Heart rate variability as a biomarker for transdiagnostic depressive and anxiety symptom trajectory in adolescents and young adults.

Internalizing psychopathology is associated with abnormalities in heart rate variability (HRV). Lower HRV that reflects reduced parasympathetic nervous system activity has been observed in depressive and anxiety disorders. Existing studies predominantly used categorical rather than dimensional approaches, the latter of which better addresses clinical comorbidity and heterogeneity. Moreover, there is little evidence on the role of HRV in longitudinal symptom trajectory in adolescents and young adults. The current study examined the association between HRV and internalizing symptom trajectory using a dimensional approach-the tri-level model of depression and anxiety. Adolescents and young adults (N = 362) were recruited in a 3-year longitudinal study, where they completed electrocardiogram recordings and self-report symptom questionnaires. Multilevel modeling was conducted with high-frequency power bands (HF power) of interbeat intervals at baseline as the predictor, and tri-level symptom factors over 3 years as the outcome. HF power significantly predicted the trajectory of the broad General Distress symptom factor, but not the intermediate Fears or Anhedonia-Apprehension symptom factors. Higher HF power was associated with a decline in General Distress over time. This association was held when neuroticism, other tri-level symptom factors, and demographic variables were covaried. That is, greater parasympathetic nervous system activity at baseline was significantly associated with a greater decline in the broad internalizing symptom factor, but not symptom factors that are more specific to depressive or anxiety disorders. Parasympathetic activity, therefore, may be a transdiagnostic biomarker for internalizing symptoms in adolescents and young adults. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Promise and Challenges of Integrating Biological and Prevention Sciences: A Community-Engaged Model for the Next Generation of Translational Research.

Beginning with the successful sequencing of the human genome two decades ago, the possibility of developing personalized health interventions based on one's biology has captured the imagination of researchers, medical providers, and individuals seeking health care services. However, the application of a personalized medicine approach to emotional and behavioral health has lagged behind the development of personalized approaches for physical health conditions. There is potential value in developing improved methods for integrating biological science with prevention science to identify risk and protective mechanisms that have biological underpinnings, and then applying that knowledge to inform prevention and intervention services for emotional and behavioral health. This report represents the work of a task force appointed by the Board of the Society for Prevention Research to explore challenges and recommendations for the integration of biological and prevention sciences. We present the state of the science and barriers to progress in integrating the two approaches, followed by recommended strategies that would promote the responsible integration of biological and prevention sciences. Recommendations are grounded in Community-Based Participatory Research approaches, with the goal of centering equity in future research aimed at integrating the two disciplines to ultimately improve the well-being of those who have disproportionately experienced or are at risk for experiencing emotional and behavioral problems.

Higher substance use is associated with low executive control neural activity and higher inflammation.

Individuals with substance use problems show lower executive control and alterations in prefrontal brain systems supporting emotion regulation and impulse control. A separate literature suggests that heightened inflammation also increases risk for substance use, in part, through targeting brain systems involved in executive control. Research on neural and inflammatory signaling in substance use, however, has occurred in parallel. Drawing on recent neuroimmune network models, we used fMRI to examine the relationships between executive control-related brain activity (as elicited by an n-back working memory task), peripheral inflammation, as quantified by inflammatory cytokines and C-reactive protein (CRP), and substance use for the past month in 93 participants [mean age = 24.4 (SD = 0.6)]. We operationalized low executive control as a neural inefficiency during the n-back task to achieve normative performance, as reflected in higher working memory-related brain activity and lower activity in the default mode network (DMN). Consistent with prediction, individuals with low executive control and high inflammation reported more substance use over the past month, controlling for behavioral performance on the n-back, sex, time between assessments, body-mass-index (BMI), and personal socioeconomic status (SES) (interaction between inflammation and working memory-related brain activity, b = 0.210, p = 0.005; interaction between inflammation and DMN, b = -0.219, p < 0.001). Findings suggest that low executive control and high inflammation may be associated with higher substance use. This has implications for understanding psychological, neural, and immunological risk for substance use problems and the development of interventions to target each of these components.

