ArticleProceedings of the National Academy of Sciences of the United States of America2016
Human amygdala engagement moderated by early life stress exposure is a biobehavioral target for predicting recovery on antidepressants.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 61 citations in OpenAlex.
- Predicting treatment outcomes in major depressive disorder using brain magnetic resonance imaging: a meta-analysis.Molecular psychiatry · 2025Pooled it
- Magnetic resonance imaging for individual prediction of treatment response in major depressive disorder: a systematic review and meta-analysis.Translational psychiatry · 2021Pooled it
- Examining fronto-limbic brain and sleep mechanisms of antidepressant effects in cognitive-behavioral therapy for insomnia.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Trial
- Association of Changes in Neural Targets and Dietary Outcomes among Patients with Comorbid Obesity and Depression: Post hoc Analysis of ENGAGE-2 Mechanistic Clinical Trial.The Journal of nutrition · 2023Trial
- Trial
- The ENGAGE-2 study: Engaging self-regulation targets to understand the mechanisms of behavior change and improve mood and weight outcomes in a randomized controlled trial (Phase 2).Contemporary clinical trials · 2020Trial
- Connectivity of the Cognitive Control Network During Response Inhibition as a Predictive and Response Biomarker in Major Depression: Evidence From a Randomized Clinical Trial.Biological psychiatry · 2020Trial
- Intrinsic functional connectivity predicts remission on antidepressants: a randomized controlled trial to identify clinically applicable imaging biomarkers.Translational psychiatry · 2018Trial
- Antidepressant Outcomes Predicted by Genetic Variation in Corticotropin-Releasing Hormone Binding Protein.The American journal of psychiatry · 2018Trial
- Emotional scars: limbic brain processing alterations in adults with childhood abuse across mental health disorders.Molecular psychiatry · 2026Article
- Insights from a methylome-wide association study of antidepressant exposure.Nature communications · 2025Article
- Personalized brain circuit scores identify clinically distinct biotypes in depression and anxiety.Nature medicine · 2024Article
- Recent developments and future avenues for human corticospinal neuroimaging.Frontiers in human neuroscience · 2024Review
- Affective neural circuits and inflammatory markers linked to depression and anxiety symptoms in patients with comorbid obesity.Journal of psychiatric research · 2023Article
- Computational approaches to treatment response prediction in major depression using brain activity and behavioral data: A systematic review.Network neuroscience (Cambridge, Mass.) · 2022Article
- The promise of machine learning in predicting treatment outcomes in psychiatry.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2021Article
- Article
- Precision Psychiatry: Biomarker-Guided Tailored Therapy for Effective Treatment and Prevention in Major Depression.Advances in experimental medicine and biology · 2021Review
- Variation in early life maternal care predicts later long range frontal cortex synapse development in mice.Developmental cognitive neuroscience · 2020Article
- Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol.Frontiers in psychiatry · 2020Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
Amygdala circuitry and early life stress (ELS) are both strongly and independently implicated in the neurobiology of depression. Importantly, animal models have revealed that the contribution of ELS to the development and maintenance of depression is likely a consequence of structural and physiological changes in amygdala circuitry in response to stress hormones. Despite these mechanistic foundations, amygdala engagement and ELS have not been investigated as biobehavioral targets for predicting functional remission in translational human studies of depression. Addressing this question, we integrated human neuroimaging and measurement of ELS within a controlled trial of antidepressant outcomes. Here we demonstrate that the interaction between amygdala activation engaged by emotional stimuli and ELS predicts functional remission on antidepressants with a greater than 80% cross-validated accuracy. Our model suggests that in depressed people with high ELS, the likelihood of remission is highest with greater amygdala reactivity to socially rewarding stimuli, whereas for those with low-ELS exposure, remission is associated with lower amygdala reactivity to both rewarding and threat-related stimuli. This full model predicted functional remission over and above the contribution of demographics, symptom severity, ELS, and amygdala reactivity alone. These findings identify a human target for elucidating the mechanisms of antidepressant functional remission and offer a target for developing novel therapeutics. The results also offer a proof-of-concept for using neuroimaging as a target for guiding neuroscience-informed intervention decisions at the level of the individual person.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.