Publications by authors named "Kathryn R Cullen"

70 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

Classification of Adolescent Major Depressive Disorder via Static and Dynamic Connectivity.

IEEE J Biomed Health Inform 2020 Dec 9;PP. Epub 2020 Dec 9.

Prior papers have explored the functional connectivity changes for patients suffering from major depressive disorder (MDD). This paper introduces an approach for classifying adolescents suffering from MDD using resting-state fMRI. Accurate diagnosis of MDD involves interviews with adolescent patients and their parents, symptom rating scales based on Diagnostic and Statistical Manual of Mental Disorders (DSM), behavioral observation as well as the experience of a clinician. Discovering predictive biomarkers for diagnosing MDD patients using functional magnetic resonance imaging (fMRI) scans can assist the clinicians in their diagnostic assessments. This paper investigates various static and dynamic connectivity measures extracted from resting-state fMRI for assisting with MDD diagnosis. First, absolute Pearson correlation matrices from 85 brain regions are computed and they are used to calculate static features for predicting MDD. A predictive sub-network extracted using sub-graph entropy classifies adolescent MDD vs. typical healthy controls with high accuracy, sensitivity and specificity. Next, approaches utilizing dynamic connectivity are employed to extract tensor based, independent component based and principal component based subject specific attributes. Finally, features from static and dynamic approaches are combined to create a feature vector for classification. A leave-one-out cross-validation method is used for the final predictor performance. Out of 49 adolescents with MDD and 33 matched healthy controls, a support vector machine (SVM) classifier using a radial basis function (RBF) kernel using differential sub-graph entropy combined with dynamic connectivity features classifies MDD vs. healthy controls with an accuracy of 0.82 for leave-one-out cross-validation. This classifier has specificity and sensitivity of 0.79 and 0.84, respectively. This performance demonstrates the utility of MRI based diagnosis of psychiatric disorders like MDD using a combination of static and dynamic functional connectivity features of the brain.
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http://dx.doi.org/10.1109/JBHI.2020.3043427DOI Listing
December 2020

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

Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders.

