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Reduced real-life affective well-being and amygdala habituation in unmedicated community individuals at risk for depression and anxiety

  • Author Footnotes
    # These authors contributed equally
    Oksana Berhe
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    # These authors contributed equally
    Affiliations
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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  • Author Footnotes
    # These authors contributed equally
    Anna Höflich
    Footnotes
    # These authors contributed equally
    Affiliations
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany

    Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
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  • Carolin Mößnang
    Affiliations
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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  • Markus Reichert
    Affiliations
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany

    mental mHealth Lab, Chair of Applied Psychology, Department of Sport and Sport Science, Karlsruhe Institute of Technology, Karlsruhe, Germany

    Department of eHealth and Sports Analytics, Ruhr-University Bochum, Bochum, Germany
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  • Thomas Kremer
    Affiliations
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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  • Gabriela Gan
    Affiliations
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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  • Ren Ma
    Affiliations
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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  • Urs Braun
    Affiliations
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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  • Ulrich Reininghaus
    Affiliations
    Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany

    Centre for Epidemiology and Public Health, Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK

    ESRC Centre for Society and Mental Health, King’s College London, London, UK
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  • Ulrich Ebner-Priemer
    Affiliations
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany

    mental mHealth Lab, Chair of Applied Psychology, Department of Sport and Sport Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
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  • Author Footnotes
    # These authors contributed equally
    Andreas Meyer-Lindenberg
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    # These authors contributed equally
    Affiliations
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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  • Author Footnotes
    # These authors contributed equally
    Heike Tost
    Correspondence
    Corresponding Author: Heike Tost, MD PhD, Central Institute of Mental Health, Department of Psychiatry and Psychotherapy, Square J5, 68159 Mannheim, Germany.
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    # These authors contributed equally
    Affiliations
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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  • Author Footnotes
    # These authors contributed equally
Open AccessPublished:June 24, 2022DOI:https://doi.org/10.1016/j.bpsc.2022.06.009

      Abstract

      Background

      Early identification of risk for depression and anxiety disorders is important for prevention, but real-life affective well-being and its biological underpinnings in the population remain understudied. Here, we combined methods from epidemiology, psychology, ecological momentary assessment (EMA) and functional magnetic resonance imaging (fMRI) to study real-life and neural affective functions in individuals with subclinical anxiety and depression from a population-based cohort of young adults.

      Methods

      We examined psychological measures, real-life affective valence, fMRI amygdala habituation to negative affective stimuli and the relevance of neural readouts for daily-life affective function in 132 non-help-seeking community individuals. We compared psychological and EMA measures of 61 unmedicated individuals at clinical risk for depression and anxiety (operationalized as subthreshold depression and anxiety symptoms or a former mood or anxiety disorder) to those of 48 non-risk individuals and 23 persons with a mood or anxiety disorder. We studied risk-associated fMRI signals in subsamples with balanced sociodemographic and image quality parameters (26 non-risk, 26 at-risk persons).

      Results

      Compared to non-risk persons, at-risk individuals showed significantly decreased real-life affective valence (p = .038), reduced amygdala habituation (pFWE = .024, region of interest [ROI] corrected) and an intermediate psychological risk profile. Amygdala habituation predicted real-life affective valence in controls, but not in participants at risk (pFWE = .005, ROI corrected).

      Conclusions

      Our data suggest real-life and neural markers for affective alterations in unmedicated community individuals at risk for depression and anxiety and highlight the significance of amygdala habituation measures for the momentary affective experience in real-world environments.

