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Ronde M, van der Zee EA, Kas MJH. Default mode network dynamics: An integrated neurocircuitry perspective on social dysfunction in human brain disorders. Neurosci Biobehav Rev 2024; 164:105839. [PMID: 39097251 DOI: 10.1016/j.neubiorev.2024.105839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 07/25/2024] [Accepted: 07/31/2024] [Indexed: 08/05/2024]
Abstract
Our intricate social brain is implicated in a range of brain disorders, where social dysfunction emerges as a common neuropsychiatric feature cutting across diagnostic boundaries. Understanding the neurocircuitry underlying social dysfunction and exploring avenues for its restoration could present a transformative and transdiagnostic approach to overcoming therapeutic challenges in these disorders. The brain's default mode network (DMN) plays a crucial role in social functioning and is implicated in various neuropsychiatric conditions. By thoroughly examining the current understanding of DMN functionality, we propose that the DMN integrates diverse social processes, and disruptions in brain communication at regional and network levels due to disease hinder the seamless integration of these social functionalities. Consequently, this leads to an altered balance between self-referential and attentional processes, alongside a compromised ability to adapt to social contexts and anticipate future social interactions. Looking ahead, we explore how adopting an integrated neurocircuitry perspective on social dysfunction could pave the way for innovative therapeutic approaches to address brain disorders.
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Affiliation(s)
- Mirthe Ronde
- Groningen Institute for Evolutionary Life Sciences (GELIFES), Neurobiology, University of Groningen, Nijenborgh 7, Groningen 9747 AG, the Netherlands
| | - Eddy A van der Zee
- Groningen Institute for Evolutionary Life Sciences (GELIFES), Neurobiology, University of Groningen, Nijenborgh 7, Groningen 9747 AG, the Netherlands
| | - Martien J H Kas
- Groningen Institute for Evolutionary Life Sciences (GELIFES), Neurobiology, University of Groningen, Nijenborgh 7, Groningen 9747 AG, the Netherlands.
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2
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Laubacher C, Imhoff-Smith TP, Klaus DR, Frye CJ, Esnault S, Busse WW, Rosenkranz MA. Salience network resting state functional connectivity during airway inflammation in asthma: A feature of mental health resilience? Brain Behav Immun 2024; 122:9-17. [PMID: 39097203 DOI: 10.1016/j.bbi.2024.07.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 07/07/2024] [Accepted: 07/28/2024] [Indexed: 08/05/2024] Open
Abstract
BACKGROUND Inflammation is an established contributor to the pathophysiology of depression and the prevalence of depression in those with chronic inflammatory disease is two- to four-fold higher than the general population. Yet little is known about the neurobiological changes that confer depression or resilience to depression, that occur when episodes of heightened inflammation are frequent or span many years. METHODS We used an innovative combination of longitudinal resting state functional magnetic resonance imaging coupled to segmental bronchial provocation with allergen (SBP-Ag) to assess changes in resting state functional connectivity (rsFC) of the salience network (SN) caused by an acute inflammatory exacerbation in twenty-six adults (15 female) with asthma and varying levels of depressive symptoms. Eosinophils measured in bronchoalveolar lavage fluid and blood provided an index of allergic inflammation and the Beck Depression Inventory provided an index of depressive symptoms. RESULTS We found that in those with the highest symptoms of depression at baseline, SN rsFC declined most from pre- to post-SBP-Ag in the context of a robust eosinophilic response to challenge, but in those with low depressive symptoms SN rsFC was maintained or increased, even in those with the most pronounced SBP-Ag response. CONCLUSIONS Thus, the maintenance of SN rsFC during inflammation may be a biomarker of resilience to depression, perhaps via more effective orchestration of large-scale brain network dynamics by the SN. These findings advance our understanding of the functional role of the SN during inflammation and inform treatment recommendations for those with comorbid inflammatory disease and depression.
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Affiliation(s)
- Claire Laubacher
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA
| | - Theodore P Imhoff-Smith
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, 600 Highland Ave, Madison, WI 53792, USA
| | - Danika R Klaus
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, 600 Highland Ave, Madison, WI 53792, USA
| | - Corrina J Frye
- Waisman Center, University of Wisconsin-Madison, 1500 Highland Ave, Madison, WI 53705, USA
| | - Stephane Esnault
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, 600 Highland Ave, Madison, WI 53792, USA; University of Lille, INSERM, CHU Lille, U1286 - INFINITE - Institute for Translational Research in Inflammation, F-59000 Lille, France
| | - William W Busse
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, 600 Highland Ave, Madison, WI 53792, USA
| | - Melissa A Rosenkranz
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA; Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719, USA.
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3
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Ho NCW, Bethlehem RAI, Seidlitz J, Nogovitsyn N, Metzak P, Ballester PL, Hassel S, Rotzinger S, Poppenk J, Lam RW, Taylor VH, Milev R, Bullmore ET, Alexander-Bloch AF, Frey BN, Harkness KL, Addington J, Kennedy SH, Dunlop K. Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:786-799. [PMID: 38679324 DOI: 10.1016/j.bpsc.2024.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 04/04/2024] [Accepted: 04/11/2024] [Indexed: 05/01/2024]
Abstract
BACKGROUND Patients with major depressive disorder (MDD) can present with altered brain structure and deficits in cognitive function similar to those seen in aging. However, the interaction between age-related brain changes and brain development in MDD remains understudied. In a cohort of adolescents and adults with and without MDD, we assessed brain aging differences and associations through a newly developed tool that quantifies normative neurodevelopmental trajectories. METHODS A total of 304 participants with MDD and 236 control participants without depression were recruited and scanned from 3 studies under the Canadian Biomarker Integration Network for Depression. Volumetric data were used to generate brain centile scores, which were examined for 1) differences between participants with MDD and control participants; 2) differences between individuals with versus without severe childhood maltreatment; and 3) correlations with depressive symptom severity, neurocognitive assessment domains, and escitalopram treatment response. RESULTS Brain centiles were significantly lower in the MDD group than in the control group. Brain centile was also significantly correlated with working memory in the control group but not the MDD group. No significant associations were observed between depression severity or antidepressant treatment response and brain centiles. Likewise, childhood maltreatment history did not significantly affect brain centiles. CONCLUSIONS Consistent with previous work on machine learning models that predict brain age, brain centile scores differed in people diagnosed with MDD, and MDD was associated with differential relationships between centile scores and working memory. The results support the notion of atypical development and aging in MDD, with implications for neurocognitive deficits associated with aging-related cognitive function.
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Affiliation(s)
- Natalie C W Ho
- Keenan Research Centre for Biomedical Research, Unity Health Toronto, Toronto, Ontario, Canada; Centre for Depression & Suicide Studies, Unity Health Toronto, Toronto, Ontario, Canada; Faculty of Arts and Sciences, University of Toronto, Toronto, Ontario, Canada
| | | | - Jakob Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Institute of Translational Medicine & Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Nikita Nogovitsyn
- Centre for Depression & Suicide Studies, Unity Health Toronto, Toronto, Ontario, Canada
| | - Paul Metzak
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
| | - Pedro L Ballester
- Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Stefanie Hassel
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute and Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, Alberta, Canada
| | - Susan Rotzinger
- Keenan Research Centre for Biomedical Research, Unity Health Toronto, Toronto, Ontario, Canada; Centre for Depression & Suicide Studies, Unity Health Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Mood Disorders Treatment and Research Centre, St Joseph's Healthcare, Hamilton, Ontario, Canada; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
| | - Jordan Poppenk
- Centre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada; Department of Psychology, Queen's University, Kingston, Ontario, Canada; School of Computing, Queen's University, Kingston, Ontario, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Valerie H Taylor
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute and Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, Alberta, Canada
| | - Roumen Milev
- Department of Psychology, Queen's University, Kingston, Ontario, Canada; Department of Psychiatry, Queen's University, Kingston, Ontario, Canada; Providence Care Hospital, Kingston, Ontario, Canada
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Institute of Translational Medicine & Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Benicio N Frey
- Mood Disorders Treatment and Research Centre, St Joseph's Healthcare, Hamilton, Ontario, Canada; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
| | - Kate L Harkness
- Department of Psychology, Queen's University, Kingston, Ontario, Canada; Department of Psychiatry, Queen's University, Kingston, Ontario, Canada
| | - Jean Addington
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute and Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, Alberta, Canada
| | - Sidney H Kennedy
- Keenan Research Centre for Biomedical Research, Unity Health Toronto, Toronto, Ontario, Canada; Centre for Depression & Suicide Studies, Unity Health Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Katharine Dunlop
- Keenan Research Centre for Biomedical Research, Unity Health Toronto, Toronto, Ontario, Canada; Centre for Depression & Suicide Studies, Unity Health Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.
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Williams LM, Whitfield Gabrieli S. Neuroimaging for precision medicine in psychiatry. Neuropsychopharmacology 2024:10.1038/s41386-024-01917-z. [PMID: 39039140 DOI: 10.1038/s41386-024-01917-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 06/24/2024] [Accepted: 06/27/2024] [Indexed: 07/24/2024]
Abstract
Although the lifetime burden due to mental disorders is increasing, we lack tools for more precise diagnosing and treating prevalent and disabling disorders such as major depressive disorder. We lack strategies for selecting among available treatments or expediting access to new treatment options. This critical review concentrates on functional neuroimaging as a modality of measurement for precision psychiatry, focusing on major depressive and anxiety disorders. We begin by outlining evidence for the use of functional neuroimaging to stratify the heterogeneity of these disorders, based on underlying circuit dysfunction. We then review the current landscape of how functional neuroimaging-derived circuit predictors can predict treatment outcomes and clinical trajectories in depression and anxiety. Future directions for advancing clinically appliable neuroimaging measures are considered. We conclude by considering the opportunities and challenges of translating neuroimaging measures into practice. As an illustration, we highlight one approach for quantifying brain circuit function at an individual level, which could serve as a model for clinical translation.
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Affiliation(s)
- Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.
- Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC) Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, 94304, USA.
| | - Susan Whitfield Gabrieli
- Department of Psychology, Northeastern University, 805 Columbus Ave, Boston, MA, 02120, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
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Smucny J, Lesh TA, Albuquerque MD, Rhilinger JP, Carter CS. Predicting Clinical Improvement in Early Psychosis Using Circuit-Based Resting-State Functional Magnetic Resonance Imaging. Schizophr Bull 2024:sbae117. [PMID: 38979781 DOI: 10.1093/schbul/sbae117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
BACKGROUND AND HYPOTHESIS Identifying biomarkers that predict treatment response in early psychosis (EP) is a priority for psychiatry research. Previous work suggests that resting-state connectivity biomarkers may have promise as predictive measures, although prior results vary considerably in direction and magnitude. Here, we evaluated the relationship between intrinsic functional connectivity of the attention, default mode, and salience resting-state networks and 12-month clinical improvement in EP. STUDY DESIGN Fifty-eight individuals with EP (less than 2 years from illness onset, 35 males, average age 20 years) had baseline and follow-up clinical data and were included in the final sample. Of these, 30 EPs showed greater than 20% improvement in Brief Psychiatric Rating Scale (BPRS) total score at follow-up and were classified as "Improvers." STUDY RESULTS The overall logistic regression predicting Improver status was significant (χ2 = 23.66, Nagelkerke's R2 = 0.45, P < .001, with 85% concordance). Significant individual predictors of Improver status included higher default mode within-network connectivity, higher attention-default mode between-network connectivity, and higher attention-salience between-network connectivity. Including baseline BPRS as a predictor increased model significance and concordance to 92%, and the model was not significantly influenced by the dose of antipsychotic medication (chlorpromazine equivalents). Linear regression models predicting percent change in BPRS were also significant. CONCLUSIONS Overall, these results suggest that resting-state functional magnetic resonance imaging connectivity may serve as a useful biomarker of clinical outcomes in recent-onset psychosis.
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Affiliation(s)
- Jason Smucny
- Department of Psychiatry, University of California, Davis, Sacramento, CA, USA
| | - Tyler A Lesh
- Department of Psychiatry, University of California, Davis, Sacramento, CA, USA
| | | | - Joshua P Rhilinger
- Department of Psychiatry, University of California, Davis, Sacramento, CA, USA
| | - Cameron S Carter
- Department of Psychiatry, University of California, Irvine, CA, USA
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Prompiengchai S, Dunlop K. Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression. Neuropsychopharmacology 2024:10.1038/s41386-024-01907-1. [PMID: 38951585 DOI: 10.1038/s41386-024-01907-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 05/17/2024] [Accepted: 06/13/2024] [Indexed: 07/03/2024]
Abstract
Treatment outcomes widely vary for individuals diagnosed with major depressive disorder, implicating a need for deeper understanding of the biological mechanisms conferring a greater likelihood of response to a particular treatment. Our improved understanding of intrinsic brain networks underlying depression psychopathology via magnetic resonance imaging and other neuroimaging modalities has helped reveal novel and potentially clinically meaningful biological markers of response. And while we have made considerable progress in identifying such biomarkers over the last decade, particularly with larger, multisite trials, there are significant methodological and practical obstacles that need to be overcome to translate these markers into the clinic. The aim of this review is to review current literature on brain network structural and functional biomarkers of treatment response or selection in depression, with a specific focus on recent large, multisite trials reporting predictive accuracy of candidate biomarkers. Regarding pharmaco- and psychotherapy, we discuss candidate biomarkers, reporting that while we have identified candidate biomarkers of response to a single intervention, we need more trials that distinguish biomarkers between first-line treatments. Further, we discuss the ways prognostic neuroimaging may help to improve treatment outcomes to neuromodulation-based therapies, such as transcranial magnetic stimulation and deep brain stimulation. Lastly, we highlight obstacles and technical developments that may help to address the knowledge gaps in this area of research. Ultimately, integrating neuroimaging-derived biomarkers into clinical practice holds promise for enhancing treatment outcomes and advancing precision psychiatry strategies for depression management. By elucidating the neural predictors of treatment response and selection, we can move towards more individualized and effective depression interventions, ultimately improving patient outcomes and quality of life.
