Intracranial Recordings of the Human Orbitofrontal Cortical Activity during Self-Referential Episodic and Valenced Self-Judgments.

We recorded directly from the orbital (oPFC) and ventromedial (vmPFC) subregions of the orbitofrontal cortex (OFC) in 22 (9 female, 13 male) epilepsy patients undergoing intracranial electroencephalography (iEEG) monitoring during an experimental task in which the participants judged the accuracy of self-referential autobiographical statements as well as valenced self-judgments (SJs). We found significantly increased high-frequency activity (HFA) in ∼13% of oPFC sites (10/18 subjects) and 16% of vmPFC sites (4/12 subjects) during both of these self-referential thought processes, with the HFA power being modulated by the content of self-referential stimuli. The location of these activated sites corresponded with the location of fMRI-identified limbic network. Furthermore, the onset of HFA in the vmPFC was significantly earlier than that in the oPFC in all patients with simultaneous recordings in both regions. In 11 patients with available depression scores from comprehensive neuropsychological assessments, we documented diminished HFA in the OFC during positive SJ trials among individuals with higher depression scores; responses during negative SJ trials were not related to the patients' depression scores. Our findings provide new temporal and anatomical information about the mode of engagement in two important subregions of the OFC during autobiographical memory and SJ conditions. Our findings from the OFC support the hypothesis that diminished brain activity during positive self-evaluations, rather than heightened activity during negative self-evaluations, plays a key role in the pathophysiology of depression.

Genetics, epigenetics, and neurobiology of childhood-onset depression: an umbrella review.

Depression is a serious and persistent psychiatric disorder that commonly first manifests during childhood. Depression that starts in childhood is increasing in frequency, likely due both to evolutionary trends and to increased recognition of the disorder. In this umbrella review, we systematically searched the extant literature for genetic, epigenetic, and neurobiological factors that contribute to a childhood onset of depression. We searched PubMed, EMBASE, OVID/PsychInfo, and Google Scholar with the following inclusion criteria: (1) systematic review or meta-analysis from a peer-reviewed journal; (2) inclusion of a measure assessing early age of onset of depression; and (3) assessment of neurobiological, genetic, environmental, and epigenetic predictors of early onset depression. Findings from 89 systematic reviews of moderate to high quality suggest that childhood-onset depressive disorders have neurobiological, genetic, environmental, and epigenetic roots consistent with a diathesis-stress theory of depression. This review identified key putative markers that may be targeted for personalized clinical decision-making and provide important insights concerning candidate mechanisms that might underpin the early onset of depression.

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

Large-scale proteomics in the first trimester of pregnancy predict psychopathology and temperament in preschool children: an exploratory study.

BACKGROUND: Understanding the prenatal origins of children's psychopathology is a fundamental goal in developmental and clinical science. Recent research suggests that inflammation during pregnancy can trigger a cascade of fetal programming changes that contribute to vulnerability for the emergence of psychopathology. Most studies, however, have focused on a handful of proinflammatory cytokines and have not explored a range of prenatal biological pathways that may be involved in increasing postnatal risk for emotional and behavioral difficulties. METHODS: Using extreme gradient boosted machine learning models, we explored large-scale proteomics, considering over 1,000 proteins from first trimester blood samples, to predict behavior in early childhood. Mothers reported on their 3- to 5-year-old children's (N = 89, 51% female) temperament (Child Behavior Questionnaire) and psychopathology (Child Behavior Checklist). RESULTS: We found that machine learning models of prenatal proteomics predict 5%-10% of the variance in children's sadness, perceptual sensitivity, attention problems, and emotional reactivity. Enrichment analyses identified immune function, nervous system development, and cell signaling pathways as being particularly important in predicting children's outcomes. CONCLUSIONS: Our findings, though exploratory, suggest processes in early pregnancy that are related to functioning in early childhood. Predictive features included far more proteins than have been considered in prior work. Specifically, proteins implicated in inflammation, in the development of the central nervous system, and in key cell-signaling pathways were enriched in relation to child temperament and psychopathology measures.

The growing interdisciplinarity of developmental psychopathology: Implications for science and training.