Anhedonia is associated with overgeneralization of conditioned fear during late adolescence and early adulthood.

BACKGROUND: Pavlovian fear paradigms involve learning to associate cues with threat or safety. Aberrances in Pavlovian fear learning correlate with psychopathology, especially anxiety disorders. This study evaluated symptom dimensions of anxiety and depression in relation to Pavlovian fear acquisition and generalization. METHODS: 256 participants (70.31 % female) completed a Pavlovian fear acquisition and generalization paradigm at ages 18-19 and 21-22 years. Analyses focused on indices of learning (self-reported US expectancy, skin conductance). Multilevel models tested associations with orthogonal symptom dimensions (Anhedonia-Apprehension, Fears, General Distress) at each timepoint. RESULTS: All dimensions were associated with weaker acquisition of US expectancies at each timepoint. Fears was associated with overgeneralization only at age 21-22. General Distress was associated with overgeneralization only at age 18-19. Anhedonia-Apprehension was associated with overgeneralization at ages 18-19 and 21-22. CONCLUSIONS: Anhedonia-Apprehension disrupts Pavlovian fear acquisition and increases overgeneralization of fear. These effects may emerge during adolescence and remain into young adulthood. General Distress and Fears also contribute to overgeneralization of fear, but these effects may vary as prefrontal mechanisms of fear inhibition continue to develop during late adolescence. Targeting specific symptom dimensions, particularly Anhedonia-Apprehension, may decrease fear generalization and augment interventions built on Pavlovian principles, such as exposure therapy.

The path from mood symptoms to substance use: A longitudinal examination in individuals with and at risk for bipolar spectrum disorders.

BACKGROUND: Adolescent substance use poses a critical public health challenge, intertwined with risk-taking behavior, criminality, functional impairment, and comorbid mental and physical health issues. Adolescents with bipolar spectrum disorders (BSD) exhibit heightened susceptibility to substance use, necessitating a nuanced exploration of the bipolar-substance use relationship. METHODS: This study addressed gaps in the literature by employing a prospective, longitudinal design with 443 Philadelphia-area adolescents, tracking BSD symptoms and substance use. We predicted that BSD symptoms would be associated with increases in substance use, and that these effects would be more pronounced for individuals with a BSD and those with high reward sensitivity. RESULTS: Hypomanic symptoms predicted subsequent substance use, with a stronger association observed in individuals diagnosed with BSD. Contrary to expectations, depressive symptoms did not exhibit a similar relationship. Although the hypothesized moderating role of reward sensitivity was not supported, higher reward sensitivity predicted increased substance use. LIMITATIONS: Symptoms and substance use are only captured for the month prior to each session due to the assessment timeline. This highlights the benefits of frequent assessments over a shorter time frame to monitor real-time changes. Alternative classification methods for reward sensitivity, such as brain or behavior-based assessments, might yield different results. CONCLUSIONS: This study's contributions include evaluating substance use broadly, utilizing a longitudinal design for temporal clarity, and shifting the focus from substance use predicting mood symptoms to the inverse. The findings underscore the need for continued exploration of mood symptom predictors of substance use, emphasizing the role of reward sensitivity.

Exposure to community violence as a mechanism linking neighborhood socioeconomic disadvantage and neural responses to reward.

A growing literature links socioeconomic disadvantage and adversity to brain function, including disruptions in reward processing. Less research has examined exposure to community violence (ECV) as a specific adversity related to differences in reward-related brain activation, despite the prevalence of community violence exposure for those living in disadvantaged contexts. The current study tested whether ECV was associated with reward-related ventral striatum (VS) activation after accounting for familial factors associated with differences in reward-related activation (e.g. parenting and family income). Moreover, we tested whether ECV is a mechanism linking socioeconomic disadvantage to reward-related activation in the VS. We utilized data from 444 adolescent twins sampled from birth records and residing in neighborhoods with above-average levels of poverty. ECV was associated with greater reward-related VS activation, and the association remained after accounting for family-level markers of disadvantage. We identified an indirect pathway in which socioeconomic disadvantage predicted greater reward-related activation via greater ECV, over and above family-level adversity. These findings highlight the unique impact of community violence exposure on reward processing and provide a mechanism through which socioeconomic disadvantage may shape brain function.