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Affiliation(s)
| | - Katharine Dunlop
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, ON, Canada.
- Keenan Research Centre for Biomedical Science, Unity Health Toronto, Toronto, ON, Canada.
- Department of Psychiatry and Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
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7
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Dunlop BW, Mayberg HS. The capacity of brain circuits to enhance psychiatry. Nat Med 2024; 30:1834-1835. [PMID: 38937589 DOI: 10.1038/s41591-024-03090-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024]
Affiliation(s)
- Boadie W Dunlop
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Helen S Mayberg
- Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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Ronneberg CR, Lv N, Ajilore OA, Kannampallil T, Smyth J, Kumar V, Barve A, Garcia C, Dosala S, Wittels N, Xiao L, Aborisade G, Zhang A, Tang Z, Johnson J, Ma J. Study of a PST-trained voice-enabled artificial intelligence counselor for adults with emotional distress (SPEAC-2): Design and methods. Contemp Clin Trials 2024; 142:107574. [PMID: 38763307 DOI: 10.1016/j.cct.2024.107574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 04/29/2024] [Accepted: 05/11/2024] [Indexed: 05/21/2024]
Abstract
BACKGROUND Novel and scalable psychotherapies are urgently needed to address the depression and anxiety epidemic. Leveraging artificial intelligence (AI), a voice-based virtual coach named Lumen was developed to deliver problem solving treatment (PST). The first pilot trial showed promising changes in cognitive control measured by functional neuroimaging and improvements in depression and anxiety symptoms. METHODS To further validate Lumen in a 3-arm randomized clinical trial, 200 participants with mild-to-moderate depression and/or anxiety will be randomly assigned in a 2:1:1 ratio to receive Lumen-coached PST, human-coached PST as active treatment comparison, or a waitlist control condition where participants can receive Lumen after the trial period. Participants will be assessed at baseline and 18 weeks. The primary aim is to confirm neural target engagement by testing whether compared with waitlist controls, Lumen participants will show significantly greater improvements from baseline to 18 weeks in the a priori neural target for cognitive control, right dorsal lateral prefrontal cortex engaged by the go/nogo task (primary superiority hypothesis). A secondary hypothesis will test whether compared with human-coached PST participants, Lumen participants will show equivalent improvements (i.e., noninferiority) in the same neural target from baseline to 18 weeks. The second aim is to examine (1) treatment effects on depression and anxiety symptoms, psychosocial functioning, and quality of life outcomes, and (2) relationships of neural target engagement to these patient-reported outcomes. CONCLUSIONS This study offers potential to improve the reach and impact of psychotherapy, mitigating access, cost, and stigma barriers for people with depression and/or anxiety. CLINICALTRIALS gov #: NCT05603923.
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Affiliation(s)
- Corina R Ronneberg
- Department of Medicine, University of Illinois Chicago, 1747 W. Roosevelt Rd, Chicago, IL 60608, United States of America.
| | - Nan Lv
- Department of Medicine, University of Illinois Chicago, 1747 W. Roosevelt Rd, Chicago, IL 60608, United States of America.
| | - Olusola A Ajilore
- Department of Psychiatry, University of Illinois Chicago, 1601 W. Taylor St., Chicago, IL 60612, United States of America.
| | - Thomas Kannampallil
- Washington University School of Medicine in St. Louis, 660 S. Euclid Ave., St. Louis, MO 63110, United States of America.
| | - Joshua Smyth
- Department of Psychology, The Ohio State University, 1835 Neil Ave., Columbus, OH 43210, United States of America.
| | - Vikas Kumar
- Department of Medicine, University of Illinois Chicago, 1747 W. Roosevelt Rd, Chicago, IL 60608, United States of America.
| | - Amruta Barve
- Department of Medicine, University of Illinois Chicago, 1747 W. Roosevelt Rd, Chicago, IL 60608, United States of America.
| | - Claudia Garcia
- Department of Medicine, University of Illinois Chicago, 1747 W. Roosevelt Rd, Chicago, IL 60608, United States of America.
| | - Sushanth Dosala
- Department of Medicine, University of Illinois Chicago, 1747 W. Roosevelt Rd, Chicago, IL 60608, United States of America.
| | - Nancy Wittels
- Department of Medicine, University of Illinois Chicago, 1747 W. Roosevelt Rd, Chicago, IL 60608, United States of America.
| | - Lan Xiao
- Department of Epidemiology and Population Health, Stanford University, 300 Pasteur Drive, Stanford, CA 94305, United States of America.
| | - Gbenga Aborisade
- Department of Medicine, University of Illinois Chicago, 1747 W. Roosevelt Rd, Chicago, IL 60608, United States of America.
| | - Aifeng Zhang
- Department of Psychiatry, University of Illinois Chicago, 1601 W. Taylor St., Chicago, IL 60612, United States of America.
| | - Zhengxin Tang
- University of Illinois College of Medicine, 1853 W Polk St, Chicago, IL 60612, United States of America.
| | - Jillian Johnson
- Comprehensive Cancer Center, Atrium Health Wake Forest Baptist, 1 Medical Center Blvd, Winston-Salem, NC 27157, United States of America.
| | - Jun Ma
- Department of Medicine, University of Illinois Chicago, 1747 W. Roosevelt Rd, Chicago, IL 60608, United States of America.
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Huang D, Fan Y, Zhang J, Wang Q, Ding M, Hou R, Yu K, Xiao X, Wu Y, Wu J. Dorsal dentate gyrus mediated enriched environment-induced anxiolytic and antidepressant effects in cortical infarcted mice. Exp Neurol 2024; 377:114801. [PMID: 38685308 DOI: 10.1016/j.expneurol.2024.114801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 04/18/2024] [Accepted: 04/25/2024] [Indexed: 05/02/2024]
Abstract
Anxiety and depression are the most common mental health disorders worldwide, each affecting around 30% stroke survivors. These complications not only affect the functional recovery and quality of life in stroke patients, but also are distressing for caregivers. However, effective treatments are still lacking. Enriched environment (EE), characterized with novel and multi-dimensional stimulation, has been reported to exert therapeutic effects on physical and cognitive function. In addition, EE also had potential positive effects on emotional disorders after ischemic stroke; however, the underling mechanisms have not been well elucidated. This study aimed to explore the effectiveness of EE on emotional disorders after cerebral ischemia and its underling mechanism. Sensorimotor cortical infarction was induced by photothrombosis with stable infarct location and volume, resulting in motor dysfunction, anxiety and depression-like behaviors in mice, with decreased ALFF and ReHo values and decreased c-fos expression in the infarction area and adjacent regions. Seven days' EE treatment significantly improved motor function of contralateral forelimb and exhibited anxiolytic and antidepressant effects in infarcted mice. Compared to the mice housing in a standard environment, those subjected to acute EE stimulation had significantly increased ALFF and ReHo values in the bilateral somatosensory cortex (S1, S2), dorsal dentate gyrus (dDG), dorsal CA1 of hippocampus (dCA1), lateral habenular nucleus (LHb), periaqueductal gray (PAG), ipsilateral primary motor cortex (M1), retrosplenial cortex (RSC), parietal association cortex (PtA), dorsal CA3 of hippocampus (dCA3), claustrum (Cl), ventral pallidum (VP), amygdala (Amy), and contralateral auditory cortex (Au). Some of, but not all, the ipsilateral brain regions mentioned above showed accompanying increases in c-fos expression with the most significant changes in the dDG. The number of FosB positive cells in the dDG, decreased in infarcted mice, was significantly increased after chronic EE treatment. Chemogenetic activation of dDG neurons reduced anxiety and depressive-like behaviors in infarcted mice, while neuronal inhibition resulted in void of the anxiolytic and antidepressant effects of EE. Altogether, these findings indicated that dDG neurons may mediate EE-triggered anxiolytic and antidepressant effects in cortical infarcted mice.
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Affiliation(s)
- Dan Huang
- Department of Rehabilitation Medicine, Huashan Hospital, Fundan University, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China; National Center for Neurological Disorders, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China
| | - Yunhui Fan
- Department of Rehabilitation Medicine, Huashan Hospital, Fundan University, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China; National Center for Neurological Disorders, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China
| | - Jingjun Zhang
- Department of Rehabilitation Medicine, The Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No. 600 Yishan Road, Xu'hui District, Shanghai 200233, China
| | - Qianfeng Wang
- Zhangjiang Brain Imaging Center, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, No. 1159 Cailun Road, Pudong New Area, Shanghai 200433, China
| | - Ming Ding
- Department of Rehabilitation Medicine, Huashan Hospital, Fundan University, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China; National Center for Neurological Disorders, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China; Behavioral and Cognitive Neuroscience Center, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, No. 1159 Cailun Road, Pudong New Area, Shanghai 200433, China
| | - Ruiqing Hou
- Behavioral and Cognitive Neuroscience Center, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, No. 1159 Cailun Road, Pudong New Area, Shanghai 200433, China
| | - Kewei Yu
- Department of Rehabilitation Medicine, Huashan Hospital, Fundan University, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China; National Center for Neurological Disorders, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China
| | - Xiao Xiao
- Behavioral and Cognitive Neuroscience Center, Institute of Science and Technology for Brain-Inspired Intelligence, Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, MOE Frontiers Center for Brain Science, Fudan University, No. 1159 Cailun Road, Pudong New Area, Shanghai 200433, China; Department of Anesthesiology, Huashan Hospital, Fundan University, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China.
| | - Yi Wu
- Department of Rehabilitation Medicine, Huashan Hospital, Fundan University, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China; National Center for Neurological Disorders, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China.
| | - Junfa Wu
- Department of Rehabilitation Medicine, Huashan Hospital, Fundan University, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China; National Center for Neurological Disorders, No. 12 Middle Urumqi Road, Jing 'an District, Shanghai 200040, China.
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Tozzi L, Zhang X, Pines A, Olmsted AM, Zhai ES, Anene ET, Chesnut M, Holt-Gosselin B, Chang S, Stetz PC, Ramirez CA, Hack LM, Korgaonkar MS, Wintermark M, Gotlib IH, Ma J, Williams LM. Personalized brain circuit scores identify clinically distinct biotypes in depression and anxiety. Nat Med 2024; 30:2076-2087. [PMID: 38886626 PMCID: PMC11271415 DOI: 10.1038/s41591-024-03057-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 05/09/2024] [Indexed: 06/20/2024]
Abstract
There is an urgent need to derive quantitative measures based on coherent neurobiological dysfunctions or 'biotypes' to enable stratification of patients with depression and anxiety. We used task-free and task-evoked data from a standardized functional magnetic resonance imaging protocol conducted across multiple studies in patients with depression and anxiety when treatment free (n = 801) and after randomization to pharmacotherapy or behavioral therapy (n = 250). From these patients, we derived personalized and interpretable scores of brain circuit dysfunction grounded in a theoretical taxonomy. Participants were subdivided into six biotypes defined by distinct profiles of intrinsic task-free functional connectivity within the default mode, salience and frontoparietal attention circuits, and of activation and connectivity within frontal and subcortical regions elicited by emotional and cognitive tasks. The six biotypes showed consistency with our theoretical taxonomy and were distinguished by symptoms, behavioral performance on general and emotional cognitive computerized tests, and response to pharmacotherapy as well as behavioral therapy. Our results provide a new, theory-driven, clinically validated and interpretable quantitative method to parse the biological heterogeneity of depression and anxiety. Thus, they represent a promising approach to advance precision clinical care in psychiatry.
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Affiliation(s)
- Leonardo Tozzi
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Xue Zhang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Adam Pines
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Alisa M Olmsted
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Sierra-Pacific Mental Illness Research, Education and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Emily S Zhai
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Esther T Anene
- Department of Counseling and Clinical Psychology, Teacher's College, Columbia University, New York, NY, USA
| | - Megan Chesnut
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Bailey Holt-Gosselin
- Interdepartmental Neuroscience Graduate Program, Yale University School of Medicine, New Haven, CT, USA
| | - Sarah Chang
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Patrick C Stetz
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Sierra-Pacific Mental Illness Research, Education and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Carolina A Ramirez
- Center for Intelligent Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Laura M Hack
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Sierra-Pacific Mental Illness Research, Education and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Mayuresh S Korgaonkar
- Brain Dynamics Centre, Westmead Institute for Medical Research, University of Sydney, Westmead, New South Wales, Australia
- Department of Radiology, Westmead Hospital, Western Sydney Local Health District, Westmead, New South Wales, Australia
| | - Max Wintermark
- Department of Neuroradiology, the University of Texas MD Anderson Center, Houston, TX, USA
| | - Ian H Gotlib
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Jun Ma
- Department of Medicine, College of Medicine, University of Illinois Chicago, Chicago, IL, USA
| | - Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.
- Sierra-Pacific Mental Illness Research, Education and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA.