The field of developmental psychopathology has grown exponentially over the past decades, and has become increasingly multifaceted. The initial focus on understanding abnormal child psychology has broadened to the study of the origins of psychopathology, with the goals of preventing and alleviating disorder and promoting healthy development. In this paper, we discuss how technological advances and global events have expanded the questions that researchers in developmental psychopathology can address. We do so by describing a longitudinal study that we have been conducting for the past dozen years. We originally planned to examine the effects of early adversity on trajectories of brain development, endocrine function, and depressive symptoms across puberty; it has since become an interdisciplinary study encompassing diverse domains like inflammation, sleep, biological aging, the environment, and child functioning post-pandemic, that we believe will advance our understanding of neurobehavioral development. This increase in the breadth in our study emerged from an expansion of the field; we encourage researchers to embrace these dynamic changes. In this context, we discuss challenges, opportunities, and institutional changes related to the growing interdisciplinarity of the field with respect to training the next generation of investigators to mitigate the burden of mental illness in youth.

Pregnancy during the pandemic: the impact of COVID-19-related stress on risk for prenatal depression.

BACKGROUND: Pregnant women may be especially susceptible to negative events (i.e. adversity) related to the coronavirus disease 2019 (COVID-19) pandemic and negative affective responses to these events (i.e. stress). We examined the latent structure of stress and adversity related to the COVID-19 pandemic among pregnant women, potential antecedents of COVID-19-related stress and adversity in this population, and associations with prenatal depressive symptoms. METHOD: We surveyed 725 pregnant women residing in the San Francisco Bay Area in March-May 2020, 343 of whom provided addresses that were geocoded and matched by census tract to measures of community-level risk. We compared their self-reported depressive symptoms to women matched on demographic factors and history of mental health difficulties who were pregnant prior to the pandemic. RESULTS: Women who were pregnant during the pandemic were nearly twice as likely to have possible depression than were matched women who were pregnant prior to the pandemic. Individual- and community-level factors tied to socioeconomic inequality were associated with latent factors of COVID-19-related stress and adversity. Beyond objective adversity, subjective stress responses were strongly associated with depressive symptoms during the pandemic. CONCLUSIONS: Highlighting the role of subjective responses in vulnerability to prenatal depression and factors that influence susceptibility to COVID-19-related stress, these findings inform the allocation of resources to support recovery from this pandemic and future disease outbreaks. In addition to policies that mitigate disruptions to the environment due to the pandemic, treatments that focus on cognitions about the self and the environment may help to alleviate depressive symptoms in pregnant women.

Social threat, fronto-cingulate-limbic morphometry, and symptom course in depressed adolescents: a longitudinal investigation.

BACKGROUND: Psychosocial stressors characterized by social threat, such as interpersonal loss and social rejection, are associated with depression in adolescents. Few studies, however, have examined whether social threat affects fronto-cingulate-limbic systems implicated in adolescent depression. METHODS: We assessed lifetime stressor severity across several domains using the Stress and Adversity Inventory (STRAIN) in 57 depressed adolescents (16.15 ± 1.32 years, 34 females), and examined whether the severity of social threat and non-social threat stressors was associated with gray matter volumes (GMVs) in the anterior cingulate cortex (ACC), amygdala, hippocampus, and nucleus accumbens (NAcc). We also examined how lifetime social threat severity and GMVs in these regions related to depressive symptoms at baseline and over 9 months. RESULTS: General stressor severity was related to greater depression severity at baseline and over 9 months. Moreover, greater severity of social threat (but not non-social threat) stressors was associated with smaller bilateral amygdala and NAcc GMVs, and smaller bilateral surface areas of caudal and rostral ACC (all pFDR ⩽ 0.048). However, neither social threat nor non-social threat stressor severity was related to hippocampal GMVs (all pFDR ⩾ 0.318). All fronto-cingulate-limbic structures that were associated with the severity of social threat were negatively associated with greater depression severity over 9 months (all pFDR ⩽ 0.014). Post-hoc analyses suggested that gray matter morphometry of bilateral amygdala, NAcc, and rostral and caudal ACC mediated the association between social threat and depression severity in adolescents over 9 months (all pFDR < 0.048). CONCLUSIONS: Social threat specifically affects fronto-cingulate-limbic pathways that contribute to the maintenance of depression in adolescents.

Psychobiological risk factors for suicidal thoughts and behaviors in adolescence: a consideration of the role of puberty.

