated with faster growth across childhood.

Abstract Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.

Background: Neighborhood- or area-level socioeconomic disadvantage is associated with neural alterations across the life span. However, few studies have examined the effects of neighborhood disadvantage on white matter microstructure during adolescence, an important period of development that coincides with increased risk for psychopathology. Methods: In 200 adolescents (ages 13–20 years; 54.5% female, 4% nonbinary) recruited from 2 studies enriched for early adversity and depression, we examined whether neighborhood socioeconomic disadvantage derived from census tract data was related to white matter microstructure in several major white matter tracts. We also examined whether depressive symptoms and sex moderated these associations. Results: Greater neighborhood socioeconomic disadvantage was associated with lower fractional anisotropy (FA) in the left arcuate fasciculus (β = −0.24, false discovery rate [FDR]–corrected p = .035) and right uncinate fasciculus (β = −0.32, FDR-corrected p = .002) above and beyond the effects of family-level socioeconomic status. Depressive symptoms significantly moderated the association between left arcuate fasciculus FA and both neighborhood (β = 0.17, FDR-corrected p = .026) and unemployment (β = 0.22, FDR-corrected p = .004) disadvantage such that these associations were only significant in adolescents who reported less severe depression. Sex did not moderate the association between socioeconomic disadvantage and FA in these tracts. Conclusions: Greater neighborhood socioeconomic disadvantage, particularly poverty and educational attainment levels, was associated with lower FA in the arcuate fasciculus and uncinate fasciculus above and beyond the effects of family-level measures of socioeconomic status. These patterns were only observed in adolescents with low levels of depression, suggesting that we must be cautious about generalizing these findings to youths who struggle with mental health difficulties.

Introduction: Parenting behaviors are formative to the psychological development of young people; however, parent and adolescent perceptions of parenting are only moderately correlated with each other. Whereas discrepant perceptions may represent a normative process of deindividuation from caregivers in some adolescents, in others a discrepancy might predict psychological maladjustment. The biological sensitivity to context model provides a framework from which individual differences in development can be estimated in adolescents whose perceptions of parenting diverge from those of their parents. Methods: At baseline we obtained diurnal cortisol samples from US adolescents (M = 13.37 years of age, SD = 1.06) as well as parents' and adolescents’ ratings of parental warmth; we obtained adolescent-reported symptoms of psychopathology at baseline and again at follow-up two years later (N = 108, 57.5% female). We estimated waking cortisol, cortisol awakening response, and daytime cortisol slopes using piecewise regression models. Results: Lower adolescent than parent ratings of parental warmth predicted increased externalizing symptoms at follow-up. Higher waking cortisol and steeper cortisol awakening response and daytime slopes predicted increased internalizing symptoms at follow-up. Further, discrepant ratings of parental warmth interacted with cortisol awakening response and daytime slopes such that greater discrepancies predicted greater increases in externalizing symptoms in adolescents with steeper cortisol slopes. Conclusions: These findings indicate that steeper changes in cortisol production throughout the day index a greater sensitivity to perceived parental warmth. Lower adolescent than parent ratings of parental warmth may represent dysfunction in the parental relationship rather than a normative process of deindividuation in adolescents with steeper diurnal cortisol slopes.

Adolescence is often characterized by sleep disturbances that can affect the development of white matter tracts implicated in affective and cognitive regulation, including the cingulate portion of the cingulum bundle (CGC) and the uncinate fasciculus (UF). These effects may be exacerbated in adolescents exposed to early life adversity (ELA). We examined the longitudinal relations between sleep problems and CGC and UF microstructure during adolescence and their relation to depressive symptoms as a function of exposure to ELA. We assessed self-reported sleep disturbances and depressive symptoms and acquired diffusion-weighted MRI scans twice: in early adolescence (9–13 years) and four years later (13–17 years) (N = 72 complete cases). Independent of ELA, higher initial levels and increases in sleep problems were related to increases in depressive symptoms. Further, increases in right CGC fractional anisotropy (FA) mediated the association between sleep problems and depressive symptoms for youth who experienced lower, but not higher, levels of ELA. In youth with higher ELA, higher initial levels of and steeper decreases in sleep problems were associated with greater decreases in right UF FA, but were unrelated to depressive symptoms. Our findings highlight the importance of sleep quality in shaping fronto-cingulate-limbic tract development and depressive symptoms during adolescence.

Abstract Background Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states. Methods We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants. Results We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites. Conclusion We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project.

Abstract Background Short leukocyte telomere length is a biomarker associated with stress and morbidity in non-pregnant adults. Little is known, however, about maternal telomere dynamics in pregnancy. To address this, we examined changes in maternal leukocyte telomere length (LTL) during uncomplicated pregnancies and explored correlations with perceived stress. Methods In this pilot study, maternal LTL was measured in blood collected from nulliparas who delivered live, term, singleton infants between 2012 and 2018 at a single institution. Participants were excluded if they had diabetes or hypertensive disease. Samples were collected over the course of pregnancy and divided into three time periods:

Abstract The impact of COVID-19-related stress on perinatal women is of heightened public health concern given the established intergenerational impact of maternal stress-exposure on infants and fetuses. There is urgent need to characterize the coping styles associated with adverse psychosocial outcomes in perinatal women during the COVID-19 pandemic to help mitigate the potential for lasting sequelae on both mothers and infants. This study uses a data-driven approach to identify the patterns of behavioral coping strategies that associate with maternal psychosocial distress during the COVID-19 pandemic in a large multicenter sample of pregnant women (N = 2876) and postpartum women (N = 1536). Data was collected from 9 states across the United States from March to October 2020. Women reported behaviors they were engaging in to manage pandemic-related stress, symptoms of depression, anxiety and global psychological distress, as well as changes in energy levels, sleep quality and stress levels. Using latent profile analysis, we identified four behavioral phenotypes of coping strategies. Critically, phenotypes with high levels of passive coping strategies (increased screen time, social media, and intake of comfort foods) were associated with elevated symptoms of depression, anxiety, and global psychological distress, as well as worsening stress and energy levels, relative to other coping phenotypes. In contrast, phenotypes with high levels of active coping strategies (social support, and self-care) were associated with greater resiliency relative to other phenotypes. The identification of these widespread coping phenotypes reveals novel behavioral patterns associated with risk and resiliency to pandemic-related stress in perinatal women. These findings may contribute to early identification of women at risk for poor long-term outcomes and indicate malleable targets for interventions aimed at mitigating lasting sequelae on women and children during the COVID-19 pandemic.