      Keywords

      1. Introduction

      Early diagnosis, treatment and ideally prevention of psychiatric disorders in the population is desirable, but the existing knowledge about daily-life psychological and neural affective alterations in community-based individuals at mental health risk is limited (
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      Normal Versus Pathological Mood: Implications for Diagnosis.
      ). Meta-analyses suggest that about ten percent of all individuals in the general population experience subclinical symptoms of anxiety (
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      The prevalence and risk of developing major depression among individuals with subthreshold depression in the general population.
      ), and a significant proportion of these individuals will eventually transition to manifest psychiatric disorder (
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      Experiencing core symptoms of anxiety and unipolar mood disorders in late adolescence predicts disorder onset in early adulthood.
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      Subthreshold conditions as precursors for full syndrome disorders: a 15-year longitudinal study of multiple diagnostic classes.
      ). However, many persons fall below the binary threshold of current diagnostic systems, which define the difference between mental health and disorder based on the presence of a predefined number and duration of psychiatric symptoms. Consequently, community-based individuals with daily-life subclinical symptoms often remain unnoticed and not sufficiently attended to, both in clinical and research settings (
      • Rodriguez M.R.
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      Definitions and factors associated with subthreshold depressive conditions: a systematic review.
      ).
      From a community care and prevention standpoint, two groups of individuals are of particular relevance for the study of the underresearched “gray area” between mental health and disorder: Those who currently experience subthreshold symptoms but do not have a history of psychiatric illness, and those who have suffered from a psychiatric disorder in the past but do not currently experience any obvious clinical signs (
      • Ruscio A.M.
      Normal Versus Pathological Mood: Implications for Diagnosis.
      ). In this work, we define these groups as community-based individuals at mental health risk. We derive this view from studies and discourses in the field that have critically addressed the clinical validity of diagnostic boundaries between normal and pathological mood and anxiety experiences (
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      The reliability and validity of discrete and continuous measures of psychopathology: a quantitative review.
      ). Here, evidence suggests that there is a smooth transition between pathological depression and anxiety and milder emotional experiences (
      • Ruscio A.M.
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      ), and that subthreshold prodromal and residual states carry a substantial risk of progression to more severe states over the life course (
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      ,
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      ). In our definition of mental health risk in the community, we thus put forward (and later explore) the notion that both risk groups map to a shared (subclinical) continuum of clinically relevant phenomena in between mental health and disease. At the biological level, the grouping of the two at-risk groups is supported by studies showing comparable abnormalities of subthreshold prodromal and residual states in social reward processing (
      • Pechtel P.
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      Blunted reward responsiveness in remitted depression.
      ,
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      Blunted cardiovascular reactivity during social reward anticipation in subclinical depression.
      ), in cognitive domains such as cognitive control and executive function (
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      Cognitive impairment in depression: a systematic review and meta-analysis.
      ,
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      Cognitive impairment in the remitted state of unipolar depressive disorder: a systematic review.
      ,
      • Yang T.
      • Xiang L.
      Executive control dysfunction in subclinical depressive undergraduates: Evidence from the Attention Network Test.
      ) and resting-state functional connectivity (
      • Gao C.
      • Wenhua L.
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      • Ruan X.
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      Decreased subcortical and increased cortical degree centrality in a nonclinical college student sample with subclinical depressive symptoms: a resting-state fMRI study.
      ,
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      • Jiang Y.
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      State-independent alterations of intrinsic brain network in current and remitted depression.
      ). We further propose that the improved understanding of the daily-life psychological and neural characteristics of such risk states is important since the identification of salient risk markers can guide the development of novel early interventions at multiple, synergistic levels of influence, including in the areas of community mental health services, digital mental health and neurofeedback therapy (
      • Tost H.
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      • Meyer-Lindenberg A.
      Environmental influence in the brain, human welfare and mental health.
      ,
      • Reichert M.
      • Gan G.
      • Renz M.
      • Braun U.
      • Brussler S.
      • Timm I.
      • et al.
      Ambulatory assessment for precision psychiatry: Foundations, current developments and future avenues.
      ).
      Important leads for this work came from the recent literature, which emphasizes the unspecific nature of symptoms at subclinical stages of psychiatric illness (
      • Ruscio A.M.
      Normal Versus Pathological Mood: Implications for Diagnosis.
      ,
      • van Os J.
      The dynamics of subthreshold psychopathology: implications for diagnosis and treatment.
      ,
      • McGorry P.D.
      • Mei C.
      Ultra-high-risk paradigm: lessons learnt and new directions.
      ). In addition, dimensional models of psychopathology such as the CHARMS (clinical high at-risk mental state) concept served as important conceptual influence, which promote the transdiagnostic investigation of subclinical risk markers and mechanisms to inform future preventive and predictive approaches (
      • McGorry P.D.
      • Mei C.
      Ultra-high-risk paradigm: lessons learnt and new directions.
      ,
      • McGorry P.D.
      • Hartmann J.A.
      • Spooner R.
      • Nelson B.
      Beyond the "at risk mental state" concept: transitioning to transdiagnostic psychiatry.
      ,
      • Hartmann J.A.
      • Nelson B.
      • Spooner R.
      • Paul Amminger G.
      • Chanen A.
      • Davey C.G.
      • et al.
      Broad clinical high-risk mental state (CHARMS): Methodology of a cohort study validating criteria for pluripotent risk.
      ). Indeed, the existing data suggest significant alterations in the daily-life experience in persons at clinical risk for mood and anxiety disorders (
      • Bakker J.M.
      • Goossens L.
      • Kumar P.
      • Lange I.M.J.
      • Michielse S.
      • Schruers K.
      • et al.
      From laboratory to life: associating brain reward processing with real-life motivated behaviour and symptoms of depression in non-help-seeking young adults.
      ,
      • Goodman F.R.
      • Rum R.
      • Silva G.
      • Kashdan T.B.