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11
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Zopfs M, Jindrová M, Gurevitch G, Keynan JN, Hendler T, Baumeister S, Aggensteiner PM, Cornelisse S, Brandeis D, Schmahl C, Paret C. Amygdala-related electrical fingerprint is modulated with neurofeedback training and correlates with deep-brain activation: proof-of-concept in borderline personality disorder. Psychol Med 2024; 54:1651-1660. [PMID: 38131344 DOI: 10.1017/s0033291723003549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
BACKGROUND The modulation of brain circuits of emotion is a promising pathway to treat borderline personality disorder (BPD). Precise and scalable approaches have yet to be established. Two studies investigating the amygdala-related electrical fingerprint (Amyg-EFP) in BPD are presented: one study addressing the deep-brain correlates of Amyg-EFP, and a second study investigating neurofeedback (NF) as a means to improve brain self-regulation. METHODS Study 1 combined electroencephalography (EEG) and simultaneous functional magnetic resonance imaging to investigate the replicability of Amyg-EFP-related brain activation found in the reference dataset (N = 24 healthy subjects, 8 female; re-analysis of published data) in the replication dataset (N = 16 female individuals with BPD). In the replication dataset, we additionally explored how the Amyg-EFP would map to neural circuits defined by the research domain criteria. Study 2 investigated a 10-session Amyg-EFP NF training in parallel to a 12-weeks residential dialectical behavior therapy (DBT) program. Fifteen patients with BPD completed the training, N = 15 matched patients served as DBT-only controls. RESULTS Study 1 replicated previous findings and showed significant amygdala blood oxygenation level dependent activation in a whole-brain regression analysis with the Amyg-EFP. Neurocircuitry activation (negative affect, salience, and cognitive control) was correlated with the Amyg-EFP signal. Study 2 showed Amyg-EFP modulation with NF training, but patients received reversed feedback for technical reasons, which limited interpretation of results. CONCLUSIONS Recorded via scalp EEG, the Amyg-EFP picks up brain activation of high relevance for emotion. Administering Amyg-EFP NF in addition to standardized BPD treatment was shown to be feasible. Clinical utility remains to be investigated.
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Affiliation(s)
- Malte Zopfs
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Miroslava Jindrová
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Guy Gurevitch
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
| | - Jackob N Keynan
- Brain Stimulation Lab, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Talma Hendler
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
- School of Psychological Sciences and Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel
| | - Sarah Baumeister
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Pascal-M Aggensteiner
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Sven Cornelisse
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Christian Schmahl
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Christian Paret
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel
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12
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Page CE, Epperson CN, Novick AM, Duffy KA, Thompson SM. Beyond the serotonin deficit hypothesis: communicating a neuroplasticity framework of major depressive disorder. Mol Psychiatry 2024:10.1038/s41380-024-02625-2. [PMID: 38816586 DOI: 10.1038/s41380-024-02625-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 05/15/2024] [Accepted: 05/21/2024] [Indexed: 06/01/2024]
Abstract
The serotonin deficit hypothesis explanation for major depressive disorder (MDD) has persisted among clinicians and the general public alike despite insufficient supporting evidence. To combat rising mental health crises and eroding public trust in science and medicine, researchers and clinicians must be able to communicate to patients and the public an updated framework of MDD: one that is (1) accessible to a general audience, (2) accurately integrates current evidence about the efficacy of conventional serotonergic antidepressants with broader and deeper understandings of pathophysiology and treatment, and (3) capable of accommodating new evidence. In this article, we summarize a framework for the pathophysiology and treatment of MDD that is informed by clinical and preclinical research in psychiatry and neuroscience. First, we discuss how MDD can be understood as inflexibility in cognitive and emotional brain circuits that involves a persistent negativity bias. Second, we discuss how effective treatments for MDD enhance mechanisms of neuroplasticity-including via serotonergic interventions-to restore synaptic, network, and behavioral function in ways that facilitate adaptive cognitive and emotional processing. These treatments include typical monoaminergic antidepressants, novel antidepressants like ketamine and psychedelics, and psychotherapy and neuromodulation techniques. At the end of the article, we discuss this framework from the perspective of effective science communication and provide useful language and metaphors for researchers, clinicians, and other professionals discussing MDD with a general or patient audience.
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Affiliation(s)
- Chloe E Page
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - C Neill Epperson
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Family Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Helen and Arthur E. Johnson Depression Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Andrew M Novick
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Korrina A Duffy
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Scott M Thompson
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
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13
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Adamic EM, Teed AR, Avery JA, de la Cruz F, Khalsa SS. Hemispheric divergence of interoceptive processing across psychiatric disorders. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.08.570759. [PMID: 38105986 PMCID: PMC10723463 DOI: 10.1101/2023.12.08.570759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Interactions between top-down attention and bottom-up visceral inputs are assumed to produce conscious perceptions of interoceptive states, and while each process has been independently associated with aberrant interoceptive symptomatology in psychiatric disorders, the neural substrates of this interface are unknown. We conducted a preregistered functional neuroimaging study of 46 individuals with anxiety, depression, and/or eating disorders (ADE) and 46 propensity-matched healthy comparisons (HC), comparing their neural activity across two interoceptive tasks differentially recruiting top-down or bottom-up processing within the same scan session. During an interoceptive attention task, top-down attention was voluntarily directed towards cardiorespiratory or visual signals, whereas during an interoceptive perturbation task, intravenous infusions of isoproterenol (a peripherally-acting beta-adrenergic receptor agonist) were administered in a double-blinded and placebo-controlled fashion to drive bottom-up cardiorespiratory sensations. Across both tasks, neural activation converged upon the insular cortex, localizing within the granular and ventral dysgranular subregions bilaterally. However, contrasting hemispheric differences emerged, with the ADE group exhibiting (relative to HCs) an asymmetric pattern of overlap in the left insula, with increased or decreased proportions of co-activated voxels within the left or right dysgranular insula, respectively. The ADE group also showed less agranular anterior insula activation during periods of bodily uncertainty (i.e., when anticipating possible isoproterenol-induced changes that never arrived). Finally, post-task changes in insula functional connectivity were associated with anxiety and depression severity. These findings confirm the dysgranular mid-insula as a key cortical interface where attention and prediction meet real-time bodily inputs, especially during heightened awareness of interoceptive states. Further, the dysgranular mid-insula may indeed be a "locus of disruption" for psychiatric disorders.
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Affiliation(s)
- Emily M Adamic
- Laureate Institute for Brain Research, Tulsa, OK, USA, 74136
- Department of Biological Sciences, University of Tulsa, Tulsa, OK, USA, 74104
| | - Adam R Teed
- Laureate Institute for Brain Research, Tulsa, OK, USA, 74136
| | - Jason A Avery
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, USA, 20814
| | - Feliberto de la Cruz
- Laboratory for Autonomic Neuroscience, Imaging, and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, Thuringia, Germany, 07743
| | - Sahib S Khalsa
- Laureate Institute for Brain Research, Tulsa, OK, USA, 74136
- Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, USA, 74119
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14
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Chivu A, Pascal SA, Damborská A, Tomescu MI. EEG Microstates in Mood and Anxiety Disorders: A Meta-analysis. Brain Topogr 2024; 37:357-368. [PMID: 37615799 PMCID: PMC11026263 DOI: 10.1007/s10548-023-00999-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 08/06/2023] [Indexed: 08/25/2023]
Abstract
To reduce the psycho-social burden increasing attention has focused on brain abnormalities in the most prevalent and highly co-occurring neuropsychiatric disorders, such as mood and anxiety. However, high inter-study variability in these patients results in inconsistent and contradictory alterations in the fast temporal dynamics of large-scale networks as measured by EEG microstates. Thus, in this meta-analysis, we aim to investigate the consistency of these changes to better understand possible common neuro-dynamical mechanisms of these disorders.In the systematic search, twelve studies investigating EEG microstate changes in participants with mood and anxiety disorders and individuals with subclinical depression were included in this meta-analysis, adding up to 787 participants.The results suggest that EEG microstates consistently discriminate mood and anxiety impairments from the general population in patients and subclinical states. Specifically, we found a small significant effect size for B microstates in patients compared to healthy controls, with larger effect sizes for increased B presence in unmedicated patients with comorbidity. In a subgroup meta-analysis of ten mood disorder studies, microstate D showed a significant effect size for decreased presence. When investigating only the two anxiety disorder studies, we found a significantly small effect size for the increased microstate A and a medium effect size for decreased microstate E (one study). However, more studies are needed to elucidate whether these findings are diagnostic-specific markers.Results are discussed in relation to the functional meaning of microstates and possible contribution to an explanatory mechanism of overlapping symptomatology of mood and anxiety disorders.
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Affiliation(s)
- Alina Chivu
- CINETic Center, National University of Theatre and Film "I.L. Caragiale" Bucharest, Bucharest, Romania
- Faculty of Psychology and Educational Sciences, Department of Applied Psychology and Psychotherapy, University of Bucharest, Bucharest, Romania
| | - Simona A Pascal
- Faculty of Psychology and Educational Sciences, Department of Applied Psychology and Psychotherapy, University of Bucharest, Bucharest, Romania
| | - Alena Damborská
- Department of Psychiatry, Faculty of Medicine, Masaryk University and University Hospital Brno, Brno, Czech Republic
- Multimodal and Functional Neuroimaging Research Group, CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Miralena I Tomescu
- CINETic Center, National University of Theatre and Film "I.L. Caragiale" Bucharest, Bucharest, Romania.
- Faculty of Educational Sciences, Department of Psychology, University "Stefan cel Mare" of Suceava, Suceava, Romania.
- Faculty of Psychology and Educational Sciences, Department of Cognitive Sciences, University of Bucharest, Bucharest, Romania.
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15
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Meinke C, Lueken U, Walter H, Hilbert K. Predicting treatment outcome based on resting-state functional connectivity in internalizing mental disorders: A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 160:105640. [PMID: 38548002 DOI: 10.1016/j.neubiorev.2024.105640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 02/29/2024] [Accepted: 03/21/2024] [Indexed: 04/07/2024]
Abstract
Predicting treatment outcome in internalizing mental disorders prior to treatment initiation is pivotal for precision mental healthcare. In this regard, resting-state functional connectivity (rs-FC) and machine learning have often shown promising prediction accuracies. This systematic review and meta-analysis evaluates these studies, considering their risk of bias through the Prediction Model Study Risk of Bias Assessment Tool (PROBAST). We examined the predictive performance of features derived from rs-FC, identified features with the highest predictive value, and assessed the employed machine learning pipelines. We searched the electronic databases Scopus, PubMed and PsycINFO on the 12th of December 2022, which resulted in 13 included studies. The mean balanced accuracy for predicting treatment outcome was 77% (95% CI: [72%- 83%]). rs-FC of the dorsolateral prefrontal cortex had high predictive value in most studies. However, a high risk of bias was identified in all studies, compromising interpretability. Methodological recommendations are provided based on a comprehensive exploration of the studies' machine learning pipelines, and potential fruitful developments are discussed.
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Affiliation(s)
- Charlotte Meinke
- Department of Psychology, Humboldt-Universität zu Berlin, Germany.
| | - Ulrike Lueken
- Department of Psychology, Humboldt-Universität zu Berlin, Germany; German Center for Mental Health (DZPG), partner site Berlin/Potsdam, Germany.
| | - Henrik Walter
- Charité Universtätsmedizin Berlin, corporate member of FU Berlin and Humboldt Universität zu Berlin, Department of Psychiatrie and Psychotherapy, CCM, Germany.
| | - Kevin Hilbert
- Department of Psychology, Humboldt-Universität zu Berlin, Germany; Department of Psychology, Health and Medical University Erfurt, Germany.
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16
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Adams RA, Zor C, Mihalik A, Tsirlis K, Brudfors M, Chapman J, Ashburner J, Paulus MP, Mourão-Miranda J. Voxelwise Multivariate Analysis of Brain-Psychosocial Associations in Adolescents Reveals 6 Latent Dimensions of Cognition and Psychopathology. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00085-5. [PMID: 38588854 DOI: 10.1016/j.bpsc.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 03/15/2024] [Accepted: 03/28/2024] [Indexed: 04/10/2024]
Abstract
BACKGROUND Adolescence heralds the onset of considerable psychopathology, which may be conceptualized as an emergence of altered covariation between symptoms and brain measures. Multivariate methods can detect such modes of covariation or latent dimensions, but none specifically relating to psychopathology have yet been found using population-level structural brain data. Using voxelwise (instead of parcellated) brain data may strengthen latent dimensions' brain-psychosocial relationships, but this creates computational challenges. METHODS We obtained voxelwise gray matter density and psychosocial variables from the baseline (ages 9-10 years) Adolescent Brain Cognitive Development (ABCD) Study cohort (N = 11,288) and employed a state-of-the-art segmentation method, sparse partial least squares, and a rigorous machine learning framework to prevent overfitting. RESULTS We found 6 latent dimensions, 4 of which pertain specifically to mental health. The mental health dimensions were related to overeating, anorexia/internalizing, oppositional symptoms (all ps < .002) and attention-deficit/hyperactivity disorder symptoms (p = .03). Attention-deficit/hyperactivity disorder was related to increased and internalizing symptoms related to decreased gray matter density in dopaminergic and serotonergic midbrain areas, whereas oppositional symptoms were related to increased gray matter in a noradrenergic nucleus. Internalizing symptoms were related to increased and oppositional symptoms to reduced gray matter density in the insular, cingulate, and auditory cortices. Striatal regions featured strongly, with reduced caudate nucleus gray matter in attention-deficit/hyperactivity disorder and reduced putamen gray matter in oppositional/conduct problems. Voxelwise gray matter density generated stronger brain-psychosocial correlations than brain parcellations. CONCLUSIONS Voxelwise brain data strengthen latent dimensions of brain-psychosocial covariation, and sparse multivariate methods increase their psychopathological specificity. Internalizing and externalizing symptoms are associated with opposite gray matter changes in similar cortical and subcortical areas.
