Publications by authors named "Bonnie Klimes-Dougan"

93 Publications

Coordination between frontolimbic resting state connectivity and hypothalamic-pituitary-adrenal axis functioning in adolescents with and without depression.

Psychoneuroendocrinology 2021 Mar 28;125:105123. Epub 2020 Dec 28.

Psychology Department, College of Liberal Arts, University of Minnesota, Twin Cities, United States. Electronic address:

Depression is associated with abnormalities in Hypothalamic-Pituitary-Adrenal (HPA) axis functioning and neural circuitry that underlie the stress response. Resting-state functional connectivity (RSFC) between frontolimbic brain regions captures intrinsic connections that may set the stage for the rallying and regulating of the HPA axis system. This study examined the association between cortisol stress response and frontolimbic (amygdala and ventral and dorsal medial prefrontal cortex [vmPFC and dmPFC respectively]) RSFC in 88 (Age: M = 15.95, SD = 2.04; 71.60% female) adolescents with (N = 55) and without (N = 33) major depressive disorder (MDD). We collected salivary cortisol in the context of a modified Trier Social Stress Test (TSST) paradigm. Key findings were that adolescents with depression and healthy controls showed different patterns of association between amygdala and vmPFC RSFC and HPA functioning: while healthy controls showed a positive relationship between frontolimbic connectivity and cortisol levels that may indicate coordination across neural and neuroendocrine systems, adolescents with depression showed a minimal or inverse relationship, suggesting poor coordination of these systems. Results were similar when examining non-suicidal self-injury subgroups within the MDD sample. These findings suggest that the intrinsic quality of this frontolimbic connection may be related to HPA axis functioning. In MDD, inverse associations may represent a compensatory response in one system in response to dysfunction in the other. Longitudinal multilevel research, however, is needed to disentangle how stress system coordination develops in normal and pathological contexts and how these systems recover with treatment.
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http://dx.doi.org/10.1016/j.psyneuen.2020.105123DOI Listing
March 2021

New Somatic Treatments for Child and Adolescent Depression.

Curr Treat Options Psychiatry 2019 Dec 12;6(4):380-400. Epub 2019 Nov 12.

Department of Psychology; University of Minnesota.

Purpose Of Review: Depression is a common clinical problem in youth, with prevalence increasing significantly during the adolescent period. Although several evidence-based treatments are currently available for treating depression in adults, only a subset of these have been investigated in a pediatric sample. Unfortunately, even well-established, first-line interventions do not lead to sufficient treatment response for many children and adolescents suffering from depression. However, recent research has been conducted in the area of somatic treatments for youth with depression. This review focuses on current (past three years, including published results and ongoing studies) research on somatic treatments for adolescent depression in the following categories: psychopharmacology, nutraceuticals, interventions implicating motor and sensory systems, and neuromodulation.

Findings: Results from recent randomized, controlled trials testing psychopharmacological options suggest that while antidepressants that have been recently approved for adult patients are safe and tolerable in children and adolescents, none have yet outperformed performed placebo in efficacy. Nutraceuticals, motor-sensory interventions, and neuromodulation techniques, present safe and promising results, but few have been tested against controls to support effectiveness over current treatment options.

Summary: This review of research on pediatric depression treatment from the past 3 years highlights some disappointments (negative results following some of the well-designed clinical trials) and gaps (preliminary studies in need of follow up with robust methodology) but also some promising directions in research of the efficacyof these treatments in a pediatric sample. We offer suggestions for future research including consideration of treatment timing, sequencing, the role of symptom severity in directing treatment selection, the potential value of combined treatments, consideration of how to best account for high placebo response rates, and the incorporation of neurobiological assessments to examine mechanisms and biomarker predictors of treatment response.
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http://dx.doi.org/10.1007/s40501-019-00194-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732147PMC
December 2019

New Somatic Treatments for Child and Adolescent Depression.

Curr Treat Options Psychiatry 2019 Dec 12;6(4):380-400. Epub 2019 Nov 12.

Department of Psychology; University of Minnesota.

Purpose Of Review: Depression is a common clinical problem in youth, with prevalence increasing significantly during the adolescent period. Although several evidence-based treatments are currently available for treating depression in adults, only a subset of these have been investigated in a pediatric sample. Unfortunately, even well-established, first-line interventions do not lead to sufficient treatment response for many children and adolescents suffering from depression. However, recent research has been conducted in the area of somatic treatments for youth with depression. This review focuses on current (past three years, including published results and ongoing studies) research on somatic treatments for adolescent depression in the following categories: psychopharmacology, nutraceuticals, interventions implicating motor and sensory systems, and neuromodulation.

Findings: Results from recent randomized, controlled trials testing psychopharmacological options suggest that while antidepressants that have been recently approved for adult patients are safe and tolerable in children and adolescents, none have yet outperformed performed placebo in efficacy. Nutraceuticals, motor-sensory interventions, and neuromodulation techniques, present safe and promising results, but few have been tested against controls to support effectiveness over current treatment options.

Summary: This review of research on pediatric depression treatment from the past 3 years highlights some disappointments (negative results following some of the well-designed clinical trials) and gaps (preliminary studies in need of follow up with robust methodology) but also some promising directions in research of the efficacyof these treatments in a pediatric sample. We offer suggestions for future research including consideration of treatment timing, sequencing, the role of symptom severity in directing treatment selection, the potential value of combined treatments, consideration of how to best account for high placebo response rates, and the incorporation of neurobiological assessments to examine mechanisms and biomarker predictors of treatment response.
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http://dx.doi.org/10.1007/s40501-019-00194-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732147PMC
December 2019

Cortical thickness and resting-state cardiac function across the lifespan: A cross-sectional pooled mega-analysis.

Psychophysiology 2020 Oct 10. Epub 2020 Oct 10.

Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Understanding the association between autonomic nervous system [ANS] function and brain morphology across the lifespan provides important insights into neurovisceral mechanisms underlying health and disease. Resting-state ANS activity, indexed by measures of heart rate [HR] and its variability [HRV] has been associated with brain morphology, particularly cortical thickness [CT]. While findings have been mixed regarding the anatomical distribution and direction of the associations, these inconsistencies may be due to sex and age differences in HR/HRV and CT. Previous studies have been limited by small sample sizes, which impede the assessment of sex differences and aging effects on the association between ANS function and CT. To overcome these limitations, 20 groups worldwide contributed data collected under similar protocols of CT assessment and HR/HRV recording to be pooled in a mega-analysis (N = 1,218 (50.5% female), mean age 36.7 years (range: 12-87)). Findings suggest a decline in HRV as well as CT with increasing age. CT, particularly in the orbitofrontal cortex, explained additional variance in HRV, beyond the effects of aging. This pattern of results may suggest that the decline in HRV with increasing age is related to a decline in orbitofrontal CT. These effects were independent of sex and specific to HRV; with no significant association between CT and HR. Greater CT across the adult lifespan may be vital for the maintenance of healthy cardiac regulation via the ANS-or greater cardiac vagal activity as indirectly reflected in HRV may slow brain atrophy. Findings reveal an important association between CT and cardiac parasympathetic activity with implications for healthy aging and longevity that should be studied further in longitudinal research.
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http://dx.doi.org/10.1111/psyp.13688DOI Listing
October 2020

Neural and Behavioral Correlates of Clinical Improvement to Ketamine in Adolescents With Treatment Resistant Depression.

Front Psychiatry 2020 18;11:820. Epub 2020 Aug 18.

Department of Psychiatry and Behavioral Sciences, School of Medicine, University of Minnesota, Twin Cities, MN, United States.

Treatment-resistant depression (TRD) is a serious problem in adolescents. Development and optimization of novel interventions for these youth will require a deeper knowledge of the neurobiology of depression. A well-established phenomenon of depression is an attention bias toward negativity and away from positivity that is evidenced behaviorally and neurally, but it is unclear how symptom reduction is related to changes to this bias. Neurobiological research using a treatment probe has promise to help discover the neural changes that accompany symptom improvement. Ketamine has utility for such research because of its known rapid and strong antidepressant effects in the context of TRD. Our previous study of six open-label ketamine infusions in 11 adolescents with TRD showed variable response, ranging from full remission, partial response, non-response, or clinical worsening. In this study, we examined the performance of these participants on Word Face Stroop (WFS) fMRI task where they indicated the valence of affective words superimposed onto either congruent or incongruent emotional faces before and after the ketamine infusions. Participants also completed a clinical assessment (including measurement of depression symptomology and anhedonia/pleasure) before and after the ketamine infusions. Following ketamine treatment, better WFS performance correlated with self-reported decreased depressive symptoms and increased pleasure. Analyses of corticolimbic, corticostriatal and default mode (DMN) networks showed that across networks, decreased activation during all conditions (congruent negative, congruent positive, incongruent negative, and incongruent positive) correlated with decreases in depressive symptoms and with increases in pleasure. These findings suggest that in adolescents with TRD, clinical improvement may require an attenuation of the negativity bias and re-tuning of these three critical neural networks to attenuate DMN and limbic regions activation and allow more efficient recruitment of the reward network. Lower activation across conditions may facilitate shifting across different salient emotional stimuli rather than getting trapped in downward negative spirals.
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http://dx.doi.org/10.3389/fpsyt.2020.00820DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7461781PMC
August 2020

Developing a data-driven algorithm for guiding selection between cognitive behavioral therapy, fluoxetine, and combination treatment for adolescent depression.

Transl Psychiatry 2020 09 21;10(1):321. Epub 2020 Sep 21.

Institute of Health Informatics, School of Medicine, University of Minnesota, Minneapolis, MN, USA.

Treating adolescent depression effectively requires providing interventions that are optimally suited to patients' individual characteristics and needs. Therefore, we aim to develop an algorithm that matches patients with optimal treatment among cognitive-behavioral therapy (CBT), fluoxetine (FLX), and combination treatment (COMB). We leveraged data from a completed clinical trial, the Treatment for adolescents with depression study, where a wide range of demographic, clinical, and psychosocial measures were collected from adolescents diagnosed with major depressive disorder prior to treatment. Machine-learning techniques were employed to derive a model that predicts treatment response (week 12 children's depression rating scale-revised [CDRS-R]) to CBT, FLX, and COMB. The resulting model successfully identified subgroups of patients that respond preferentially to specific types of treatment. Specifically, our model identified a subgroup of patients (25%) that achieved on average a 16.9 point benefit on the CDRS-R from FLX compared to CBT. The model also identified a subgroup of patients (50%) that achieved an average benefit up to 19.0 points from COMB compared to CBT. Physical illness and disability were identified as overall predictors of response to treatment, regardless of treatment type, whereas baseline CDRS-R, psychosomatic symptoms, school missed, view of self, treatment expectations, and attention problems determined the patients' response to specific treatments. The model developed in this study provides a critical starting point for personalized treatment planning for adolescent depression.
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http://dx.doi.org/10.1038/s41398-020-01005-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506003PMC
September 2020

Early pubertal maturation and externalizing behaviors: Examination of peer delinquency as mediator and cognitive flexibility as a moderator.

J Adolesc 2020 10 24;84:45-55. Epub 2020 Aug 24.

Psychology Department, University of Minnesota, 75 East River Road, Minneapolis, MN, 55455, USA. Electronic address:

Introduction: While peer delinquency is a known mediator between early pubertal timing and externalizing behaviors, little is known about factors that could protect against the adverse influence of peer delinquency. This study assesses the possible moderating role of cognitive flexibility, which is one index of executive functioning that facilitates flexible and adaptive responses to challenging situations. We assessed the interactive influence of peer delinquency and cognitive flexibility in the association between pubertal maturation and externalizing behaviors in boys and girls.

Method: Participants were 220 adolescents (111 boys) from the United States, between the ages of 11 and 16 years (M = 13.2, SD = 1.53) who participated in the Adolescent Emotion Study (AES).

