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Record W7118064860 · doi:10.1093/geroni/igaf122.1566

sTNFR1 is Associated with Depressive Symptoms in Community-Dwelling Older Adults: A Logistic Regression Analysis

2025· article· en· W7118064860 on OpenAlexaboutno aff
Russell Calderon, Nada Lukkahatai, Jing Huang, Melissa Hladek, Junxin Li

Bibliographic record

VenueInnovation in Aging · 2025
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)Logistic regressionPsychological interventionDementiaBiomarkerCognitionDemographicsDepressive symptoms

Abstract

fetched live from OpenAlex

Abstract Inflammation has been implicated in the pathophysiology of depression, but specific inflammatory pathways may differentially contribute to depressive symptoms in older adults. This study examines the relationship between inflammatory biomarkers and depression in 91 community-dwelling older adults without dementia [Montreal Cognitive Assessment ≥17] using baseline data from a randomized clinical trial (NCT03959202). Depression was assessed using the Geriatric Depression Scale, with scores >5 indicating depression. Plasma-derived inflammatory biomarkers, including C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and soluble TNF receptor-1 (sTNFR1), were Z-score normalized. A logistic regression model examined associations between biomarkers and depression, adjusting for age, sex, body mass index, and mild cognitive impairment (MCI) status. Participants were 70.2±6.2 years old, 80.2% females, 19.8% with MCI. Overall, 20.8% of participants (n = 19) were classified as having depression. In adjusted analyses, sTNFR1—a key mediator for TNF signaling—was significantly associated with depression (OR = 2.89, 95% CI [1.20, 5.60], p = 0.009), indicating that individuals with higher sTNFR1 levels had nearly three times the odds of depression. However, CRP, IL-6, and TNF-α were not significantly related to depression. These findings support sTNFR1 as a potential inflammatory biomarker linked to late-life depression, independent of demographics and cognitive status. Clinically, measuring sTNFR1 levels in routine visits may help in identifying older adults with risk for depression and informing early intervention strategies. Given its role in TNF-mediated inflammation, sTNFR1 warrants investigation as a potential target for interventions addressing late-life depression. Larger longitudinal studies should further elucidate the causal role of TNF signaling pathways in geriatric depression.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.026
GPT teacher head0.305
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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