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Affiliation(s)
- Rick A Adams
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom.
| | - Cemre Zor
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Agoston Mihalik
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom; Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Konstantinos Tsirlis
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
| | - Mikael Brudfors
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom; School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - James Chapman
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
| | - John Ashburner
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | | | - Janaina Mourão-Miranda
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
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17
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Song EJ, Tozzi L, Williams LM. Brain Circuit-Derived Biotypes for Treatment Selection in Mood Disorders: A Critical Review and Illustration of a Functional Neuroimaging Tool for Clinical Translation. Biol Psychiatry 2024:S0006-3223(24)01175-2. [PMID: 38552866 DOI: 10.1016/j.biopsych.2024.03.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 03/16/2024] [Accepted: 03/20/2024] [Indexed: 05/12/2024]
Abstract
Although the lifetime burden due to major depressive disorder is increasing, we lack tools for selecting the most effective treatments for each patient. One-third to one-half of patients with major depressive disorder do not respond to treatment, and we lack strategies for selecting among available treatments or expediting access to new treatment options. This critical review concentrates on functional neuroimaging as a modality of measurement for precision psychiatry. We begin by summarizing the current landscape of how functional neuroimaging-derived circuit predictors can forecast treatment outcomes in depression. Then, we outline the opportunities and challenges in integrating circuit predictors into clinical practice. We highlight one standardized and reproducible approach for quantifying brain circuit function at an individual level, which could serve as a model for clinical translation. We conclude by evaluating the prospects and practicality of employing neuroimaging tools, such as the one that we propose, in routine clinical practice.
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Affiliation(s)
- Evelyn Jiayi Song
- Stanford Center for Precision Mental Health and Wellness, Psychiatry and Behavioral Sciences, Stanford, California; Stanford School of Engineering, Stanford, California
| | - Leonardo Tozzi
- Stanford Center for Precision Mental Health and Wellness, Psychiatry and Behavioral Sciences, Stanford, California
| | - Leanne M Williams
- Stanford Center for Precision Mental Health and Wellness, Psychiatry and Behavioral Sciences, Stanford, California; Mental Illness Research, Education and Clinical Center of Excellence (MIRECC), VA Palo Alto Health Care System, Palo Alto, California.
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18
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Cash RFH, Zalesky A. Personalized and Circuit-Based Transcranial Magnetic Stimulation: Evidence, Controversies, and Opportunities. Biol Psychiatry 2024; 95:510-522. [PMID: 38040047 DOI: 10.1016/j.biopsych.2023.11.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 11/13/2023] [Accepted: 11/18/2023] [Indexed: 12/03/2023]
Abstract
The development of neuroimaging methodologies to map brain connectivity has transformed our understanding of psychiatric disorders, the distributed effects of brain stimulation, and how transcranial magnetic stimulation can be best employed to target and ameliorate psychiatric symptoms. In parallel, neuroimaging research has revealed that higher-order brain regions such as the prefrontal cortex, which represent the most common therapeutic brain stimulation targets for psychiatric disorders, show some of the highest levels of interindividual variation in brain connectivity. These findings provide the rationale for personalized target site selection based on person-specific brain network architecture. Recent advances have made it possible to determine reproducible personalized targets with millimeter precision in clinically tractable acquisition times. These advances enable the potential advantages of spatially personalized transcranial magnetic stimulation targeting to be evaluated and translated to basic and clinical applications. In this review, we outline the motivation for target site personalization, preliminary support (mostly in depression), convergent evidence from other brain stimulation modalities, and generalizability beyond depression and the prefrontal cortex. We end by detailing methodological recommendations, controversies, and notable alternatives. Overall, while this research area appears highly promising, the value of personalized targeting remains unclear, and dedicated large prospective randomized clinical trials using validated methodology are critical.
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Affiliation(s)
- Robin F H Cash
- Melbourne Neuropsychiatry Centre and Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria, Australia.
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre and Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria, Australia
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19
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Oh EY, Han KM, Kim A, Kang Y, Tae WS, Han MR, Ham BJ. Integration of whole-exome sequencing and structural neuroimaging analysis in major depressive disorder: a joint study. Transl Psychiatry 2024; 14:141. [PMID: 38461185 PMCID: PMC10924915 DOI: 10.1038/s41398-024-02849-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 02/07/2024] [Accepted: 02/22/2024] [Indexed: 03/11/2024] Open
Abstract
Major depressive disorder (MDD) is a common mental illness worldwide and is triggered by an intricate interplay between environmental and genetic factors. Although there are several studies on common variants in MDD, studies on rare variants are relatively limited. In addition, few studies have examined the genetic contributions to neurostructural alterations in MDD using whole-exome sequencing (WES). We performed WES in 367 patients with MDD and 161 healthy controls (HCs) to detect germline and copy number variations in the Korean population. Gene-based rare variants were analyzed to investigate the association between the genes and individuals, followed by neuroimaging-genetic analysis to explore the neural mechanisms underlying the genetic impact in 234 patients with MDD and 135 HCs using diffusion tensor imaging data. We identified 40 MDD-related genes and observed 95 recurrent regions of copy number variations. We also discovered a novel gene, FRMPD3, carrying rare variants that influence MDD. In addition, the single nucleotide polymorphism rs771995197 in the MUC6 gene was significantly associated with the integrity of widespread white matter tracts. Moreover, we identified 918 rare exonic missense variants in genes associated with MDD susceptibility. We postulate that rare variants of FRMPD3 may contribute significantly to MDD, with a mild penetration effect.
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Affiliation(s)
- Eun-Young Oh
- Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon, Republic of Korea
| | - Kyu-Man Han
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
- Brain Convergence Research Center, Korea University College of Medicine, Seoul, Republic of Korea
| | - Aram Kim
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Youbin Kang
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Woo-Suk Tae
- Brain Convergence Research Center, Korea University College of Medicine, Seoul, Republic of Korea
| | - Mi-Ryung Han
- Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon, Republic of Korea.
| | - Byung-Joo Ham
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
- Brain Convergence Research Center, Korea University College of Medicine, Seoul, Republic of Korea.
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20
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Williams LM, Carpenter WT, Carretta C, Papanastasiou E, Vaidyanathan U. Precision psychiatry and Research Domain Criteria: Implications for clinical trials and future practice. CNS Spectr 2024; 29:26-39. [PMID: 37675453 DOI: 10.1017/s1092852923002420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
Psychiatric disorders are associated with significant social and economic burdens, many of which are related to issues with current diagnosis and treatments. The coronavirus (COVID-19) pandemic is estimated to have increased the prevalence and burden of major depressive and anxiety disorders, indicating an urgent need to strengthen mental health systems globally. To date, current approaches adopted in drug discovery and development for psychiatric disorders have been relatively unsuccessful. Precision psychiatry aims to tailor healthcare more closely to the needs of individual patients and, when informed by neuroscience, can offer the opportunity to improve the accuracy of disease classification, treatment decisions, and prevention efforts. In this review, we highlight the growing global interest in precision psychiatry and the potential for the National Institute of Health-devised Research Domain Criteria (RDoC) to facilitate the implementation of transdiagnostic and improved treatment approaches. The need for current psychiatric nosology to evolve with recent scientific advancements and increase awareness in emerging investigators/clinicians of the value of this approach is essential. Finally, we examine current challenges and future opportunities of adopting the RDoC-associated translational and transdiagnostic approaches in clinical studies, acknowledging that the strength of RDoC is that they form a dynamic framework of guiding principles that is intended to evolve continuously with scientific developments into the future. A collaborative approach that recruits expertise from multiple disciplines, while also considering the patient perspective, is needed to pave the way for precision psychiatry that can improve the prognosis and quality of life of psychiatric patients.
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Affiliation(s)
- Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - William T Carpenter
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Evangelos Papanastasiou
- Boehringer Ingelheim Pharma GmbH & Co, Ingelheim am Rhein, Rhineland-Palatinate, Germany
- HMNC Holding GmbH, Wilhelm-Wagenfeld-Strasse 20, 80807Munich, Bavaria, Germany
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21
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Park HRP, Chilver MR, Quidé Y, Montalto A, Schofield PR, Williams LM, Gatt JM. Heritability of cognitive and emotion processing during functional MRI in a twin sample. Hum Brain Mapp 2024; 45:e26557. [PMID: 38224545 PMCID: PMC10785190 DOI: 10.1002/hbm.26557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 11/22/2023] [Accepted: 11/25/2023] [Indexed: 01/17/2024] Open
Abstract
Despite compelling evidence that brain structure is heritable, the evidence for the heritability of task-evoked brain function is less robust. Findings from previous studies are inconsistent possibly reflecting small samples and methodological variations. In a large national twin sample, we systematically evaluated heritability of task-evoked brain activity derived from functional magnetic resonance imaging. We used established standardised tasks to engage brain regions involved in cognitive and emotional functions. Heritability was evaluated across a conscious and nonconscious Facial Expressions of Emotion Task (FEET), selective attention Oddball Task, N-back task of working memory maintenance, and a Go-NoGo cognitive control task in a sample of Australian adult twins (N ranged from 136 to 226 participants depending on the task and pairs). Two methods for quantifying associations of heritability and brain activity were utilised; a multivariate independent component analysis (ICA) approach and a univariate brain region-of-interest (ROI) approach. Using ICA, we observed that a significant proportion of task-evoked brain activity was heritable, with estimates ranging from 23% to 26% for activity elicited by nonconscious facial emotion stimuli, 27% to 34% for N-back working memory maintenance and sustained attention, and 32% to 33% for selective attention in the Oddball task. Using the ROI approach, we found that activity of regions specifically implicated in emotion processing and selective attention showed significant heritability for three ROIs, including estimates of 33%-34% for the left and right amygdala in the nonconscious processing of sad faces and 29% in the medial superior prefrontal cortex for the Oddball task. Although both approaches show similar levels of heritability for the Nonconscious Faces and Oddball tasks, ICA results displayed a more extensive network of heritable brain function, including additional regions beyond the ROI analysis. Furthermore, multivariate twin modelling of both ICA networks and ROI activation suggested a mix of common genetic and unique environmental factors that contribute to the associations between networks/regions. Together, the results indicate a complex relationship between genetic factors and environmental interactions that ultimately give rise to neural activation underlying cognition and emotion.
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Affiliation(s)
- Haeme R. P. Park
- Neuroscience Research AustraliaSydneyNew South WalesAustralia
- School of PsychologyUniversity of New South WalesSydneyNew South WalesAustralia
| | - Miranda R. Chilver
- Neuroscience Research AustraliaSydneyNew South WalesAustralia
- School of PsychologyUniversity of New South WalesSydneyNew South WalesAustralia
| | - Yann Quidé
- Neuroscience Research AustraliaSydneyNew South WalesAustralia
- School of PsychologyUniversity of New South WalesSydneyNew South WalesAustralia
| | - Arthur Montalto
- Neuroscience Research AustraliaSydneyNew South WalesAustralia
- School of PsychologyUniversity of New South WalesSydneyNew South WalesAustralia
| | - Peter R. Schofield
- Neuroscience Research AustraliaSydneyNew South WalesAustralia
- School of Biomedical SciencesUniversity of New South WalesSydneyNew South WalesAustralia
| | - Leanne M. Williams
- Psychiatry and Behavioral Sciences, Stanford School of MedicineStanford UniversityCaliforniaUSA
| | - Justine M. Gatt
- Neuroscience Research AustraliaSydneyNew South WalesAustralia
- School of PsychologyUniversity of New South WalesSydneyNew South WalesAustralia
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22
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Widge AS. Closing the loop in psychiatric deep brain stimulation: physiology, psychometrics, and plasticity. Neuropsychopharmacology 2024; 49:138-149. [PMID: 37415081 PMCID: PMC10700701 DOI: 10.1038/s41386-023-01643-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 05/28/2023] [Accepted: 06/20/2023] [Indexed: 07/08/2023]
Abstract
Deep brain stimulation (DBS) is an invasive approach to precise modulation of psychiatrically relevant circuits. Although it has impressive results in open-label psychiatric trials, DBS has also struggled to scale to and pass through multi-center randomized trials. This contrasts with Parkinson disease, where DBS is an established therapy treating thousands of patients annually. The core difference between these clinical applications is the difficulty of proving target engagement, and of leveraging the wide range of possible settings (parameters) that can be programmed in a given patient's DBS. In Parkinson's, patients' symptoms change rapidly and visibly when the stimulator is tuned to the correct parameters. In psychiatry, those same changes take days to weeks, limiting a clinician's ability to explore parameter space and identify patient-specific optimal settings. I review new approaches to psychiatric target engagement, with an emphasis on major depressive disorder (MDD). Specifically, I argue that better engagement may come by focusing on the root causes of psychiatric illness: dysfunction in specific, measurable cognitive functions and in the connectivity and synchrony of distributed brain circuits. I overview recent progress in both those domains, and how it may relate to other technologies discussed in companion articles in this issue.
