Latent Profile Analysis of Childhood Maltreatment and Neural Markers in Depression
Bibliographic record
Abstract
Importance: The limited success of major depressive disorder (MDD) treatments is largely due to the disorder's etiological and pathophysiological heterogeneity. Addressing this heterogeneity is essential for developing accurate prognostic models and personalized treatment strategies. Objective: To characterize MDD heterogeneity using a mechanism-first latent profile analysis based on environmental, neurostructural, and neurofunctional indicators, and to validate profiles via associations with MDD course, severity, and antidepressant treatment remission. Design, Setting, and Participants: This cross-sectional study used data from 2 Canadian Biomarker Integration Network in Depression (CAN-BIND) studies: CAN-BIND-1 (2014-2017), a multicenter outpatient antidepressant trial, and CAN-BIND-4 (2015-2018), a single-site study. Data analyses were completed from February to September 2024. Participants meeting Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) diagnostic criteria for unipolar depression were included. Individuals with lifetime bipolar, psychotic, substance use disorder, acute suicidality, and neurological disorders were excluded. Exposure: In CAN-BIND-1, patients received 10 to 20 mg of escitalopram daily; nonresponders at 8 weeks received aripiprazole augmentation for 8 additional weeks. CAN-BIND-4 was observational. Main Outcomes and Measures: Primary outcomes were latent profiles derived from childhood maltreatment (CM; semistructured interview); hippocampal, amygdala, thalamus structural volume (SV); anterior cingulate thickness (image segmentation); and DMN functional connectivity (average time series of the blood oxygen level-dependent signal). Secondary outcomes included associations with MDD course, symptom severity (including anhedonia, measured using Montgomery-Åsberg Depression Rating Scale), and remission rates. Results: In a sample of 309 adults with clinical depression (mean [SD] age, 33.81 [13.17] years; 206 female [66.67%]), 4 profiles emerged: (1) low CM and high SV, (2) low CM and low SV, (3) high CM and high SV, and (4) high CM and low SV with default mode network hypoconnectivity. Profile 4 was associated with the worst course, with the highest morbidity (mean number of years of morbidity, 19.91 years; 95% CI, 12.45-20.69 years), anhedonia (mean, 10.72; 95% CI, 9.74-11.70), and lowest remission rate (mean, 21.5%; 95% CI, 17.6%-23.5%) at week 16. Profile 3 had the highest remission rates (mean, 90.9%; 95% CI, 63.4%-118.0%). Conclusions and Relevance: In this cross-sectional study of 309 adults with depression, 4 latent profiles were identified. Default mode network hypoconnectivity defined profile 4, supporting its role as a key neural indicator of antidepressant response. CM was associated with both the highest and lowest remission rates, indicating it does not uniformly project negative outcomes and suggesting that neurobiological resilience in the context of childhood trauma may have contributed to more favorable clinical outcomes; further research is needed to refine clinical applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".