Psychosocial and stress-related factors (PSFs), defined as internal or external stimuli that induce biological changes, are potentially modifiable factors and accessible targets for interventions that are associated with adverse pregnancy outcomes (APOs). Although individual APOs have been shown to be connected to PSFs, they are biologically interconnected, relatively infrequent, and therefore challenging to model. In this context, multi-task machine learning (MML) is an ideal tool for exploring the interconnectedness of APOs on the one hand and building on joint combinatorial outcomes to increase predictive power on the other hand. Additionally, by integrating single cell immunological profiling of underlying biological processes, the effects of stress-based therapeutics may be measurable, facilitating the development of precision medicine approaches.ObjectivesThe primary objectives were to jointly model multiple APOs and their connection to stress early in pregnancy, and to explore the underlying biology to guide development of accessible and measurable interventions.Materials and MethodsIn a prospective cohort study, PSFs were assessed during the first trimester with an extensive self-filled questionnaire for 200 women. We used MML to simultaneously model, and predict APOs (severe preeclampsia, superimposed preeclampsia, gestational diabetes and early gestational age) as well as several risk factors (BMI, diabetes, hypertension) for these patients based on PSFs. Strongly interrelated stressors were categorized to identify potential therapeutic targets. Furthermore, for a subset of 14 women, we modeled the connection of PSFs to the maternal immune system to APOs by building corresponding ML models based on an extensive single cell immune dataset generated by mass cytometry time of flight (CyTOF).ResultsJointly modeling APOs in a MML setting significantly increased modeling capabilities and yielded a highly predictive integrated model of APOs underscoring their interconnectedness. Most APOs were associated with mental health, life stress, and perceived health risks. Biologically, stressors were associated with specific immune characteristics revolving around CD4/CD8 T cells. Immune characteristics predicted based on stress were in turn found to be associated with APOs.ConclusionsElucidating connections among stress, multiple APOs simultaneously, and immune characteristics has the potential to facilitate the implementation of ML-based, individualized, integrative models of pregnancy in clinical decision making. The modifiable nature of stressors may enable the development of accessible interventions, with success tracked through immune characteristics.

Background: Several studies have evaluated whether depressed persons have older appearing brains than their nondepressed peers. However, the estimated neuroimaging-derived “brain age gap” has varied from study to study, likely driven by differences in training and testing sample (size), age range, and used modality/features. To validate our previously developed ENIGMA brain age model and the identified brain age gap, we aim to replicate the presence and effect size estimate previously found in the largest study in depression to date (N = 2126 controls & N = 2675 cases; +1.08 years [SE 0.22], Cohen's d = 0.14, 95% CI: 0.08–0.20), in independent cohorts that were not part of the original study. Methods: A previously trained brain age model (www.photon-ai.com/enigma_brainage) based on 77 FreeSurfer brain regions of interest was used to obtain unbiased brain age predictions in 751 controls and 766 persons with depression (18–75 years) from 13 new cohorts collected from 20 different scanners. Meta-regressions were used to examine potential moderating effects of basic cohort characteristics (e.g., clinical and scan technical) on the brain age gap. Results: Our ENIGMA MDD brain age model generalized reasonably well to controls from the new cohorts (predicted age vs. age: r = 0.73, R2 = 0.47, MAE = 7.50 years), although the performance varied from cohort to cohort. In these new cohorts, on average, depressed persons showed a significantly higher brain age gap of +1 year (SE 0.35) (Cohen's d = 0.15, 95% CI: 0.05–0.25) compared with controls, highly similar to our previous finding. Significant moderating effects of FreeSurfer version 6.0 (d = 0.41, p = 0.007) and Philips scanner vendor (d = 0.50, p 3400 patients and >2800 controls worldwide show reliable but subtle effects of brain aging in adult depression. Future studies are needed to identify factors that may further explain the brain age gap variance between cohorts.

Abstract Major depressive disorder (MDD) is associated with abnormal neural circuitry. It can be measured by assessing functional connectivity (FC) at resting-state functional MRI, that may help identifying neural markers of MDD and provide further efficient diagnosis and monitor treatment outcomes. The main aim of the present study is to investigate, in an unbiased way, functional alterations in patients with MDD using a large multi-center dataset from the PsyMRI consortium including 1546 participants from 19 centers ( www.psymri.com ). After applying strict exclusion criteria, the final sample consisted of 606 MDD patients (age: 35.8 ± 11.9 y.o.; females: 60.7%) and 476 healthy participants (age: 33.3 ± 11.0 y.o.; females: 56.7%). We found significant relative hypoconnectivity within somatosensory motor (SMN), salience (SN) networks and between SMN, SN, dorsal attention (DAN), and visual (VN) networks in MDD patients. No significant differences were detected within the default mode (DMN) and frontoparietal networks (FPN). In addition, alterations in network organization were observed in terms of significantly lower network segregation of SMN in MDD patients. Although medicated patients showed significantly lower FC within DMN, FPN, and SN than unmedicated patients, there were no differences between medicated and unmedicated groups in terms of network organization in SMN. We conclude that the network organization of cortical networks, involved in processing of sensory information, might be a more stable neuroimaging marker for MDD than previously assumed alterations in higher-order neural networks like DMN and FPN.