Suicide is the second leading cause of death among adolescents. While clinicians and researchers have begun to recognize the importance of considering multidimensional factors in understanding risk for suicidal thoughts and behaviors (STBs) during this developmental period, the role of puberty has been largely ignored. In this review, we contend that the hormonal events that occur during puberty have significant effects on the organization and development of brain systems implicated in the regulation of social stressors, including amygdala, hippocampus, striatum, medial prefrontal cortex, orbitofrontal cortex, and anterior cingulate cortex. Guided by previous experimental work in adults, we also propose that the influence of pubertal hormones and social stressors on neural systems related to risk for STBs is especially critical to consider in adolescents with a neurobiological sensitivity to hormonal changes. Furthermore, facets of the pubertal transition, such as pubertal timing, warrant deeper investigation and may help us gain a more comprehensive understanding of sex differences in the neurobiological and psychosocial mechanisms underlying adolescent STBs. Ultimately, advancing our understanding of the pubertal processes that contribute to suicide risk will improve early detection and facilitate the development of more effective, sex-specific, psychiatric interventions for adolescents.

Maternal attachment insecurity, maltreatment history, and depressive symptoms are associated with broad DNA methylation signatures in infants.

The early environment, including maternal characteristics, provides many cues to young organisms that shape their long-term physical and mental health. Identifying the earliest molecular events that precede observable developmental outcomes could help identify children in need of support prior to the onset of physical and mental health difficulties. In this study, we examined whether mothers' attachment insecurity, maltreatment history, and depressive symptoms were associated with alterations in DNA methylation patterns in their infants, and whether these correlates in the infant epigenome were associated with socioemotional and behavioral functioning in toddlerhood. We recruited 156 women oversampled for histories of depression, who completed psychiatric interviews and depression screening during pregnancy, then provided follow-up behavioral data on their children at 18 months. Buccal cell DNA was obtained from 32 of their infants for a large-scale analysis of methylation patterns across 5 × 106 individual CpG dinucleotides, using clustering-based significance criteria to control for multiple comparisons. We found that tens of thousands of individual infant CpGs were alternatively methylated in association with maternal attachment insecurity, maltreatment in childhood, and antenatal and postpartum depressive symptoms, including genes implicated in developmental patterning, cell-cell communication, hormonal regulation, immune function/inflammatory response, and neurotransmission. Density of DNA methylation at selected genes from the result set was also significantly associated with toddler socioemotional and behavioral problems. This is the first report to identify novel regions of the human infant genome at which DNA methylation patterns are associated longitudinally both with maternal characteristics and with offspring socioemotional and behavioral problems in toddlerhood.

Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium.

Identifying brain alterations associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and improving early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth. We performed analyses in three separate stages, in samples ranging from most to least homogeneous in terms of suicide assessment instrument and mental disorder. First, in a sample of 577 young people with mood disorders, in which STBs were assessed with the Columbia Suicide Severity Rating Scale (C-SSRS). Second, in a sample of young people with mood disorders, in which STB were assessed using different instruments, MRI metrics were compared among healthy controls without STBs (HC; N = 519), clinical controls with a mood disorder but without STBs (CC; N = 246) and young people with current suicidal ideation (N = 223). In separate analyses, MRI metrics were compared among HCs (N = 253), CCs (N = 217), and suicide attempters (N = 64). Third, in a larger transdiagnostic sample with various assessment instruments (HC = 606; CC = 419; Ideation = 289; HC = 253; CC = 432; Attempt=91). In the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and a history of actual suicide attempts (N = 163) than those without a lifetime suicide attempt (N = 323; FDR-p = 0.035, Cohen's d = 0.34). No associations with suicidal ideation were found. When examining more heterogeneous samples, we did not observe significant associations. Lower frontal pole surface area may represent a vulnerability for a (non-interrupted and non-aborted) suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk.

Associations among early life adversity, sleep disturbances, and depressive symptoms in adolescent females and males: a longitudinal investigation.