Annual Research Review: Neuroimmune network model of depression: a developmental perspective.

Depression is a serious public health problem, and adolescence is an 'age of risk' for the onset of Major Depressive Disorder. Recently, we and others have proposed neuroimmune network models that highlight bidirectional communication between the brain and the immune system in both mental and physical health, including depression. These models draw on research indicating that the cellular actors (particularly monocytes) and signaling molecules (particularly cytokines) that orchestrate inflammation in the periphery can directly modulate the structure and function of the brain. In the brain, inflammatory activity heightens sensitivity to threats in the cortico-amygdala circuit, lowers sensitivity to rewards in the cortico-striatal circuit, and alters executive control and emotion regulation in the prefrontal cortex. When dysregulated, and particularly under conditions of chronic stress, inflammation can generate feelings of dysphoria, distress, and anhedonia. This is proposed to initiate unhealthy, self-medicating behaviors (e.g. substance use, poor diet) to manage the dysphoria, which further heighten inflammation. Over time, dysregulation in these brain circuits and the inflammatory response may compound each other to form a positive feedback loop, whereby dysregulation in one organ system exacerbates the other. We and others suggest that this neuroimmune dysregulation is a dynamic joint vulnerability for depression, particularly during adolescence. We have three goals for the present paper. First, we extend neuroimmune network models of mental and physical health to generate a developmental framework of risk for the onset of depression during adolescence. Second, we examine how a neuroimmune network perspective can help explain the high rates of comorbidity between depression and other psychiatric disorders across development, and multimorbidity between depression and stress-related medical illnesses. Finally, we consider how identifying neuroimmune pathways to depression can facilitate a 'next generation' of behavioral and biological interventions that target neuroimmune signaling to treat, and ideally prevent, depression in youth and adolescents.

Neuroimmune mechanisms connecting violence with internalizing symptoms: A high-dimensional multimodal mediation analysis.

Violence exposure is associated with worsening anxiety and depression symptoms among adolescents. Mechanistically, social defeat stress models in mice indicate that violence increases peripherally derived macrophages in threat appraisal regions of the brain, which have been causally linked to anxious behavior. In the present study, we investigate if there is a path connecting violence exposure with internalizing symptom severity through peripheral inflammation and amygdala connectivity. Two hundred and thirty-three adolescents, ages 12-15, from the Chicago area completed clinical assessments, immune assays and neuroimaging. A high-dimensional multimodal mediation model was fit, using violence exposure as the predictor, 12 immune variables as the first set of mediators and 288 amygdala connectivity variables as the second set, and internalizing symptoms as the primary outcome measure. 56.2% of the sample had been exposed to violence in their lifetime. Amygdala-hippocampus connectivity mediated the association between violence exposure and internalizing symptoms ( ζ ̂ Hipp π ̂ Hipp = 0.059 $$ {\hat{\zeta}}_{\mathrm{Hipp}}{\hat{\pi}}_{\mathrm{Hipp}}=0.059 $$ , 95 % CI boot = 0.009,0.134 $$ 95\%{\mathrm{CI}}_{\mathrm{boot}}=\left[\mathrm{0.009,0.134}\right] $$ ). There was no evidence that inflammation or inflammation and amygdala connectivity in tandem mediated the association. Considering the amygdala and the hippocampus work together to encode, consolidate, and retrieve contextual fear memories, violence exposure may be associated with greater connectivity between the amygdala and the hippocampus because it could be adaptive for the amygdala and the hippocampus to be in greater communication following violence exposure to facilitate evaluation of contextual threat cues. Therefore, chronic elevations of amygdala-hippocampal connectivity may indicate persistent vigilance that leads to internalizing symptoms.

Transdiagnostic symptom of depression and anxiety associated with reduced gray matter volume in prefrontal cortex.