      Are people with social anxiety disorder happier alone?.
      ,
      • Al-Dajani N.
      • Uliaszek A.A.
      The after-effects of momentary suicidal ideation: A preliminary examination of emotion intensity changes following suicidal thoughts.
      ). These include, among others, higher negative affect and lower hedonic capacity in real-world contexts, i.e., changes in daily experience that can be addressed with e-health based interventions. At the neural system level, altered habituation of the amygdala to threatening stimuli is a good candidate for mechanistic investigation. This view is supported by the demonstrated reliability of the phenotype (
      • Plichta M.M.
      • Grimm O.
      • Morgen K.
      • Mier D.
      • Sauer C.
      • Haddad L.
      • et al.
      Amygdala habituation: a reliable fMRI phenotype.
      ) as well as its documented role as an evolutionarily conserved neural mechanism for affective processing and behavioral adaptation (
      • Bordi F.
      • LeDoux J.
      Sensory tuning beyond the sensory system: an initial analysis of auditory response properties of neurons in the lateral amygdaloid nucleus and overlying areas of the striatum.
      ,
      • Breiter H.C.
      • Etcoff N.L.
      • Whalen P.J.
      • Kennedy W.A.
      • Rauch S.L.
      • Buckner R.L.
      • et al.
      Response and habituation of the human amygdala during visual processing of facial expression.
      ). Altered amygdala habituation has further been associated with a range of psychiatric disorders and related risk constellations (
      • Bilek E.
      • Itz M.L.
      • Stossel G.
      • Ma R.
      • Berhe O.
      • Clement L.
      • et al.
      Deficient Amygdala Habituation to Threatening Stimuli in Borderline Personality Disorder Relates to Adverse Childhood Experiences.
      ,
      • Avery S.N.
      • JU Blackford
      Slow to warm up: the role of habituation in social fear.
      ,
      • JU Blackford
      • Allen A.H.
      • Cowan R.L.
      • Avery S.N.
      Amygdala and hippocampus fail to habituate to faces in individuals with an inhibited temperament.
      ,
      • Kanske P.
      • Heissler J.
      • Schonfelder S.
      • Wessa M.
      Neural correlates of emotion regulation deficits in remitted depression: the influence of regulation strategy, habitual regulation use, and emotional valence.
      ,
      • Demers C.H.
      • Drabant Conley E.
      • Bogdan R.
      • Hariri A.R.
      Interactions Between Anandamide and Corticotropin-Releasing Factor Signaling Modulate Human Amygdala Function and Risk for Anxiety Disorders: An Imaging Genetics Strategy for Modeling Molecular Interactions.
      ), including in community-based samples and across a dimensional range of symptom severity for anxiety, depression, and stress-related disorders (
      • van den Bulk B.G.
      • Somerville L.H.
      • van Hoof M.J.
      • van Lang N.D.
      • van der Wee N.J.
      • Crone E.A.
      • et al.
      Amygdala habituation to emotional faces in adolescents with internalizing disorders, adolescents with childhood sexual abuse related PTSD and healthy adolescents.
      ,
      • Hein T.C.
      • Goetschius L.G.
      • McLoyd V.C.
      • Brooks-Gunn J.
      • McLanahan S.S.
      • Mitchell C.
      • et al.
      Childhood violence exposure and social deprivation are linked to adolescent threat and reward neural function.
      ,
      • Kim Y.J.
      • van Rooij S.J.H.
      • Ely T.D.
      • Fani N.
      • Ressler K.J.
      • Jovanovic T.
      • et al.
      Association between posttraumatic stress disorder severity and amygdala habituation to fearful stimuli.
      ,
      • Stevens J.S.
      • van Rooij S.J.H.
      • Stenson A.F.
      • Ely T.D.
      • Powers A.
      • Clifford A.
      • et al.
      Amygdala responses to threat in violence-exposed children depend on trauma context and maternal caregiving.
      ). However, studies in community-based individuals at clinical risk are still scarce and the interpretation of existing data is often complicated by concomitant, interfering factors such as the preferential inclusion of help-seeking individuals or the contamination of neural readouts by confounding factors (e.g., treatment effects). Also, barely any study on this topic to date seized the opportunity of contemporary multimodal ecological neuroscience approaches, which allow for the coordinated inquiry of clinical, neural and daily-life psychological functions in naturalistic cohorts (
      • Bakker J.M.
      • Goossens L.
      • Kumar P.
      • Lange I.M.J.
      • Michielse S.
      • Schruers K.
      • et al.
      From laboratory to life: associating brain reward processing with real-life motivated behaviour and symptoms of depression in non-help-seeking young adults.
      ).
      In the present study, we combined methods from epidemiology, clinical psychology, ecological momentary assessment (EMA) and functional MRI (fMRI) to study affective functions in community-based persons at clinical risk for depression and anxiety disorders derived from a population-based cohort of young, non-help-seeking adults. We used EMA with smartphone-based e-diaries to study momentary affective responses in real-world environments (
      • Tost H.
      • Reichert M.
      • Braun U.
      • Reinhard I.
      • Peters R.
      • Lautenbach S.
      • et al.
      Neural correlates of individual differences in affective benefit of real-life urban green space exposure.
      ), used fMRI and a well-established implicit emotion processing task (
      • Hariri A.R.
      • Mattay V.S.
      • Tessitore A.
      • Kolachana B.
      • Fera F.
      • Goldman D.
      • et al.
      Serotonin transporter genetic variation and the response of the human amygdala.
      ) to uncover alterations in amygdala signaling, and probed the significance of the identified neural phenotype for the affective experience in daily life.
      We studied EMA and questionnaire data in 61 unmedicated individuals at clinical risk, 48 demographically similar non-risk persons and 23 community-based individuals identified as fulfilling the criteria for a current mood or anxiety disorder. We derived all study participants from the same naturalistic population by random selection. We hypothesized that momentary affective valence in daily life would be significantly lower in the at-risk group and in the clinical group compared with the non-risk group. We further compared fMRI readouts between carefully matched subsamples of 26 unmedicated persons at clinical risk and 26 non-risk individuals to identify alterations in neural affective signaling related to community psychiatric risk in the absence of demographic, medication and image quality confounds. Here, we expected to see a blunted amygdala habituation in community-based persons at clinical risk reminiscent of that of clinical states (
      • Bilek E.
      • Itz M.L.
      • Stossel G.
      • Ma R.
      • Berhe O.
      • Clement L.
      • et al.
      Deficient Amygdala Habituation to Threatening Stimuli in Borderline Personality Disorder Relates to Adverse Childhood Experiences.
      ,
      • Avery S.N.
      • JU Blackford
      Slow to warm up: the role of habituation in social fear.
      ,
      • Kanske P.
      • Heissler J.
      • Schonfelder S.
      • Wessa M.
      Neural correlates of emotion regulation deficits in remitted depression: the influence of regulation strategy, habitual regulation use, and emotional valence.
      ). We further expected these neural affective signals to be relevant for the real-life affective experience of the non-risk individuals, the persons at clinical risk, or both groups. Beyond formal hypothesis testing, we further explored other EMA and questionnaire measures to yield novel insights into the nature and range of altered affective functions in community-based individuals at clinical risk.