Authors:
Yash Patel Nadine Parker Jean Shin Derek Howard Leon French Sophia I Thomopoulos Elena Pozzi Yoshinari Abe Christoph Abé Alan Anticevic Martin Alda Andre Aleman Clara Alloza Silvia Alonso-Lana Stephanie H Ameis Evdokia Anagnostou Andrew A McIntosh Celso Arango Paul D Arnold Philip Asherson Francesca Assogna Guillaume Auzias Rosa Ayesa-Arriola Geor Bakker Nerisa Banaj Tobias Banaschewski Cibele E Bandeira Alexandr Baranov Núria Bargalló Claiton H D Bau Sarah Baumeister Bernhard T Baune Mark A Bellgrove Francesco Benedetti Alessandro Bertolino Premika S W Boedhoe Marco Boks Irene Bollettini Caterina Del Mar Bonnin Tiana Borgers Stefan Borgwardt Daniel Brandeis Brian P Brennan Jason M Bruggemann Robin Bülow Geraldo F Busatto Sara Calderoni Vince D Calhoun Rosa Calvo Erick J Canales-Rodríguez Dara M Cannon Vaughan J Carr Nicola Cascella Mara Cercignani Tiffany M Chaim-Avancini Anastasia Christakou David Coghill Annette Conzelmann Benedicto Crespo-Facorro Ana I Cubillo Kathryn R Cullen Renata B Cupertino Eileen Daly Udo Dannlowski Christopher G Davey Damiaan Denys Christine Deruelle Annabella Di Giorgio Erin W Dickie Danai Dima Katharina Dohm Stefan Ehrlich Benjamin A Ely Tracy Erwin-Grabner Thomas Ethofer Damien A Fair Andreas J Fallgatter Stephen V Faraone Mar Fatjó-Vilas Jennifer M Fedor Kate D Fitzgerald Judith M Ford Thomas Frodl Cynthia H Y Fu Janice M Fullerton Matt C Gabel David C Glahn Gloria Roberts Tinatin Gogberashvili Jose M Goikolea Ian H Gotlib Roberto Goya-Maldonado Hans J Grabe Melissa J Green Eugenio H Grevet Nynke A Groenewold Dominik Grotegerd Oliver Gruber Patricia Gruner Amalia Guerrero-Pedraza Raquel E Gur Ruben C Gur Shlomi Haar Bartholomeus C M Haarman Jan Haavik Tim Hahn Tomas Hajek Benjamin J Harrison Neil A Harrison Catharina A Hartman Heather C Whalley Dirk J Heslenfeld Derrek P Hibar Eva Hilland Yoshiyuki Hirano Tiffany C Ho Pieter J Hoekstra Liesbeth Hoekstra Sarah Hohmann L E Hong Cyril Höschl Marie F Høvik Fleur M Howells Igor Nenadic Maria Jalbrzikowski Anthony C James Joost Janssen Fern Jaspers-Fayer Jian Xu Rune Jonassen Georgii Karkashadze Joseph A King Tilo Kircher Matthias Kirschner Kathrin Koch Peter Kochunov Gregor Kohls Kerstin Konrad Bernd Krämer Axel Krug Jonna Kuntsi Jun Soo Kwon Mikael Landén Nils I Landrø Luisa Lazaro Irina S Lebedeva Elisabeth J Leehr Sara Lera-Miguel Klaus-Peter Lesch Christine Lochner Mario R Louza Beatriz Luna Astri J Lundervold Frank P MacMaster Luigi A Maglanoc Charles B Malpas Maria J Portella Rachel Marsh Fiona M Martyn David Mataix-Cols Daniel H Mathalon Hazel McCarthy Colm McDonald Genevieve McPhilemy Susanne Meinert José M Menchón Luciano Minuzzi Philip B Mitchell Carmen Moreno Pedro Morgado Filippo Muratori Clodagh M Murphy Declan Murphy Benson Mwangi Leila Nabulsi Akiko Nakagawa Takashi Nakamae Leyla Namazova Janardhanan Narayanaswamy Neda Jahanshad Danai D Nguyen Rosa Nicolau Ruth L O'Gorman Tuura Kirsten O'Hearn Jaap Oosterlaan Nils Opel Roel A Ophoff Bob Oranje Victor Ortiz García de la Foz Bronwyn J Overs Yannis Paloyelis Christos Pantelis Mara Parellada Paul Pauli Maria Picó-Pérez Felipe A Picon Fabrizio Piras Federica Piras Kerstin J Plessen Edith Pomarol-Clotet Adrian Preda Olga Puig Yann Quidé Joaquim Radua J Antoni Ramos-Quiroga Paul E Rasser Lisa Rauer Janardhan Reddy Ronny Redlich Andreas Reif Liesbeth Reneman Jonathan Repple Alessandra Retico Vanesa Richarte Anja Richter Pedro G P Rosa Katya K Rubia Ryota Hashimoto Matthew D Sacchet Raymond Salvador Javier Santonja Kelvin Sarink Salvador Sarró Theodore D Satterthwaite Akira Sawa Ulrich Schall Peter R Schofield Anouk Schrantee Jochen Seitz Mauricio H Serpa Esther Setién-Suero Philip Shaw Devon Shook Tim J Silk Kang Sim Schmitt Simon Helen Blair Simpson Aditya Singh Antonin Skoch Norbert Skokauskas Jair C Soares Noam Soreni Carles Soriano-Mas Gianfranco Spalletta Filip Spaniel Stephen M Lawrie Emily R Stern S Evelyn Stewart Yoichiro Takayanagi Henk S Temmingh David F Tolin David Tomecek Diana Tordesillas-Gutiérrez Michela Tosetti Anne Uhlmann Therese van Amelsvoort Nic J A van der Wee Steven J A van der Werff Neeltje E M van Haren Guido A van Wingen Alasdair Vance Javier Vázquez-Bourgon Daniela Vecchio Ganesan Venkatasubramanian Eduard Vieta Oscar Vilarroya Yolanda Vives-Gilabert Aristotle N Voineskos Henry Völzke Georg G von Polier Esther Walton Thomas W Weickert Cynthia Shannon Weickert Andrea S Weideman Katharina Wittfeld Daniel H Wolf Mon-Ju Wu T T Yang Kun Yang Yuliya Yoncheva Je-Yeon Yun Yuqi Cheng Marcus V Zanetti Georg C Ziegler Barbara Franke Martine Hoogman Jan K Buitelaar Daan van Rooij Ole A Andreassen Christopher R K Ching Dick J Veltman Lianne Schmaal Dan J Stein Odile A van den Heuvel Jessica A Turner Theo G M van Erp Zdenka Pausova Paul M Thompson Tomáš Paus

JAMA Psychiatry 2021 Jan;78(1):47-63

Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.