Dimensional models of psychopathology may provide insight into mechanisms underlying comorbid depression and anxiety and improve specificity and sensitivity of neuroanatomical findings. The present study is the first to examine neural structure alterations using the empirically derived Tri-level Model. Depression and anxiety symptoms of 269 young adults were assessed using the Tri-level Model dimensions: General Distress (transdiagnostic depression and anxiety symptoms), Anhedonia-Apprehension (relatively specific depression symptoms), and Fears (specific anxiety symptoms). Using structural MRI, gray matter volumes were extracted for emotion generation (amygdala, nucleus accumbens) and regulation (orbitofrontal, ventrolateral, and dorsolateral prefrontal cortex) regions, often implicated in depression and anxiety. Each Tri-level symptom was regressed onto each region of interest, separately, adjusting for relevant covariates. General Distress was significantly associated with smaller gray matter volumes in bilateral orbitofrontal cortex and ventrolateral prefrontal cortex, independent of Anhedonia-Apprehension and Fears symptom dimensions. These results suggests that prefrontal alterations are associated with transdiagnostic dysphoric mood common across depression and anxiety, rather than unique symptoms of these disorders. Additionally, no regions of interest were associated with Anhedonia-Apprehension or Fears, highlighting the importance of studying transdiagnostic features of depression and anxiety. This has implications for understanding mechanisms of and interventions for depression and anxiety.

Major stress in early childhood strengthens the association between peripheral inflammatory activity and corticostriatal responsivity to reward.

BACKGROUND: Severe, chronic stress during childhood accentuates vulnerability to mental and physical health problems across the lifespan. To explain this phenomenon, the neuroimmune network hypothesis proposes that childhood stressors amplify signaling between peripheral inflammatory cells and developing brain circuits that support processing of rewards and threats. Here, we conducted a preliminary test of the basic premises of this hypothesis. METHODS: 180 adolescents (mean age = 19.1 years; 68.9 % female) with diverse racial and ethnic identities (56.1 % White; 28.3 % Hispanic; 26.1 % Asian) participated. The Childhood Trauma Interview was administered to quantify early adversity. Five inflammatory biomarkers were assayed in antecubital blood - C-reactive protein, tumor necrosis factor-a, and interleukins-6, -8, and -10 - and were averaged to form a composite score. Participants also completed a functional MRI task to measure corticostriatal responsivity to the anticipation and acquisition of monetary rewards. RESULTS: Stress exposure and corticostriatal responsivity interacted statistically to predict the inflammation composite. Among participants who experienced major stressors in the first decade of life, higher inflammatory activity covaried with lower corticostriatal responsivity during acquisition of monetary rewards. This relationship was specific to participants who experienced major stress in early childhood, implying a sensitive period for exposure, and were evident in both the orbitofrontal cortex and the ventral striatum, suggesting the broad involvement of corticostriatal regions. The findings were independent of participants' age, sex, racial and ethnic identity, family income, and depressive symptoms. CONCLUSIONS: Collectively, the results are consistent with hypotheses suggesting that major stress in childhood alters brain-immune signaling.

Lack of effect of methamphetamine on reward-related brain activity in healthy adults.

INTRODUCTION: Stimulant drugs are thought to alter processing of rewarding stimuli. However, the mechanisms by which they do this are not fully understood. METHOD: In this study we used EEG to assess effects of single doses of methamphetamine (MA) on neural responses during anticipation and receipt of reward in healthy volunteers. Healthy young men and women (N = 28) completed three sessions in which they received placebo, a low MA dose (10 mg) or a higher MA dose (20 mg) under double blind conditions. Subjective and cardiovascular measures were obtained, and EEG was used to assess brain activity during an electrophysiological version of the Monetary Incentive Delay (eMID) task. RESULTS: EEG measures showed expected patterns during anticipation and receipt of reward, and MA produced its expected effects on mood and cardiovascular function. However, MA did not affect EEG responses during either anticipation or receipt of rewards. CONCLUSIONS: These findings suggest that the effects of MA on EEG signals of reward processing are subtle, and not related to the drug's effects on subjective feelings of well-being. The findings contribute to our understanding of the neural effects of MA during behaviors related to reward.