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Affiliation(s)
- Alik S Widge
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
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23
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Wang X, Zhou X, Li J, Gong Y, Feng Z. A feasibility study of goal-directed network-based real-time fMRI neurofeedback for anhedonic depression. Front Psychiatry 2023; 14:1253727. [PMID: 38125285 PMCID: PMC10732355 DOI: 10.3389/fpsyt.2023.1253727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 11/06/2023] [Indexed: 12/23/2023] Open
Abstract
Anhedonia is a hallmark symptom of depression that often lacks adequate interventions. The translational gap remains in clinical treatments based on neural substrates of anhedonia. Our pilot study found that depressed individuals depended less on goal-directed (GD) reward learning (RL), with reduced reward prediction error (RPE) BOLD signal. Previous studies have found that anhedonia is related to abnormal activities and/or functional connectivities of the central executive network (CEN) and salience network (SN), both of which belong to the goal-directed system. In addition, it was found that real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF) could improve the balance between CEN and SN in healthy individuals. Therefore, we speculate that rt-fMRI NF of the CEN and SN associated with the GD system may improve depressive and/or anhedonic symptoms. Therefore, this study (1) will examine individuals with anhedonic depression using GD-RL behavioral task, combined with functional magnetic resonance imaging and computational modeling to explore the role of CEN/SN deficits in anhedonic depression; and (2) will utilize network-based rt-fMRI NF to investigate whether it is feasible to regulate the differential signals of brain CEN/SN of GD system through rt-fMRI NF to alleviate depressive and/or anhedonic symptoms. This study highlights the need to elucidate the intervention effects of rt-fMRI NF and the underlying computational network neural mechanisms.
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Affiliation(s)
- Xiaoxia Wang
- Department of Basic Psychology, School of Psychology, Army Medical University, Chongqing, China
| | - Xiaoyan Zhou
- Chongqing City Mental Health Center, Southwest University, Chongqing, China
| | - Jing Li
- Department of Radiology, Southwest Hospital, Army Medical University, Chongqing, China
| | - Yushun Gong
- Department of Medical Equipment and Metrology, College of Biomedical Engineering, Army Medical University, Chongqing, China
| | - Zhengzhi Feng
- School of Psychology, Army Medical University, Chongqing, China
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24
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Tsuchiyagaito A, Misaki M, Cochran G, Philip NS, Paulus MP, Guinjoan SM. Thalamo-cortical circuits associated with trait- and state-repetitive negative thinking in major depressive disorder. J Psychiatr Res 2023; 168:184-192. [PMID: 37913745 PMCID: PMC10872862 DOI: 10.1016/j.jpsychires.2023.10.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/10/2023] [Accepted: 10/25/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND Repetitive negative thinking (RNT), often referred to as rumination in the mood disorders literature, is a symptom dimension associated with poor prognosis and suicide in major depressive disorder (MDD). Given the transdiagnostic nature of RNT, this study aimed to evaluate the hypothesis that neurobiological substrates of RNT in MDD may share the brain mechanisms underlying obsessions, particularly those involving cortico-striatal-thalamic-cortical (CSTC) circuits. METHODS Thirty-nine individuals with MDD underwent RNT induction during fMRI. Trait-RNT was measured by the Ruminative Response Scale (RRS) and state-RNT was measured by a visual analogue scale. We employed a connectome-wide association analysis examining the association between RNT intensity with striatal and thalamic connectivity. RESULTS A greater RRS score was associated with hyperconnectivity of the right mediodorsal thalamus with prefrontal cortex, including lateral orbitofrontal cortex, along with Wernicke's area and posterior default mode network nodes (t = 4.66-6.70). A greater state-RNT score was associated with hyperconnectivity of the right laterodorsal thalamus with bilateral primary sensory and motor cortices, supplementary motor area, and Broca's area (t = 4.51-6.57). Unexpectedly, there were no significant findings related to the striatum. CONCLUSIONS The present results suggest RNT in MDD is subserved by abnormal connectivity between right thalamic nuclei and cortical regions involved in both visceral and higher order cognitive processing. Emerging deep-brain neuromodulation methods may be useful to establish causal relationships between dysfunction of right thalamic-cortical circuits and RNT in MDD.
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Affiliation(s)
- Aki Tsuchiyagaito
- Laureate Institute for Brain Research, Tulsa, OK, USA; Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK, USA; Research Center for Child Mental Development, Chiba University, Chiba, Japan.
| | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, USA; Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK, USA
| | - Gabe Cochran
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Noah S Philip
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA; Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, RI, USA
| | | | - Salvador M Guinjoan
- Laureate Institute for Brain Research, Tulsa, OK, USA; Department of Psychiatry, Oklahoma University Health Sciences Center at Tulsa, Tulsa, OK, USA; Laureate Psychiatric Hospital and Clinic, Tulsa, OK, USA
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25
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Misaki M, Tsuchiyagaito A, Guinjoan SM, Rohan ML, Paulus MP. Trait repetitive negative thinking in depression is associated with functional connectivity in negative thinking state rather than resting state. J Affect Disord 2023; 340:843-854. [PMID: 37582464 PMCID: PMC10528904 DOI: 10.1016/j.jad.2023.08.052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 08/08/2023] [Accepted: 08/09/2023] [Indexed: 08/17/2023]
Abstract
Resting-state functional connectivity (RSFC) has been proposed as a potential indicator of repetitive negative thinking (RNT) in depression. However, identifying the specific functional process associated with RSFC alterations is challenging, and it remains unclear whether alterations in RSFC for depressed individuals are directly related to the RNT process or to individual characteristics distinct from the negative thinking process per se. To investigate the relationship between RSFC alterations and the RNT process in individuals with major depressive disorder (MDD), we compared RSFC with functional connectivity during an induced negative-thinking state (NTFC) in terms of their predictability of RNT traits and associated whole-brain connectivity patterns using connectome-based predictive modeling (CPM) and connectome-wide association (CWA) analyses. Thirty-six MDD participants and twenty-six healthy control participants underwent both resting state and induced negative thinking state fMRI scans. Both RSFC and NTFC distinguished between healthy and depressed individuals with CPM. However, trait RNT in depressed individuals, as measured by the Ruminative Responses Scale-Brooding subscale, was only predictable from NTFC, not from RSFC. CWA analysis revealed that negative thinking in depression was associated with higher functional connectivity between the default mode and executive control regions, which was not observed in RSFC. These findings suggest that RNT in depression involves an active mental process encompassing multiple brain regions across functional networks, which is not represented in the resting state. Although RSFC indicates brain functional alterations in MDD, they may not directly reflect the negative thinking process.
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Affiliation(s)
- Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, USA; Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK, USA.
| | - Aki Tsuchiyagaito
- Laureate Institute for Brain Research, Tulsa, OK, USA; Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK, USA
| | - Salvador M Guinjoan
- Laureate Institute for Brain Research, Tulsa, OK, USA; Department of Psychiatry, Oklahoma University Health Sciences Center at Tulsa, Tulsa, OK, USA
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26
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Mansouri S, Pessoni AM, Marroquín-Rivera A, Parise EM, Tamminga CA, Turecki G, Nestler EJ, Chen TH, Labonté B. Transcriptional dissection of symptomatic profiles across the brain of men and women with depression. Nat Commun 2023; 14:6835. [PMID: 37884562 PMCID: PMC10603117 DOI: 10.1038/s41467-023-42686-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 10/18/2023] [Indexed: 10/28/2023] Open
Abstract
Major depressive disorder (MDD) is one of the most important causes of disability worldwide. While recent work provides insights into the molecular alterations in the brain of patients with MDD, whether these molecular signatures can be associated with the expression of specific symptom domains remains unclear. Here, we identified sex-specific gene modules associated with the expression of MDD, combining differential gene expression and co-expression network analyses in six cortical and subcortical brain regions. Our results show varying levels of network homology between males and females across brain regions, although the associations between these structures and the expression of MDD remain highly sex specific. We refined these associations to several symptom domains and identified transcriptional signatures associated with distinct functional pathways, including GABAergic and glutamatergic neurotransmission, metabolic processes and intracellular signal transduction, across brain regions associated with distinct symptomatic profiles in a sex-specific fashion. In most cases, these associations were specific to males or to females with MDD, although a subset of gene modules associated with common symptomatic features in both sexes were also identified. Together, our findings suggest that the expression of distinct MDD symptom domains associates with sex-specific transcriptional structures across brain regions.
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Affiliation(s)
- Samaneh Mansouri
- CERVO Brain Research Centre, Quebec, QC, Canada
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - André M Pessoni
- CERVO Brain Research Centre, Quebec, QC, Canada
- Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, Quebec, QC, Canada
| | - Arturo Marroquín-Rivera
- CERVO Brain Research Centre, Quebec, QC, Canada
- Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, Quebec, QC, Canada
| | - Eric M Parise
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Carol A Tamminga
- Department of Psychiatry, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Gustavo Turecki
- McGill Group for Suicide Studies, Douglas Mental Health University Institute, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
| | - Eric J Nestler
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ting-Huei Chen
- CERVO Brain Research Centre, Quebec, QC, Canada
- Department of Mathematics and Statistics, Laval University, Québec, QC, Canada
| | - Benoit Labonté
- CERVO Brain Research Centre, Quebec, QC, Canada.
- Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, Quebec, QC, Canada.
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27
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Hack LM, Zhang X, Heifets BD, Suppes T, van Roessel PJ, Yesavage JA, Gray NJ, Hilton R, Bertrand C, Rodriguez CI, Deisseroth K, Knutson B, Williams LM. Ketamine's acute effects on negative brain states are mediated through distinct altered states of consciousness in humans. Nat Commun 2023; 14:6631. [PMID: 37857620 PMCID: PMC10587184 DOI: 10.1038/s41467-023-42141-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 09/27/2023] [Indexed: 10/21/2023] Open
Abstract
Ketamine commonly and rapidly induces dissociative and other altered states of consciousness (ASCs) in humans. However, the neural mechanisms that contribute to these experiences remain unknown. We used functional neuroimaging to engage key regions of the brain's affective circuits during acute ketamine-induced ASCs within a randomized, multi-modal, placebo-controlled design examining placebo, 0.05 mg/kg ketamine, and 0.5 mg/kg ketamine in nonclinical adult participants (NCT03475277). Licensed clinicians monitored infusions for safety. Linear mixed effects models, analysis of variance, t-tests, and mediation models were used for statistical analyses. Our design enabled us to test our pre-specified primary and secondary endpoints, which were met: effects of ketamine across dose conditions on (1) emotional task-evoked brain activity, and (2) sub-components of dissociation and other ASCs. With this design, we also could disentangle which ketamine-induced affective brain states are dependent upon specific aspects of ASCs. Differently valenced ketamine-induced ASCs mediated opposing effects on right anterior insula activity. Participants experiencing relatively higher depersonalization induced by 0.5 mg/kg of ketamine showed relief from negative brain states (reduced task-evoked right anterior insula activity, 0.39 SD). In contrast, participants experiencing dissociative amnesia showed an exacerbation of insula activity (0.32 SD). These results in nonclinical participants may shed light on the mechanisms by which specific dissociative states predict response to ketamine in depressed individuals.
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Affiliation(s)
- Laura M Hack
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Sierra-Pacific Mental Illness Research, Education and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Xue Zhang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Boris D Heifets
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Trisha Suppes
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Peter J van Roessel
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Sierra-Pacific Mental Illness Research, Education and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Jerome A Yesavage
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Sierra-Pacific Mental Illness Research, Education and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Nancy J Gray
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Rachel Hilton
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Claire Bertrand
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Carolyn I Rodriguez
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Karl Deisseroth
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Brian Knutson
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.
- Sierra-Pacific Mental Illness Research, Education and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA.
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28
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Sanchez SM, Tsuchiyagaito A, Kuplicki R, Park H, Postolski I, Rohan M, Paulus MP, Guinjoan SM. Repetitive Negative Thinking-Specific and -Nonspecific White Matter Tracts Engaged by Historical Psychosurgical Targets for Depression. Biol Psychiatry 2023; 94:661-671. [PMID: 36965550 PMCID: PMC10517085 DOI: 10.1016/j.biopsych.2023.03.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 03/06/2023] [Accepted: 03/09/2023] [Indexed: 03/27/2023]
Abstract
BACKGROUND Repetitive negative thinking (RNT) is a frequent symptom of major depressive disorder (MDD) that is associated with poor outcomes and treatment resistance. While most studies on RNT have focused on structural and functional characteristics of gray matter, this study aimed to examine the association between white matter (WM) tracts and interindividual variability in RNT. METHODS A probabilistic tractography approach was used to characterize differences in the size and anatomical trajectory of WM fibers traversing psychosurgery targets historically useful in the treatment of MDD (anterior capsulotomy, anterior cingulotomy, and subcaudate tractotomy) in patients with MDD and low (n = 53) or high (n = 52) RNT, and healthy control subjects (n = 54). MDD samples were propensity matched on depression and anxiety severity and demographics. RESULTS WM tracts traversing left hemisphere targets and reaching the ventral anterior body of the corpus callosum (thus extending to contralateral regions) were larger in the high-RNT MDD group compared with low-RNT (effect size D = 0.27, p = .042) and healthy control (D = 0.23, p = .02) groups. MDD was associated with greater size of tracts that converge onto the right medial orbitofrontal cortex regardless of RNT intensity. Other RNT-nonspecific findings in MDD involved tracts reaching the left primary motor and right primary somatosensory cortices. CONCLUSIONS This study provides the first evidence to our knowledge that WM connectivity patterns, which could become targets of intervention, differ between high- and low-RNT participants with MDD. These WM differences extend to circuits that are not specific to RNT, possibly subserving reward mechanisms and psychomotor activity.
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Affiliation(s)
| | - Aki Tsuchiyagaito
- Laureate Institute for Brain Research, Tulsa, Oklahoma; Research Center for Child Mental Development, Chiba University, Chiba, Japan
| | | | - Heekyeong Park
- Laureate Institute for Brain Research, Tulsa, Oklahoma; Department of Psychology, University of North Texas, Dallas, Texas
| | - Ivan Postolski
- Institute for Research in Computational Sciences, National Scientific and Technical Research Council-University of Buenos Aires, Buenos Aires, Argentina
| | - Michael Rohan
- Laureate Institute for Brain Research, Tulsa, Oklahoma
| | - Martin P Paulus
- Laureate Institute for Brain Research, Tulsa, Oklahoma; Oxley College of Health Sciences, University of Tulsa, Tulsa, Oklahoma
| | - Salvador M Guinjoan
- Laureate Institute for Brain Research, Tulsa, Oklahoma; Department of Psychiatry, Oklahoma University Health Sciences Center, Tulsa, Oklahoma.