      2. Methods and Materials

      2.1 Study participants and clinical assessment

      The Psychoepidemiological Center at the Central Institute of Mental Health in Mannheim, Germany, recruited a total of 349 individuals for this study. Participants were young adults in the age range of 18 to 28 years, which we randomly drew from local population registries based on a two-stage proportionally layered procedure (see (
      • Tost H.
      • Reichert M.
      • Braun U.
      • Reinhard I.
      • Peters R.
      • Lautenbach S.
      • et al.
      Neural correlates of individual differences in affective benefit of real-life urban green space exposure.
      ,
      • Reichert M.
      • Braun U.
      • Gan G.
      • Reinhard I.
      • Giurgiu M.
      • Ma R.
      • et al.
      A neural mechanism for affective well-being: Subgenual cingulate cortex mediates real-life effects of nonexercise activity on energy.
      ) for details). General exclusion criteria were the presence of a relevant medical or neurological disorder. We assessed past and current psychiatric symptoms by screening forms and MINI-DIPS interviews (

      Margraf J (1994): Diagnostisches Kurzinterview bei psychischen Störungen (MINI-DIPS). Berlin, Heidelberg, New York: Springer.

      ,
      • Margraf J.
      • Cwik J.C.
      • Pflug V.
      • Schneider S.
      Strukturierte klinische Interviews zur Erfassung psychischer Störungen über die Lebensspanne: Gütekriterien und Weiterentwicklungen der DIPS-Verfahren. [Structured clinical interviews for mental disorders across the life span: Psychometric quality and further developments of the DIPS open access interviews.].
      ,
      • Hibell B.
      • Guttormsson U.
      • Ahlström S.
      • Balakireva O.
      • Bjarnason T.
      • Kokkevi A.
      • et al.
      The 2007 ESPAD report.
      ) that were evaluated by two independent clinical raters (A.H., T.K.). The MINI-DIPS covers the most common mental disorders in adulthood according to ICD-10 and clarifies the presence of psychopathologically relevant experiences for the diagnostic categories. Based on these assessments, we defined four initial participants groups: 1) individuals with current psychiatric symptoms above the diagnostic threshold (clinical group, n = 23, mean age: 23.17 ± 2.68 years, 20 females), 2) individuals with one or more current symptoms on the mood-anxiety spectrum that did not qualify for the diagnosis of a psychiatric disorder (subclinical group, n = 40, mean age: 22.37 ± 2.55 years, 33 females), 3) clinically remitted individuals with a personal history of relevant psychiatric symptoms in the past who denied the current presence of psychopathologically relevant experiences (history group, n = 21, mean age: 22.82 ± 3.01 years, 12 females), and 4) healthy non-risk individuals that were free of any current or former psychiatric symptoms, diagnosis or treatment (healthy non-risk group, n = 48, 21.86 ± 1.56 years, 39 females) that we derived from a larger sample of non-risk individuals.
      We later combined the individuals of the subclinical and history groups to a joint group of community-based individuals at mental health risk since we expected that both groups would map on a shared continuum of affective alterations in between mental health and disease (
      • Hartmann J.A.
      • Nelson B.
      • Spooner R.
      • Paul Amminger G.
      • Chanen A.
      • Davey C.G.
      • et al.
      Broad clinical high-risk mental state (CHARMS): Methodology of a cohort study validating criteria for pluripotent risk.
      ) (see Results and Supplemental Table S1). None of the at-risk individuals had received psychotropic medication in the preceding 12 months of study and only one of the persons was currently in formal psychiatric care (Supplemental Table S2). We then drew a sample of 48 individuals from the total pool of 264 identified non-risk individuals using internal software to achieve a non-risk group with a comparable distribution of basic sociodemographic characteristics (i.e., age, gender, education) to the combined at-risk group.
      After study inclusion, we first collected questionnaire measures on time-stable psychological constructs. Subsequently, we collected EMA data over 7 days in everyday life. We performed the neuroimaging examination of the study participants immediately after the end of the EMA study week (i.e., 1.50 ± 1.36 (Min/Max=0/6) days after EMA completion). We compared the acquired questionnaire and e-diary measures between the groups to identify psychological and real-life indicators of community mental health risk (Table 1). For the ensuing neuroimaging analysis of risk indicators, we compared subgroups of 26 at-risk and 26 non-risk individuals with available neuroimaging data that we carefully matched for a broader panel of sociodemographic attributes and data quality indicators known for impacting mental health-related neural readouts (e.g., fMRI task performance, fMRI image quality metrics [including tSNR, spikes, translation/rotation metrics and frame-wise displacement], socioeconomic status, current urbanicity, adverse childhood experiences, see Supplemental Table S3) (
      • Tost H.
      • Champagne F.A.
      • Meyer-Lindenberg A.
      Environmental influence in the brain, human welfare and mental health.
      ).
      Table 1Sample description for community subject groups
      Non-risk group (n=48)Clinical at-risk group (n=61)Clinical group (n= 23)ANOVA / χ2/H-test/MLAaNon-risk vs. RiskRisk vs. ClinicalNon-risk vs. Clinical
      M ± SD / countmin/maxnM ± SD / countmin/maxnM ± SD / countmin/maxnß-valuep valuep valuebp valuebp valueb
      Demographic data
      Age (year)21.86 ±1.5618.14/25.584822.53 ±2.718.10/27.836123.17 ±2.6818.88/27.30232.630.076---
      Sex (male/female)9/39N/A4816/45N/A613/20N/A232.010.366---
      Education (years)12.48 ± 1.2910/164812.68±1.788/166012.61±1.6710/16230.2120.784---
      Socioeconomic status (SES)12.80± 3.006.20/19.404813.47± 3.316.90/20.206111.20± 2.885.50/15.30234.400.0140.5120.0090.088
      Psychological data
      Trait anxiety (STAI-T, sum)33.00±6.7820/504739.82±9.6021/666052.09±10.7134/712335.52<0.001<0.001<0.001<0.001
      Mental wellbeing (WHO-5, sum)16.52±4.1510/254815.19±4.574/235911.05±5.772/23209.91<0.0010.2590.0190.002
      Satisfaction with life (SWLS)27.74±4.3514/354725.77±6.099/346021.00±8.725/32239.95<0.0010.1280.0570.04
      BCOPE-adaptive coping42.72±5.1031/524741.33±7.7421/566040.52±7.4627/54232.160.336---
      BCOPE-maladaptive coping21.26±3.9315/324723.68±4.4515/365925.26±4.2818/36237.280.0010.0120.3930.001
      Self-efficacy (SWE, sum)29.85 ±4.2421/384829.05 ±4.3817/406025.91 ±5.4719/35236.040.0030.600.0490.012
      Loneliness (UCLA, mean)29.37 ±6.9420/484834.32 ±11.2220/766039.91 ±16.7420/87237.270.0020.0160.3140.020
      Optimism (LOT-R, optimism sum)16.98 ±3.479/234815.60 ±4.484/236012.04 ±5.440/222310.14<0.0010.1740.0230.001
      Perceived social support (BSSS, sum)31.17 ± 1.6325.00/32.004829.85±3.1619.00/32.006027.69±5.7615/32238.36<0.0010.1350.0300.001
      Sense of coherence (SOC, sum)152.79 ± 17.73115/18948138.76±20.9088/18159114.95±23.1764/1522226.65<0.0010.001<0.001<0.001
      Daily Stress (ABF)2.04±0.631.09/3.88422.50±0.761.09/4.75472.90±1.021.84/5.42158.36<0.0010.0070.3600.017
      Early adversity (CTS)5.96±1.995/16486.65±2.085/16608.45±3.915/17227.830.0010.190.1190.023
      EMAc
      Valence (MDBF)d75.82±11.6348.99/99.144769.04±10.1847.88/89.596160.10±14.8528.19/84.322210.90<0.0010.0380.012<0.001
      Energetic arousal (MDBF)d60.76±12.7627.96/85.494756.00±11.3530.72/79.586149.89±11.2130.31/70.68224.300.0160.2540.2770.014
      Calmness (MDBF)d72.16±13.0436.60/98.594766.48±11.0245.38/89.196157.43±14.3727.39/86.71228.47<0.0010.1640.016<0.001
      Alone (alone/not alone)34/72NA4731/64NA6131/61NA220.400.673---
      Rather be aloned11.20±9.590.73/38.434716.32±14.341.57/65.146125.7±20.341.21/63.92228.280.0020.3150.0090.001
      Don’t like the companyd10.70±12.990.63/77.174714.14±14.340.70/65.806117.81±14.092.91/59.92224.180.0180.390.1990.014
      Positive event appraisald23.14±11.312.54/48.684724.97±14.291.39/56.046123.35±10.692.36/44.84220.260.771---
      Negative event appraisald8.91±6.180.67/33.224712.78±7.360.68/32.566117.16±11.456.32/56.63226.440.0020.1190.1100.002
      Affective (in)stability (valence MSSD)235,24±166,311.07/793.7547337.06±219.3516.75/897.1561592.98±479.7075.49/2141.76226.530.0020.8870.0020.007
      E-diary prompts per day12.56±1.329/154712.29±1.0710/156112.56±1.2910/15220.7440.453---
      E-diary Compliance (%)f85.61±11.4957.58/1004777.81±19.0032.93/1006173.79±19.5932.91/100224.2710.0110.0541.0000.022
      Broad-based changes in the clinical group on most outcome measures compared with limited changes in the at-risk group in areas involving stress experience, negative emotions, and personal coping skills. For details on the psychological questionnaires including acronyms, see Supplemental Table S4. Abbreviations: M = mean, SD = standard deviation, n = number of participants with available data, ANOVA = univariate analysis of variance, χ2 = chi-squared test, H-test - Kruskal-Wallis Test. MLA = multilevel analysis controlling for time of the day and time of the day-squared (level 1); and controlling for differences in compliance (level 2), MSSD valence = mean square of successive differences of valence ratings.
      aEmployed tests: χ2 tests for group comparisons with categorical variables, ANOVA and Tukey tests for group comparisons and variables with equal variance and normal distribution, Welch-ANOVA and Games-Howell tests for group comparisons with normally distributed variables with unequal variance (as identified by Levene-test), Kruskal-Wallis and Dunn tests for group comparisons with not-normally distributed variables with (un)equal variance.
      bAll p-values of post-hoc pairwise group comparisons are Bonferroni corrected for multiple group comparisons.
      cAggregation of EMA indices within and between subjects for use for sample description only.
      dmean/day/participant
      enumber of prompts participants have been alone out of all prompts across 7 days of measurement
      fPercent of answered prompts.
      The fMRI at-risk group included 18 individuals from the subclinical group and 8 individuals from the history group. All enrolled study participants provided written informed consent for a protocol approved by the Medical Ethics Committee II of the Medical Faculty Mannheim at the Ruprecht-Karls-University in Heidelberg, Germany.

      Psychological data acquisition and analysis

      We acquired a battery of well-established psychological and demographic questionnaires quantifying socioeconomic status (
      • Lampert T.
      • Kroll L.E.
      • Müters S.
      • Stolzenberg H.
      Measurement of the socioeconomic status within the German Health Update 2009 (GEDA).
      ), perceived social status (
      • Goodman E.
      • Adler N.E.
      • Kawachi I.
      • Frazier A.L.
      • Huang B.
      • Colditz G.A.
      Adolescents' perceptions of social status: development and evaluation of a new indicator.
      ,
      • Schweiger J.I.
      • Capraz N.
      • Akdeniz C.
      • Braun U.
      • Ebalu T.
      • Moessnang C.
      • et al.
      Brain structural correlates of upward social mobility in ethnic minority individuals.
      ), degree of current urbanicity (
      • Lederbogen F.
      • Kirsch P.
      • Haddad L.
      • Streit F.
      • Tost H.
      • Schuch P.
      • et al.
      City living and urban upbringing affect neural social stress processing in humans.
      ), trait anxiety (

      Laux L, Glanzmann P, Schaffner P, C. S (1981): Das State-Trait-Angstinventar. Göttingen: Hogrefe.

