Optimizing Antidepressant Efficacy: Generalizable Multimodal Neuroimaging Biomarkers for Prediction of Treatment Response.

Autor:	Tong X; Department of Bioengineering, Lehigh University, Bethlehem, PA, USA., Zhao K; Department of Bioengineering, Lehigh University, Bethlehem, PA, USA., Fonzo GA; Center for Psychedelic Research and Therapy, Department of Psychiatry and Behavioral Sciences, Dell Medical School, The University of Texas at Austin, Austin, TX, USA., Xie H; Center for Neuroscience Research, Children's National Hospital, Washington, DC, USA., Carlisle NB; Department of Psychology, Lehigh University, Bethlehem, PA, USA., Keller CJ; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.; 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., Oathes DJ; Center for Brain Imaging and Stimulation, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.; Center for Neuromodulation in Depression and Stress, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA., Sheline Y; Center for Neuromodulation in Depression and Stress, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA., Nemeroff CB; Center for Psychedelic Research and Therapy, Department of Psychiatry and Behavioral Sciences, Dell Medical School, The University of Texas at Austin, Austin, TX, USA., Trivedi M; The University of Texas Southwestern Medical Center, Department of Psychiatry, Center for Depression Research and Clinical Care, Dallas, TX, USA., Etkin A; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.; Alto Neuroscience, Inc., Los Altos, CA, USA., Zhang Y; Department of Bioengineering, Lehigh University, Bethlehem, PA, USA.; Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA, USA.
Jazyk:	angličtina
Zdroj:	MedRxiv : the preprint server for health sciences [medRxiv] 2024 Oct 08. Date of Electronic Publication: 2024 Oct 08.
DOI:	10.1101/2024.04.11.24305583
Abstrakt:	Major depressive disorder (MDD) is a common and often severe condition that profoundly diminishes quality of life for individuals across ages and demographic groups. Unfortunately, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates in a substantial number of patients. The development of effective therapies for MDD is hindered by the insufficiently understood heterogeneity within the disorder and its elusive underlying mechanisms. To address these challenges, we present a target-oriented multimodal fusion framework that robustly predicts antidepressant response by integrating structural and functional connectivity data (sertraline: R 2 = 0.31; placebo: R 2 = 0.22). Remarkably, the sertraline response biomarker is further tested on an independent escitalopram-medicated cohort of MDD patients, validating its generalizability (p = 0.01) and suggesting an overlap of psychopharmacological mechanisms across selective serotonin reuptake inhibitors. Through the model, we identify multimodal neuroimaging biomarkers of antidepressant response and observe that sertraline and placebo show distinct predictive patterns. We further decompose the overall predictive patterns into constitutive network constellations with generalizable structural-functional co-variation, which exhibit treatment-specific association with personality traits and behavioral/cognitive task performance. Our innovative and interpretable multimodal framework provides novel and reliable insights into the intricate neuropsychopharmacology of antidepressant treatment, paving the way for advances in precision medicine and development of more targeted antidepressant therapeutics. Competing Interests: Financial Disclosures G.A.F. received monetary compensation for consulting work for SynapseBio AI and owns equity in Alto Neuroscience. A.E. reports salary and equity from Alto Neuroscience and equity in Akili Interactive and Mindstrong Health. C.J.K reports equity from Alto Neuroscience. The remaining authors declare no competing interests. C.N. is a consultant for ANeuroTech (division Anima BV), Janssen Research and Development, BioXcel Therapeutics, Engrail Therapeutics, Clexio Biosciences LTD, EmbarkNeuro, Galen Mental Health LLC, Goodcap Pharmaceuticals, ITI Inc, LUCY Scientific Discovery, Relmada Therapeutics, Sage Therapeutics, Senseye Inc, Precisement Health, Autobahn Therapeutics Inc, EMA Wellness, Skyland Trails, Denovo Biopharma, and the Brain & Behavior Research Foundation. C.N. owns the following patents: Method and devices for transdermal delivery of lithium (US 6,375,990B1), Method of assessing antidepressant drug therapy via transport inhibition of monoamine neurotransmitters by ex vivo assay (US 7,148,027B2), Compounds, Compositions, Methods of Synthesis, and Methods of Treatment (CRF Receptor Binding Ligand) (US 8,551, 996 B2). C.N. owns stock in Corcept Therapeutics Company, EMA Wellness, Precisement Health, Relmada Therapeutics, Signant Health, Galen Mental Health LLC, and Senseye Inc. The remaining authors have no conflicts of interest to declare.
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu