A Transcriptomic Signature of Depressive Symptoms in Late Life
Why this work is in the frame
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Bibliographic record
Abstract
Depressive symptoms in late-life can impair daily function and accompany cognitive decline. However, the molecular mechanisms underlying these changes in the brain remain poorly understood. Differential expression analysis was performed on bulk tissue RNA sequencing data generated from dorsolateral prefrontal cortex samples of elderly participants in the Religious Orders Study and Memory and Aging Project (ROS/MAP: n=998, age at death mean=89.6). Bulk tissue RNA sequencing was analyzed against depressive symptoms measured prior to death, controlling for Alzheimer’s disease (AD) neuropathology, medication status, and lifestyle factors. Sex-stratified models were also tested. Increased abundance of the Prader-Willi syndrome-associated gene, PWAR1 (corrected p =5.47x10 -3 ) and CTDSPL2 (corrected p =0.03) were associated with a higher burden of depressive symptoms in the combined sample. An additional 14 genes showed suggestive associations, including several with known links to neuropsychiatric illness (e.g. ACVR2B-AS1, COL19A1) . Functional enrichment analysis revealed downregulation of aerobic metabolism and upregulation of both amino acid catabolism and DNA modification processes. Differential expression signatures were poorly correlated between males and females (Pearson r=0.12; 95%CI = [0.10,0.13]), and only the male group showed independently significant differential expression. Little overlap was found with previously published analyses of major depressive disorder. Building upon recently-published single-nucleus profiling, we present the largest-ever study of transcriptomic correlates of depressive symptoms in late-life, revealing new insights into sex-specific regulators. PWAR1 and CTDSPL2 were identified as putative markers of late-life depression in dorsolateral prefrontal cortex and warrant further study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| 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 it