      ), loneliness (
      • Döring N.
      • Bortz J.
      Psychometrische Einsamkeitsforschung: Deutsche Neukonstruktion der UCLA Loneliness Scale.
      ), self-efficacy (

      Jerusalem M, Schwarzer R (1992): Self-efficacy as a resource factor in stress appraisal processes. Self-efficacy: Thought control of action. Washington, DC: Hemisphere, pp 195-213.

      ), sense of coherence (
      • Hannöver W.
      • Michael A.
      • Meyer C.
      • Rumpf H.-J.
      • Hapke U.
      • John U.
      Die Sense of coherence Scale von Antonovsky und das Vorliegen einer psychiatrischen Diagnose.
      ), optimism (
      • Herzberg P.Y.
      • Glaesmer H.
      • Hoyer J.
      Separating Optimism and Pessimism: A robust psychometric analysis of the revised Life Orientation Test (LOT-R).
      ), perceived mental wellbeing (
      • Topp C.W.
      • Ostergaard S.D.
      • Sondergaard S.
      • Bech P.
      The WHO-5 Well-Being Index: a systematic review of the literature.
      ), satisfaction with life (
      • Glaesmer H.
      • Grande G.
      • Braehler E.
      • Roth M.
      The German Version of the Satisfaction with Life Scale (SWLS): Psychometric Properties, Validity, and Population-Based Norms.
      ), perceived daily hassles (
      • Traue H.C.
      • Hrabal V.
      • Kosarz P.
      ), chronic stress (

      Schulz P, Schlotz W, Becker P (2004): Trierer Inventar zum Chronischen Stress (TICS). Göttingen: Hogrefe.

      ), coping strategies (
      • Carver C.S.
      You want to measure coping but your protocol's too long: consider the brief COPE.
      ,
      • Knoll N.
      • Rieckmann N.
      • Schwarzer R.
      Coping as a mediator between personality and stress outcomes: a longitudinal study with cataract surgery patients.
      ), perceived social support (
      • Schulz U.
      • Schwarzer R.
      Soziale Unterstützung bei der Krankheitsbewältigung. Die Berliner Social Support Skalen (BSSS).
      ) and retrospective self-ratings of adverse childhood experiences (
      • Glaesmer H.
      • Schulz A.
      • Hauser W.
      • Freyberger H.J.
      • Brahler E.
      • Grabe H.J.
      The childhood trauma screener (CTS) - development and validation of cut-off-scores for classificatory diagnostics.
      ). We provide further details on the assessed questionnaires in Supplemental Table S4. We assessed group differences in SPSS (IBM, SPSS, version 25) using variable type and distribution appropriate tests (i.e., χ2 test, classical analysis of variance (ANOVA), Welch’s ANOVA, Kruskal-Wallis H test, see Table 1 for details).

      E-diary data acquisition and analysis

      We assessed e-diary-ratings for 7 consecutive days in daily life with study smartphones (Motorola Moto G, Motorola Mobility) and a flexible time and location-based sampling scheme with 9 to 23 prompts per day in between 7:30 AM and 22:30 PM (minimum/maximum interval: 40/100 minutes) as previously detailed (
      • Tost H.
      • Reichert M.
      • Braun U.
      • Reinhard I.
      • Peters R.
      • Lautenbach S.
      • et al.
      Neural correlates of individual differences in affective benefit of real-life urban green space exposure.
      ,
      • Reichert M.
      • Braun U.
      • Gan G.
      • Reinhard I.
      • Giurgiu M.
      • Ma R.
      • et al.
      A neural mechanism for affective well-being: Subgenual cingulate cortex mediates real-life effects of nonexercise activity on energy.
      ,
      • Gan G.
      • Ma R.
      • Reichert M.
      • Giurgiu M.
      • Ebner-Priemer U.W.
      • Meyer-Lindenberg A.
      • et al.
      Neural Correlates of Affective Benefit From Real-life Social Contact and Implications for Psychiatric Resilience.
      ). Our primary interest was to capture potential alterations in real-life affective valence in clinically at-risk individuals. For this, we used a well-known short scale for EMA with established psychometric properties (
      • Wilhelm P.
      • Schoebi D.
      Assessing mood in daily life: Structural validity, sensitivity to change, and reliability of a short-scale to measure three basic dimensions of mood.
      ) capturing within-subject fluctuations in real-life affective valence with the two bipolar items “content” to “discontent” (German translation: “zufrieden” – “unzufrieden”) and “unwell” to “well” (German translation: “unwohl” – “wohl”) presented at the edges of two computerized visual analogue scales with sliding locators (score range of 0 to 100). We instructed participants to place, upon each e-diary prompt, the locators at the scale positions representing their momentary affective state. We averaged the two item scores for use as dependent variable in our multilevel analyses.
      For exploratory analysis, we further calculated an established EMA measure of daily-life affective (in)stability (i.e., the mean square of successive differences in valence, MSSD (
      • Trull T.J.
      • Lane S.P.
      • Koval P.
      • Ebner-Priemer U.W.
      Affective Dynamics in Psychopathology.
      )) and assessed e-diary items quantifying momentary calmness and energetic arousal, social contact (
      • Gan G.
      • Ma R.
      • Reichert M.
      • Giurgiu M.
      • Ebner-Priemer U.W.
      • Meyer-Lindenberg A.
      • et al.
      Neural Correlates of Affective Benefit From Real-life Social Contact and Implications for Psychiatric Resilience.
      ), social anhedonia (
      • Gan G.
      • Ma R.
      • Reichert M.
      • Giurgiu M.
      • Ebner-Priemer U.W.
      • Meyer-Lindenberg A.
      • et al.
      Neural Correlates of Affective Benefit From Real-life Social Contact and Implications for Psychiatric Resilience.
      ), and the appraisal of negative and positive events (
      • Wichers M.C.
      • Barge-Schaapveld D.Q.
      • Nicolson N.A.
      • Peeters F.
      • de Vries M.
      • Mengelers R.
      • et al.
      Reduced stress-sensitivity or increased reward experience: the psychological mechanism of response to antidepressant medication.
      ,
      • Koval P.
      • Brose A.
      • Pe M.L.
      • Houben M.
      • Erbas Y.
      • Champagne D.
      • et al.
      Emotional inertia and external events: The roles of exposure, reactivity, and recovery.
      ). E-diaries and sampling strategy were implemented with the ambulatory assessment software movisensXS (version 0.6.3658, movisens GmbH, Germany). We used multilevel models in SAS (version 9.4., SAS Institute Inc., Cary, NC, USA) to test for group differences, thereby nesting within-subject e-diary assessments (level 1) within participants (level 2), and using a categorical group variable (level 2) (

      Bolger N, Laurenceau J-P (2013): Intensive longitudinal methods: An introduction to diary and experience sampling research. New York: The Guilford Press.

