Literature DB >> 33435926

Identifying response and predictive biomarkers for Transcranial magnetic stimulation outcomes: protocol and rationale for a mechanistic study of functional neuroimaging and behavioral biomarkers in veterans with Pharmacoresistant depression.

Leanne M Williams1,2, John T Coman3,4, Patrick C Stetz3,4, Nicole C Walker4, F Andrew Kozel5,6, Mark S George7,8, Jong Yoon3,4, Laura M Hack3,4, Michelle R Madore3,4, Kelvin O Lim9,10, Noah S Philip11,12, Paul E Holtzheimer13,14.   

Abstract

BACKGROUND: Although repetitive transcranial magnetic stimulation ('TMS') is becoming a gold standard treatment for pharmacoresistant depression, we lack neural target biomarkers for identifying who is most likely to respond to TMS and why. To address this gap in knowledge we evaluate neural targets defined by activation and functional connectivity of the dorsolateral prefrontal cortex-anchored cognitive control circuit, regions of the default mode network and attention circuit, and interactions with the subgenual anterior cingulate. We evaluate whether these targets and interactions between them change in a dose-dependent manner, whether changes in these neural targets correspond to changes in cognitive behavioral performance, and whether baseline and early change in neural target and cognitive behavioral performance predict subsequent symptom severity, suicidality, and quality of life outcomes. This study is designed as a pragmatic, mechanistic trial partnering with the National Clinical TMS Program of the Veteran's Health Administration.
METHODS: Target enrollment consists of 100 veterans with pharmacoresistant Major Depressive Disorder (MDD). All veterans will receive a clinical course of TMS and will be assessed at 'baseline' pre-TMS commencement, 'first week' after initiation of TMS (targeting five sessions) and 'post-treatment' at the completion of TMS (targeting 30 sessions). Veterans will be assessed using functional magnetic resonance imaging (fMRI), a cognitive behavioral performance battery, and established questionnaires. Multivariate linear mixed models will be used to assess whether neural targets change with TMS as a function of dose (Aim 1), whether extent and change of neural target relates to and predicts extent of behavioral performance (Aim 3), and whether extent of neural target change predicts improvement in symptom severity, suicidality, and quality of life (Aim 3). For all three aims, we will also assess the contribution of baseline moderators such as biological sex and age. DISCUSSION: To our knowledge, our study will be the first pragmatic, mechanistic observational trial to use fMRI imaging and cognitive-behavioral performance as biomarkers of TMS treatment response in pharmacoresistant MDD. The results of this trial will allow providers to select suitable candidates for TMS treatment and better predict treatment response by assessing circuit connectivity and cognitive-behavioral performance at baseline and during early treatment. TRIAL REGISTRATION: ClinicalTrials.gov NCT04663481 , December 5th, 2020, retrospectively registered. The first veteran was enrolled October 30th, 2020.

Entities:  

Keywords:  Biomarker; Cognitive control network; Default mode network (DMN); Dorsolateral prefrontal cortex (DLPFC); Functional magnetic resonance imaging (fMRI); Major depressive disorder (MDD); Neuroimaging; Repetitive Transcranial magnetic stimulation (TMS); Treatment resistant depression (TRD); Veterans

Year:  2021        PMID: 33435926      PMCID: PMC7805238          DOI: 10.1186/s12888-020-03030-z

Source DB:  PubMed          Journal:  BMC Psychiatry        ISSN: 1471-244X            Impact factor:   3.630


  71 in total

1.  Explicit identification and implicit recognition of facial emotions: II. Core domains and relationships with general cognition.

Authors:  Danielle Mathersul; Donna M Palmer; Ruben C Gur; Raquel E Gur; Nick Cooper; Evian Gordon; Leanne M Williams
Journal:  J Clin Exp Neuropsychol       Date:  2008-08-19       Impact factor: 2.475

2.  Analysis of an Oral Paradigm for the Trail Making Test

Authors: 
Journal:  Assessment       Date:  1994-03

3.  Initial changes in neuropsychologists clinical practice during the COVID-19 pandemic: A survey study.

Authors:  David E Marra; James B Hoelzle; Jeremy J Davis; Eben S Schwartz
Journal:  Clin Neuropsychol       Date:  2020-07-29       Impact factor: 3.535

4.  Prospective Validation That Subgenual Connectivity Predicts Antidepressant Efficacy of Transcranial Magnetic Stimulation Sites.

Authors:  Anne Weigand; Andreas Horn; Ruth Caballero; Danielle Cooke; Adam P Stern; Stephan F Taylor; Daniel Press; Alvaro Pascual-Leone; Michael D Fox
Journal:  Biol Psychiatry       Date:  2017-11-10       Impact factor: 13.382

5.  Frontoparietal Activation During Response Inhibition Predicts Remission to Antidepressants in Patients With Major Depression.

