@article{a8fee56d652647f89f6876c0fc0f6d61,
title = "Brain morphometric features predict medication response in youth with bipolar disorder: A prospective randomized clinical trial",
abstract = "Background Identification of treatment-specific predictors of drug therapies for bipolar disorder (BD) is important because only about half of individuals respond to any specific medication. However, medication response in pediatric BD is variable and not well predicted by clinical characteristics. Methods A total of 121 youth with early course BD (acute manic/mixed episode) were prospectively recruited and randomized to 6 weeks of double-blind treatment with quetiapine (n = 71) or lithium (n = 50). Participants completed structural magnetic resonance imaging (MRI) at baseline before treatment and 1 week after treatment initiation, and brain morphometric features were extracted for each individual based on MRI scans. Positive antimanic treatment response at week 6 was defined as an over 50% reduction of Young Mania Rating Scale scores from baseline. Two-stage deep learning prediction model was established to distinguish responders and non-responders based on different feature sets. Results Pre-treatment morphometry and morphometric changes occurring during the first week can both independently predict treatment outcome of quetiapine and lithium with balanced accuracy over 75% (all p < 0.05). Combining brain morphometry at baseline and week 1 allows prediction with the highest balanced accuracy (quetiapine: 83.2% and lithium: 83.5%). Predictions in the quetiapine and lithium group were found to be driven by different morphometric patterns. Conclusions These findings demonstrate that pre-treatment morphometric measures and acute brain morphometric changes can serve as medication response predictors in pediatric BD. Brain morphometric features may provide promising biomarkers for developing biologically-informed treatment outcome prediction and patient stratification tools for BD treatment development. ",
keywords = "Deep learning; bipolar disorder; MRI; cortical thickness; treatment; Young Mania Rating Scale",
author = "Du Lei and Kun Qin and Wenbin Li and Pinaya, {Walter H.L.} and Tallman, {Maxwell J.} and Patino, {L. Rodrigo} and Strawn, {Jeffrey R.} and David Fleck and Klein, {Christina C.} and Su Lui and Qiyong Gong and Adler, {Caleb M.} and Andrea Mechelli and Sweeney, {John A.} and Delbello, {Melissa P.}",
note = "Funding Information: This study was supported by the National Institute of Mental Health (NIMH) Grant (M.P.D., Grant No. 5R01MH080973) and the National Natural Science Foundation of China (Q.G., Grant No. 81621003). Funding Information: Dr Strawn has received research support from the National Institutes of Health (NIMH/NIEHS/NICHD) as well as Allergan, Neuronetics, and Otsuka. He has received material support from and provided consultation to Myriad Genetics and receives royalties from the publication of two texts (Springer) and serves as an author for UpToDate and an Associate Editor for Current Psychiatry. He has spoken in CME presentations for Neuroscience Education Institute and CMEology. Finally, Dr Strawn also has provided consultation to the FDA and Intracellular Therapeutics. Dr Sweeney consults to VeriSci. Dr DelBello and Dr Adler are on the lecture bureau for Otsuka, and Dr Adler is on the lecture bureau for Janssen. Dr Patino and Dr DelBello have received research support from Acadia, Allergan, Janssen, Johnson and Johnson, Lundbeck, Otsuka, Pfizer, Sunovion, and Supernus, and Dr DelBello has provided consultation or advisory board services for Alkermes, Allergan, Assurex, CMEology, Janssen, Johnson and Johnson, Lundbeck, Neuronetics, Otsuka, Pfizer, Sunovion, and Supernus. Dr Adler has received research support from Merck, Forest, and Alkermes, and provided consultation for Janssen. All other authors declare that they have no competing interests. Publisher Copyright: {\textcopyright} The Author(s), 2022. Published by Cambridge University Press.",
year = "2022",
month = apr,
day = "8",
doi = "10.1017/S0033291722000757",
language = "English",
journal = "Psychological Medicine",
issn = "0033-2917",
publisher = "Cambridge University Press",
}