      ). We provide further details on the EMA acquisition and analysis methods in the Supplemental Information. All participant groups surpassed an average compliance rate of 70% and we covaried for between-group differences in compliance in our multilevel analysis (Table S5).

      fMRI data acquisition and preprocessing

      We performed blood oxygen level–dependent fMRI on a 3T MRI scanner (Siemens Trio, Erlangen, Germany) using a well-established implicit emotion processing paradigm with two task conditions (emotional face matching, shapes matching) (
      • Hariri A.R.
      • Mattay V.S.
      • Tessitore A.
      • Kolachana B.
      • Fera F.
      • Goldman D.
      • et al.
      Serotonin transporter genetic variation and the response of the human amygdala.
      ) providing reliable measures of amygdala habituation (
      • Plichta M.M.
      • Grimm O.
      • Morgen K.
      • Mier D.
      • Sauer C.
      • Haddad L.
      • et al.
      Amygdala habituation: a reliable fMRI phenotype.
      ). We processed and analyzed the fMRI data with SPM12 (www.fil.ion.ucl.ac.uk/spm) implemented in MATLAB (The MathWorks, Inc., Natick, MA). Data preprocessing consisted of standard procedures. We provide further methods details on the employed fMRI sequence, paradigm and preprocessing routines in the Supplemental Information.

      Amygdala activation and habituation analysis

      fMRI data analysis consisted of a two-level procedure. At the first level, we defined a general linear model (GLM) for each subject that included the boxcar reference vectors for the task blocks of the two conditions (convolved with the standard SPM hemodynamic response function) and the 6 head motion parameters from the realignment step (covariates of non-interest). During model estimation, we defined a high-pass filter with a cut-off frequency of 262s to remove low frequency signal components and used first-order autoregressive (AR[1]) modeling to correct for temporal autocorrelations. We computed individual maps of voxel-wise habituation indices as previously described (
      • Plichta M.M.
      • Grimm O.
      • Morgen K.
      • Mier D.
      • Sauer C.
      • Haddad L.
      • et al.
      Amygdala habituation: a reliable fMRI phenotype.
      ) by calculating the mean response amplitude difference between the first and the last block of the face matching condition ([block 1 > block 4]. At the second level, we entered these maps into univariate ANOVA models with group (clinical at-risk, non-risk) as factor. Consistent with our previous work (
      • Bilek E.
      • Itz M.L.
      • Stossel G.
      • Ma R.
      • Berhe O.
      • Clement L.
      • et al.
      Deficient Amygdala Habituation to Threatening Stimuli in Borderline Personality Disorder Relates to Adverse Childhood Experiences.
      ), we defined a group contrast to test for the hypothesized amygdala habituation deficits in community-based individuals at clinical risk (clinical at-risk < non-risk). We further tested for general and group-specific associations between daily-life affective valence and amygdala habituation estimates. For this we used univariate ANOVA models with the mean individual EMA-derived valence measures and a corresponding interaction term (group x valence) as regressors of interest, respectively.

      fMRI Statistical Inference

      We assessed statistical significance at p < 0.05, peak voxel-level familywise error (FWE) corrected for multiple comparisons within an a priori defined anatomical region of interest (ROI) mask of the right amygdala derived from the Wake Forest University (WFU) PickAtlas (
      • Maldjian J.A.
      • Laurienti P.J.
      • Kraft R.A.
      • Burdette J.H.
      An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets.
      ). As in our previous work (
      • Bilek E.
      • Itz M.L.
      • Stossel G.
      • Ma R.
      • Berhe O.
      • Clement L.
      • et al.
      Deficient Amygdala Habituation to Threatening Stimuli in Borderline Personality Disorder Relates to Adverse Childhood Experiences.
      ), we chose the right amygdala as a priori ROI for hypothesis testing since the literature suggests a different functional role and habituation rate for the right amygdala, with a specialization for the rapid and dynamical detection of affective stimuli (
      • Wright C.I.
      • Fischer H.
      • Whalen P.J.
      • McInerney S.C.
      • Shin L.M.
      • Rauch S.L.
      Differential prefrontal cortex and amygdala habituation to repeatedly presented emotional stimuli.
      ,
      • Baas D.
      • Aleman A.
      • Kahn R.S.
      Lateralization of amygdala activation: a systematic review of functional neuroimaging studies.
      ,
      • Phillips M.L.
      • Medford N.
      • Young A.W.
      • Williams L.
      • Williams S.C.
      • Bullmore E.T.
      • et al.
      Time courses of left and right amygdalar responses to fearful facial expressions.
      ) and a higher retest reliability of habituation estimates (
      • Plichta M.M.
      • Grimm O.
      • Morgen K.
      • Mier D.
      • Sauer C.
      • Haddad L.
      • et al.
      Amygdala habituation: a reliable fMRI phenotype.
      ).

      3. Results

      Psychological questionnaire data

      Descriptive analysis of psychological data revealed a regular pattern across variables, with the group means of the at-risk group mapping in between those of the non-risk group and the clinical group, respectively. Inferential statistics revealed significant differences of the at-risk group for daily hassles, maladaptive coping and perceived loneliness compared to the non-risk group (all ps < .016, all reported p values are Bonferroni corrected for multiple group comparisons) but not the clinical group (all ps > .31). In contrast, in other psychological variables such as perceived mental well-being, satisfaction with life, optimism, self-efficacy and social support at-risk persons did not differ significantly from the non-risk group (all ps > .12) but differed significantly from the clinical group (all ps < .05). For trait anxiety and dispositional sense of coherence, the at-risk individuals displayed fully intermediate properties, in that they differed significantly from both the non-risk group and the clinical group (all ps < .001). We provide further statistical details in Table 1. There were no significant group differences in psychological questionnaire data between the community-based subgroups at mental health risk (i.e., subclinical group vs. history group, see Supplemental Table S2 for details).