Importance: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood.

Objective: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.

Design, Setting, And Participants: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244.

Main Outcomes And Measures: Interregional profiles of group difference in cortical thickness between cases and controls.

Results: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders.

Conclusions And Relevance: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.
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http://dx.doi.org/10.1001/jamapsychiatry.2020.2694DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450410PMC
January 2021

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

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

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

Sub-graph entropy based network approaches for classifying adolescent obsessive-compulsive disorder from resting-state functional MRI.

Neuroimage Clin 2020 6;26:102208. Epub 2020 Feb 6.

Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis. Electronic address:

This paper presents a novel approach for classifying obsessive-compulsive disorder (OCD) in adolescents from resting-state fMRI data. Currently, the state-of-the-art for diagnosing OCD in youth involves interviews with adolescent patients and their parents by an experienced clinician, symptom rating scales based on Diagnostic and Statistical Manual of Mental Disorders (DSM), and behavioral observation. Discovering signal processing and network-based biomarkers from functional magnetic resonance imaging (fMRI) scans of patients has the potential to assist clinicians in their diagnostic assessments of adolescents suffering from OCD. This paper investigates the clinical diagnostic utility of a set of univariate, bivariate and multivariate features extracted from resting-state fMRI using an information-theoretic approach in 15 adolescents with OCD and 13 matched healthy controls. Results indicate that an information-theoretic approach based on sub-graph entropy is capable of classifying OCD vs. healthy subjects with high accuracy. Mean time-series were extracted from 85 brain regions and were used to calculate Shannon wavelet entropy, Pearson correlation matrix, network features and sub-graph entropy. In addition, two special cases of sub-graph entropy, namely node and edge entropy, were investigated to identify important brain regions and edges from OCD patients. A leave-one-out cross-validation method was used for the final predictor performance. The proposed methodology using differential sub-graph (edge) entropy achieved an accuracy of 0.89 with specificity 1 and sensitivity 0.80 using leave-one-out cross-validation with in-fold feature ranking and selection. The high classification accuracy indicates the predictive power of the sub-network as well as edge entropy metric.
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http://dx.doi.org/10.1016/j.nicl.2020.102208DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7025090PMC
February 2020

Sub-graph entropy based network approaches for classifying adolescent obsessive-compulsive disorder from resting-state functional MRI.

Neuroimage Clin 2020 6;26:102208. Epub 2020 Feb 6.

Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis. Electronic address:

This paper presents a novel approach for classifying obsessive-compulsive disorder (OCD) in adolescents from resting-state fMRI data. Currently, the state-of-the-art for diagnosing OCD in youth involves interviews with adolescent patients and their parents by an experienced clinician, symptom rating scales based on Diagnostic and Statistical Manual of Mental Disorders (DSM), and behavioral observation. Discovering signal processing and network-based biomarkers from functional magnetic resonance imaging (fMRI) scans of patients has the potential to assist clinicians in their diagnostic assessments of adolescents suffering from OCD. This paper investigates the clinical diagnostic utility of a set of univariate, bivariate and multivariate features extracted from resting-state fMRI using an information-theoretic approach in 15 adolescents with OCD and 13 matched healthy controls. Results indicate that an information-theoretic approach based on sub-graph entropy is capable of classifying OCD vs. healthy subjects with high accuracy. Mean time-series were extracted from 85 brain regions and were used to calculate Shannon wavelet entropy, Pearson correlation matrix, network features and sub-graph entropy. In addition, two special cases of sub-graph entropy, namely node and edge entropy, were investigated to identify important brain regions and edges from OCD patients. A leave-one-out cross-validation method was used for the final predictor performance. The proposed methodology using differential sub-graph (edge) entropy achieved an accuracy of 0.89 with specificity 1 and sensitivity 0.80 using leave-one-out cross-validation with in-fold feature ranking and selection. The high classification accuracy indicates the predictive power of the sub-network as well as edge entropy metric.
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http://dx.doi.org/10.1016/j.nicl.2020.102208DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7025090PMC
February 2020

Sub-graph entropy based network approaches for classifying adolescent obsessive-compulsive disorder from resting-state functional MRI.

Neuroimage Clin 2020 6;26:102208. Epub 2020 Feb 6.

Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis. Electronic address:

This paper presents a novel approach for classifying obsessive-compulsive disorder (OCD) in adolescents from resting-state fMRI data. Currently, the state-of-the-art for diagnosing OCD in youth involves interviews with adolescent patients and their parents by an experienced clinician, symptom rating scales based on Diagnostic and Statistical Manual of Mental Disorders (DSM), and behavioral observation. Discovering signal processing and network-based biomarkers from functional magnetic resonance imaging (fMRI) scans of patients has the potential to assist clinicians in their diagnostic assessments of adolescents suffering from OCD. This paper investigates the clinical diagnostic utility of a set of univariate, bivariate and multivariate features extracted from resting-state fMRI using an information-theoretic approach in 15 adolescents with OCD and 13 matched healthy controls. Results indicate that an information-theoretic approach based on sub-graph entropy is capable of classifying OCD vs. healthy subjects with high accuracy. Mean time-series were extracted from 85 brain regions and were used to calculate Shannon wavelet entropy, Pearson correlation matrix, network features and sub-graph entropy. In addition, two special cases of sub-graph entropy, namely node and edge entropy, were investigated to identify important brain regions and edges from OCD patients. A leave-one-out cross-validation method was used for the final predictor performance. The proposed methodology using differential sub-graph (edge) entropy achieved an accuracy of 0.89 with specificity 1 and sensitivity 0.80 using leave-one-out cross-validation with in-fold feature ranking and selection. The high classification accuracy indicates the predictive power of the sub-network as well as edge entropy metric.
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http://dx.doi.org/10.1016/j.nicl.2020.102208DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7025090PMC
February 2020

Sub-graph entropy based network approaches for classifying adolescent obsessive-compulsive disorder from resting-state functional MRI.

Neuroimage Clin 2020 6;26:102208. Epub 2020 Feb 6.

Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis. Electronic address:

This paper presents a novel approach for classifying obsessive-compulsive disorder (OCD) in adolescents from resting-state fMRI data. Currently, the state-of-the-art for diagnosing OCD in youth involves interviews with adolescent patients and their parents by an experienced clinician, symptom rating scales based on Diagnostic and Statistical Manual of Mental Disorders (DSM), and behavioral observation. Discovering signal processing and network-based biomarkers from functional magnetic resonance imaging (fMRI) scans of patients has the potential to assist clinicians in their diagnostic assessments of adolescents suffering from OCD. This paper investigates the clinical diagnostic utility of a set of univariate, bivariate and multivariate features extracted from resting-state fMRI using an information-theoretic approach in 15 adolescents with OCD and 13 matched healthy controls. Results indicate that an information-theoretic approach based on sub-graph entropy is capable of classifying OCD vs. healthy subjects with high accuracy. Mean time-series were extracted from 85 brain regions and were used to calculate Shannon wavelet entropy, Pearson correlation matrix, network features and sub-graph entropy. In addition, two special cases of sub-graph entropy, namely node and edge entropy, were investigated to identify important brain regions and edges from OCD patients. A leave-one-out cross-validation method was used for the final predictor performance. The proposed methodology using differential sub-graph (edge) entropy achieved an accuracy of 0.89 with specificity 1 and sensitivity 0.80 using leave-one-out cross-validation with in-fold feature ranking and selection. The high classification accuracy indicates the predictive power of the sub-network as well as edge entropy metric.
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http://dx.doi.org/10.1016/j.nicl.2020.102208DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7025090PMC
February 2020

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

No Alterations of Brain Structural Asymmetry in Major Depressive Disorder: An ENIGMA Consortium Analysis.

Am J Psychiatry 2019 12 29;176(12):1039-1049. Epub 2019 Jul 29.