Background: Leukocyte telomere length (LTL) is a biomarker that is affected by older age, psychosocial stress, and medical comorbidities. Despite the relevance of these factors to obstetric practice, little is known about LTL in pregnancy. Our study explored longitudinal LTL dynamics in pregnant and non-pregnant people. Objective: This pilot study compares changes in LTL between pregnant and non-pregnant people over time, explores potential correlations between LTL and mental health measures, and investigates associations between short first-trimester LTL and adverse pregnancy outcomes. Study design: This was a prospective pilot cohort study of nulliparous pregnant and non-pregnant people between ages 18 and 50 who presented for care at a single institution from January to November 2020. Pregnant people were enrolled between 10 and 14 weeks gestation. Participants had two blood samples drawn for LTL; the first on the day of enrollment and the second on postpartum day 1 (pregnant cohort) or 7 months later (non-pregnant cohort). LTL was measured using quantitative PCR. The primary outcome was the difference between pregnant and non-pregnant people in LTL change between the two timepoints (basepair difference per 30-day period). Secondary outcomes included differences in responses to the Patient Health Questionnaire-9 (PHQ-9) and a survey about stress related to COVID-19. Differences in LTL were tested using t-tests and linear regression models, both crude and adjusted for age. A subgroup analysis was conducted within the pregnant cohort to examine whether shorter first-trimester LTL was associated with adverse pregnancy outcomes. We conducted t-tests to compare LTL between people with and without each categorical outcome and computed Pearson correlation coefficients between LTL and continuous outcomes such as gestational age at delivery. Results: 46 pregnant and 30 non-pregnant people were enrolled; 44 pregnant and 18 non-pregnant people completed all LTL assessments. There were no between-group differences in LTL change (−4.2 ± 22.2 bp per 30 days pregnant versus −6.4 ± 11.2 bp per 30 days non-pregnant, adjusted beta 2.1, 95% CI -9.0-13.2, p = 0.60). The prevalence of depression and pandemic-related stress were both low overall. The two groups did not differ in PHQ-9 scores, and no correlations were significant between LTL and PHQ-9 scores. Among the 44 pregnant people, shorter first-trimester LTL was significantly correlated with earlier gestational age at delivery (r = 0.35, p = 0.02). Conclusion: In this exploratory pilot cohort of reproductive-aged people with low levels of psychological stress, we described baseline changes in LTL over time in pregnant and non-pregnant participants. We found a correlation between shorter first-trimester LTL and earlier gestational age at delivery, which warrants further investigation in a larger cohort.

Abstract The transition from suicidal ideas to a suicide act is an important topic of research for the identification of those patients at risk of acting out. We investigated here whether specific brain activity and connectivity measures at rest may be differently associated with suicidal thoughts and behaviors. A large sample of acutely depressed patients with major depressive disorder was recruited in three different centers (Montreal/Canada, Stanford/USA, and Jena/Germany), covering four different phenotypes: patients with a past history of suicide attempt (n = 53), patients with current suicidal ideas but no past history of suicide attempt (n = 40), patients without current suicidal ideation nor past suicide attempts (n = 42), and healthy comparison subjects (n = 107). 3-T resting-state functional magnetic resonance imaging (fMRI) measures of the amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC) were obtained and examined in a whole-brain data-driven analysis. Past suicide attempt was associated with a double cortico-subcortical dissociation in ALFF values. Decreased ALFF and DC values mainly in a frontoparietal network and increased ALFF values in some subcortical regions (hippocampus and thalamus) distinguished suicide attempters from suicide ideators, patient controls, and healthy controls. No clear neural differences were identified in relation to suicidal ideas. Suicide attempters appear to be a distinct subgroup of patients with widespread brain alterations in functional activity and connectivity that could represent factors of vulnerability. Our results also indirectly support at the neurobiological level the relevance of the transition model described at the psychological and clinical levels. The brain bases of suicidal ideas occurrence in depressed individuals needs further investigations.

Abstract Suicidal ideation (SI) and non-suicidal self-injury (NSSI) are two distinct yet often co-occurring risk factors for suicide deaths in adolescents. Elucidating the neurobiological patterns that specifically characterize SI and NSSI in adolescents is needed to inform the use of these markers in intervention studies and to develop brain-based treatment targets. Here, we clinically assessed 70 adolescents—49 adolescents with depression and 21 healthy controls—to determine SI and NSSI history. Twenty-eight of the depressed adolescents had a history of SI and 29 had a history of NSSI (20 overlapping). All participants underwent a resting-state fMRI scan. We compared groups in network coherence of subdivisions of the central executive network (CEN), default mode network (DMN), and salience network (SN). We also examined group differences in between-network connectivity and explored brain-behavior correlations. Depressed adolescents with SI and with NSSI had lower coherence in the ventral DMN compared to those without SI or NSSI, respectively, and healthy controls (all ps

Abstract It has been difficult to find robust brain structural correlates of the overall severity of major depressive disorder (MDD). We hypothesized that specific symptoms may better reveal correlates and investigated this for the severity of insomnia, both a key symptom and a modifiable major risk factor of MDD. Cortical thickness, surface area and subcortical volumes were assessed from T1-weighted brain magnetic resonance imaging (MRI) scans of 1053 MDD patients (age range 13-79 years) from 15 cohorts within the ENIGMA MDD Working Group. Insomnia severity was measured by summing the insomnia items of the Hamilton Depression Rating Scale (HDRS). Symptom specificity was evaluated with correlates of overall depression severity. Disease specificity was evaluated in two independent samples comprising 2108 healthy controls, and in 260 clinical controls with bipolar disorder. Results showed that MDD patients with more severe insomnia had a smaller cortical surface area, mostly driven by the right insula, left inferior frontal gyrus pars triangularis, left frontal pole, right superior parietal cortex, right medial orbitofrontal cortex, and right supramarginal gyrus. Associations were specific for insomnia severity, and were not found for overall depression severity. Associations were also specific to MDD; healthy controls and clinical controls showed differential insomnia severity association profiles. The findings indicate that MDD patients with more severe insomnia show smaller surfaces in several frontoparietal cortical areas. While explained variance remains small, symptom-specific associations could bring us closer to clues on underlying biological phenomena of MDD.