Results: Findings from the cross-sectional path modeling analyses provided evidence for the mediating role of peer delinquency for boys and girls, indicating that early maturing adolescents tend to affiliate with delinquent peers, which in turn exacerbates externalizing problems. Additionally, the moderating role of cognitive flexibility was also demonstrated for both boys and girls. Region of significance tests revealed that relatively well-developed cognitive flexibility skills could protect against the adverse influences of peer delinquency, whereas lower levels could exacerbate those negative influences.

Conclusion: These findings suggest that involvement with deviant peers increases vulnerability for both early maturing boys and girls. Additionally, cognitive flexibility was an important moderating factor for adolescents, such that youths with less developed skills would be at a higher risk for psychopathology, whereas those with better development could be protected.
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http://dx.doi.org/10.1016/j.adolescence.2020.07.008DOI Listing
October 2020

Emotion socialization in mothers with mood disorders: Affective modeling and recollected responses to childhood emotion.

Dev Psychopathol 2020 Jul 16:1-14. Epub 2020 Jul 16.

Department of Psychology, University of Minnesota, Elliott Hall, 75 East River Road, Minneapolis, MN55455, USA.

Growing evidence suggests that emotion socialization may be disrupted by maternal depression. However, little is known about emotion-related parenting by mothers with bipolar disorder or whether affective modeling in early childhood is linked to young adults' recollections of emotion socialization practices. The current study investigates emotion socialization by mothers with histories of major depression, bipolar disorder, or no mood disorder. Affective modeling was coded from parent-child interactions in early childhood and maternal responses to negative emotions were recollected by young adult offspring (n = 131, 59.5% female, M age = 22.16, SD = 2.58). Multilevel models revealed that maternal bipolar disorder was associated with more neglecting, punishing, and magnifying responses to children's emotions, whereas maternal major depression was associated with more magnifying responses; links between maternal diagnosis and magnifying responses were robust to covariates. Young adult recollections of maternal responses to emotion were predicted by affective modeling in early childhood, providing preliminary validity evidence for the Emotions as a Child Scale. Findings provide novel evidence that major depression and bipolar disorder are associated with altered emotion socialization and that maternal affective modeling in early childhood prospectively predicts young adults' recollections of emotion socialization in families with and without mood disorder.
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http://dx.doi.org/10.1017/S0954579420000395DOI Listing
July 2020

Brain entropy and neurotrophic molecular markers accompanying clinical improvement after ketamine: Preliminary evidence in adolescents with treatment-resistant depression.

J Psychopharmacol 2021 Feb 9;35(2):168-177. Epub 2020 Jul 9.

Department of Psychiatry and Behavioral Sciences, Medical School, University of Minnesota, Minneapolis, USA.

Background: Current theory suggests that treatment-resistant depression (TRD) involves impaired neuroplasticity resulting in cognitive and neural rigidity, and that clinical improvement may require increasing brain flexibility and adaptability.

Aims: In this hypothesis-generating study, we sought to identify preliminary evidence of brain flexibility correlates of clinical change within the context of an open-label ketamine trial in adolescents with TRD, focusing on two promising candidate markers of neural flexibility: (a) entropy of resting-state functional magnetic resonance imaging (fMRI) signals; and (b) insulin-stimulated phosphorylation of mammalian target of rapamycin (mTOR) and glycogen synthase-3-beta (GSK3β) in peripheral blood mononuclear cells.

Methods: We collected resting-state functional magnetic resonance imaging data and blood samples from 13 adolescents with TRD before and after a series of six ketamine infusions over 2 weeks. Usable pre/post ketamine data were available from 11 adolescents for imaging and from 10 adolescents for molecular signaling. We examined correlations between treatment response and changes in the central and peripheral flexibility markers.

Results: Depression reduction correlated with increased nucleus accumbens entropy. Follow-up analyses suggested that physiological changes were associated with treatment response. In contrast to treatment non-responders (=6), responders (=5) showed greater increase in nucleus accumbens entropy after ketamine, together with greater post-treatment insulin/mTOR/GSK3β signaling.

Conclusions: These data provide preliminary evidence that changes in neural flexibility may underlie symptom relief in adolescents with TRD following ketamine. Future research with adequately powered samples is needed to confirm resting-state entropy and insulin-stimulated mTOR and GSK3β as brain flexibility markers and candidate targets for future clinical trials.

Clinical Trial Name: Ketamine in adolescents with treatment-resistant depression https://clinicaltrials.gov/ct2/show/NCT02078817 NCT02078817.
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http://dx.doi.org/10.1177/0269881120928203DOI Listing
February 2021

Editorial: The Ups and Downs of Mind-Wandering in Adolescents.

J Am Acad Child Adolesc Psychiatry 2021 Mar 16;60(3):340-342. Epub 2020 Jun 16.

School of Medicine, University of Minnesota, Twin Cities. Electronic address:

The human brain is always active; it wanders freely during rest as well as when we lose focus during tasks. Mind-wandering encompasses spontaneous thinking, such as processing recent experiences, problem solving, and achieving insights. Understanding this unconstrained brain activity may lead to clues about the neural mechanisms of mental health problems. Brain networks implicated in mind-wandering include the default mode network (DMN), the salience network, and task-positive networks including the frontoparietal control network and dorsal attention network. Given that these networks mature during adolescence, coinciding with a time notable for the emergence of mental health problems, quantifying and examining the neural correlates of mind-wandering in adolescents with psychopathology may shed light on how the healthy and pathological brain functions and point to possible methods of intervening.
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http://dx.doi.org/10.1016/j.jaac.2020.06.001DOI Listing
March 2021

ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing.

Transl Psychiatry 2020 05 29;10(1):172. Epub 2020 May 29.

Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research.
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http://dx.doi.org/10.1038/s41398-020-0842-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7260219PMC
May 2020

Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders : Evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group.

Mol Psychiatry 2020 May 28. Epub 2020 May 28.