The Department of Language and Genetics, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands (de Kovel, Francks); Orygen, the National Centre of Excellence in Youth Mental Health, Melbourne, Australia (Davey); the Department of Psychiatry, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam (Veltman); the Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey (Jahanshad, Thompson); the Laboratory of Affective, Cognitive, and Translational Neuroscience, Scientific Research Institute of Physiology and Basic Medicine, Novosibirsk, Russian Federation (Aftanas, Brack, Osipov); the Department of Neuroscience, Neuroimaging Center, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (Aleman); the Department of Psychiatry, University of Melbourne, Melbourne (Baune); the Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany (Bülow); the Laboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil (Busatto Filho, Rosa); the Department of Psychiatry, Trinity College Dublin (Carballedo, Frodl); the Department of Psychiatry and the Weill Institute for Neurosciences, Division of Child and Adolescent Psychiatry, University of California, San Francisco (Connolly, Ho, Yang); the Department of Psychiatry, University of Minnesota Medical School, Minneapolis (Cullen, Mueller, Ubani, Schreiner); the Department of Psychiatry, University of Münster, Münster, Germany (Dannlowski, Dohm, Grotegerd, Leehr, Sindermann, Winter, Zaremba); the Department of Psychology, School of Arts and Social Sciences, City, University of London, London (Dima); the Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany (Erwin-Grabner; Goya-Maldonado, Schnell, Singh); the Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany (Frodl); the Centre for Affective Disorders, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Fu); the Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, Canada (Hall); the Department of Psychiatry, Yale School of Medicine, New Haven, Conn. (Alexander-Bloch, Glahn); the Psychopharmacology Research Unit, Department of Psychiatry, University of Oxford, Oxford, U.K. (Godlewska); the Department of Psychology, Stanford University, Stanford, Calif. (Gotlib, Ho); the Department of Psychiatry and Psychotherapy, University Medicine Greifswald (Grabe, Wittfeld); the Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, University Medical Center Groningen (Groenewold); the Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany (Gruber, Krämer, Simulionyte); the Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, and Melbourne Health, Melbourne (Harrison); the Youth Mental Health Team, Brain and Mind Centre, University of Sydney, Sydney, Australia (Hatton, Hickie, Lagopoulos); the Department of Psychiatry and Psychotherapy, Philipps University Marburg, Marburg, Germany (Kircher, Krug, Nenadic, Yüksel); the Department of Neurology, University of Magdeburg, Magdeburg (Li); the Departments of Psychiatry and Paediatrics, University of Calgary, Calgary, Canada (MacMaster, McLellan); the Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary (MacQueen); the Division of Psychiatry, University of Edinburgh, Edinburgh (Harris, McIntosh, Papmeyer, Whalley); Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia (Medland); the Department. of Psychiatry, Institute of Biomedical Research Sant Pau, Barcelona, Spain (Portella); the Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam (Reneman, Schrantee); the Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Sacchet); West Region and Research Division, Institute of Mental Health, Singapore (Sim); Medical Research Council Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa (Groenewold, Stein); Brain Function and Dysfunction, Leids Universitair Medisch Centrum, Leiden, the Netherlands (Van der Wee); the Department of Psychiatry, Leiden University Medical Center, Leiden (Van der Werff); the Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin (Veer, H. Walter); the Institute of Information and Communication Technologies (Instituto ITACA), Universitat Politècnica de València, València, Spain (Gilabert); the Institute for Community Medicine, University Medicine Greifswald, Greifswald (Völzke); the Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany (M. Walter); the Department of Psychology, University of Minnesota, Minneapolis (Schreiner); the German Center for Neurodegenerative Diseases, Site Rostock/Greifswald (Grabe, Wittfeld); the Department of Neuroscience, Novosibirsk State University, Novosibirsk (Aftanas); the Department of Psychology, University of Groningen, Groningen (Aleman); the Center for Interdisciplinary Research on Applied Neurosciences, University of São Paulo, São Paulo (Busatto Filho, Rosa); the Department of Biomedical Sciences, Florida State University, Tallahassee (Connolly); the Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Dima); the Donders Institute for Brain, Cognition, and Behavior, Radboud University Nijmegen (Francks); the School of Psychology, University of East London, London (Fu); the Sunshine Coast Mind and Neuroscience Thompson Institute, Queensland, Australia (Lagopoulos); Strategic Clinical Network for Addictions and Mental Health, Alberta, Canada (MacMaster); the Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh (McIntosh); the Rehabilitation Services and Care Unit, Swiss Paraplegic Research, Nottwil, Switzerland (Papmeyer); CIBERSAM, Madrid (Portella); the Centre for Youth Mental Health, University of Melbourne, Melbourne (Davey, Schmaal); the Spinoza Center for Neuroimaging, Royal Netherlands Academy of Arts and Sciences, Amsterdam (Schrantee); Yong Loo Lin School of Medicine, National University of Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (Sim); the School of Public Health, Boston University, Boston (Ubani); the Leiden Institute for Brain and Cognition, Leiden (Van der Werff); the German Center for Cardiovascular Research, partner site Greifswald, Greifswald (Völzke).