Clinical high risk for psychosis syndrome is associated with reduced neural responding to unpleasant images.

Deficits in emotion processing are core features of psychotic disorders. Electrophysiology research in schizophrenia suggests deficits in sustained engagement with emotional content (indexed by the late positive potential [LPP]) may contribute to emotion processing impairments. Despite similar behavioral emotion processing dysfunction in those at clinical high risk (CHR) for psychosis, limited research has examined neural mechanisms of impaired emotion processing in the high-risk period, where research can inform risk models. To examine mechanisms of emotion processing deficits in those at CHR for psychosis, the present study used a passive viewing task to elicit the LPP in response to emotionally engaging and neutral stimuli in 28 CHR and 32 control participants (60% female). Relative to controls, CHR participants showed reduced LPP amplitude when viewing unpleasant images (d = 0.75, p = .005) but similar LPP amplitude in response to both neutral (d = 0.35, p = .19) and pleasant images (d = 0.31, p = .24). This pattern suggests that individuals at CHR for psychosis exhibit a deficit in sustained engagement with unpleasant stimuli. Clinical and trait questionnaires were administered to examine potential exploratory explanations for group differences in LPP amplitude. Consistent with evidence suggesting LPP amplitude reflects engagement of approach/avoidance motivational systems, greater LPP amplitude was associated with greater trait-level behavioral avoidance in control participants (r = .42, p = .032) but not CHR participants (r = -.21, p = .40). Together, the present research is consistent with LPP studies in psychosis and implicates reduced sustained engagement with emotional content in the high-risk period. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The Role of Positive and Negative Aspects of Life Events in Depressive and Anxiety Symptoms.

Negative or stressful life events are robust risk factors for depression and anxiety. Less attention has been paid to positive aspects of events and whether positivity buffers the impact of negative aspects of events. The present study examined positivity and negativity of interpersonal and non-interpersonal episodic life events in predicting anxiety and depressive symptoms in a sample of 373 young adults. Regressions tested main and interactive effects of positivity and negativity ratings of events in predicting symptom factors (Fears, Anhedonia-Apprehension (AA), General Distress (GD)) relevant to anxiety and depression. A significant interaction demonstrated that positivity protected against high levels of negativity of non-interpersonal events in predicting GD. A main effect of interpersonal negativity predicting higher AA was observed. Results for Fears were non-significant. Findings suggest that positivity of life events may buffer against negativity in predicting symptoms shared between anxiety and depression.

Circadian, Reward, and Emotion Systems in Teens prospective longitudinal study: protocol overview of an integrative reward-circadian rhythm model of first onset of bipolar spectrum disorder in adolescence.

BACKGROUND: Bipolar spectrum disorders (BSDs) are associated with a heightened sensitivity to rewards and elevated reward-related brain function in cortico-striatal circuitry. A separate literature documents social and circadian rhythm disruption in BSDs. Recently, integrated reward-circadian models of BSDs have been proposed. These models draw on work indicating that the two systems influence each other and interact to affect mood functioning. When dysregulated, reward and circadian system signaling may combine to form a positive feedback loop, whereby dysregulation in one system exacerbates dysregulation in the other. Project CREST (Circadian, Reward, and Emotion Systems in Teens) provides a first systematic test of reward-circadian dysregulation as a synergistic and dynamic vulnerability for first onset of BSD and increases in bipolar symptoms during adolescence. METHODS: This NIMH-funded R01 study is a 3-year prospective, longitudinal investigation of approximately 320 community adolescents from the broader Philadelphia area, United States of America. Eligible participants must be 13-16 years old, fluent in English, and without a prior BSD or hypomanic episode. They are being selected along the entire dimension of self-reported reward responsiveness, with oversampling at the high tail of the dimension in order to increase the likelihood of BSD onsets. At Times 1-6, every 6 months, participants will complete assessments of reward-relevant and social rhythm disruption life events and self-report and diagnostic assessments of bipolar symptoms and episodes. Yearly, at Times 1, 3, and 5, participants also will complete self-report measures of circadian chronotype (morningness-eveningness) and social rhythm regularity, a salivary dim light melatonin onset (DLMO) procedure to assess circadian phase, self-report, behavioral, and neural (fMRI) assessments of monetary and social reward responsiveness, and a 7-day ecological momentary assessment (EMA) period. During each EMA period, participants will complete continuous measures of sleep/wake and activity (actigraphy), a daily sleep diary, and three within-day (morning, afternoon, evening) measures of life events coded for reward-relevance and social rhythm disruption, monetary and social reward responsiveness, positive and negative affect, and hypo/manic and depressive symptoms. The fMRI scan will occur on the day before and the DLMO procedure will occur on the first evening of the 7-day EMA period. DISCUSSION: This study is an innovative integration of research on multi-organ systems involved in reward and circadian signaling in understanding first onset of BSD in adolescence. It has the potential to facilitate novel pharmacological, neural, and behavioral interventions to treat, and ideally prevent, bipolar conditions.