Abstract Background Females are at higher risk for developing depression during adolescence than are males, particularly during exposure to stressors like the COVID‐19 pandemic. Examining structural connections between brain regions involved in executive functioning may advance our understanding of sex biases in stress and depression. Here, we examined the role of the cingulum bundle in differentiating trajectories of depressive symptoms in males and females across adolescence and during the pandemic. Methods In a longitudinal study of 214 youth (121 females; ages 9–13 years at baseline), we examined whether fixel‐based properties of the cingulum bundle at baseline predict changes in females' and males' severity of depressive symptoms across four timepoints (4–7 years) in adolescence, including during the COVID‐19 pandemic. We also tested whether cingulum properties predict self‐reported resilience and stress during the pandemic. Results Females had lower fiber density and cross‐section (FDC) of the cingulum than did males, a neural pattern that predicted greater increases in depressive symptoms, lower resilience, and higher stress during the COVID‐19 pandemic. Cingulum morphometry predicted changes in depressive trajectories in females, but not in males; specifically, females with lower FDC had significant increases in symptoms throughout adolescence, whereas females with higher cingulum FDC did not. Conversely, males had low, stable depressive symptoms throughout adolescence and higher resilience and lower stress during the pandemic compared to females. Higher cingulum FDC predicted higher resilience and lower stress in both sexes. Conclusions In adults, the cingulum has been implicated in sex differences in stress reactivity. We show that in adolescents, the cingulum reflects sex differences in reports of stress and resilience that might contribute to the increased risk of stress‐related mood disorders in females. Adolescent females might benefit from cognitive interventions that strengthen the structural properties of the cingulum and increase their perceived resilience during periods of adversity and disruption.

Women experience dramatic physiological changes during pregnancy, including changes in the production of the “stress hormone,” cortisol. Evidence has been mixed regarding whether hair cortisol concentration (HCC) can be used to accurately capture the trajectory of cortisol during this period and whether factors related to psychosocial stress are related to HCC in pregnant and postpartum women. In the current study, we collected hair samples from 85 individuals during the peripartum period (with collection occasions in pregnancy [12–37 weeks], at 3–8 weeks postpartum, and at 5–8 months postpartum) from which we derived 783 monthly observations of HCC. In addition, at each assessment individuals reported their current depressive symptoms and experiences of recent psychosocial adversity. Using piecewise mixed effects modeling, we identified significant increases in HCC across pregnancy (approximately a 2-fold rise) followed by significant decreases in HCC postpartum. Beyond these effects, however, there was substantial within-individual variability in HCC. Disaggregating between- from within-individual associations of depressive symptoms and adversity with HCC, we found that within-individual fluctuations in adversity were positively coupled with levels of HCC. Overall, the current findings suggest that measurement of cortisol in human hair captures its trajectory from conception through six months postpartum, including prenatal increases and gradual recovery of typical levels following childbirth. In addition to the overall severity of psychosocial adversity, change in women's experiences of adversity during the peripartum period merit attention.

In this paper we provide an overview of the rationale, methods, and preliminary results of the four Connectome Studies Related to Human Disease investigating mood and anxiety disorders. The first study, “Dimensional connectomics of anxious misery” (HCP-DAM), characterizes brain-symptom relations of a transdiagnostic sample of anxious misery disorders. The second study, “Human connectome Project for disordered emotional states” (HCP-DES), tests a hypothesis-driven model of brain circuit dysfunction in a sample of untreated young adults with symptoms of depression and anxiety. The third study, “Perturbation of the treatment resistant depression connectome by fast-acting therapies” (HCP-MDD), quantifies alterations of the structural and functional connectome as a result of three fast-acting interventions: electroconvulsive therapy, serial ketamine therapy, and total sleep deprivation. Finally, the fourth study, “Connectomes related to anxiety and depression in adolescents” (HCP-ADA), investigates developmental trajectories of subtypes of anxiety and depression in adolescence.The four projects use comparable and standardized Human Connectome Project magnetic resonance imaging (MRI) protocols, including structural MRI, diffusion-weighted MRI, and both task and resting state functional MRI. All four projects also conducted comprehensive and convergent clinical and neuropsychological assessments, including (but not limited to) demographic information, clinical diagnoses, symptoms of mood and anxiety disorders, negative and positive affect, cognitive function, and exposure to early life stress. The first round of analyses conducted in the four projects offered novel methods to investigate relations between functional connectomes and self-reports in large datasets, identified new functional correlates of symptoms of mood and anxiety disorders, characterized the trajectory of connectome-symptom profiles over time, and quantified the impact of novel treatments on aberrant connectivity.Taken together, the data obtained and reported by the four Connectome Studies Related to Human Disease investigating mood and anxiety disorders describe a rich constellation of convergent biological, clinical, and behavioral phenotypes that span the peak ages for the onset of emotional disorders. These data are being prepared for open sharing with the scientific community following screens for quality by the Connectome Coordinating Facility (CCF). The CCF also plans to release data from all projects that have been pre-processed using identical state-of-the-art pipelines. The resultant dataset will give researchers the opportunity to pool complementary data across the four projects to study circuit dysfunctions that may underlie mood and anxiety disorders, to map cohesive relations among circuits and symptoms, and to probe how these relations change as a function of age and acute interventions. This large and combined dataset may also be ideal for using data-driven analytic approaches to inform neurobiological targets for future clinical trials and interventions focused on clinical or behavioral outcomes.