Objective: Asymmetry is a subtle but pervasive aspect of the human brain, and it may be altered in several psychiatric conditions. MRI studies have shown subtle differences of brain anatomy between people with major depressive disorder and healthy control subjects, but few studies have specifically examined brain anatomical asymmetry in relation to this disorder, and results from those studies have remained inconclusive. At the functional level, some electroencephalography studies have indicated left fronto-cortical hypoactivity and right parietal hypoactivity in depressive disorders, so aspects of lateralized anatomy may also be affected. The authors used pooled individual-level data from data sets collected around the world to investigate differences in laterality in measures of cortical thickness, cortical surface area, and subcortical volume between individuals with major depression and healthy control subjects.

Methods: The authors investigated differences in the laterality of thickness and surface area measures of 34 cerebral cortical regions in 2,256 individuals with major depression and 3,504 control subjects from 31 separate data sets, and they investigated volume asymmetries of eight subcortical structures in 2,540 individuals with major depression and 4,230 control subjects from 32 data sets. T-weighted MRI data were processed with a single protocol using FreeSurfer and the Desikan-Killiany atlas. The large sample size provided 80% power to detect effects of the order of Cohen's d=0.1.

Results: The largest effect size (Cohen's d) of major depression diagnosis was 0.085 for the thickness asymmetry of the superior temporal cortex, which was not significant after adjustment for multiple testing. Asymmetry measures were not significantly associated with medication use, acute compared with remitted status, first episode compared with recurrent status, or age at onset.

Conclusions: Altered brain macro-anatomical asymmetry may be of little relevance to major depression etiology in most cases.
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http://dx.doi.org/10.1176/appi.ajp.2019.18101144DOI Listing
December 2019

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

Sertraline Effects on Striatal Resting-State Functional Connectivity in Youth With Obsessive-Compulsive Disorder: A Pilot Study.

J Am Acad Child Adolesc Psychiatry 2019 05 30;58(5):486-495. Epub 2018 Oct 30.

University of Minnesota, Minneapolis.

Objective: Foundational knowledge on neural circuitry underlying pediatric obsessive-compulsive disorder (OCD) and how it changes during standard treatment is needed to provide the basis for conceptualization and development of novel targeted treatments. This study explored the effects of sertraline, a selective serotonin reuptake inhibitor, on resting-state functional connectivity in cortico-striatal-thalamic-cortical circuits in pediatric OCD.

Method: Medication-free youths with OCD (n = 14) and healthy controls (n = 14) were examined at baseline and 12 weeks with resting-state functional magnetic resonance imaging. Between scan sessions, participants with OCD received 12 weeks of sertraline. For each scan, seed-based whole-brain resting-state functional connectivity analyses were conducted with 6 striatal seeds. Analysis of variance examined the interaction between group and time on striatal connectivity, including cluster-based thresholding to correct for multiple tests. Connectivity changes within circuits identified in group analyses were correlated with clinical change.

Results: Two significant group-by-time effects in the OCD group showed increased striatal connectivity from baseline to 12 weeks compared with controls. Circuits demonstrating this pattern included the right putamen with the left frontal cortex and insula and the left putamen with the left frontal cortex and pre- and post-central cortices. Increase in connectivity in the left putamen circuit was significantly correlated with clinical improvement on the Children's Yale-Brown Obsessive-Compulsive Scale score (r = -0.58, p = .03).

Conclusion: Sertraline appears to affect specific striatal-based circuits in pediatric OCD, and these changes in part could account for clinical improvement. Future work is needed to confirm these preliminary findings, which would facilitate identification of circuit-based targets for novel treatment development.

Clinical Trial Registration Information: Effects of Sertraline on Brain Connectivity in Adolescents with OCD; https://clinicaltrials.gov/; NCT02797808.
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http://dx.doi.org/10.1016/j.jaac.2018.07.897DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6487209PMC
May 2019

Sertraline Effects on Striatal Resting-State Functional Connectivity in Youth With Obsessive-Compulsive Disorder: A Pilot Study.

J Am Acad Child Adolesc Psychiatry 2019 05 30;58(5):486-495. Epub 2018 Oct 30.

University of Minnesota, Minneapolis.

Objective: Foundational knowledge on neural circuitry underlying pediatric obsessive-compulsive disorder (OCD) and how it changes during standard treatment is needed to provide the basis for conceptualization and development of novel targeted treatments. This study explored the effects of sertraline, a selective serotonin reuptake inhibitor, on resting-state functional connectivity in cortico-striatal-thalamic-cortical circuits in pediatric OCD.