      Daily-life ecological momentary assessments

      Daily-life affective valence in the at-risk individuals was significantly lower than that of the non-risk group (p = .038, all p values are Bonferroni corrected for multiple group comparisons) and significantly higher than that of the clinical group (p = .012) (Figure 2B). Exploratory analyses suggested no group differences in the frequency of social contacts and the appraisal of positive events (all reported ps > .67). We further did not detect any group differences between the at-risk group and the non-risk group for affective (in)stability, negative event appraisal, liking of social contact, preference of being alone and momentary feelings of calmness and energetic arousal (all ps > .11). In contrast to this, individuals in the clinical group exhibited widespread changes in these variables, which distinguished this group from both the at-risk and non-risk groups. We provide further statistical details in Table 1 and Supplemental Table S5.
      Figure thumbnail gr1
      Figure 1Group differences in amygdala reactivity changes to threatening stimuli over the course of the functional magnetic resonance imaging experiment. Significant difference in amygdala habituation manifesting as a rapid signal decrement to successive emotional stimulation blocks in the community-based individuals not at clinical risk (non-risk group) but not the community-based at clinical risk (at-risk group) (t = 3.03, pFWE = .024). The functional map is thresholded at p = .005, uncorrected for illustration purposes, and is displayed on the coronal section of a structural-template magnetic resonance image. The plot shows habituation estimates (and standard errors of the mean) of the peak voxel in the right amygdala for each fMRI task block and group, respectively. FWE, family-wise error. MNI, Montreal Neurological Institute standard space.
      Figure thumbnail gr2
      Figure 2Study methods and amygdala habituation−affective valence associations. (A) Illustration of the smartphone-based assessment of affective valence in daily life in connection with a person's movement pattern in downtown Mannheim. Left: Visualization of the affective valence and social contact e-diary items. Smartphone image by ElisaRiva (http://www.pixabay.com). Right: White check marks on a red background displayed on the route symbolize positions where e-diary assessments were prompted (for illustration purposes, not real study participant). (B) Significant group differences in EMA valence between community-based individuals not at clinical risk, those at clinical risk, and those with a current mood or anxiety disorder. Community-based individuals at clinical risk display significantly lower valence levels than non-risk persons, and significantly higher valence levels than individuals in the clinical group; error bars display standard error (SE) from the MLM (for details see ). (C, D) Differential association of amygdala habituation and affective valence in daily life in community persons at clinical risk compared to those not at risk (t = 3.70, pFWE = .005). The functional map in panel (C) is thresholded at p = .005, uncorrected for illustration purposes, and is displayed on the coronal section of a structural-template magnetic resonance image. The scatterplot in panel (D) depicts the associations of the habituation estimates (extracted from the amygdala peak voxel) and valence values for the two groups. The reported interaction analysis finding in imaging space also survived FWE correction after excluding one outlier from the analysis. FWE, family-wise error. MNI, Montreal Neurological Institute standard space.

      Amygdala habituation analyses

      Comparison of the at-risk group and the non-risk group confirmed a significant reduction of right amygdala habituation to repeated negative affective stimuli in the at-risk individuals (t = 3.03, pFWE = .024, all reported p values are peak-level corrected for region of interest) (Figure 1B). This finding also survived correction for a bilateral amygdala mask (t = 3.03, pFWE = .047). In the non-risk individuals, data inspection suggested a high initial responsivity of the right amygdala followed by a rapid decline in activity with successive emotional block repetitions, whereas in the at-risk individuals the amygdala responsivity appeared blunted and uniform over time (Figure 1C). A regression analysis with daily-life affective valence scores as a predictor did not provide evidence for a significant association with amygdala habituation across all individuals (t = 1.96, pFWE = .330). However, we detected a significant group by EMA valence interaction effect on right amygdala habituation (t = 3.70, pFWE = .005; after correction for a bilateral amygdala mask: t = 3.70, pFWE = .009) (Figure 2). Post-hoc regression analysis confirmed that higher right amygdala habituation was significantly related to higher daily-life affective well-being in the non-risk group (t = 3.33, pFWE = .012; after correction for a bilateral amygdala mask: t = 3.33, pFWE = .024) but not in the at-risk group (t = 0.96, pFWE = 0.76).