Department of Psychiatry, University of Münster, Münster, Germany.

Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = -0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.
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http://dx.doi.org/10.1038/s41380-020-0774-9DOI Listing
May 2020

Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group.

Authors:
Laura K M Han Richard Dinga Tim Hahn Christopher R K Ching Lisa T Eyler Lyubomir Aftanas Moji Aghajani André Aleman Bernhard T Baune Klaus Berger Ivan Brak Geraldo Busatto Filho Angela Carballedo Colm G Connolly Baptiste Couvy-Duchesne Kathryn R Cullen Udo Dannlowski Christopher G Davey Danai Dima Fabio L S Duran Verena Enneking Elena Filimonova Stefan Frenzel Thomas Frodl Cynthia H Y Fu Beata R Godlewska Ian H Gotlib Hans J Grabe Nynke A Groenewold Dominik Grotegerd Oliver Gruber Geoffrey B Hall Ben J Harrison Sean N Hatton Marco Hermesdorf Ian B Hickie Tiffany C Ho Norbert Hosten Andreas Jansen Claas Kähler Tilo Kircher Bonnie Klimes-Dougan Bernd Krämer Axel Krug Jim Lagopoulos Ramona Leenings Frank P MacMaster Glenda MacQueen Andrew McIntosh Quinn McLellan Katie L McMahon Sarah E Medland Bryon A Mueller Benson Mwangi Evgeny Osipov Maria J Portella Elena Pozzi Liesbeth Reneman Jonathan Repple Pedro G P Rosa Matthew D Sacchet Philipp G Sämann Knut Schnell Anouk Schrantee Egle Simulionyte Jair C Soares Jens Sommer Dan J Stein Olaf Steinsträter Lachlan T Strike Sophia I Thomopoulos Marie-José van Tol Ilya M Veer Robert R J M Vermeiren Henrik Walter Nic J A van der Wee Steven J A van der Werff Heather Whalley Nils R Winter Katharina Wittfeld Margaret J Wright Mon-Ju Wu Henry Völzke Tony T Yang Vasileios Zannias Greig I de Zubicaray Giovana B Zunta-Soares Christoph Abé Martin Alda Ole A Andreassen Erlend Bøen Caterina M Bonnin Erick J Canales-Rodriguez Dara Cannon Xavier Caseras Tiffany M Chaim-Avancini Torbjørn Elvsåshagen Pauline Favre Sonya F Foley Janice M Fullerton Jose M Goikolea Bartholomeus C M Haarman Tomas Hajek Chantal Henry Josselin Houenou Fleur M Howells Martin Ingvar Rayus Kuplicki Beny Lafer Mikael Landén Rodrigo Machado-Vieira Ulrik F Malt Colm McDonald Philip B Mitchell Leila Nabulsi Maria Concepcion Garcia Otaduy Bronwyn J Overs Mircea Polosan Edith Pomarol-Clotet Joaquim Radua Maria M Rive Gloria Roberts Henricus G Ruhe Raymond Salvador Salvador Sarró Theodore D Satterthwaite Jonathan Savitz Aart H Schene Peter R Schofield Mauricio H Serpa Kang Sim Marcio Gerhardt Soeiro-de-Souza Ashley N Sutherland Henk S Temmingh Garrett M Timmons Anne Uhlmann Eduard Vieta Daniel H Wolf Marcus V Zanetti Neda Jahanshad Paul M Thompson Dick J Veltman Brenda W J H Penninx Andre F Marquand James H Cole Lianne Schmaal

Mol Psychiatry 2020 May 18. Epub 2020 May 18.

Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia.

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.
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http://dx.doi.org/10.1038/s41380-020-0754-0DOI Listing
May 2020

Apophenia as the disposition to false positives: A unifying framework for openness and psychoticism.

J Abnorm Psychol 2020 Apr;129(3):279-292

Department of Psychology, University of Minnesota Twin Cities.

Positive symptoms of schizophrenia and its extended phenotype-often termed psychoticism or positive schizotypy-are characterized by the inclusion of novel, erroneous mental contents. One promising framework for explaining positive symptoms involves apophenia, conceptualized here as a disposition toward false-positive errors. Apophenia and positive symptoms have shown relations to openness to experience (more specifically, to the openness aspect of the broader openness/intellect domain), and all of these constructs involve tendencies toward pattern seeking. Nonetheless, few studies have investigated the relations between psychoticism and non-self-report indicators of apophenia, let alone the role of normal personality variation. The current research used structural equation models to test associations between psychoticism, openness, intelligence, and non-self-report indicators of apophenia comprising false-positive error rates on a variety of computerized tasks. In Sample 1, 1,193 participants completed digit identification, theory of mind, and emotion recognition tasks. In Sample 2, 195 participants completed auditory signal detection and semantic word association tasks. Psychoticism and the openness aspect were positively correlated. Self-reported psychoticism, openness, and their shared variance were positively associated with apophenia, as indexed by false-positive error rates, whether or not intelligence was controlled for. Apophenia was not associated with other personality traits, and openness and psychoticism were not associated with false-negative errors. Findings provide insights into the measurement of apophenia and its relation to personality and psychopathology. Apophenia and pattern seeking may be promising constructs for unifying the openness aspect of personality with the psychosis spectrum and for providing an explanation of positive symptoms. Results are discussed in the context of possible adaptive characteristics of apophenia as well as potential risk factors for the development of psychotic disorders. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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http://dx.doi.org/10.1037/abn0000504DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112154PMC
April 2020

Apophenia as the disposition to false positives: A unifying framework for openness and psychoticism.

J Abnorm Psychol 2020 Apr;129(3):279-292

Department of Psychology, University of Minnesota Twin Cities.