Method: Medication-free youths with OCD (n = 14) and healthy controls (n = 14) were examined at baseline and 12 weeks with resting-state functional magnetic resonance imaging. Between scan sessions, participants with OCD received 12 weeks of sertraline. For each scan, seed-based whole-brain resting-state functional connectivity analyses were conducted with 6 striatal seeds. Analysis of variance examined the interaction between group and time on striatal connectivity, including cluster-based thresholding to correct for multiple tests. Connectivity changes within circuits identified in group analyses were correlated with clinical change.

Results: Two significant group-by-time effects in the OCD group showed increased striatal connectivity from baseline to 12 weeks compared with controls. Circuits demonstrating this pattern included the right putamen with the left frontal cortex and insula and the left putamen with the left frontal cortex and pre- and post-central cortices. Increase in connectivity in the left putamen circuit was significantly correlated with clinical improvement on the Children's Yale-Brown Obsessive-Compulsive Scale score (r = -0.58, p = .03).

Conclusion: Sertraline appears to affect specific striatal-based circuits in pediatric OCD, and these changes in part could account for clinical improvement. Future work is needed to confirm these preliminary findings, which would facilitate identification of circuit-based targets for novel treatment development.

Clinical Trial Registration Information: Effects of Sertraline on Brain Connectivity in Adolescents with OCD; https://clinicaltrials.gov/; NCT02797808.
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http://dx.doi.org/10.1016/j.jaac.2018.07.897DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6487209PMC
May 2019

Resting state functional connectivity of networks associated with reward and habit in anorexia nervosa.

Hum Brain Mapp 2019 02 25;40(2):652-662. Epub 2018 Sep 25.

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

Neurobiological disturbances associated with reward and/or habit learning are theorized to maintain symptoms of anorexia nervosa (AN). Although research has investigated responses in brain regions associated with reward and habit to disorder-specific cues (e.g., food) and presumed rewards (e.g., money), little is known about the functional organization of the circuits underlying these constructs independent of stimulus. This study aimed to provide initial data on the synchrony of networks associated with reward and habit in AN by comparing resting-state functional connectivity (RSFC) patterns between AN and healthy control (HC) participants in these circuits and delineating how these patterns relate to symptoms. Using theoretically selected seeds in the nucleus accumbens (NAcc), ventral caudate, and dorsal caudate, reflecting a continuum from reward- to habit- oriented regions, RSFC patterns were compared between AN restricting subtype (n = 19) and HC (n = 19) participants (cluster threshold: p < .01). Exploratory correlations between RSFC z-scores and Eating Disorder Examination (EDE) scores, BMI, and illness duration were conducted. The AN group demonstrated lower RSFC between the NAcc and superior frontal gyrus, between the ventral caudate and frontal and posterior regions, and between the dorsal caudate and frontal, temporal, and posterior regions. In the AN group, lower NAcc- superior frontal gyrus RSFC correlated with greater EDE Global scores (r = -.58, CI: -.83, -.13). These resting-state synchrony disruptions of the ventral and dorsal frontostriatal circuits, considered in context of the broader literature, support the utility of further investigating possible reward and habit disturbances supporting symptoms in AN.
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http://dx.doi.org/10.1002/hbm.24402DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314844PMC
February 2019

Increases in orbitofrontal cortex thickness following antidepressant treatment are associated with changes in resting state autonomic function in adolescents with major depression - Preliminary findings from a pilot study.

Psychiatry Res Neuroimaging 2018 11 24;281:35-42. Epub 2018 Aug 24.

Department of Psychiatry, University of Minnesota, Medical School, F256/2B West Building, 2450 Riverside Avenue, Minneapolis, MN, USA. Electronic address:

In adults with major depressive disorder (MDD), effective treatment has been associated with increases in both heart rate variability (HRV) and cortical thickness. However, the impact of treatment on these indices has not yet been examined in adolescents. Cortical thickness and HRV were measured in twelve adolescents with MDD before and after 8 weeks of treatment with a selective serotonin reuptake inhibitor (SSRI). We examined treatment-related changes in depression symptoms, HRV, heart rate (HR), and cortical thickness, and analyzed correlations among these change indices. At follow-up, patients showed significantly decreased depression severity, increased HRV and increased thickness of the left medial orbitofrontal cortex (OFC). Clinical improvement was associated with increased HRV and decreased HR. Increased HRV was associated with increased cortical thickness of left lateral OFC and superior frontal cortex. Due to the small sample size, results represent preliminary findings that need replication. Further, in the absence of a placebo arm, we cannot confirm that the observed effects are due solely to medication. These preliminary findings suggest that SSRI treatment in adolescents impacts both cortical thickness and autonomic functioning. Confirmation of these findings would support OFC thickness and HRV as neurobiological mediators of treatment outcome.
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http://dx.doi.org/10.1016/j.pscychresns.2018.08.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6204080PMC
November 2018

Spontaneous Thoughts and Brain Connectivity: Possible Links Between Early Maltreatment and Later Depression.