A meta-analysis and systematic review of single vs. multimodal neuroimaging techniques in the classification of psychosis.

BACKGROUND: Psychotic disorders are characterized by structural and functional abnormalities in brain networks. Neuroimaging techniques map and characterize such abnormalities using unique features (e.g., structural integrity, coactivation). However, it is unclear if a specific method, or a combination of modalities, is particularly effective in identifying differences in brain networks of someone with a psychotic disorder. METHODS: A systematic meta-analysis evaluated machine learning classification of schizophrenia spectrum disorders in comparison to healthy control participants using various neuroimaging modalities (i.e., T1-weighted imaging (T1), diffusion tensor imaging (DTI), resting state functional connectivity (rs-FC), or some combination (multimodal)). Criteria for manuscript inclusion included whole-brain analyses and cross-validation to provide a complete picture regarding the predictive ability of large-scale brain systems in psychosis. For this meta-analysis, we searched Ovid MEDLINE, PubMed, PsychInfo, Google Scholar, and Web of Science published between inception and March 13th 2023. Prediction results were averaged for studies using the same dataset, but parallel analyses were run that included studies with pooled sample across many datasets. We assessed bias through funnel plot asymmetry. A bivariate regression model determined whether differences in imaging modality, demographics, and preprocessing methods moderated classification. Separate models were run for studies with internal prediction (via cross-validation) and external prediction. RESULTS: 93 studies were identified for quantitative review (30 T1, 9 DTI, 40 rs-FC, and 14 multimodal). As a whole, all modalities reliably differentiated those with schizophrenia spectrum disorders from controls (OR = 2.64 (95%CI = 2.33 to 2.95)). However, classification was relatively similar across modalities: no differences were seen across modalities in the classification of independent internal data, and a small advantage was seen for rs-FC studies relative to T1 studies in classification in external datasets. We found large amounts of heterogeneity across results resulting in significant signs of bias in funnel plots and Egger's tests. Results remained similar, however, when studies were restricted to those with less heterogeneity, with continued small advantages for rs-FC relative to structural measures. Notably, in all cases, no significant differences were seen between multimodal and unimodal approaches, with rs-FC and unimodal studies reporting largely overlapping classification performance. Differences in demographics and analysis or denoising were not associated with changes in classification scores. CONCLUSIONS: The results of this study suggest that neuroimaging approaches have promise in the classification of psychosis. Interestingly, at present most modalities perform similarly in the classification of psychosis, with slight advantages for rs-FC relative to structural modalities in some specific cases. Notably, results differed substantially across studies, with suggestions of biased effect sizes, particularly highlighting the need for more studies using external prediction and large sample sizes. Adopting more rigorous and systematized standards will add significant value toward understanding and treating this critical population.

Broadening the scope: Multiple functional connectivity networks underlying threat and safety signaling.