Positive symptoms of schizophrenia and its extended phenotype-often termed psychoticism or positive schizotypy-are characterized by the inclusion of novel, erroneous mental contents. One promising framework for explaining positive symptoms involves apophenia, conceptualized here as a disposition toward false-positive errors. Apophenia and positive symptoms have shown relations to openness to experience (more specifically, to the openness aspect of the broader openness/intellect domain), and all of these constructs involve tendencies toward pattern seeking. Nonetheless, few studies have investigated the relations between psychoticism and non-self-report indicators of apophenia, let alone the role of normal personality variation. The current research used structural equation models to test associations between psychoticism, openness, intelligence, and non-self-report indicators of apophenia comprising false-positive error rates on a variety of computerized tasks. In Sample 1, 1,193 participants completed digit identification, theory of mind, and emotion recognition tasks. In Sample 2, 195 participants completed auditory signal detection and semantic word association tasks. Psychoticism and the openness aspect were positively correlated. Self-reported psychoticism, openness, and their shared variance were positively associated with apophenia, as indexed by false-positive error rates, whether or not intelligence was controlled for. Apophenia was not associated with other personality traits, and openness and psychoticism were not associated with false-negative errors. Findings provide insights into the measurement of apophenia and its relation to personality and psychopathology. Apophenia and pattern seeking may be promising constructs for unifying the openness aspect of personality with the psychosis spectrum and for providing an explanation of positive symptoms. Results are discussed in the context of possible adaptive characteristics of apophenia as well as potential risk factors for the development of psychotic disorders. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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http://dx.doi.org/10.1037/abn0000504DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112154PMC
April 2020

Apophenia as the disposition to false positives: A unifying framework for openness and psychoticism.

J Abnorm Psychol 2020 Apr;129(3):279-292

Department of Psychology, University of Minnesota Twin Cities.

Positive symptoms of schizophrenia and its extended phenotype-often termed psychoticism or positive schizotypy-are characterized by the inclusion of novel, erroneous mental contents. One promising framework for explaining positive symptoms involves apophenia, conceptualized here as a disposition toward false-positive errors. Apophenia and positive symptoms have shown relations to openness to experience (more specifically, to the openness aspect of the broader openness/intellect domain), and all of these constructs involve tendencies toward pattern seeking. Nonetheless, few studies have investigated the relations between psychoticism and non-self-report indicators of apophenia, let alone the role of normal personality variation. The current research used structural equation models to test associations between psychoticism, openness, intelligence, and non-self-report indicators of apophenia comprising false-positive error rates on a variety of computerized tasks. In Sample 1, 1,193 participants completed digit identification, theory of mind, and emotion recognition tasks. In Sample 2, 195 participants completed auditory signal detection and semantic word association tasks. Psychoticism and the openness aspect were positively correlated. Self-reported psychoticism, openness, and their shared variance were positively associated with apophenia, as indexed by false-positive error rates, whether or not intelligence was controlled for. Apophenia was not associated with other personality traits, and openness and psychoticism were not associated with false-negative errors. Findings provide insights into the measurement of apophenia and its relation to personality and psychopathology. Apophenia and pattern seeking may be promising constructs for unifying the openness aspect of personality with the psychosis spectrum and for providing an explanation of positive symptoms. Results are discussed in the context of possible adaptive characteristics of apophenia as well as potential risk factors for the development of psychotic disorders. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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http://dx.doi.org/10.1037/abn0000504DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112154PMC
April 2020

Classification of Major Depressive Disorder from Resting-State fMRI.

Annu Int Conf IEEE Eng Med Biol Soc 2019 Jul;2019:3511-3514

Major Depressive Disorder (MDD) is a very serious mental illness that can affect the daily lives of patients. Accurate diagnosis of this disorder is necessary for planning individualized treatment. However, diagnosing MDD requires the clinicians to personally interview the subjects and rate the symptoms based on Diagnostic and Statistical Manual of Mental Disorders (DSM), which can be very time consuming. Discovering quantifiable signals and biomarkers associated with MDD using functional magnetic resonance imaging (fMRI) scans of patients have the potential to assist the clinicians in their assessment. This paper explores the use of resting-state functional connectivity and network features to classify MDD vs. healthy subjects. For each subject, mean time-series are extracted from 85 brain regions and they are decomposed to 4-frequency bands. Mean time-series for each of the frequency bands are utilized to compute the Pearson correlation and network characteristics. Features are selected separately from correlation and network characteristics using Minimum Redundancy Maximum Relevance (mRMR) to create the final classifier. The proposed scheme achieves 79% accuracy (65 out of 82 subjects classified correctly) with 86% sensitivity (42 out of 49 MDD subjects identified correctly) and 70% specificity (23 out of 33 controls identified correctly) using leave-one-out classification with in-fold feature selection. Pearson correlation had the highest discrimination in band 0.015-0.03 Hz and network based features had the highest discrimination in band 0.03-0.06 Hz for distinguishing MDD vs. healthy subjects.
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http://dx.doi.org/10.1109/EMBC.2019.8856453DOI Listing
July 2019

Classification of Major Depressive Disorder from Resting-State fMRI.

Annu Int Conf IEEE Eng Med Biol Soc 2019 Jul;2019:3511-3514

Major Depressive Disorder (MDD) is a very serious mental illness that can affect the daily lives of patients. Accurate diagnosis of this disorder is necessary for planning individualized treatment. However, diagnosing MDD requires the clinicians to personally interview the subjects and rate the symptoms based on Diagnostic and Statistical Manual of Mental Disorders (DSM), which can be very time consuming. Discovering quantifiable signals and biomarkers associated with MDD using functional magnetic resonance imaging (fMRI) scans of patients have the potential to assist the clinicians in their assessment. This paper explores the use of resting-state functional connectivity and network features to classify MDD vs. healthy subjects. For each subject, mean time-series are extracted from 85 brain regions and they are decomposed to 4-frequency bands. Mean time-series for each of the frequency bands are utilized to compute the Pearson correlation and network characteristics. Features are selected separately from correlation and network characteristics using Minimum Redundancy Maximum Relevance (mRMR) to create the final classifier. The proposed scheme achieves 79% accuracy (65 out of 82 subjects classified correctly) with 86% sensitivity (42 out of 49 MDD subjects identified correctly) and 70% specificity (23 out of 33 controls identified correctly) using leave-one-out classification with in-fold feature selection. Pearson correlation had the highest discrimination in band 0.015-0.03 Hz and network based features had the highest discrimination in band 0.03-0.06 Hz for distinguishing MDD vs. healthy subjects.
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http://dx.doi.org/10.1109/EMBC.2019.8856453DOI Listing
July 2019

Classification of Major Depressive Disorder from Resting-State fMRI.