Authors:
Kathryn R Cullen

J Am Acad Child Adolesc Psychiatry 2018 09;57(9):634-636

University of Minnesota Medical School, Minneapolis. Electronic address:

Maltreatment (MT) during childhood wreaks lasting havoc on the developing central nervous system and is one of the most salient risk factors for numerous psychiatric disorders, including depression. Early intervention and prevention strategies to improve outcomes of youth who have experienced MT are sorely needed; advancement in this area will require a deeper understanding of the neurobiological trajectory between the occurrence of MT and the later emergence of illness. One approach is to select neurobiological measures that are known to be impaired in the fully fledged disorder and use them to assess youth with a history of MT who have not yet shown impairment. In depression research, an emerging research area is to study spontaneously generated thoughts that occur while awake but at unstructured times, when thoughts tend to wander. Mind wandering has been linked with intelligence, creative thought generation, and resting-state functional connectivity within the default mode network. However, in depression, these wandering thoughts can get stuck on negative content and could represent a core feature of the illness. Therefore, examination of spontaneously generated thoughts, and their neural correlates, is a promising avenue for research seeking precursors of depression in youth with a history of MT.
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http://dx.doi.org/10.1016/j.jaac.2018.06.008DOI Listing
September 2018

Persistent Impairment: Life After Losing a Parent.

Authors:
Kathryn R Cullen

Am J Psychiatry 2018 09;175(9):820-821

From the Department of Psychiatry, Division of Child and Adolescent Psychiatry, University of Minnesota Medical School, Minneapolis.

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http://dx.doi.org/10.1176/appi.ajp.2018.18050572DOI Listing
September 2018

Brain metabolism changes in women with BPD undergoing olanzapine treatment.

Psychiatry Res Neuroimaging 2018 09 27;279:19-21. Epub 2018 Jul 27.

Department of Psychiatry, University of Minnesota, 717 Delaware St SE, Minneapolis, MN 55414, USA.

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http://dx.doi.org/10.1016/j.pscychresns.2018.06.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6368919PMC
September 2018

Intravenous Ketamine for Adolescents with Treatment-Resistant Depression: An Open-Label Study.

J Child Adolesc Psychopharmacol 2018 09 13;28(7):437-444. Epub 2018 Jul 13.

3 Psychology Department, College of Liberal Arts, University of Minnesota , Minneapolis, Minnesota.

Background: Novel interventions for treatment-resistant depression (TRD) in adolescents are urgently needed. Ketamine has been studied in adults with TRD, but little information is available for adolescents. This study investigated efficacy and tolerability of intravenous ketamine in adolescents with TRD, and explored clinical response predictors.

Methods: Adolescents, 12-18 years of age, with TRD (failure to respond to two previous antidepressant trials) were administered six ketamine (0.5 mg/kg) infusions over 2 weeks. Clinical response was defined as a 50% decrease in Children's Depression Rating Scale-Revised (CDRS-R); remission was CDRS-R score ≤28. Tolerability assessment included monitoring vital signs and dissociative symptoms using the Clinician-Administered Dissociative States Scale (CADSS).

Results: Thirteen participants (mean age 16.9 years, range 14.5-18.8 years, eight biologically male) completed the protocol. Average decrease in CDRS-R was 42.5% (p = 0.0004). Five (38%) adolescents met criteria for clinical response. Three responders showed sustained remission at 6-week follow-up; relapse occurred within 2 weeks for the other two responders. Ketamine infusions were generally well tolerated; dissociative symptoms and hemodynamic symptoms were transient. Higher dose was a significant predictor of treatment response.

Conclusions: These results demonstrate the potential role for ketamine in treating adolescents with TRD. Limitations include the open-label design and small sample; future research addressing these issues are needed to confirm these results. Additionally, evidence suggested a dose-response relationship; future studies are needed to optimize dose. Finally, questions remain regarding the long-term safety of ketamine as a depression treatment; more information is needed before broader clinical use.
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http://dx.doi.org/10.1089/cap.2018.0030DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6154760PMC
September 2018