TY - JOUR
T1 - Transcranial Magnetic Stimulation Indices of Cortical Excitability Enhance the Prediction of Response to Pharmacotherapy in Late-Life Depression
AU - Lissemore, Jennifer I.
AU - Mulsant, Benoit H.
AU - Bonner, Anthony J.
AU - Butters, Meryl A.
AU - Chen, Robert
AU - Downar, Jonathan
AU - Karp, Jordan F.
AU - Lenze, Eric J.
AU - Rajji, Tarek K.
AU - Reynolds, Charles F.
AU - Zomorrodi, Reza
AU - Daskalakis, Zafiris J.
AU - Blumberger, Daniel M.
N1 - Funding Information:
This study was funded in part by a Brain and Behaviour Research Foundation New Investigator Award (Grant No. 17806 [to DMB]), the Canadian Institutes of Health Research (Grant No. MOP-123455 [to DMB]), and the National Institutes of Health (Grant Nos. R01MH083643 [to BMH] and R34MH101365 [to BMH]).
Funding Information:
This study was funded in part by a Brain and Behaviour Research Foundation New Investigator Award (Grant No. 17806 [to DMB]), the Canadian Institutes of Health Research (Grant No. MOP-123455 [to DMB]), and the National Institutes of Health (Grant Nos. R01MH083643 [to BMH] and R34MH101365 [to BMH]). We acknowledge Yu Qi Zhang, Shang Wang, Hsin-Yu Lo, and Weicheng Cao for their contributions to the feature selection and machine learning methods. We would also like to acknowledge the Temerty Centre and the Canada Foundation for Innovation for providing transcranial magnetic stimulation equipment. BHM currently receives research funding from Brain Canada, the Centre for Addiction and Mental Health (CAMH) Foundation, Patient-Centered Outcomes Research Institute (PCORI), and the U.S. National Institute of Health (NIH). During the last 5 years, he also received research funding from the Canadian Institutes of Health Research (CIHR) and support in kind from Capital Solution Design LLC (software used in a study funded by CAMH Foundation), HAPPYneuron (software used in a study funded by Brain Canada), Bristol-Myers Squibb (medications for a NIH-funded clinical trial), Eli Lilly (medications for a NIH-funded clinical trial), and Pfizer (medications for a NIH-funded clinical trial). He directly owns stocks of General Electric (<$5000). RC has received research support from a CIHR Foundation Grant, Catherine Manson Chair in Movement Disorders, Dystonia Medical Research Foundation, and Weston Brain Institute. He received honoraria from GE Healthcare, Merz, and Allergan. JD has received research support from the Arrell Family Foundation, Brain Canada, the Buchan Family Foundation, the Canadian Biomarker Integration Network in Depression, the CIHR, the Klarman Family Foundation, National Institutes of Mental Health, the Ontario Brain Institute, and the Weston Family Foundation; he has received travel stipends from Lundbeck and ANT Neuro; he has served as an adviser for BrainCheck, Restorative Brain Clinics, and TMS Neuro Solutions. JFK received medication supplies from Indivior to support this investigator-initiated trial. He has also received medication supplies from Pfizer for investigator-initiated work. JFK receives research funding from NIH and PCORI. EJL reports research funding (current/past) from Janssen, Alkermes, Acadia, Takeda, Lundbeck, Barnes Jewish Foundation, PCORI, and Taylor Family Institute for Innovative Psychiatric Research. TKR has received research support from Brain Canada, Brain and Behavior Research Foundation, BrightFocus Foundation, Canada Foundation for Innovation, Canada Research Chair, CIHR, Centre for Aging and Brain Health Innovation, National Institutes of Health, Ontario Ministry of Health and Long-Term Care, Ontario Ministry of Research and Innovation, and the Weston Brain Institute. CFR has received research support from the NIH, PCORI, the Center for Medicare and Medicaid Services, the American Foundation for Suicide Prevention, the Brain and Behavior Research Foundation, and the Commonwealth of Pennsylvania. Bristol Meyers Squib and Pfizer have provided pharmaceutical supplies for his NIH sponsored research. In the last 5 years, ZJD has received research and equipment in-kind support for an investigator-initiated study through Brainsway Inc. and Magventure Inc. His work was supported by the Ontario Mental Health Foundation, the CIHR, the National Institutes of Mental Health, and the Temerty Family and Grant Family and through the CAMH Foundation and the Campbell Institute. DMB has received research support from CIHR, NIH, Brain Canada, and the Temerty Family through the CAMH Foundation and the Campbell Research Institute. He receives research support and in-kind equipment support for an investigator-initiated study from Brainsway Ltd. and he is the site principal investigator for three sponsor-initiated studies for Brainsway Ltd. He also receives in-kind equipment support from Magventure for an investigator-initiated study. He receives medication supplies for an investigator-initiated trial from Indivior. All other authors report no biomedical financial interests or potential conflicts of interest. ClinicalTrials.gov: Incomplete Response in Late-Life Depression: Getting to Remission; https://clinicaltrials.gov/ct2/show/NCT00892047 https://clinicaltrials.gov/ct2/show/NCT02263248; NCT00892047 and NCT02263248.