Annu Int Conf IEEE Eng Med Biol Soc 2019 Jul;2019:3511-3514

Major Depressive Disorder (MDD) is a very serious mental illness that can affect the daily lives of patients. Accurate diagnosis of this disorder is necessary for planning individualized treatment. However, diagnosing MDD requires the clinicians to personally interview the subjects and rate the symptoms based on Diagnostic and Statistical Manual of Mental Disorders (DSM), which can be very time consuming. Discovering quantifiable signals and biomarkers associated with MDD using functional magnetic resonance imaging (fMRI) scans of patients have the potential to assist the clinicians in their assessment. This paper explores the use of resting-state functional connectivity and network features to classify MDD vs. healthy subjects. For each subject, mean time-series are extracted from 85 brain regions and they are decomposed to 4-frequency bands. Mean time-series for each of the frequency bands are utilized to compute the Pearson correlation and network characteristics. Features are selected separately from correlation and network characteristics using Minimum Redundancy Maximum Relevance (mRMR) to create the final classifier. The proposed scheme achieves 79% accuracy (65 out of 82 subjects classified correctly) with 86% sensitivity (42 out of 49 MDD subjects identified correctly) and 70% specificity (23 out of 33 controls identified correctly) using leave-one-out classification with in-fold feature selection. Pearson correlation had the highest discrimination in band 0.015-0.03 Hz and network based features had the highest discrimination in band 0.03-0.06 Hz for distinguishing MDD vs. healthy subjects.
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http://dx.doi.org/10.1109/EMBC.2019.8856453DOI Listing
July 2019

White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group.

Mol Psychiatry 2020 07 30;25(7):1511-1525. Epub 2019 Aug 30.

Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, Australia.

Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12-88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen's d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen's d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD.
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http://dx.doi.org/10.1038/s41380-019-0477-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055351PMC
July 2020

Transcendental meditation and hypothalamic-pituitary-adrenal axis functioning: a pilot, randomized controlled trial with young adults.

Stress 2020 01 11;23(1):105-115. Epub 2019 Sep 11.

Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA.

Transcendental meditation (TM) is effective in alleviating stress and anxiety and promoting well-being. While the underlying biological mechanisms of TM are not yet fully explored, the hypothalamic-pituitary-adrenal (HPA) axis represents an index providing important clues embodying the stress system cascade. In this pilot study, young adults were randomly assigned to TM training followed by 8 weeks of meditation practice or a wait-list control condition. TM was conducted over 8 weeks. Thirty-four young adult participants were randomized; 27 participants completed the HPA outcome assessments (41% male). To assess HPA axis functioning, salivary samples to assess cortisol awakening response (CAR) that were collected in the morning, both at baseline and at week-4. Salivary cortisol in the context of a social stressor using the Trier Social Stress Test (TSST) was collected at week-8. The results indicate that participants who were randomly assigned to TM had lower awakening salivary cortisol levels and a greater drop in CAR from baseline to week-4 than the control group. There were no significant differences in HPA axis functioning in the context of the TSST. Primary limitations of this randomized controlled trial were the small sample size, the use of a wait-list as opposed to an active control, and the limited scope of HPA axis assessments. The results of this pilot study provide tentative evidence that TM may impact biological stress system functioning and suggests that this may be a worthwhile avenue to continue to examine. It will also be useful to extend these findings to a broader array of meditative and mindful practices, particularly for those who are experiencing more distress.
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http://dx.doi.org/10.1080/10253890.2019.1656714DOI Listing
January 2020

Neurocircuitry associated with symptom dimensions at baseline and with change in borderline personality disorder.

Psychiatry Res Neuroimaging 2019 08 5;290:58-65. Epub 2019 Jul 5.

University of Minnesota Medical School, Department of Psychiatry, 2450 Riverside Avenue, Minneapolis, MN 55454, United States. Electronic address:

Borderline personality disorder (BPD) is a serious illness associated with chronic suffering and self-injurious behavior. Parsing the relationships between specific symptom domains and their underlying biological mechanisms may help us further understand the neural circuits implicated in these symptoms and how they might be amenable to change with treatment. This study examines the association between symptom dimensions (Affective Disturbance, Cognitive Disturbance, Disturbed Relationships, and Impulsivity) and amygdala resting-state functional connectivity (RSFC) in a sample of adults with BPD (n = 18). We also explored the relationships between change in symptom dimensions and change in amygdala RSFC in a subset of this sample (n = 13) following 8 weeks of quetiapine or placebo. At baseline, higher impulsivity was associated with increased positive RSFC between right amygdala and left hippocampus. There were no significant differences in neural change between treatment groups. Improvement in cognitive disturbance was associated with increased positive RSFC between left amygdala and temporal fusiform and parahippocampal gyri. Improvement in disturbed relationships was associated with increased negative RSFC between right amygdala and frontal pole. These results support that specific dimensions of BPD are associated with specific neural connectivity patterns at baseline and with change, which may represent neural treatment targets.
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http://dx.doi.org/10.1016/j.pscychresns.2019.07.001DOI Listing
August 2019

White matter microstructure relates to lassitude but not diagnosis in adolescents with depression.

Brain Imaging Behav 2020 Oct;14(5):1507-1520

Department of Psychiatry and Behavioral Sciences, School of Medicine, University of Minnesota, 2450 Riverside Avenue, Minneapolis, MN, 55454, USA.