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29
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Murphy N, Tamman AJF, Lijffijt M, Amarneh D, Iqbal S, Swann A, Averill LA, O'Brien B, Mathew SJ. Neural complexity EEG biomarkers of rapid and post-rapid ketamine effects in late-life treatment-resistant depression: a randomized control trial. Neuropsychopharmacology 2023; 48:1586-1593. [PMID: 37076582 PMCID: PMC10516885 DOI: 10.1038/s41386-023-01586-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 04/03/2023] [Accepted: 04/05/2023] [Indexed: 04/21/2023]
Abstract
Ketamine is an effective intervention for treatment-resistant depression (TRD), including late-in-life (LL-TRD). The proposed mechanism of antidepressant effects of ketamine is a glutamatergic surge, which can be measured by electroencephalogram (EEG) gamma oscillations. Yet, non-linear EEG biomarkers of ketamine effects such as neural complexity are needed to capture broader systemic effects, represent the level of organization of synaptic communication, and elucidate mechanisms of action for treatment responders. In a secondary analysis of a randomized control trial, we investigated two EEG neural complexity markers (Lempel-Ziv complexity [LZC] and multiscale entropy [MSE]) of rapid (baseline to 240 min) and post-rapid ketamine (24 h and 7 days) effects after one 40-min infusion of IV ketamine or midazolam (active control) in 33 military veterans with LL-TRD. We also studied the relationship between complexity and Montgomery-Åsberg Depression Rating Scale score change at 7 days post-infusion. We found that LZC and MSE both increased 30 min post-infusion, with effects not localized to a single timescale for MSE. Post-rapid effects of reduced complexity with ketamine were observed for MSE. No relationship was observed between complexity and reduction in depressive symptoms. Our findings support the hypothesis that a single sub-anesthetic ketamine infusion has time-varying effects on system-wide contributions to the evoked glutamatergic surge in LL-TRD. Further, changes to complexity were observable outside the time-window previously shown for effects on gamma oscillations. These preliminary results have clinical implications in providing a functional marker of ketamine that is non-linear, amplitude-independent, and represents larger dynamic properties, providing strong advantages over linear measures in highlighting ketamine's effects.
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Affiliation(s)
- Nicholas Murphy
- Baylor College of Medicine, Menninger Department of Psychiatry and Behavioral Sciences, Houston, TX, USA
- The Menninger Clinic, Houston, TX, USA
| | - Amanda J F Tamman
- Baylor College of Medicine, Menninger Department of Psychiatry and Behavioral Sciences, Houston, TX, USA.
| | - Marijn Lijffijt
- Baylor College of Medicine, Menninger Department of Psychiatry and Behavioral Sciences, Houston, TX, USA
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
| | - Dania Amarneh
- Baylor College of Medicine, Menninger Department of Psychiatry and Behavioral Sciences, Houston, TX, USA
| | - Sidra Iqbal
- Baylor College of Medicine, Menninger Department of Psychiatry and Behavioral Sciences, Houston, TX, USA
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
| | - Alan Swann
- Baylor College of Medicine, Menninger Department of Psychiatry and Behavioral Sciences, Houston, TX, USA
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
| | - Lynnette A Averill
- Baylor College of Medicine, Menninger Department of Psychiatry and Behavioral Sciences, Houston, TX, USA
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
| | - Brittany O'Brien
- Baylor College of Medicine, Menninger Department of Psychiatry and Behavioral Sciences, Houston, TX, USA
- The Menninger Clinic, Houston, TX, USA
| | - Sanjay J Mathew
- Baylor College of Medicine, Menninger Department of Psychiatry and Behavioral Sciences, Houston, TX, USA
- The Menninger Clinic, Houston, TX, USA
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
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Marx W, Penninx BWJH, Solmi M, Furukawa TA, Firth J, Carvalho AF, Berk M. Major depressive disorder. Nat Rev Dis Primers 2023; 9:44. [PMID: 37620370 DOI: 10.1038/s41572-023-00454-1] [Citation(s) in RCA: 42] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/11/2023] [Indexed: 08/26/2023]
Abstract
Major depressive disorder (MDD) is characterized by persistent depressed mood, loss of interest or pleasure in previously enjoyable activities, recurrent thoughts of death, and physical and cognitive symptoms. People with MDD can have reduced quality of life owing to the disorder itself as well as related medical comorbidities, social factors, and impaired functional outcomes. MDD is a complex disorder that cannot be fully explained by any one single established biological or environmental pathway. Instead, MDD seems to be caused by a combination of genetic, environmental, psychological and biological factors. Treatment for MDD commonly involves pharmacological therapy with antidepressant medications, psychotherapy or a combination of both. In people with severe and/or treatment-resistant MDD, other biological therapies, such as electroconvulsive therapy, may also be offered.
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Affiliation(s)
- Wolfgang Marx
- Deakin University, IMPACT - the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong, Victoria, Australia.
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Marco Solmi
- Department of Psychiatry, University of Ottawa, Ottawa, Ontario, Canada
- On Track: The Champlain First Episode Psychosis Program, Department of Mental Health, The Ottawa Hospital, Ottawa, Ontario, Canada
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | - Toshi A Furukawa
- Department of Health Promotion and Human Behavior, Kyoto University Graduate School of Medicine/School of Public Health, Kyoto, Japan
| | - Joseph Firth
- Division of Psychology and Mental Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Greater Manchester Mental Health NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Andre F Carvalho
- Deakin University, IMPACT - the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong, Victoria, Australia
| | - Michael Berk
- Deakin University, IMPACT - the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong, Victoria, Australia
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31
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Lv N, Ajilore OA, Xiao L, Venditti EM, Lavori PW, Gerber BS, Snowden MB, Wittels NE, Ronneberg CR, Stetz P, Barve A, Shrestha R, Dosala S, Kumar V, Eckley TL, Goldstein-Piekarski AN, Smyth JM, Rosas LG, Kannampallil T, Zulueta J, Suppes T, Williams LM, Ma J. Mediating Effects of Neural Targets on Depression, Weight, and Anxiety Outcomes of an Integrated Collaborative Care Intervention: The ENGAGE-2 Mechanistic Pilot Randomized Clinical Trial. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:430-442. [PMID: 37519462 PMCID: PMC10382700 DOI: 10.1016/j.bpsgos.2022.03.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 02/25/2022] [Accepted: 03/24/2022] [Indexed: 12/28/2022] Open
Abstract
Background Integrated treatments for comorbid depression (often with anxiety) and obesity are lacking; mechanisms are poorly investigated. Methods In a mechanistic pilot trial, adults with body mass index ≥30 and Patient Health Questionnaire-9 scores ≥10 were randomized to usual care (n = 35) or an integrated behavioral intervention (n = 71). Changes at 6 months in body mass index and Depression Symptom Checklist-20 scores were co-primary outcomes, and Generalized Anxiety Disorder Scale-7 score was a secondary outcome. Changes at 2 months in the activation and functional connectivity of regions of interest in the negative affect circuit were primary neural targets, and secondary targets were in the cognitive control, default mode, and positive affect circuits. Results Participants were 47.0 years (SD = 11.9 years), 76% women, 55% Black, and 20% Latino. Depression Symptom Checklist-20 (between-group difference, -0.3 [95% CI: -0.6 to -0.1]) and Generalized Anxiety Disorder Scale-7 (-2.9 [-4.7 to -1.1]) scores, but not body mass index, decreased significantly at 6 months in the intervention versus usual care groups. Only Generalized Anxiety Disorder Scale-7 score changes at 6 months significantly correlated with neural target changes at 2 months in the negative affect (anterior insula, subgenual/pregenual anterior cingulate cortex, amygdala) and cognitive control circuits (dorsal lateral prefrontal cortex, dorsal anterior cingulate cortex). Effects were medium to large (0.41-1.18 SDs). Neural target changes at 2 months in the cognitive control circuit only differed by treatment group. Effects were medium (0.58-0.79 SDs). Conclusions Compared with usual care, the study intervention led to significantly improved depression but not weight loss, and the results on neural targets were null for both outcomes. The significant intervention effect on anxiety might be mediated through changes in the cognitive control circuit, but this warrants replication.
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Affiliation(s)
- Nan Lv
- Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois
| | - Olusola A. Ajilore
- Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois
| | - Lan Xiao
- Department of Epidemiology and Population Health, Stanford University, Palo Alto, California
| | - Elizabeth M. Venditti
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Philip W. Lavori
- Department of Biomedical Data Science, Stanford University, Palo Alto, California
| | - Ben S. Gerber
- Department of Population and Quantitative Health Sciences, University of Massachusetts, Worcester, Massachusetts
| | - Mark B. Snowden
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington
| | - Nancy E. Wittels
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Corina R. Ronneberg
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Patrick Stetz
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, California
| | - Amruta Barve
- Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois
| | - Rohit Shrestha
- Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois
| | - Sushanth Dosala
- Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois
| | - Vikas Kumar
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Tessa L. Eckley
- Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois
| | - Andrea N. Goldstein-Piekarski
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, California
- MIRECC VISN21, Veterans Affairs Palo Alto Health Care System, Palo Alto, California
| | - Joshua M. Smyth
- Departments of Biobehavioral Health and Medicine, Pennsylvania State University, State College, Pennsylvania
| | - Lisa G. Rosas
- Department of Epidemiology and Population Health, Stanford University, Palo Alto, California
| | - Thomas Kannampallil
- Department of Anesthesiology and Institute for Informatics, Washington University School of Medicine, St. Louis, Missouri
| | - John Zulueta
- Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois
| | - Trisha Suppes
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, California
- MIRECC VISN21, Veterans Affairs Palo Alto Health Care System, Palo Alto, California
| | - Leanne M. Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, California
- MIRECC VISN21, Veterans Affairs Palo Alto Health Care System, Palo Alto, California
| | - Jun Ma
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
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Misaki M, Tsuchiyagaito A, Guinjoan SM, Rohan ML, Paulus MP. Trait repetitive negative thinking in depression is associated with functional connectivity in negative thinking state rather than resting state. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.23.533932. [PMID: 36993382 PMCID: PMC10055358 DOI: 10.1101/2023.03.23.533932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
Abstract
Resting-state functional connectivity (RSFC) has been proposed as a potential indicator of repetitive negative thinking (RNT) in depression. However, identifying the specific functional process associated with RSFC alterations is challenging, and it remains unclear whether alterations in RSFC for depressed individuals are directly related to the RNT process or to individual characteristics distinct from the negative thinking process per se. To investigate the relationship between RSFC alterations and the RNT process in individuals with major depressive disorder (MDD), we compared RSFC with functional connectivity during an induced negative-thinking state (NTFC) in terms of their predictability of RNT traits and associated whole-brain connectivity patterns using connectome-based predictive modeling (CPM) and connectome-wide association (CWA) analyses. Thirty-six MDD participants and twenty-six healthy control participants underwent both resting state and induced negative thinking state fMRI scans. Both RSFC and NTFC distinguished between healthy and depressed individuals with CPM. However, trait RNT in depressed individuals, as measured by the Ruminative Responses Scale-Brooding subscale, was only predictable from NTFC, not from RSFC. CWA analysis revealed that negative thinking in depression was associated with higher functional connectivity between the default mode and executive control regions, which was not observed in RSFC. These findings suggest that RNT in depression involves an active mental process encompassing multiple brain regions across functional networks, which is not represented in the resting state. Although RSFC indicates brain functional alterations in MDD, they may not directly reflect the negative thinking process.