BACKGROUND: Exposure to adversity early in life (ELA) has been associated with elevated risk for depression during adolescence, particularly for females; the mechanisms underlying this association, however, are poorly understood. One potential mechanism linking ELA and sex differences in depressive symptoms is sleep disturbances, which increase during adolescence and are more common in females. Here, we examined whether sleep disturbances mediate the association between ELA and increases in depressive symptoms during adolescence and whether this mediation differs by sex. METHODS: 224 (N = 132 females) youth were recruited at age 9-13 years and assessed every 2 years across three timepoints. At the first timepoint, we conducted extensive interviews about stressful events participants experienced; participants provided subjective severity ratings of events and we objectively scored the severity of each event. Self-reported sleep disturbances and depressive symptoms were assessed at all timepoints. We conducted linear mixed models to estimate both initial levels and changes in sleep disturbances and depressive symptoms, and moderated mediation analyses to test whether initial levels and/or changes in sleep disturbances mediated the association of ELA (objective and subjective) with increases in depressive symptoms across adolescence and whether the mediations differed by sex. RESULTS: While higher initial levels and increases in sleep problems were uniquely associated with increases in depressive symptoms for males and females, they were related to ELA differently by sex. For females, greater ELA (both objectively and subjectively rated) was associated with higher initial levels of sleep problems, which in turn were associated with increases in depressive symptoms from early to late adolescence. In contrast, for males, ELA exposure was not associated with either initial levels of, or increases in, sleep problems. CONCLUSIONS: These findings highlight the role of sleep disturbances during the transition to adolescence in mediating sex differences in the effects of ELA on depressive symptoms.

Objective and subjective sleep health in adolescence: Associations with puberty and affect.

Sleep health tends to worsen during adolescence, partially due to pubertal-related changes that, in combination with social and psychological factors, can lead to long-lasting impairments in sleep health and affective functioning. Discrepant findings between subjective and objective measures of sleep in relation to affect have been reported in studies of adults; however, few investigations have assessed both subjective and objective sleep quality in a single sample, and fewer have examined this in the context of pubertal development. We aimed to (1) characterise pubertal associations with subjective sleep satisfaction, objective sleep efficiency, and objective and subjective sleep duration in adolescents; (2) examine the longitudinal association between daily affect and sleep metrics; and (3) test whether pubertal stage moderated this association. Eighty-nine participants (64% female, ages 13-20) completed an ecological momentary assessment (EMA) and actigraphy protocol. Independent of age, advanced pubertal stage was associated with lower subjective sleep satisfaction but not with objective sleep indices. Subjective sleep satisfaction was associated with within-person trajectories of negative affect, but not with positive affect. Pubertal stage and sleep satisfaction did not interact to predict within-day negative or positive affect. These findings are consistent with previous reports showing that objective and subjective sleep health are associated differently with puberty, and that subjective sleep health is associated with daily affect. Pubertal stage may be a more important indicator of subjective sleep quality in adolescence than is chronological age, most likely due to hormonal changes and psychological adjustment to the physical changes associated with the pubertal transition.

Fine Particulate Air Pollution, Early Life Stress, and Their Interactive Effects on Adolescent Structural Brain Development: A Longitudinal Tensor-Based Morphometry Study.

Air pollution is a major environmental threat to public health; we know little, however, about its effects on adolescent brain development. Exposure to air pollution co-occurs, and may interact, with social factors that also affect brain development, such as early life stress (ELS). Here, we show that severity of ELS and fine particulate air pollution (PM2.5) are associated with volumetric changes in distinct brain regions, but also uncover regions in which ELS moderates the effects of PM2.5. We interviewed adolescents about ELS events, used satellite-derived estimates of ambient PM2.5 concentrations, and conducted longitudinal tensor-based morphometry to assess regional changes in brain volume over an approximately 2-year period (N = 115, ages 9-13 years at Time 1). For adolescents who had experienced less severe ELS, PM2.5 was associated with volumetric changes across several gray and white matter regions. Fewer effects of PM2.5 were observed for adolescents who had experienced more severe ELS, although occasionally they were in the opposite direction. This pattern of results suggests that for many brain regions, moderate to severe ELS largely constrains the effects of PM2.5 on structural development. Further theory and research is needed on the joint effects of ELS and air pollution on the brain.

AI-based dimensional neuroimaging system for characterizing heterogeneity in brain structure and function in major depressive disorder: COORDINATE-MDD consortium design and rationale.

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.

The default mode network is associated with changes in internalizing and externalizing problems differently in adolescent boys and girls.

Internalizing and externalizing problems that emerge during adolescence differentially increase boys' and girls' risk for developing psychiatric disorders. It is not clear, however, whether there are sex differences in the intrinsic functional architecture of the brain that underlie changes in the severity of internalizing and externalizing problems in adolescents. Using resting-state fMRI data and self-reports of behavioral problems obtained from 128 adolescents (73 females; 9-14 years old) at two timepoints, we conducted multivoxel pattern analysis to identify resting-state functional connectivity markers at baseline that predict changes in the severity of internalizing and externalizing problems in boys and girls 2 years later. We found sex-differentiated involvement of the default mode network in changes in internalizing and externalizing problems. Whereas changes in internalizing problems were associated with the dorsal medial subsystem in boys and with the medial temporal subsystem in girls, changes in externalizing problems were predicted by hyperconnectivity between core nodes of the DMN and frontoparietal network in boys and hypoconnectivity between the DMN and affective networks in girls. Our results suggest that different neural mechanisms predict changes in internalizing and externalizing problems in adolescent boys and girls and offer insights concerning mechanisms that underlie sex differences in the expression of psychopathology in adolescence.