The neurobiology of adolescent depression remains poorly understood. Initial studies suggested impaired white matter microstructure in adults and adolescents, but findings have not been consistent. Challenges in this literature have included small samples, medication confounds and inconsistent correction for type I error. This study addressed these issues in a new examination of fractional anisotropy (FA) in adolescents with major depressive disorder (MDD) using diffusion tensor imaging. We examined FA in 81 adolescents aged 12-19 (44 MDD [all unmedicated], 37 controls). We conducted logistic regression analyses to examine the odds of MDD versus control based on FA within standard white matter tracts that were delineated by probabilistic tractography. We also examined relationships between FA and disease severity (overall depression and dimensions of illness). Finally, we conducted a voxel-wise group comparison of FA. All analyses covaried for age, sex and socioeconomic status, and applied rigorous corrections for multiple testing. Logistic regression did not reveal significant associations between diagnosis and FA within white matter tracts defined by probabilistic tractography. Dimensional analyses revealed that greater lassitude was associated with higher FA in right cingulum bundle and bilateral corticospinal tracts, but with lower FA in right anterior thalamic radiation. Voxel-wise group comparisons of FA did not reveal significant group differences. The current findings do not support low FA as a neurobiological marker of adolescent depression. Dimensional results suggest that FA relates to lassitude but not overall depression. Given the clinical and neurobiological heterogeneity of depression, future work utilizing dimensional approaches may help elucidate the role of white matter microstructure in adolescent depression neurobiology.
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http://dx.doi.org/10.1007/s11682-019-00078-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752996PMC
October 2020

White matter microstructure relates to lassitude but not diagnosis in adolescents with depression.

Brain Imaging Behav 2020 Oct;14(5):1507-1520

Department of Psychiatry and Behavioral Sciences, School of Medicine, University of Minnesota, 2450 Riverside Avenue, Minneapolis, MN, 55454, USA.

The neurobiology of adolescent depression remains poorly understood. Initial studies suggested impaired white matter microstructure in adults and adolescents, but findings have not been consistent. Challenges in this literature have included small samples, medication confounds and inconsistent correction for type I error. This study addressed these issues in a new examination of fractional anisotropy (FA) in adolescents with major depressive disorder (MDD) using diffusion tensor imaging. We examined FA in 81 adolescents aged 12-19 (44 MDD [all unmedicated], 37 controls). We conducted logistic regression analyses to examine the odds of MDD versus control based on FA within standard white matter tracts that were delineated by probabilistic tractography. We also examined relationships between FA and disease severity (overall depression and dimensions of illness). Finally, we conducted a voxel-wise group comparison of FA. All analyses covaried for age, sex and socioeconomic status, and applied rigorous corrections for multiple testing. Logistic regression did not reveal significant associations between diagnosis and FA within white matter tracts defined by probabilistic tractography. Dimensional analyses revealed that greater lassitude was associated with higher FA in right cingulum bundle and bilateral corticospinal tracts, but with lower FA in right anterior thalamic radiation. Voxel-wise group comparisons of FA did not reveal significant group differences. The current findings do not support low FA as a neurobiological marker of adolescent depression. Dimensional results suggest that FA relates to lassitude but not overall depression. Given the clinical and neurobiological heterogeneity of depression, future work utilizing dimensional approaches may help elucidate the role of white matter microstructure in adolescent depression neurobiology.
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http://dx.doi.org/10.1007/s11682-019-00078-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752996PMC
October 2020

White matter microstructure relates to lassitude but not diagnosis in adolescents with depression.

Brain Imaging Behav 2020 Oct;14(5):1507-1520

Department of Psychiatry and Behavioral Sciences, School of Medicine, University of Minnesota, 2450 Riverside Avenue, Minneapolis, MN, 55454, USA.

The neurobiology of adolescent depression remains poorly understood. Initial studies suggested impaired white matter microstructure in adults and adolescents, but findings have not been consistent. Challenges in this literature have included small samples, medication confounds and inconsistent correction for type I error. This study addressed these issues in a new examination of fractional anisotropy (FA) in adolescents with major depressive disorder (MDD) using diffusion tensor imaging. We examined FA in 81 adolescents aged 12-19 (44 MDD [all unmedicated], 37 controls). We conducted logistic regression analyses to examine the odds of MDD versus control based on FA within standard white matter tracts that were delineated by probabilistic tractography. We also examined relationships between FA and disease severity (overall depression and dimensions of illness). Finally, we conducted a voxel-wise group comparison of FA. All analyses covaried for age, sex and socioeconomic status, and applied rigorous corrections for multiple testing. Logistic regression did not reveal significant associations between diagnosis and FA within white matter tracts defined by probabilistic tractography. Dimensional analyses revealed that greater lassitude was associated with higher FA in right cingulum bundle and bilateral corticospinal tracts, but with lower FA in right anterior thalamic radiation. Voxel-wise group comparisons of FA did not reveal significant group differences. The current findings do not support low FA as a neurobiological marker of adolescent depression. Dimensional results suggest that FA relates to lassitude but not overall depression. Given the clinical and neurobiological heterogeneity of depression, future work utilizing dimensional approaches may help elucidate the role of white matter microstructure in adolescent depression neurobiology.
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http://dx.doi.org/10.1007/s11682-019-00078-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752996PMC
October 2020

Critical Decision Points for Augmenting Interpersonal Psychotherapy for Depressed Adolescents: A Pilot Sequential Multiple Assignment Randomized Trial.

J Am Acad Child Adolesc Psychiatry 2019 01 27;58(1):80-91. Epub 2018 Oct 27.

University of Minnesota, MN.

Objective: Practice parameters recommend systematic assessment of depression symptoms over the course of treatment to inform treatment planning; however, there are currently no guidelines regarding how to use symptom monitoring to guide treatment decisions for psychotherapy. The current study compared two time points (week 4 and week 8) for assessing symptoms during interpersonal psychotherapy for depressed adolescents (IPT-A) and explored four algorithms that use the symptom assessments to select the subsequent treatment.