Background Mental disorders are currently the greatest global health burden. The coronavirus diseases 2019 (COVID-19) pandemic is having an adverse impact on people's mental health, particularly in vulnerable populations, such as refugees. Aims The present study was designed to examine the association between COVID-19 and changes in mental health in Syrian refugees in Turkey. Method We conducted a two-wave panel survey of a representative sample of 302 of the estimated 500 000 Syrian refugees (ages 18 and older) living under humanitarian support in Istanbul (first wave between 9 and 15 July 2020 and the follow-up between 11 and 14 September 2020). We administered seven items from the CoRonavIruS Health Impact Survey in addition to one-context specific item about life changes because of COVID-19, and measures of depression (10-item Center for Epidemiologic Study Depression Scale, CESD-10), anxiety (6-item State-Trait Anxiety Inventory, STAI-6) and perceived stress (Perceived Stress Scale, PSS-4). Results A factor analysis yielded three COVID-19 factors, labelled ‘social relationships’, ‘stress’ and ‘hope.’ We conducted a series of cross-lag panel analyses to test associations between the COVID-19 factors and mental health. We found associations between all COVID-19 factors and CESD-10, between COVID-19 ‘stress’ and STAI-6, and between COVID-19 ‘stress’ and COVID-19 ‘hope’ and PSS-4. Conclusions Our measures of life changes because of the COVID-19 pandemic are associated with changes in the mental health of Syrian refugees living in Istanbul. It is therefore important that they are provided with services to reduce what may be particularly debilitating consequences of COVID-19.

Animal models of stress and related conditions, including depression, have shown that elevated peripheral levels of inflammatory cytokines have downstream consequences on glutamate (Glu) in the brain. Although studies in human adults with depression have reported evidence of higher inflammation but lower Glu in the anterior cingulate cortex (ACC), the extent to which peripheral inflammation contributes to glutamatergic abnormalities in adolescents with depression is not well-understood. It is also unclear whether antioxidants, such as ascorbate (Asc), may buffer against the effects of inflammation on Glu metabolism. Fifty-five depressed adolescents were recruited in the present cross-sectional study and provided blood samples, from which we assayed pro-inflammatory cytokines, and underwent a short-TE proton magnetic spectroscopy scan at 3T, from which we estimated Glu and Asc in the dorsal ACC. In the 31 adolescents with usable cytokine and Glu data, we found that IL-6 was significantly positively associated with dorsal ACC Glu (β = 0.466 ± 0.199, p = 0.029). Of the 16 participants who had usable Asc data, we found that at higher levels of dorsal ACC Asc, there was a negative association between IL-6 and Glu (interaction effect: β = −0.906 ± 0.433, p = 0.034). Importantly, these results remained significant when controlling for age, gender, percentage of gray matter in the dorsal ACC voxel, BMI, and medication (antidepressant and anti-inflammatory) usage. While preliminary, our results underscore the importance of examining both immune and neural contributors to depression and highlight the potential role of anti-inflammatory compounds in mitigating the adverse effects of inflammation (e.g., glutamatergic neuroexcitotoxicity). Future studies that experimentally manipulate levels of inflammation, and of ascorbate, and that characterize these effects on cortical glutamate concentrations and subsequent behavior in animals and in humans are needed.

Researchers have reported sex-differentiated maturation of white matter (WM) during puberty. It is not clear, however, whether such distinctions contribute to documented sex differences in sensitivity to reward and punishment during adolescence. Given the role of the orbitofrontal cortex (OFC) and nucleus accumbens (NAcc) in reward and punishment-related behaviors, we tested in a cross-sectional study whether males and females (N = 156, 89 females; ages 9–14 years) differ in the association between pubertal stage and fixel-based morphometry of WM fibers connecting the OFC and NAcc (i.e., the fronto-accumbal tract). Further, we examined whether males and females differ in associations between fronto-accumbal WM measures and self-reported sensitivity to reward and punishment. Pubertal stage was positively associated with fronto-accumbal fiber density and cross-section (FDC) in males, but not in females. Consistent with previous reports, males reported higher reward sensitivity than did females, although fronto-accumbal combined FDC was not related to reward sensitivity in either sex. Meanwhile, only males showed a negative association between fronto-accumbal tract FDC and sensitivity to punishment. Follow-up analyses revealed that fiber cross-section, but not density, was related to pubertal stage and punishment sensitivity in males, as well as to reward sensitivity in all participants. Our findings suggest there are sex differences in puberty-related maturation of the fronto-accumbal tract, and this tract is related to lower punishment sensitivity in adolescent males compared to females.

The motivation to approach or avoid incentives can change during adolescence. Advances in neuroimaging allow researchers to characterize specific brain circuits that underlie these developmental changes. Whereas activity in the nucleus accumbens (NAcc) can predict approach toward incentive gain, activity in anterior insula (AIns) is associated with avoidance of incentive loss. Recent research characterized the structural white-matter tract connecting the two brain regions, but the tract has neither been characterized in adolescence nor linked to functional activity during incentive anticipation. In this study, we collected diffusion MRI and characterized the tract connecting the AIns to the NAcc for the first time in early adolescents. We then measured NAcc functional activity during a monetary incentive delay task and found that structural coherence of the AIns-NAcc tract is correlated with decreased functional activity at the NAcc terminal of the tract during anticipation of no incentives. In adolescents who completed an assessment 2 years later, we found that AIns-NAcc tract coherence could predict greater future self-reported motivation, and that NAcc functional activity could statistically mediate this association. Together, the findings establish links from brain structure to function to future motivation and provide targets to study the reciprocal development of brain structure and function.