Validation of the Assessment of Parent and Child Adversity (APCA) in Mothers and Young Children.

OBJECTIVE: Advancing understanding of how early adversity arises, manifests, and contributes to health difficulties depends on accurate measurement of children's experiences. In early life, exposure to adversity is often intertwined with that of one's caregivers. We present preliminary psychometric properties of a novel measure of adversity, the Assessment of Parent and Child Adversity (APCA), which simultaneously characterizes parents' and children's adversity. METHODS: During pregnancy, women reported their past adverse experiences. When their children were ages 3-5 years (47% female), 97 mothers (71% White, 17% Hispanic/Latinx) completed the APCA, the Childhood Trauma Questionnaire, and the Benevolent Childhood Experiences scale. They reported their current symptoms of depression and anxiety and their child's emotional and behavioral problems. Using the APCA, we distinguished between maternal adversity during different life periods and obtained metrics of child witnessing of and direct exposure to adversity. RESULTS: The APCA demonstrated validity with other measures of maternal adverse experiences, maternal positive childhood experiences, and maternal symptoms of psychopathology. Children whose mothers experienced greater adversity, particularly in the prenatal period, had more emotional and behavioral problems, as did children who were directly exposed to greater adversity. CONCLUSIONS: The APCA has good usability and validity. Leveraging the ability of the APCA to distinguish between adversity during different life stages and originating from different sources, our findings highlight potentially distinct effects of different aspects of maternal and child adversity on difficulties in maternal and child mental health.

Prefrontal activation in preschool children is associated with maternal adversity and child temperament: A preliminary fNIRS study of inhibitory control.

Exposure to adversity is a well-documented risk factor for cognitive, behavioral, and mental health problems. In fact, the consequences of adversity may be intergenerational. A growing body of research suggests that maternal exposures to adversity, including those prior to childbirth, are associated with offspring biobehavioral development. In a sample of 36 mothers and their preschool-age children (mean child age = 4.21 ± 0.92 years), we used functional near-infrared spectroscopy to replicate and extend this work to include brain activation during inhibitory control in young children. We found that measures of maternal exposure to adversity, including cumulative, childhood, and preconception exposures, were significantly and positively associated with activation in the right frontopolar prefrontal cortex (PFC) and in the left temporal and parietal clusters during inhibitory control. In addition, and consistent with previous findings, children's increased negative affect and decreased effortful control were associated with increased right PFC activation during inhibitory control. These findings provide preliminary evidence that maternal and dispositional risk factors are linked to alterations in PFC functioning during the preschool years. Children of mothers with a history of exposure to adversity, as well as children who are less temperamentally regulated, may require increased neural resources to meet the cognitive demands of inhibitory control.

Early life stress predicts trajectories of emotional problems and hippocampal volume in adolescence.

Exposure to early life stress (ELS) has been consistently associated with adverse emotional and neural consequences in youth. The development of brain structures such as the hippocampus, which plays a significant role in stress and emotion regulation, may be particularly salient in the development of psychopathology. Prior work has documented smaller hippocampal volume (HCV) in relation to both ELS exposure and risk for psychopathology. We used longitudinal k-means clustering to identify simultaneous trajectories of HCV and emotional problems in 155 youth across three assessments conducted approximately two years apart (mean baseline age = 11.33 years, 57% female). We also examined depressive symptoms and resilience approximately two years after the third timepoint. We identified three clusters of participants: a cluster with high HCV and low emotional problems; a cluster with low HCV and high emotional problems; and a cluster with low HCV and low emotional problems. Importantly, severity of ELS was associated with greater likelihood of belonging to the low HCV/high symptom cluster than to the low HCV/low symptom cluster. Further, low HCV/high symptom participants had more depressive symptoms and lower resilience scores than did participants in the low HCV/low symptom, but not than in the high HCV/low symptom cluster. Our findings suggest that smaller HCV indexes biological sensitivity to stress. This adds to our understanding of the ways in which ELS can affect hippocampal and emotional development in young people and points to hippocampal volume as a marker of susceptibility to context.

