A transcriptomic signature of late‐life depression
Bibliographic record
Abstract
Abstract Background Late‐onset Alzheimer’s disease (AD) is commonly accompanied by symptoms of depression. While genes associated with pathological AD diagnosis and mid‐life depression have been identified, the transcriptomic signature of late‐life depression has not been described. We hypothesized that neocortical gene expression would be associated with symptoms of late‐life depression proximal to death, independent of pathologic AD diagnosis and medication status. Method Bulk tissue RNA sequencing data from frontal cortex of 1,001 elderly brain donors were analyzed (mean age at death: 89.7yrs [range: 67‐108]). All donors had genotype, demographic, and clinical assessments within one year prior to autopsy, as well as detailed postmortem neuropathological characterization. Differential expression analysis was performed with robust linear modeling including technical and demographic covariates, cell type proportions, educational attainment, APOE e4 genotype, and medication status for AD‐ and depression‐prescribed drugs. We then included main effects of depressive symptom burden proximal to death (CESD‐sum) and pathologic diagnosis of AD (NIA‐Reagan criteria). Result After false discovery rate correction (FDR q<0.05), only one gene, Prader Willi/Angelman region RNA1 (PWAR1), was associated with depressive symptoms (t=5.2, q=0.005); greater PWAR1 abundance was linked to higher symptom burden. At q<0.1, 14 genes showed association. Strikingly, a majority of these genes (e.g. CTDSPL2, ACR2B‐AS1, ADGRE2, MRM1, IRF8, COL19A1) have been previously implicated in unipolar depression or bipolar disorder. Gene Set Enrichment Analysis revealed upregulation of processes related to energy metabolism (top: “oxidative phosphorylation”, p=2.1x10‐8) and downregulation of DNA modifying processes (top: “DNA conformation change”, p=2.0x10‐7), among others. Results were not changed when controlling for smoking and alcohol consumption, and no significant associations were observed for depression medication status (top q>0.23). Conclusion Here we describe a cortical transcriptomic signature of late‐life depressive symptoms. Among our top signals are genes with known links to mid‐life depression, as well as biological processes relevant to energy metabolism, synaptic plasticity, DNA modification, antigen presentation, and response to pH. Our work provides a depression‐specific expression signature for elderly frontal cortex and lays the foundation for investigation of specific mechanisms toward precision therapeutics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".