Early life stress (ELS) is associated with increased risk for internalizing disorders and variations in gray matter development. It is unclear, however, whether ELS affects normative age-related changes in white matter (WM) morphology, and if such maturational differences are associated with risk for internalizing psychopathology. We conducted comprehensive interviews in a cross-sectional sample of young adolescents (N = 156; 89 F; Ages 9–14) to assess lifetime exposure to stress and objective cumulative ELS severity. We used diffusion-weighted imaging to measure WM fixel-based morphometry and tested the effects of age and ELS on WM fiber density and cross-section (FDC), and associations between WM FDC and internalizing problems. Age was positively associated with FDC in all WM tracts; greater ELS severity was related to stronger age-WM associations in several association tracts connecting the frontal lobes with limbic, parietal, and occipital regions, including bilateral superior and inferior longitudinal and uncinate fasciculi (UF). Among older adolescents with greater ELS severity, a higher UF FDC was associated with fewer internalizing problems. Greater ELS severity predicted more mature WM morphometry in tracts implicated in emotion regulation and cognitive processing. More phenotypically mature UF WM may be adaptive against internalizing psychopathology in adolescents exposed to ELS.

BackgroundExposure to early life stress (ELS) is alarmingly prevalent and has been linked to the high rates of depression documented in adolescence. Researchers have theorized that ELS may increase adolescents’ vulnerability or reactivity to the effects of subsequent stressors, placing them at higher risk for developing symptoms of depression.MethodsWe tested this formulation in a longitudinal study by assessing levels of stress and depression during the COVID-19 pandemic in a sample of adolescents from the San Francisco Bay Area (N = 109; 43 male; ages 13–20 years) who had been characterized 3–7 years earlier (M = 5.06, SD = 0.86 years) with respect to exposure to ELS and symptoms of depression.ResultsAs expected, severity of ELS predicted levels of depressive symptoms during the pandemic [r(107) = 0.26, p = 0.006], which were higher in females than in males [t(107) = −3.56, p < 0.001]. Importantly, the association between ELS and depression was mediated by adolescents’ reported levels of stress, even after controlling for demographic variables.ConclusionsThese findings underscore the importance of monitoring the mental health of vulnerable children and adolescents during this pandemic and targeting perceived stress in high-risk youth.

Research suggests that exposure to fine particulate air pollution (PM2.5) increases hypothalamic-pituitary-adrenal (HPA) axis activation in adults; it is unclear, however, whether PM2.5 is associated with HPA-axis functioning in psychosocial contexts, such as during the experience of social stress. One recent study of adolescents found that PM2.5 was associated with heightened autonomic reactivity to a social stress task, and that this association was strongest for adolescents with more severe internalizing symptoms. Here, we sought to replicate and extend these findings to HPA-axis stress responsivity in an independent sample of adolescent girls (N ​= ​130). We estimated PM2.5 concentrations at each participant’s address using data from nearby air quality monitoring stations, and assessed participants’ anxiety symptoms. We measured salivary cortisol in response to a social stress task and characterized HPA-axis functioning by computing area under the curve with respect to ground (AUCg) and with respect to increase (AUCi). Controlling for demographic factors, we found that PM2.5 was associated with heightened HPA-axis stress responsivity (both AUCg and AUCi) for girls who reported more severe levels of anxiety. We did not find a main effect of PM2.5 on HPA-axis functioning. These findings suggest that anxious adolescents are particularly vulnerable to the adverse effects of PM2.5 exposure on biological sensitivity to social stress.

This article provides an overview of the study protocol for the Teen Inflammation Glutamate Emotion Research (TIGER) project, a longitudinal study in which we plan to recruit 60 depressed adolescents (ages 13–18 years) and 30 psychiatrically healthy controls in order to examine the inflammatory and glutamatergic pathways that contribute to the recurrence of depression in adolescents. TIGER is the first study to examine the effects of peripheral inflammation on neurodevelopmental trajectories by assessing changes in cortical glutamate in depressed adolescents. Here, we describe the scientific rationale, design, and methods for the TIGER project. This article is intended to serve as an introduction to this project and to provide details for investigators who may be seeking to replicate or extend these methods for other related research endeavors.

Deviations in neurodevelopment may underlie the association between lower childhood socioeconomic status and difficulties in cognitive and socioemotional domains. Most previous investigations of the association between childhood socioeconomic status and brain morphology have used cross-sectional designs with samples that span wide age ranges, occluding effects specific to adolescence. Sex differences in the association between socioeconomic status and neurodevelopment may emerge or intensify during adolescence. In a sample representative of the San Francisco Bay Area, we used whole-brain tensor-based morphometry to examine sex differences in the cross-sectional association between variation in family income-to-needs ratio (INR) and cortical and subcortical gray and white matter volume during early adolescence (ages 9–13 years; N = 147), as well as in the longitudinal association between INR and change in volume from early to later adolescence (ages 11–16 years, N = 109). Biological sex interacted with INR to explain variation in volume in several areas cross-sectionally and longitudinally. Effects were primarily in cortical gray matter areas, including regions of the association cortex and sensorimotor processing areas. Effect sizes tended to be larger in boys than in girls. Biological sex may be an important variable to consider in analyses of the effects of family income on structural neurodevelopment during adolescence.