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Affiliation(s)
- Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK, USA
| | - Aki Tsuchiyagaito
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK, USA
| | - Salvador M. Guinjoan
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Department of Psychiatry, Oklahoma University Health Sciences Center at Tulsa, Tulsa, OK, USA
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33
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Hack LM, Tozzi L, Zenteno S, Olmsted AM, Hilton R, Jubeir J, Korgaonkar MS, Schatzberg AF, Yesavage JA, O’Hara R, Williams LM. A Cognitive Biotype of Depression and Symptoms, Behavior Measures, Neural Circuits, and Differential Treatment Outcomes: A Prespecified Secondary Analysis of a Randomized Clinical Trial. JAMA Netw Open 2023; 6:e2318411. [PMID: 37318808 PMCID: PMC10273022 DOI: 10.1001/jamanetworkopen.2023.18411] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 04/27/2023] [Indexed: 06/16/2023] Open
Abstract
Importance Cognitive deficits in depression have been associated with poor functional capacity, frontal neural circuit dysfunction, and worse response to conventional antidepressants. However, it is not known whether these impairments combine together to identify a specific cognitive subgroup (or "biotype") of individuals with major depressive disorder (MDD), and the extent to which these impairments mediate antidepressant outcomes. Objective To undertake a systematic test of the validity of a proposed cognitive biotype of MDD across neural circuit, symptom, social occupational function, and treatment outcome modalities. Design, Setting, and Participants This secondary analysis of a randomized clinical trial implemented data-driven clustering in findings from the International Study to Predict Optimized Treatment in Depression, a pragmatic biomarker trial in which patients with MDD were randomized in a 1:1:1 ratio to antidepressant treatment with escitalopram, sertraline, or venlafaxine extended-release and assessed at baseline and 8 weeks on multimodal outcomes between December 1, 2008, and September 30, 2013. Eligible patients were medication-free outpatients with nonpsychotic MDD in at least the moderate range, and were recruited from 17 clinical and academic practices; a subset of these patients underwent functional magnetic resonance imaging. This prespecified secondary analysis was performed between June 10, 2022, and April 21, 2023. Main Outcomes and Measures Pretreatment and posttreatment behavioral measures of cognitive performance across 9 domains, depression symptoms assessed using 2 standard depression scales, and psychosocial function assessed using the Social and Occupational Functioning Assessment Scale and World Health Organization Quality of Life scale were analyzed. Neural circuit function engaged during a cognitive control task was measured using functional magnetic resonance imaging. Results A total of 1008 patients (571 [56.6%] female; mean [SD] age, 37.8 [12.6] years) participated in the overall trial and 96 patients participated in the imaging substudy (45 [46.7%] female; mean [SD] age, 34.5 [13.5] years). Cluster analysis identified what may be referred to as a cognitive biotype of 27% of depressed patients with prominent behavioral impairment in executive function and response inhibition domains of cognitive control. This biotype was characterized by a specific profile of pretreatment depressive symptoms, worse psychosocial functioning (d = -0.25; 95% CI, -0.39 to -0.11; P < .001), and reduced activation of the cognitive control circuit (right dorsolateral prefrontal cortex: d = -0.78; 95% CI, -1.28 to -0.27; P = .003). Remission was comparatively lower in the cognitive biotype positive subgroup (73 of 188 [38.8%] vs 250 of 524 [47.7%]; P = .04) and cognitive impairments persisted regardless of symptom change (executive function: ηp2 = 0.241; P < .001; response inhibition: ηp2 = 0.750; P < .001). The extent of symptom and functional change was specifically mediated by change in cognition but not the reverse. Conclusions and Relevance Our findings suggest the presence of a cognitive biotype of depression with distinct neural correlates, and a functional clinical profile that responds poorly to standard antidepressants and instead may benefit from therapies specifically targeting cognitive dysfunction. Trial Registration ClinicalTrials.gov Identifier: NCT00693849.
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Affiliation(s)
- Laura M. Hack
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California
- Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC) Veterans Affairs Palo Alto Health Care System, Palo Alto, California
| | - Leonardo Tozzi
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California
| | - Samantha Zenteno
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California
| | - Alisa M. Olmsted
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California
- Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC) Veterans Affairs Palo Alto Health Care System, Palo Alto, California
| | - Rachel Hilton
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California
| | - Jenna Jubeir
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California
| | - Mayuresh S. Korgaonkar
- Brain Dynamic Centre, Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
| | - Alan F. Schatzberg
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California
| | - Jerome A. Yesavage
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California
- Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC) Veterans Affairs Palo Alto Health Care System, Palo Alto, California
| | - Ruth O’Hara
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California
- Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC) Veterans Affairs Palo Alto Health Care System, Palo Alto, California
| | - Leanne M. Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California
- Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC) Veterans Affairs Palo Alto Health Care System, Palo Alto, California
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Mulholland MM, Prinsloo S, Kvale E, Dula AN, Palesh O, Kesler SR. Behavioral and biologic characteristics of cancer-related cognitive impairment biotypes. Brain Imaging Behav 2023; 17:320-328. [PMID: 37127832 PMCID: PMC10195718 DOI: 10.1007/s11682-023-00774-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2023] [Indexed: 05/03/2023]
Abstract
Psychiatric diagnosis is moving away from symptom-based classification and towards multi-dimensional, biologically-based characterization, or biotyping. We previously identified three biotypes of chemotherapy-related cognitive impairment based on functional brain connectivity. In this follow-up study of 80 chemotherapy-treated breast cancer survivors and 80 non-cancer controls, we evaluated additional factors to help explain biotype expression: neurofunctional stability, brain age, apolipoprotein (APOE) genotype, and psychoneurologic symptoms. We also compared the discriminative ability of a traditional, symptom-based cognitive impairment definition with that of biotypes. We found significant differences in cortical brain age (F = 10.50, p < 0.001), neurofunctional stability (F = 2.83, p = 0.041), APOE e4 genotype (X2 = 7.68, p = 0.050), and psychoneurological symptoms (Pillai = 0.378, p < 0.001) across the three biotypes. The more resilient Biotype 2 demonstrated significantly higher neurofunctional stability compared to the other biotypes. Symptom-based classification of cognitive impairment did not differentiate biologic or other behavioral variables, suggesting that traditional categorization of cancer-related cognitive effects may miss important characteristics which could inform targeted treatment strategies. Additionally, biotyping, but not symptom-typing, was able to distinguish survivors with cognitive versus psychological effects. Our results suggest that Biotype 1 survivors might benefit from first addressing symptoms of anxiety and fatigue, Biotype 3 might benefit from a treatment plan which includes sleep hygiene, and Biotype 2 might benefit most from cognitive skills training or rehabilitation. Future research should include additional demographic and clinical information to further investigate biotype expression related to risk and resilience and examine integration of more clinically feasible imaging approaches.
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Affiliation(s)
- Michele M Mulholland
- Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX, USA
| | - Sarah Prinsloo
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Elizabeth Kvale
- Department of Geriatrics and Palliative Care, Baylor College of Medicine, Houston, TX, USA
| | - Adrienne N Dula
- Department of Neurology, Dell School of Medicine, The University of Texas at Austin, Austin, TX, USA
| | - Oxana Palesh
- Department of Psychiatry, Massey Cancer Center, Virginia Commonwealth University School of Medicine, Richmond,, VA, USA
| | - Shelli R Kesler
- Department of Geriatrics and Palliative Care, Baylor College of Medicine, Houston, TX, USA.
- Department of Adult Health, School of Nursing, The University of Texas at Austin, 1710 Red River St, D0100, Austin, TX, 78712, USA.
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35
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Kannampallil T, Ajilore OA, Lv N, Smyth JM, Wittels NE, Ronneberg CR, Kumar V, Xiao L, Dosala S, Barve A, Zhang A, Tan KC, Cao KK, Patel CR, Gerber BS, Johnson JA, Kringle EA, Ma J. Effects of a virtual voice-based coach delivering problem-solving treatment on emotional distress and brain function: a pilot RCT in depression and anxiety. Transl Psychiatry 2023; 13:166. [PMID: 37173334 PMCID: PMC10175049 DOI: 10.1038/s41398-023-02462-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 04/14/2023] [Accepted: 04/26/2023] [Indexed: 05/15/2023] Open
Abstract
Consumer-based voice assistants have the ability to deliver evidence-based treatment, but their therapeutic potential is largely unknown. In a pilot trial of a virtual voice-based coach, Lumen, delivering problem-solving treatment, adults with mild-to-moderate depression and/or anxiety were randomized to the Lumen intervention (n = 42) or waitlist control (n = 21). The main outcomes included changes in neural measures of emotional reactivity and cognitive control, and Hospital Anxiety and Depression Scale [HADS] symptom scores over 16 weeks. Participants were 37.8 years (SD = 12.4), 68% women, 25% Black, 24% Latino, and 11% Asian. Activation of the right dlPFC (neural region of interest in cognitive control) decreased in the intervention group but increased in the control group, with an effect size meeting the prespecified threshold for a meaningful effect (Cohen's d = 0.3). Between-group differences in the change in activation of the left dlPFC and bilateral amygdala were observed, but were of smaller magnitude (d = 0.2). Change in right dlPFC activation was also meaningfully associated (r ≥ 0.4) with changes in self-reported problem-solving ability and avoidance in the intervention. Lumen intervention also led to decreased HADS depression, anxiety, and overall psychological distress scores, with medium effect sizes (Cohen's d = 0.49, 0.51, and 0.55, respectively), compared with the waitlist control group. This pilot trial showed promising effects of a novel digital mental health intervention on cognitive control using neuroimaging and depression and anxiety symptoms, providing foundational evidence for a future confirmatory study.
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Affiliation(s)
- Thomas Kannampallil
- Department of Anesthesiology, Washington University School of Medicine, St Louis, MO, USA
- Institute for Informatics, Washington University School of Medicine, St Louis, MO, USA
| | - Olusola A Ajilore
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - Nan Lv
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Joshua M Smyth
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, USA
| | - Nancy E Wittels
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Corina R Ronneberg
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Vikas Kumar
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Lan Xiao
- Department of Epidemiology and Population Health, Stanford University, Stanford, USA
| | - Susanth Dosala
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Amruta Barve
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Aifeng Zhang
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - Kevin C Tan
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Kevin K Cao
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Charmi R Patel
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Ben S Gerber
- Department of Population & Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - Jillian A Johnson
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, USA
| | - Emily A Kringle
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Jun Ma
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA.
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36
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Szymkowicz SM, Gerlach AR, Homiack D, Taylor WD. Biological factors influencing depression in later life: role of aging processes and treatment implications. Transl Psychiatry 2023; 13:160. [PMID: 37160884 PMCID: PMC10169845 DOI: 10.1038/s41398-023-02464-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 04/23/2023] [Accepted: 04/27/2023] [Indexed: 05/11/2023] Open
Abstract
Late-life depression occurring in older adults is common, recurrent, and malignant. It is characterized by affective symptoms, but also cognitive decline, medical comorbidity, and physical disability. This behavioral and cognitive presentation results from altered function of discrete functional brain networks and circuits. A wide range of factors across the lifespan contributes to fragility and vulnerability of those networks to dysfunction. In many cases, these factors occur earlier in life and contribute to adolescent or earlier adulthood depressive episodes, where the onset was related to adverse childhood events, maladaptive personality traits, reproductive events, or other factors. Other individuals exhibit a later-life onset characterized by medical comorbidity, pro-inflammatory processes, cerebrovascular disease, or developing neurodegenerative processes. These later-life processes may not only lead to vulnerability to the affective symptoms, but also contribute to the comorbid cognitive and physical symptoms. Importantly, repeated depressive episodes themselves may accelerate the aging process by shifting allostatic processes to dysfunctional states and increasing allostatic load through the hypothalamic-pituitary-adrenal axis and inflammatory processes. Over time, this may accelerate the path of biological aging, leading to greater brain atrophy, cognitive decline, and the development of physical decline and frailty. It is unclear whether successful treatment of depression and avoidance of recurrent episodes would shift biological aging processes back towards a more normative trajectory. However, current antidepressant treatments exhibit good efficacy for older adults, including pharmacotherapy, neuromodulation, and psychotherapy, with recent work in these areas providing new guidance on optimal treatment approaches. Moreover, there is a host of nonpharmacological treatment approaches being examined that take advantage of resiliency factors and decrease vulnerability to depression. Thus, while late-life depression is a recurrent yet highly heterogeneous disorder, better phenotypic characterization provides opportunities to better utilize a range of nonspecific and targeted interventions that can promote recovery, resilience, and maintenance of remission.
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Affiliation(s)
- Sarah M Szymkowicz
- Center for Cognitive Medicine, Department of Psychiatry and Behavioral Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Andrew R Gerlach
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Damek Homiack
- Department of Psychiatry, University of Illinois-Chicago, Chicago, IL, USA
| | - Warren D Taylor
- Center for Cognitive Medicine, Department of Psychiatry and Behavioral Science, Vanderbilt University Medical Center, Nashville, TN, USA.
- Geriatric Research, Education, and Clinical Center, Veterans Affairs Tennessee Valley Health System, Nashville, TN, USA.
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37
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Montalto A, Park HRP, Williams LM, Korgaonkar MS, Chilver MR, Jamshidi J, Schofield PR, Gatt JM. Negative association between anterior insula activation and resilience during sustained attention: an fMRI twin study. Psychol Med 2023; 53:3187-3199. [PMID: 37449488 DOI: 10.1017/s0033291721005262] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND While previous studies have suggested that higher levels of cognitive performance may be related to greater wellbeing and resilience, little is known about the associations between neural circuits engaged by cognitive tasks and wellbeing and resilience, and whether genetics or environment contribute to these associations. METHODS The current study consisted of 253 monozygotic and dizygotic adult twins, including a subsample of 187 early-life trauma-exposed twins, with functional Magnetic Resonance Imaging data from the TWIN-E study. Wellbeing was measured using the COMPAS-W Wellbeing Scale while resilience was defined as a higher level of positive adaptation (higher levels of wellbeing) in the presence of trauma exposure. We probed both sustained attention and working memory processes using a Continuous Performance Task in the scanner. RESULTS We found significant negative associations between resilience and activation in the bilateral anterior insula engaged during sustained attention. Multivariate twin modelling showed that the association between resilience and the left and right insula activation was mostly driven by common genetic factors, accounting for 71% and 87% of the total phenotypic correlation between these variables, respectively. There were no significant associations between wellbeing/resilience and neural activity engaged during working memory updating. CONCLUSIONS The findings suggest that greater resilience to trauma is associated with less activation of the anterior insula during a condition requiring sustained attention but not working memory updating. This possibly suggests a pattern of 'neural efficiency' (i.e. more efficient and/or attenuated activity) in people who may be more resilient to trauma.