Publisher Copyright:
© 2021 Society of Biological Psychiatry
PY - 2022/3
Y1 - 2022/3
N2 - Background: Older adults with late-life depression (LLD) often experience incomplete or lack of response to first-line pharmacotherapy. The treatment of LLD could be improved using objective biological measures to predict response. Transcranial magnetic stimulation (TMS) can be used to measure cortical excitability, inhibition, and plasticity, which have been implicated in LLD pathophysiology and associated with brain stimulation treatment outcomes in younger adults with depression. TMS measures have not yet been investigated as predictors of treatment outcomes in LLD or pharmacotherapy outcomes in adults of any age with depression. Methods: We assessed whether pretreatment single-pulse and paired-pulse TMS measures, combined with clinical and demographic measures, predict venlafaxine treatment response in 76 outpatients with LLD. We compared the predictive performance of machine learning models including or excluding TMS predictors. Results: Two single-pulse TMS measures predicted venlafaxine response: cortical excitability (neuronal membrane excitability) and the variability of cortical excitability (dynamic fluctuations in excitability levels). In cross-validation, models using a combination of these TMS predictors, clinical markers of treatment resistance, and age classified patients with 73% ± 11% balanced accuracy (average correct classification rate of responders and nonresponders; permutation testing, p < .005); these models significantly outperformed (corrected t test, p = .025) models using clinical and demographic predictors alone (60% ± 10% balanced accuracy). Conclusions: These preliminary findings suggest that single-pulse TMS measures of cortical excitability may be useful predictors of response to pharmacotherapy in LLD. Future studies are needed to confirm these findings and determine whether combining TMS predictors with other biomarkers further improves the accuracy of predicting LLD treatment outcome.
AB - Background: Older adults with late-life depression (LLD) often experience incomplete or lack of response to first-line pharmacotherapy. The treatment of LLD could be improved using objective biological measures to predict response. Transcranial magnetic stimulation (TMS) can be used to measure cortical excitability, inhibition, and plasticity, which have been implicated in LLD pathophysiology and associated with brain stimulation treatment outcomes in younger adults with depression. TMS measures have not yet been investigated as predictors of treatment outcomes in LLD or pharmacotherapy outcomes in adults of any age with depression. Methods: We assessed whether pretreatment single-pulse and paired-pulse TMS measures, combined with clinical and demographic measures, predict venlafaxine treatment response in 76 outpatients with LLD. We compared the predictive performance of machine learning models including or excluding TMS predictors. Results: Two single-pulse TMS measures predicted venlafaxine response: cortical excitability (neuronal membrane excitability) and the variability of cortical excitability (dynamic fluctuations in excitability levels). In cross-validation, models using a combination of these TMS predictors, clinical markers of treatment resistance, and age classified patients with 73% ± 11% balanced accuracy (average correct classification rate of responders and nonresponders; permutation testing, p < .005); these models significantly outperformed (corrected t test, p = .025) models using clinical and demographic predictors alone (60% ± 10% balanced accuracy). Conclusions: These preliminary findings suggest that single-pulse TMS measures of cortical excitability may be useful predictors of response to pharmacotherapy in LLD. Future studies are needed to confirm these findings and determine whether combining TMS predictors with other biomarkers further improves the accuracy of predicting LLD treatment outcome.
KW - Cortical excitability
KW - Genetic algorithm
KW - Geriatric depression
KW - Late-life depression
KW - Neurophysiology
KW - Predictive biomarker
KW - Support vector machine
KW - TMS
UR - http://www.scopus.com/inward/record.url?scp=85125528266&partnerID=8YFLogxK
U2 - 10.1016/j.bpsc.2021.07.005
DO - 10.1016/j.bpsc.2021.07.005
M3 - Article
C2 - 34311121
AN - SCOPUS:85125528266
SN - 2451-9022
VL - 7
SP - 265
EP - 275
JO - Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
JF - Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
IS - 3
ER -