Introduction: Threat learning and extinction processes are thought to be foundational to anxiety and fear-related disorders. However, the study of these processes in the human brain has largely focused on a priori regions of interest, owing partly to the ease of translating between these regions in human and non-human animals. Moving beyond analyzing focal regions of interest to whole-brain dynamics during threat learning is essential for understanding the neuropathology of fear-related disorders in humans. Methods: 223 participants completed a 2-day Pavlovian threat conditioning paradigm while undergoing fMRI. Participants completed threat acquisition and extinction. Extinction recall was assessed 48 hours later. Using a data-driven group independent component analysis (ICA), we examined large-scale functional connectivity networks during each phase of threat conditioning. Connectivity networks were tested to see how they responded to conditional stimuli during early and late phases of threat acquisition and extinction and during early trials of extinction recall. Results: A network overlapping with the default mode network involving hippocampus, vmPFC, and posterior cingulate was implicated in threat acquisition and extinction. Another network overlapping with the salience network involving dACC, mPFC, and inferior frontal gyrus was implicated in threat acquisition and extinction recall. Other networks overlapping with parts of the salience, somatomotor, visual, and fronto-parietal networks were involved in the acquisition or extinction of learned threat responses. Conclusions: These findings help confirm previous investigations of specific brain regions in a model-free fashion and introduce new findings of spatially independent networks during threat and safety learning. Rather than being a single process in a core network of regions, threat learning involves multiple brain networks operating in parallel coordinating different functions at different timescales. Understanding the nature and interplay of these dynamics will be critical for comprehensive understanding of the multiple processes that may be at play in the neuropathology of anxiety and fear-related disorders.

Reward and Immune Systems in Emotion (RISE) prospective longitudinal study: Protocol overview of an integrative reward-inflammation model of first onset of major depression in adolescence.

Background: Depression is associated with a reduced sensitivity to rewards and low reward-related brain function in cortico-striatal circuitry. A separate literature documents elevated peripheral inflammation in depression. Recently, integrated reward-inflammation models of depression have been proposed. These models draw on work indicating that peripheral inflammatory proteins access the brain, where they lower reward responsiveness. This blunted reward responsiveness is proposed to initiate unhealthy behaviors (substance use, poor diet), as well as sleep disruption and stress generation, which further heighten inflammation. Over time, dysregulation in reward responsiveness and immune signaling may synergize in a positive feedback loop, whereby dysregulation in each system exacerbates dysregulation in the other. Project RISE (Reward and Immune Systems in Emotion) provides a first systematic test of reward-immune dysregulation as a synergistic and dynamic vulnerability for first onset of major depressive disorder and increases in depressive symptoms during adolescence. Methods: This NIMH-funded R01 study is a 3-year prospective, longitudinal investigation of approximately 300 community adolescents from the broader Philadelphia area, United States of America. Eligible participants must be 13-16 years old, fluent in English, and without a prior major depressive disorder. They are being selected along the entire dimension of self-reported reward responsiveness, with oversampling at the low tail of the dimension in order to increase the likelihood of major depression onsets. At Time 1 (T1), T3, and T5, each a year apart, participants complete blood draws to quantify biomarkers of low-grade inflammation, self-report and behavioral measures of reward responsiveness, and fMRI scans of reward neural activity and functional connectivity. At T1-T5 (with T2 and T4 six months between the yearly sessions), participants also complete diagnostic interviews and measures of depressive symptoms, reward-relevant life events, and behaviors that increase inflammation. Adversity history is assessed at T1 only. Discussion: This study is an innovative integration of research on multi-organ systems involved in reward and inflammatory signaling in understanding first onset of major depression in adolescence. It has the potential to facilitate novel neuroimmune and behavioral interventions to treat, and ideally prevent, depression.

Personality predicts pre-COVID-19 to COVID-19 trajectories of transdiagnostic anxiety and depression symptoms.