Authors:  Anett Gyurak; Brian Patenaude; Mayuresh S Korgaonkar; Stuart M Grieve; Leanne M Williams; Amit Etkin
Journal:  Biol Psychiatry       Date:  2015-03-27       Impact factor: 13.382

6.  Changes in brain connectivity during a sham-controlled, transcranial magnetic stimulation trial for depression.

Authors:  Stephan F Taylor; S Shaun Ho; Tessa Abagis; Mike Angstadt; Daniel F Maixner; Robert C Welsh; Luis Hernandez-Garcia
Journal:  J Affect Disord       Date:  2018-02-21       Impact factor: 4.839

Review 7.  Depressive Rumination, the Default-Mode Network, and the Dark Matter of Clinical Neuroscience.

Authors:  J Paul Hamilton; Madison Farmer; Phoebe Fogelman; Ian H Gotlib
Journal:  Biol Psychiatry       Date:  2015-02-24       Impact factor: 13.382

8.  Statistical improvements in functional magnetic resonance imaging analyses produced by censoring high-motion data points.

Authors:  Joshua S Siegel; Jonathan D Power; Joseph W Dubis; Alecia C Vogel; Jessica A Church; Bradley L Schlaggar; Steven E Petersen
Journal:  Hum Brain Mapp       Date:  2013-07-17       Impact factor: 5.038

Review 9.  Defining biotypes for depression and anxiety based on large-scale circuit dysfunction: a theoretical review of the evidence and future directions for clinical translation.

Authors:  Leanne M Williams
Journal:  Depress Anxiety       Date:  2016-09-21       Impact factor: 6.505

10.  Repetitive transcranial magnetic stimulation (rTMS) for treatment-resistant major depression (TRMD) Veteran patients: study protocol for a randomized controlled trial.

Authors:  Zhibao Mi; Kousick Biswas; J Kaci Fairchild; Anne Davis-Karim; Ciaran S Phibbs; Steven D Forman; Michael Thase; Gerald Georgette; Tamara Beale; David Pittman; Margaret Windy McNerney; Allyson Rosen; Grant D Huang; Mark George; Art Noda; Jerome A Yesavage
Journal:  Trials       Date:  2017-09-02       Impact factor: 2.279

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  5 in total

1.  Prefrontal transcranial magnetic stimulation for depression in US military veterans - A naturalistic cohort study in the veterans health administration.

Authors:  Michelle R Madore; F Andrew Kozel; Leanne M Williams; L Chauncey Green; Mark S George; Paul E Holtzheimer; Jerome A Yesavage; Noah S Philip
Journal:  J Affect Disord       Date:  2021-10-20       Impact factor: 4.839

2.  Mapping Neural Circuit Biotypes to Symptoms and Behavioral Dimensions of Depression and Anxiety.

Authors:  Andrea N Goldstein-Piekarski; Tali M Ball; Zoe Samara; Brooke R Staveland; Arielle S Keller; Scott L Fleming; Katherine A Grisanzio; Bailey Holt-Gosselin; Patrick Stetz; Jun Ma; Leanne M Williams
Journal:  Biol Psychiatry       Date:  2021-07-11       Impact factor: 12.810

3.  Cold Cognition as Predictor of Treatment Response to rTMS; A Retrospective Study on Patients With Unipolar and Bipolar Depression.

Authors:  Reza Rostami; Reza Kazemi; Zahra Nasiri; Somayeh Ataei; Abed L Hadipour; Nematollah Jaafari
Journal:  Front Hum Neurosci       Date:  2022-07-25       Impact factor: 3.473

4.  Sex differences in rTMS treatment response: A deep learning-based EEG investigation.

Authors:  M Adamson; A L Hadipour; C Uyulan; T Erguzel; O Cerezci; R Kazemi; A Phillips; S Seenivasan; S Shah; N Tarhan
Journal:  Brain Behav       Date:  2022-07-25       Impact factor: 3.405

5.  Dynamic Functional Connectivity Predicts Treatment Response to Electroconvulsive Therapy in Major Depressive Disorder.

Authors:  Hossein Dini; Mohammad S E Sendi; Jing Sui; Zening Fu; Randall Espinoza; Katherine L Narr; Shile Qi; Christopher C Abbott; Sanne J H van Rooij; Patricio Riva-Posse; Luis Emilio Bruni; Helen S Mayberg; Vince D Calhoun
Journal:  Front Hum Neurosci       Date:  2021-07-06       Impact factor: 3.169

  5 in total

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