      Discussion

      In this study, we took a multimodal ecological neuroscience approach to identify psychological, real world, and neural markers of altered affective function in unmedicated individuals at clinical risk for mood and anxiety disorders drawn from a population-based cohort of young adults. Specifically, we aimed to characterize the psychological profile of at-risk individuals in the community, determine the nature and extent of their current affective alterations in daily life, and examine the relevance of the neural signals examined to real-world affective experience. We obtained several interesting results, which we discuss below.
      In terms of psychological profile, we posited that community-based individuals at clinical risk are on a continuum of change that spans between healthy non-risk individuals and individuals with a current manifest disorder. At the descriptive level, we observed just this: mean scores for the risk group were intermediate between those of the other two groups in all variables, and our supplemental analysis revealed no significant differences between the “history” and “subclinical” subgroups, which we combined into one risk group. At the same time, the areas in which at-risk persons differed significantly from the non-risk individuals were relatively specific, while the group with a manifest disorder showed clear changes in almost all of the areas examined. Specifically, significant differences in risk individuals clustered around variables indicating heightened stress awareness, a tendency to negative emotions and a limited ability to use personal resources to cope with such experiences. These focal differences presented against a background of mostly unremarkable functions and resources, such as preserved satisfaction with life, optimism and social support. We conclude from these data that psychological alteration in the community is a gradual phenomenon, and that the psychological profile of individuals with subclinical mood and anxiety symptoms is comparable to that of fully remitted individuals with a previous mood or anxiety disorder. Further, the clearly salient psychological deficits of community-based individuals at clinical risk appear selective and involve the processing of stress and negative emotions.
      Regarding the nature and extent of daily life impairments, we hypothesized that young community-based individuals with subclinical depression and anxiety would show a significant reduction in affective valence, and our study results confirmed this assumption. Although there are few comparable studies to date, this finding aligns well with our own findings on the impact of psychiatric risk and resilience factors on real-life affective valence (
      • Tost H.
      • Reichert M.
      • Braun U.
      • Reinhard I.
      • Peters R.
      • Lautenbach S.
      • et al.
      Neural correlates of individual differences in affective benefit of real-life urban green space exposure.
      ,
      • Gan G.
      • Ma R.
      • Reichert M.
      • Giurgiu M.
      • Ebner-Priemer U.W.
      • Meyer-Lindenberg A.
      • et al.
      Neural correlates of affective benefit from real-life social contact and implications for psychiatric resilience.
      ) and changes in emotional experience of children and adolescents with subclinical symptoms reported in other community-based EMA studies (
      • Frost A.
      • Hoyt L.T.
      • Chung A.L.
      • Adam E.K.
      Daily life with depressive symptoms: Gender differences in adolescents' everyday emotional experiences.
      ,
      • Scott L.N.
      • Wright A.G.C.
      • Beeney J.E.
      • Lazarus S.A.
      • Pilkonis P.A.
      • Stepp S.D.
      Borderline personality disorder symptoms and aggression: A within-person process model.
      ,
      • Scott L.N.
      • Stepp S.D.
      • Hallquist M.N.
      • Whalen D.J.
      • Wright A.G.C.
      • Pilkonis P.A.
      Daily shame and hostile irritability in adolescent girls with borderline personality disorder symptoms.
      ). In relative terms, our exploratory analysis of other EMA outcomes further suggests selective changes in the daily-life experience of community-based individuals at clinical risk. Precisely, while the clinical group differed significantly in almost all measures recorded, including those indicative of daily-life depressed mood, reduced drive, social anhedonia, affective instability, and increased stress experience, the decrease in affective valence in the at-risk subjects seemed to occur against a background of otherwise unremarkable real-life functions. Together with the psychological profile elaborated above, this suggests that community-based individuals at increased risk for mood and anxiety disorders exhibit selective risk phenotypes on the behavioral and experiential level, including limited personal resources to cope with stress-associated experiences and a reduction in affective valence in daily life. In addition to traditional psychotherapy, deficits in the daily-life experience can be addressed with targeted ecological moment interventions (EMI), especially when the real-world “risk marker” or target phenomenon is known, as in this case (
      • Myin-Germeys I.
      • Klippel A.
      • Steinhart H.
      • Reininghaus U.
      Ecological momentary interventions in psychiatry.
      ).
      At the neural systems level, our results identify reduced amygdala habituation in community-based individuals with subclinical depression and anxiety. Specifically, whereas the non-risk group showed a decrease in estimated amygdala response of about 60%, it was only 1% for the risk subjects (emotional stimulation block 1 - 4). The amygdala plays an evolutionarily conserved role in threat processing (
      • LeDoux J.
      The amygdala.
      ) and the robust habituation phenotype studied (
      • Plichta M.M.
      • Grimm O.
      • Morgen K.
      • Mier D.
      • Sauer C.
      • Haddad L.
      • et al.
      Amygdala habituation: a reliable fMRI phenotype.
      ) reflects a basic neural plasticity mechanism that supports a basic and innate form of learning. Specifically, it protects the organism from repeatedly responding to threat-associated stimuli with no meaningful consequences for survival, thereby freeing up important neural and behavioral resources for more pressing tasks. The detected difference in habituation in community-based individuals at risk is thus suggestive of a neural plasticity-related alteration in the affective processing of environmental stimuli in this group. In our non-risk individuals, amygdala response habituated as expected and predicted increased momentary affective valence, indicating the relevance of this neurofunction in daily life. This link was not found in our community-based individuals at clinical risk, whose diminished real-life affective well-being was unrelated to amygdala habituation. Although further experiments will be necessary to determine the origin of this dissociation, we speculate that reduced biological plasticity in the amygdala may require alternative regulatory strategies to deal with perceived threat (e.g., cognitive appraisal), which may disrupt the direct link of amygdala habituation to real-life affective well-being. Deficient amygdala habituation as such is unlikely specific to certain psychiatric disorders (
      • Bilek E.
      • Itz M.L.
      • Stossel G.
      • Ma R.
      • Berhe O.
      • Clement L.
      • et al.
      Deficient Amygdala Habituation to Threatening Stimuli in Borderline Personality Disorder Relates to Adverse Childhood Experiences.
      ,
      • Tam F.I.
      • King J.A.
      • Geisler D.
      • Korb F.M.
      • Sareng J.
      • Ritschel F.
      • et al.
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      ) or sources of illness risk (
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      • Ma R.
      • Berhe O.
      • Clement L.
      • et al.
      Deficient Amygdala Habituation to Threatening Stimuli in Borderline Personality Disorder Relates to Adverse Childhood Experiences.
      ,
      • Holz N.E.
      • Hage A.
      • Plichta M.M.
      • Boecker-Schlier R.
      • Jennen-Steinmetz C.
      • Baumeister S.
      • et al.
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      ,
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      • New A.S.
      • Goldstein K.E.
      • Rosell D.
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      • Zhou Z.
      • et al.
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      ). However, since amygdala function can be directly targeted and modulated with neurofeedback-based interventions (
      • Linhartova P.
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      • Kasparek T.
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      • Paret C.
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      ), this neural risk phenotype is an attractive candidate for novel multimodal treatment (and ideally prevention) concepts with multiple, synergistic starting points.
      The results presented must be evaluated against the background of some limitations of our study, which we explain below. First, the size of the studied groups is limited. This is mainly because we obtained our participants from an epidemiological sample of young adults in the population, in which the prevalence of subclinical syndromes and full remissions of a previous disorder is finite. Second, we departed from a purely population-based approach by matching the composition of the non-risk comparison group using a set of predefined demographic and treatment-related variables. We consider both of these decisions important because we wanted to reflect as closely as possible the situation of young, non-help-seeking, and clinically vulnerable individuals in the community, while minimizing bias in our results from confounding variables that are known to affect the outcomes we studied. Third, we could not consistently apply the three-group design of the questionnaire and EMA analyses in neuroimaging space because we did not have enough usable fMRI data from the clinical group. However, because our primary goal was to study a neuronal risk marker in individuals from the general population in the absence of treatment effects, the availability of sufficient patient data for this purpose would have been of limited help anyway. Fourth, beyond affective valence, the reported EMA results are based on exploratory analyses, and any interpretations based on these findings are therefore preliminary. However, we felt it was important to report these data and our opinions in this regard, as they may promote the formation of new hypotheses in future studies. Finally, the reported associations between neural and everyday affective measures are based on cross-sectional data and therefore do not allow for causal interpretations. We speculate that the relationship between brain function and everyday experience is a complex, reciprocal causal process, an assumption that should be further explored in future experimental studies.

      Acknowledgments and disclosure

      This research was supported by grants from the German Research Foundation, Research Training Group GRK2350/1 (project B02 [to HT and AM-L]), Collaborative Research Center 1158 projects B04 [to HT] and B09 [to AM-L] and Collaborative Research Center TRR 265 projects A04 [to HT and UE-P] and S02 [to UE-P and AM-L]. Additional support was received from the Ministry of Science, Research and the Arts of the State of Baden-Wuerttemberg, Germany (grant Nos. 42-5400/136/1 [to HT and AM-L] and 42-04HV.MED(16)/16/1 [to AM-L]), the German Federal Ministry of Education and Research (grant 01EF1803A [to AM-L, HT and UE-P]), Heidelberg University (Olympia-Morata Program, [to GG]), German Academic Exchange Service (DAAD, [to GG]) and Chinese Scholarship Council (to RM). We thank Beate Höchemer, Kristina Schwarz, Ceren Akdeniz, Janina I. Schweiger, Carina Sebald, Alexander Moldavski and our research assistants for valuable support.
      Dr Meyer-Lindenberg has received lecture fees from the Lundbeck International Foundation, Paul-Martini-Stiftung, Lilly Deutschland, Atheneum, Fama Public Relations, IDIBAPS, Janssen-Cilag, Hertie-Stiftung, Bodelschwingh-Klinik, Pfizer, Universität Freiburg, Schizophrenia Academy, Hong Kong Society of Biological Psychiatry, Spanish Society of Psychiatry, Italian Society of Biological Psychiatry, Reunions I Ciencia S.L. Brain Center Rudolf Magnus UMC Utrecht, Friedrich-Merz-Stiftung, and consultant fees from Boehringer Ingelheim, Elsevier, Brainsway, Lundbeck Int. Neuroscience Foundation, Lundbeck A/S, Sumitomo Dainippon Pharma Co., Academic Medical Center of the University of Amsterdam, Synapsis Foundation-Alzheimer Research Switzerland, IBS Center for Synaptic Brain Dysfunction, Blueprint Partnership, University of Cambridge, Dt. Zentrum für Neurodegenerative Erkrankungen, Zürich University, Brain Mind Institute, L.E.K. Consulting, ICARE Schizophrenia, Science Advances, Fondation FondaMental, von Behring Röntgen Stiftung, The Wolfson Foundation, Sage Therapeutics. Dr. Ebner-Priemer reports consultancy for Boehringer-Ingelheim. The other authors report no biomedical financial interests or potential conflicts of interest.

      Supplementary Material

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