This study aimed to characterize within-person pre-COVID-19 and coronavirus pandemic (COVID-19) transdiagnostic anxiety and depression symptom trajectories in emerging adults and determine the roles of neuroticism and behavioral activation in predicting these COVID-19-related changes. We recruited a sample of 342 emerging adults (aged 18-19 at baseline) who were screened on neuroticism and behavioral activation and completed symptom questionnaires on multiple occasions before and after the start of the pandemic. We examined estimates of the symptom factors of General Distress, Anhedonia-Apprehension, and Fears at each wave. The stress amplification model predicts a multiplicative neuroticism-adversity interaction with those high on neuroticism showing the greatest symptom increases to the pandemic. The stably elevated negative affect model is an additive model and predicts that persons high on neuroticism will display elevated symptoms at every wave. General Distress and Anhedonia-Apprehension showed large increases from the pre-COVID-19 to COVID-19 transition then decreased thereafter. The increase brought the average General Distress score to clinical levels at the first COVID-19 wave. There was a small decrease in Fears from the pre-COVID-19 to COVID-19 transition followed by a large increase. Thus, COVID-19 was associated with both increases in psychological symptoms and some resilience. Neuroticism positively predicted the pre-COVID-19 to COVID-19 transition change in Fears but was associated with a dampening of increases in General Distress and Anhedonia-Apprehension. The results disconfirmed the stress amplification model of neuroticism but partially supported the stably elevated negative affect model. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Insights from personalized models of brain and behavior for identifying biomarkers in psychiatry.

A main goal in translational neuroscience is to identify neural correlates of psychopathology ("biomarkers") that can be used to facilitate diagnosis, prognosis, and treatment. This goal has led to substantial research into how psychopathology symptoms relate to large-scale brain systems. However, these efforts have not yet resulted in practical biomarkers used in clinical practice. One reason for this underwhelming progress may be that many study designs focus on increasing sample size instead of collecting additional data within each individual. This focus limits the reliability and predictive validity of brain and behavioral measures in any one person. As biomarkers exist at the level of individuals, an increased focus on validating them within individuals is warranted. We argue that personalized models, estimated from extensive data collection within individuals, can address these concerns. We review evidence from two, thus far separate, lines of research on personalized models of (1) psychopathology symptoms and (2) fMRI measures of brain networks. We close by proposing approaches uniting personalized models across both domains to improve biomarker research.

Trauma History Predicts Decoupling of C-Reactive Protein and Somatic Symptoms: Results From a Cohort Study of Sexual and Gender Minority Youth.

OBJECTIVE: Systemic inflammation can induce somatic symptoms (e.g., pain, nausea, fatigue) through neuroimmune signaling pathways. Previous research suggests that early-life adversity amplifies signaling between peripheral inflammation and the brain. We therefore hypothesized that greater lifetime trauma exposure at baseline would predict stronger associations between systemic inflammation and somatic symptoms at 2.5-year follow-up in a cohort study of sexual and gender minority youth assigned male at birth ( n = 694). METHODS: We measured prior trauma exposure (lifetime count of traumatic event types reported at baseline), somatic symptoms (Brief Symptom Inventory somatization score), and systemic inflammation (C-reactive protein, interleukin 6, interleukin 1ß, and tumor necrosis factor α). All models included age, gender, education, recent trauma exposure, substance use, body mass index, and HIV status as covariates. RESULTS: Higher C-reactive protein concentrations were associated with greater somatic symptoms in the main effects model ( ß = 0.019, 95% confidence interval [CI] = 0.006 to 0.031). Contrary to our hypothesis, we observed a negative interaction between prior trauma exposure and C-reactive protein levels in predicting somatic symptoms ( ß = -0.017, 95% CI = -0.030 to -0.004). Higher C-reactive protein was associated with greater somatic symptoms only in participants without prior trauma exposure at baseline ( ß = 0.044, 95% CI = 0.026 to 0.062). Specificity analyses revealed similar patterns when nonsomatic depressive symptoms were used as the outcome variable. CONCLUSIONS: These results suggest that sexual and gender minority youth assigned male at birth who have a history of prior trauma exposure may experience decoupling of systemic inflammation and somatic symptoms. The absence of inflammation-related symptoms may prevent individuals from seeking necessary medical care by reducing interoceptive awareness of pathological states.