Method: Forty adolescents (aged 12-17 years) with a depression diagnosis began IPT-A with an initial treatment plan of 12 sessions delivered over 16 weeks. Adolescents were randomized to a week 4 or week 8 decision point for considering a change in treatment. Insufficient responders at either time point were randomized a second time to increased frequency of IPT-A (twice per week) or addition of fluoxetine. Measures were administered at baseline and weeks 4, 8, 12, and 16.

Results: The week 4 decision point for assessing response and implementing treatment augmentation for insufficient responders was more efficacious for reducing depression symptoms than the week 8 decision point. There were significant differences between algorithms in depression and psychosocial functioning outcomes.

Conclusion: Therapists implementing IPT-A should routinely monitor depression symptoms and consider augmenting treatment for insufficient responders as early as week 4 of treatment.

Clinical Trial Registration Information: An Adaptive Treatment Strategy for Adolescent Depression. https://clinicaltrials.gov; NCT02017535.
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http://dx.doi.org/10.1016/j.jaac.2018.06.032DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7549148PMC
January 2019

Critical Decision Points for Augmenting Interpersonal Psychotherapy for Depressed Adolescents: A Pilot Sequential Multiple Assignment Randomized Trial.

J Am Acad Child Adolesc Psychiatry 2019 01 27;58(1):80-91. Epub 2018 Oct 27.

University of Minnesota, MN.

Objective: Practice parameters recommend systematic assessment of depression symptoms over the course of treatment to inform treatment planning; however, there are currently no guidelines regarding how to use symptom monitoring to guide treatment decisions for psychotherapy. The current study compared two time points (week 4 and week 8) for assessing symptoms during interpersonal psychotherapy for depressed adolescents (IPT-A) and explored four algorithms that use the symptom assessments to select the subsequent treatment.

Method: Forty adolescents (aged 12-17 years) with a depression diagnosis began IPT-A with an initial treatment plan of 12 sessions delivered over 16 weeks. Adolescents were randomized to a week 4 or week 8 decision point for considering a change in treatment. Insufficient responders at either time point were randomized a second time to increased frequency of IPT-A (twice per week) or addition of fluoxetine. Measures were administered at baseline and weeks 4, 8, 12, and 16.

Results: The week 4 decision point for assessing response and implementing treatment augmentation for insufficient responders was more efficacious for reducing depression symptoms than the week 8 decision point. There were significant differences between algorithms in depression and psychosocial functioning outcomes.

Conclusion: Therapists implementing IPT-A should routinely monitor depression symptoms and consider augmenting treatment for insufficient responders as early as week 4 of treatment.

Clinical Trial Registration Information: An Adaptive Treatment Strategy for Adolescent Depression. https://clinicaltrials.gov; NCT02017535.
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http://dx.doi.org/10.1016/j.jaac.2018.06.032DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7549148PMC
January 2019

Biomarkers for Adolescent MDD from Anatomical Connectivity and Network Topology Using Diffusion MRI.

Annu Int Conf IEEE Eng Med Biol Soc 2018 Jul;2018:1152-1155

Due to the high resistance (35%) to the current treatment methods in adolescent Major Depressive Disorder (MDD) and its tragic outcomes, the discovery of treatmentrelated responders is critical to developing effective treatments. In this paper, the permutation test is performed to identify statistically significant changes in anatomical characteristics during pairwise comparisons among the control group (n=27), treated MDD group (n=37), and untreated MDD group (n=15). The anatomical characteristics include: 1) anatomical connectivity defined using DTI metrics between a pair of brain regions, and 2) topological measurements of anatomical networks. With the Bonferroni correction for multiple-comparison, significant alterations in community structure and local topology were identified as the p-value < 5%, which include: 1) a reduced nodal centrality (degree and strength) on right hippocampus for treated compared to untreated group, 2) an elevated clustering coefficient and local efficiency on right lateral orbitofrontal cortex for untreated compared to the combination of control and treated groups, 3) an increased participation coefficient for untreated patients on left insula cortex in the meandiffusivity network compared to the combination of control and treated groups, and 4) a degraded module degree z-score on right caudate nucleus for all the patients compared to the control group. Two connections, hippocampus-insula in the right hemisphere and parahippocampal-insula in the left hemisphere, were found significantly altered in TR, AD, and FA due to MDD.
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http://dx.doi.org/10.1109/EMBC.2018.8512505DOI Listing
July 2018

Classifying Treated vs. Untreated MDD Adolescents from Anatomical Connectivity using Nonlinear SVM.

Annu Int Conf IEEE Eng Med Biol Soc 2018 Jul;2018:1-4

Identification of the treatment-related responders for adolescent Major Depressive Disorder (MDD) is urgently needed to develop effective treatments. In this paper, machine learning based classifiers are used to reveal anatomical features as responders for distinguishing MDD patients who have received treatment from those who never received any treatment. The features are drawn from two sets of measurements: 1) anatomical connectivity defined by diffusion tensor imaging measurements between a pair of brain regions, and 2) topological measurements from anatomical networks. Feature selection was performed based on p-value and minimum redundancy maximum relevance (mRMR) method to achieve improved classification accuracy. The classification performance is evaluated with a leave-one-out cross-validation method using 37 treated and 15 untreated subjects. The proposed methodology achieves 73% accuracy, 100% specificity, and 100% precision for 52 subjects. The most distinguishing features are the strength of the right hippocampus of the mean diffusivity (MD) network at 18% density and of the track-count (TR) network, the participation coefficient of the left middle temporal gyrus of the radial diffusivity (RD) network at 20% density, the axial diffusivity (AD) connectivity between right middle temporal gyrus and right supramarginal gyrus, the betweenness centrality of the right hippocampus of the TR network at 11% density, the apparent diffusion coefficient (ADC) connectivity between the left pars opercularis and the left rostral anterior cingulate cortex, the clustering coefficient of the middle anterior corpus callosum of the TR network at 11% density, and the AD connectivity between the left pars opercularis and the left rostral anterior cingulate cortex.
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http://dx.doi.org/10.1109/EMBC.2018.8513168DOI Listing
July 2018