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Affiliation(s)
- Arthur Montalto
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
| | - Haeme R P Park
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
| | - Leanne M Williams
- Stanford School of Medicine, Stanford University, Stanford, CA, USA
- Mental Illness Research Education and Clinical Centers VISN21, Veterans Administration Palo Alto Health Care System, Palo Alto, CA, 94304-151-Y, USA
| | - Mayuresh S Korgaonkar
- Brain Dynamics Centre, The Westmead Institute for Medical Research, University of Sydney, Sydney, NSW, Australia
- School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Miranda R Chilver
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
| | - Javad Jamshidi
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Medical Science, University of New South Wales, Sydney, NSW, Australia
| | - Justine M Gatt
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
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38
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Mansouri S, Pessoni AM, Rivera AM, Tamminga CA, Parise E, Turecki G, Nestler EJ, Chen TH, Labonté B. Transcriptional dissection of symptomatic profiles across the brain of men and women with depression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.21.537733. [PMID: 37131585 PMCID: PMC10153251 DOI: 10.1101/2023.04.21.537733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Major depressive disorder (MDD) is one of the most important causes of disability worldwide. While recent work provides insights into the molecular alterations in the brain of patients with MDD, whether these molecular signatures can be associated with the expression of specific symptom domains in males and females remains unclear. Here, we identified sex-specific gene modules associated with the expression of MDD, combining differential gene expression and co-expression network analyses in six cortical and subcortical brain regions. Our results show varying levels of network homology between males and females across brain regions, although the association between these structures and the expression of MDD remains highly sex-specific. We refined these associations to several symptom domains and identified transcriptional signatures associated with distinct functional pathways, including GABAergic and glutamatergic neurotransmission, metabolic processes, and intracellular signal transduction, across brain regions associated with distinct symptomatic profiles in a sex-specific fashion. In most cases, these associations were specific to males or to females with MDD, although a subset of gene modules associated with common symptomatic features in both sexes was also identified. Together, our findings suggest that the expression of distinct MDD symptom domains is associated with sex-specific transcriptional structures across brain regions.
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Dhamala E, Yeo BTT, Holmes AJ. One Size Does Not Fit All: Methodological Considerations for Brain-Based Predictive Modeling in Psychiatry. Biol Psychiatry 2023; 93:717-728. [PMID: 36577634 DOI: 10.1016/j.biopsych.2022.09.024] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 09/07/2022] [Accepted: 09/23/2022] [Indexed: 12/30/2022]
Abstract
Psychiatric illnesses are heterogeneous in nature. No illness manifests in the same way across individuals, and no two patients with a shared diagnosis exhibit identical symptom profiles. Over the last several decades, group-level analyses of in vivo neuroimaging data have led to fundamental advances in our understanding of the neurobiology of psychiatric illnesses. More recently, access to computational resources and large, publicly available datasets alongside the rise of predictive modeling and precision medicine approaches have facilitated the study of psychiatric illnesses at an individual level. Data-driven machine learning analyses can be applied to identify disease-relevant biological subtypes, predict individual symptom profiles, and recommend personalized therapeutic interventions. However, when developing these predictive models, methodological choices must be carefully considered to ensure accurate, robust, and interpretable results. Choices pertaining to algorithms, neuroimaging modalities and states, data transformation, phenotypes, parcellations, sample sizes, and populations we are specifically studying can influence model performance. Here, we review applications of neuroimaging-based machine learning models to study psychiatric illnesses and discuss the effects of different methodological choices on model performance. An understanding of these effects is crucial for the proper implementation of predictive models in psychiatry and will facilitate more accurate diagnoses, prognoses, and therapeutics.
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Affiliation(s)
- Elvisha Dhamala
- Department of Psychology, Yale University, New Haven, Connecticut; Kavli Institute for Neuroscience, Yale University, New Haven, Connecticut.
| | - B T Thomas Yeo
- Centre for Sleep & Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, Singapore, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health & Institute for Digital Medicine, National University of Singapore, Singapore; Integrative Sciences and Engineering Programme, National University of Singapore, Singapore; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Avram J Holmes
- Department of Psychology, Yale University, New Haven, Connecticut; Kavli Institute for Neuroscience, Yale University, New Haven, Connecticut; Department of Psychiatry, Yale University, New Haven, Connecticut; Wu Tsai Institute, Yale University, New Haven, Connecticut.
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40
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Kan RLD, Padberg F, Giron CG, Lin TTZ, Zhang BBB, Brunoni AR, Kranz GS. Effects of repetitive transcranial magnetic stimulation of the left dorsolateral prefrontal cortex on symptom domains in neuropsychiatric disorders: a systematic review and cross-diagnostic meta-analysis. Lancet Psychiatry 2023; 10:252-259. [PMID: 36898403 DOI: 10.1016/s2215-0366(23)00026-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 12/16/2022] [Accepted: 01/06/2023] [Indexed: 03/09/2023]
Abstract
BACKGROUND The left dorsolateral prefrontal cortex is a prime target for repetitive transcranial magnetic stimulation (TMS) to treat neuropsychiatric disorders; thus, abundant efficacy data from controlled trials are available. A cross-diagnostic meta-analysis was conducted to identify the symptom domains susceptible to repetitive TMS to the left dorsolateral prefrontal cortex. METHODS This systematic review and meta-analysis investigated the effects of repetitive TMS to the left dorsolateral prefrontal cortex on neuropsychiatric symptoms presenting across diagnoses. We searched PubMed, MEDLINE, Embase, Web of Science, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, and WHO International Clinical Trials Registry Platform for randomised and sham controlled trials published from inception to Aug 17, 2022. Included studies assessed symptoms using clinical measures and reported sufficient data to calculate effect sizes pooled with a random effects model. Two independent reviewers conducted screening and used the Cochrane risk-of-bias tool for quality assessment. Summary data were extracted from published reports. The main outcome was the therapeutic effects of repetitive TMS of the left dorsolateral prefrontal cortex on distinct symptom domains. This study is registered with PROSPERO (CRD42021278458). FINDINGS Of 9056 studies identified (6704 from databases and 2352 from registers), 174 were included in the analysis including 7905 patients. 163 of 174 studies reported gender data; 3908 (52·35%) of 7465 patients were male individuals, and 3557 (47·65%) were female individuals. Mean age was 44·63 years (range 19·79-72·80). Ethnicity data were mostly not available. Effect size was large for craving (Hedges'g -0·803 [95% CI -1·099 to -0·507], p<0·0001; I2=82·40%), medium for depressive symptoms (-0·725 [-0·889 to -0·561], p<0·0001; I2=85·66%), small for anxiety, obsessions or compulsions, pain, global cognition, declarative memory, working memory, cognitive control, and motor coordination (Hedges'g -0·198 to -0·491), and non-significant for attention, suicidal ideation, language, walking ability, fatigue, and sleep. INTERPRETATION The cross-diagnostic meta-analysis shows the efficacy of repetitive TMS of the left dorsolateral prefrontal cortex on distinct symptom domains, providing a novel framework for assessing target or efficacy interactions of repetitive TMS, and informing personalised applications for conditions for which regular trials are uninformative. FUNDING The University Grants Committee of Hong Kong and the Mental Health Research Center, The Hong Kong Polytechnic University.
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Affiliation(s)
- Rebecca L D Kan
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China
| | - Frank Padberg
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg, Munich, Germany
| | - Cristian G Giron
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China
| | - Tim T Z Lin
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China
| | - Bella B B Zhang
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China
| | - Andre R Brunoni
- Departamento de Clínica Médica, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Laboratory of Neurosciences (LIM-27), Instituto de Psiquiatria, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Georg S Kranz
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China; Mental Health Research Centre, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China; Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria; The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong Special Administrative Region, China.
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41
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Scangos KW, State MW, Miller AH, Baker JT, Williams LM. New and emerging approaches to treat psychiatric disorders. Nat Med 2023; 29:317-333. [PMID: 36797480 PMCID: PMC11219030 DOI: 10.1038/s41591-022-02197-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 12/21/2022] [Indexed: 02/18/2023]
Abstract
Psychiatric disorders are highly prevalent, often devastating diseases that negatively impact the lives of millions of people worldwide. Although their etiological and diagnostic heterogeneity has long challenged drug discovery, an emerging circuit-based understanding of psychiatric illness is offering an important alternative to the current reliance on trial and error, both in the development and in the clinical application of treatments. Here we review new and emerging treatment approaches, with a particular emphasis on the revolutionary potential of brain-circuit-based interventions for precision psychiatry. Limitations of circuit models, challenges of bringing precision therapeutics to market and the crucial advances needed to overcome these obstacles are presented.
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Affiliation(s)
- Katherine W Scangos
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
| | - Matthew W State
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Andrew H Miller
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Justin T Baker
- McLean Hospital Institute for Technology in Psychiatry, Belmont, MA, USA
| | - Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Mental Illness Research Education and Clinical Center (MIRECC), VA Palo Alto Health Care System, Palo Alto, CA, USA
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42
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Stout DM, Bomyea J. From Magnetic Resonance Imaging to the Clinic: Using Neuroimaging to Characterize Psychiatric Phenotypes. Biol Psychiatry 2022; 91:526-528. [PMID: 35177204 DOI: 10.1016/j.biopsych.2021.12.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 12/27/2021] [Indexed: 11/02/2022]
Affiliation(s)
- Daniel M Stout
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, La Jolla, California; Department of Psychiatry, University of California San Diego, La Jolla, California.
| | - Jessica Bomyea
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, La Jolla, California; Department of Psychiatry, University of California San Diego, La Jolla, California.
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43
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Holt-Gosselin B, Keller AS, Chesnut M, Ling R, Grisanzio KA, Williams LM. Greater baseline connectivity of the salience and negative affect circuits are associated with natural improvements in anxiety over time in untreated participants. J Affect Disord 2021; 295:366-376. [PMID: 34492429 DOI: 10.1016/j.jad.2021.08.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 08/18/2021] [Accepted: 08/20/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND There is limited research examining the natural trajectories of depression and anxiety, how these trajectories relate to baseline neural circuit function, and how symptom trajectory-circuit relationships are impacted by engagement in lifestyle activities including exercise, hobbies, and social interactions. To address these gaps, we assessed these relations over three months in untreated participants. METHODS 262 adults (59.5% female, mean age 35) with symptoms of anxiety and depression, untreated with pharmacotherapy or behavioral therapy, completed the DASS-42, WHOQOL, and custom surveys at baseline and follow-up to assess symptoms, psychosocial function, and lifestyle activity engagement. At baseline, participants underwent fMRI under task-free and task-evoked conditions. We quantified six circuits implicated in these symptoms: default mode, salience, negative and positive affect, attention, and cognitive control. RESULTS From baseline to 3 months, some participants demonstrated a natural improvement in anxiety (24%) and depression (26%) symptoms. Greater baseline salience circuit connectivity (pFDR=0.045), specifically between the left and right insula (pFDR=0.045), and greater negative affect circuit connectivity elicited by sad faces (pFDR=0.030) were associated with anxiety symptom improvement. While engagement in lifestyle activities were not associated with anxiety improvements, engagement in hobbies moderated the association between negative affect circuit connectivity and anxiety symptom improvement (p = 0.048). LIMITATIONS The observational design limits causal inference. CONCLUSIONS Our findings highlight the role of the salience and negative affect circuits as potential circuit markers of natural anxiety symptom improvements over time. Future studies that identify biomarkers associated with symptom improvements are critical for the development of personalized treatment targets.
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Affiliation(s)
- Bailey Holt-Gosselin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States; Interdepartmental Neuroscience Graduate Program, Yale University, New Haven, CT, United States
| | - Arielle S Keller
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States; Neurosciences PhD Program, Stanford University, Stanford CA, United States
| | - Megan Chesnut
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States
| | - Ruth Ling
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States
| | - Katherine A Grisanzio
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States
| | - Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States; Mental Illness Research, Education and Clinical Center, Palo Alto VA Healthcare System, Palo Alto, CA, United States.
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44
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Woody ML, Panny B, Degutis M, Griffo A, Price RB. Resting state functional connectivity subtypes predict discrete patterns of cognitive-affective functioning across levels of analysis among patients with treatment-resistant depression. Behav Res Ther 2021; 146:103960. [PMID: 34488187 PMCID: PMC8653528 DOI: 10.1016/j.brat.2021.103960] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 07/22/2021] [Accepted: 09/01/2021] [Indexed: 01/02/2023]
Abstract
Resting state functional connectivity (RSFC) in ventral affective (VAN), default mode (DMN) and cognitive control (CCN) networks may partially underlie heterogeneity in depression. The current study used data-driven parsing of RSFC to identify subgroups of patients with treatment-resistant depression (TRD; n = 70) and determine if subgroups generalized to transdiagnostic measures of cognitive-affective functioning relevant to depression (indexed across self-report, behavioral, and molecular levels of analysis). RSFC paths within key networks were characterized using Subgroup-Group Iterative Multiple Model Estimation. Three connectivity-based subgroups emerged: Subgroup A, the largest subset and containing the fewest pathways; Subgroup B, containing unique bidirectional VAN/DMN negative feedback; and Subgroup C, containing the most pathways. Compared to other subgroups, subgroup B was characterized by lower self-reported positive affect and subgroup C by higher self-reported positive affect, greater variability in induced positive affect, worse response inhibition, and reduced striatal tissue iron concentration. RSFC-based categorization revealed three TRD subtypes associated with discrete aberrations in transdiagnostic cognitive-affective functioning that were largely unified across levels of analysis and were maintained after accounting for the variability captured by a disorder-specific measure of depressive symptoms. Findings advance understanding of transdiagnostic brain-behavior heterogeneity in TRD and may inform novel treatment targets for this population.
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Affiliation(s)
- Mary L Woody
- Department of Psychiatry, University of Pittsburgh School of Medicine, USA.
| | - Benjamin Panny
- Department of Psychiatry, University of Pittsburgh School of Medicine, USA
| | - Michelle Degutis
- Heinz College of Information Systems and Public Policy, Carnegie Mellon University, USA
| | - Angela Griffo
- Department of Psychiatry, University of Pittsburgh School of Medicine, USA
| | - Rebecca B Price
- Department of Psychiatry, University of Pittsburgh School of Medicine, USA; Department of Psychology, University of Pittsburgh, USA
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