Through the Human Connectome Project (HCP) our understanding of the functional connectome of the healthy brain has been dramatically accelerated. Given the pressing public health need, we must increase our understanding of how connectome dysfunctions give rise to disordered mental states. Mental disorders arising from high levels of negative emotion or from the loss of positive emotional experience affect over 400 million people globally. Such states of disordered emotion cut across multiple diagnostic categories of mood and anxiety disorders and are compounded by accompanying disruptions in cognitive function. Not surprisingly, these forms of psychopathology are the leading cause of disability worldwide. The Research Domain Criteria (RDoC) initiative spearheaded by NIMH offers a framework for characterizing the relations among connectome dysfunctions, anchored in neural circuits and phenotypic profiles of behavior and self-reported symptoms. Here, we report on our Connectomes Related to Human Disease protocol for integrating an RDoC framework with HCP protocols to characterize connectome dysfunctions in disordered emotional states, and present quality control data from a representative sample of participants. We focus on three RDoC domains and constructs most relevant to depression and anxiety: 1) loss and acute threat within the Negative Valence System (NVS) domain; 2) reward valuation and responsiveness within the Positive Valence System (PVS) domain; and 3) working memory and cognitive control within the Cognitive System (CS) domain. For 29 healthy controls, we present preliminary imaging data: functional magnetic resonance imaging collected in the resting state and in tasks matching our constructs of interest (“Emotion”, “Gambling” and “Continuous Performance” tasks), as well as diffusion-weighted imaging. All functional scans demonstrated good signal-to-noise ratio. Established neural networks were robustly identified in the resting state condition by independent component analysis. Processing of negative emotional faces significantly activated the bilateral dorsolateral prefrontal and occipital cortices, fusiform gyrus and amygdalae. Reward elicited a response in the bilateral dorsolateral prefrontal, parietal and occipital cortices, and in the striatum. Working memory was associated with activation in the dorsolateral prefrontal, parietal, motor, temporal and insular cortices, in the striatum and cerebellum. Diffusion tractography showed consistent profiles of fractional anisotropy along known white matter tracts. We also show that results are comparable to those in a matched sample from the HCP Healthy Young Adult data release. These preliminary data provide the foundation for acquisition of 250 subjects who are experiencing disordered emotional states. When complete, these data will be used to develop a neurobiological model that maps connectome dysfunctions to specific behaviors and symptoms.

Adolescence is characterized by rapid brain development in white matter (WM) that is attributed in part to surges in gonadal hormones. To date, however, there have been few longitudinal investigations relating changes in gonadal hormones and WM development in adolescents. We acquired diffusion-weighted MRI to estimate mean fractional anisotropy (FA) from 10 WM tracts and salivary testosterone from 51 females and 29 males (ages 9–14 years) who were matched on pubertal stage and followed, on average, for 2 years. We tested whether interactions between sex and changes in testosterone levels significantly explained changes in FA. We found positive associations between changes in testosterone and changes in FA within the corpus callosum, cingulum cingulate, and corticospinal tract in females (all ps

Children from lower-SES families exhibit smaller hippocampal volume than do their higher-SES peers. Few studies, however, have compared hippocampal developmental trajectories as a function of SES. Thus, it is unclear whether initial rank-order stability is preserved, or whether volumes diverge/converge over the course of adolescence. In a sample of 101 girls ages 10–24 years, we examined the longitudinal association between family income and parental education, proxies for SES, and changes in hippocampal volume. Hippocampal volume was obtained using MRI; using mixed modeling, we examined the effects of income and education on hippocampal volume across age. As expected, changes in volume were non-linear across development. Further, trajectories diverged in mid-adolescence, with lower-income girls exhibiting reductions in hippocampal volume. Maximal income-related differences were observed at 18 years, and trajectories converged thereafter. This interaction remained significant when accounting for maternal hippocampal volume, suggesting a unique contribution of environment over potential heritable differences. In contrast, the association between parental education and offspring hippocampal volume appeared to be stable across adolescence, with higher levels of parental education predicting consistently larger hippocampal volume. These findings constitute preliminary evidence that girls from lower-income homes exhibit unique trajectories of hippocampal growth, with differences most evident in late adolescence. Keywords: Adolescence, Adversity, Environmental influences, Family factors, Socioeconomic status

Exposure to stress, particularly in periods of rapid brain maturation such as adolescence, can profoundly influence developmental processes that undergird the organization of structural and functional brain networks and that may mediate the association between stressful experiences and maladaptive outcomes. While studies in translational developmental neuroscience often focus on how specific brain regions or targeted connections are altered by stress and psychiatric disease, the emerging field of network science may be especially valuable for elucidating the impact of stress on the intricate connectomics of the adolescent brain. Here we review recent studies that use graph theory and other network science approaches to understand normative adolescent brain development, effects of childhood maltreatment on the brain, and disorders characterized by pathological responses to stress in adolescents. Overall, these studies demonstrate that graph theory can be useful in identifying and quantifying developmental processes related to segregation, integration, and localized hub influence that are affected by stress exposure and that may lead to psychopathology. Finally, we discuss limitations in the current application of graph theory in this area and suggest what we believe are important directions for future work. Keywords: Graph theory, Stress, Adolescent, Diffusion tensor imaging, Resting-state functional magnetic resonance imaging, Depression

Abstract Evidence from post-mortem, genetic, neuroimaging, and non-human animal research suggests that Major Depressive Disorder (MDD) is associated with abnormalities in brain myelin content. Brain regions implicated in this research, and in MDD more generally, include the nucleus accumbens (NAcc), lateral prefrontal cortex (LPFC), insula, subgenual anterior cingulate cortex (sgACC), and medial prefrontal cortex (mPFC). We examined whether MDD is characterized by reduced myelin at the whole-brain level and in NAcc, LPFC, insula, sgACC, and mPFC. Quantitative magnetic resonance imaging (qMRI) permits the assessment of myelin content, in vivo, in the human brain through the measure of R1. In this study we used qMRI to measure R1 in 40 MDD and 40 healthy control (CTL) participants. We found that the MDD participants had lower levels of myelin than did the CTL participants at the whole-brain level and in the NAcc, and that myelin in the LPFC was reduced in MDD participants who had experienced a greater number of depressive episodes. Although further research is needed to elucidate the role of myelin in affecting emotional, cognitive, behavioral, and clinical aspects of MDD, the current study provides important new evidence that a fundamental property of brain composition, myelin, is altered in this disorder.