Deleterious and Protective Psychosocial and Stress-Related Factors Predict Risk of Spontaneous Preterm Birth.

OBJECTIVES: The aim of the study was to: (1) Identify (early in pregnancy) psychosocial and stress-related factors that predict risk of spontaneous preterm birth (PTB, gestational age <37 weeks); (2) Investigate whether "protective" factors (e.g., happiness/social support) decrease risk; (3) Use the Dhabhar Quick-Assessment Questionnaire for Stress and Psychosocial Factors (DQAQ-SPF) to rapidly quantify harmful or protective factors that predict increased or decreased risk respectively, of PTB. STUDY DESIGN: This is a prospective cohort study. Relative risk (RR) analyses investigated association between individual factors and PTB. Machine learning-based interdependency analysis (IDPA) identified factor clusters, strength, and direction of association with PTB. A nonlinear model based on support vector machines was built for predicting PTB and identifying factors that most strongly predicted PTB. RESULTS: Higher levels of deleterious factors were associated with increased RR for PTB: General anxiety (RR = 8.9; 95% confidence interval [CI] = 2.0,39.6), pain (RR = 5.7; CI = 1.7,17.0); tiredness/fatigue (RR = 3.7; CI = 1.09,13.5); perceived risk of birth complications (RR = 4; CI = 1.6,10.01); self-rated health current (RR = 2.6; CI = 1.0,6.7) and previous 3 years (RR = 2.9; CI = 1.1,7.7); and divorce (RR = 2.9; CI = 1.1,7.8). Lower levels of protective factors were also associated with increased RR for PTB: low happiness (RR = 9.1; CI = 1.25,71.5); low support from parents/siblings (RR = 3.5; CI = 0.9,12.9), and father-of-baby (RR = 3; CI = 1.1,9.9). These factors were also components of the clusters identified by the IDPA: perceived risk of birth complications (p < 0.05 after FDR correction), and general anxiety, happiness, tiredness/fatigue, self-rated health, social support, pain, and sleep (p < 0.05 without FDR correction). Supervised analysis of all factors, subject to cross-validation, produced a model highly predictive of PTB (AUROC or area under the receiver operating characteristic = 0.73). Model reduction through forward selection revealed that even a small set of factors (including those identified by RR and IDPA) predicted PTB. CONCLUSION: These findings represent an important step toward identifying key factors, which can be assessed rapidly before/after conception, to predict risk of PTB, and perhaps other adverse pregnancy outcomes. Quantifying these factors, before, or early in pregnancy, could identify women at risk of delivering preterm, pinpoint mechanisms/targets for intervention, and facilitate the development of interventions to prevent PTB. KEY POINTS: · Newly designed questionnaire used for rapid quantification of stress and psychosocial factors early during pregnancy.. · Deleterious factors predict increased preterm birth (PTB) risk.. · Protective factors predict decreased PTB risk..

Naturalistic Language Input is Associated with Resting-State Functional Connectivity in Infancy.

The quantity and quality of the language input that infants receive from their caregivers affects their future language abilities; however, it is unclear how variation in this input relates to preverbal brain circuitry. The current study investigated the relation between naturalistic language input and the functional connectivity (FC) of language networks in human infancy using resting-state functional magnetic resonance imaging (rsfMRI). We recorded the naturalistic language environments of five- to eight-month-old male and female infants using the Linguistic ENvironment Analysis (LENA) system and measured the quantity and consistency of their exposure to adult words (AWs) and adult-infant conversational turns (CTs). Infants completed an rsfMRI scan during natural sleep, and we examined FC among regions of interest (ROIs) previously implicated in language comprehension, including the auditory cortex, the left inferior frontal gyrus (IFG), and the bilateral superior temporal gyrus (STG). Consistent with theory of the ontogeny of the cortical language network (Skeide and Friederici, 2016), we identified two subnetworks posited to have distinct developmental trajectories: a posterior temporal network involving connections of the auditory cortex and bilateral STG and a frontotemporal network involving connections of the left IFG. Independent of socioeconomic status (SES), the quantity of CTs was uniquely associated with FC of these networks. Infants who engaged in a larger number of CTs in daily life had lower connectivity in the posterior temporal language network. These results provide evidence for the role of vocal interactions with caregivers, compared with overheard adult speech, in the function of language networks in infancy.