In the nascent field of the cognitive neuroscience of socioeconomic status (SES), researchers are using neuroimaging to examine how growing up in poverty affects children’s neurocognitive development, particularly their language abilities. In this review we highlight difficulties inherent in the frequent use of reverse inference to interpret SES-related abnormalities in brain regions that support language. While there is growing evidence suggesting that SES moderates children’s developing brain structure and function, no studies to date have elucidated explicitly how these neural findings are related to variations in children’s language abilities, or precisely what it is about SES that underlies or contributes to these differences. This issue is complicated by the fact that SES is confounded with such linguistic factors as cultural language use, first language, and bilingualism. Thus, SES-associated differences in brain regions that support language may not necessarily indicate differences in neurocognitive abilities. In this review we consider the multidimensionality of SES, discuss studies that have found SES-related differences in structure and function in brain regions that support language, and suggest future directions for studies in the area of cognitive neuroscience of SES that are less reliant on reverse inference. Keywords: Socioeconomic status (SES), Neuroimaging, Reverse inference, Language, Development, Childhood poverty

Although behavioral sensitivity to reward predicts the onset and course of mania in bipolar disorder, the evidence for neural abnormalities in reward processing in bipolar disorder is mixed. To probe neural responsiveness to anticipated and received rewards in the context of bipolar disorder, we scanned individuals with remitted bipolar I disorder (n = 24) and well-matched controls (n = 24; matched for age and gender) using Functional Magnetic Resonance Imaging (FMRI) during a Monetary Incentive Delay (MID) task. Relative to controls, the bipolar group showed reduced NAcc activity during anticipation of gains. Across groups, this blunting correlated with individual differences in impulsive responses to positive emotions (Positive Urgency), which statistically accounted for the association of blunted NAcc activity with bipolar diagnosis. These results suggest that blunted NAcc responses during gain anticipation in the context of bipolar disorder may reflect individual differences in Positive Urgency. These findings may help resolve discrepancies in the literature on neural responses to reward in bipolar disorder, and clarify the relationship between brain activity and the propensity to experience manic episodes. Keywords: Bipolar, Imaging, Reward, Anticipation, Accumbens, Monetary, Human

In the general population, females experience depression at significantly higher rates than males. Individuals with traumatic brain injury (TBI) are at substantially greater risk for depression compared to the overall population. Treatment of, and recovery from, TBI can be hindered by depression; comorbid TBI and depression can lead to adverse outcomes and negatively affect multiple aspects of individuals’ lives. Gender differences in depression following TBI are not well understood, and relevant empirical findings have been mixed. Utilizing the Patient Health Questionnaire-9 (PHQ-9) 1 year after TBI, we examined whether women would experience more severe depressive symptoms, and would endorse higher levels of depression within each category of depression severity, than would men. Interestingly, and contrary to our hypothesis, men and women reported mild depression at equal rates; PHQ-9 total scores were slightly lower in women than in men. Men and women did not differ significantly in any PHQ-9 depression severity category. Item analyses, yielded significant gender differences on the following items: greater concentration difficulties (cognitive problems) in men and more sleep disturbances (psychosomatic issues) in women per uncorrected two-sample Z-test for proportions analyses; however, these results were not significant after the family-wise Bonferroni correction. Our results indicate that, in contrast to the general population, mild depression in persons with moderate to severe TBI may not be gender-specific. These findings underscore the need for early identification, active screening, and depression treatment equally for men and women to improve emotional well-being, promote recovery, and enhance quality of life following TBI.

Recent research detailing the intrinsic functional organization of the brain provides a unique and useful framework to gain a better understanding of the neural bases of Major Depressive Disorder (MDD). In this review, we first present a brief history of neuroimaging research that has increased our understanding of the functional macro-architecture of the brain. From this macro-architectural perspective, we examine the extant body of functional neuroimaging research assessing MDD with a specific emphasis on the contributions of default-mode, executive, and salience networks in this debilitating disorder. Next, we describe recent investigations conducted in our laboratory in which we explicitly adopt a neural-system perspective in examining the relations among these networks in MDD. Finally, we offer directions for future research that we believe will facilitate the development of more detailed and integrative models of neural dysfunction in depression.

Major Depressive Disorder (MDD) is characterized by several emotional disturbances. One possible but not well-examined disturbance is in attention to emotion, an important facet of emotional awareness. We examined whether attention to emotion predicted recovery from MDD. Fifty-three adults with current MDD completed a week of experience sampling (Time 1). At each prompt, participants reported attention to emotion, negative affect (NA), and positive affect (PA). Approximately one year later (Time 2), the depressive status of 27 participants was reassessed. Participants who had recovered from MDD (n=8) indicated paying less attention to their emotions at Time 1 than did participants who had not fully recovered (n=19). Attention to emotion was better predictor of recovery than was severity of MDD, NA, or PA at Time 1. Levels of attention to emotion at Time 1 in participants who recovered from MDD did not differ significantly from the levels reported by 53 never-depressed individuals who had participated in the experience sampling. Findings indicate that high levels of an otherwise adaptive emotional facet can adversely affect the course of MDD.