Plasma Cell–Free Mitochondrial DNA as a Marker of Geriatric Syndromes in Older Adults With HIV
Bibliographic record
Abstract
BACKGROUND: Older people with HIV experience more comorbidities and geriatric syndromes than their HIV-negative peers, perhaps due to residual inflammation despite suppressive antiretroviral therapy. Cell-free mitochondrial DNA (cfmtDNA) released during necrosis-mediated cell death potentially acts as both mediator and marker of inflammatory dysregulation. Thus, we evaluated plasma cfmtDNA as a potential biomarker of geriatric syndromes. METHODS: Participants underwent the Montreal Cognitive Assessment (MoCA), frailty testing, and measurement of plasma cfmtDNA by qPCR and inflammatory markers including C-reactive protein, interleukin-6 (IL-6), interferon gamma, and tumor necrosis factor alpha in this cross-sectional study. RESULTS: Across 155 participants, the median age was 60 years (Q1, Q3: 56, 64), one-third were female, and 92% had HIV-1 viral load <200 copies/mL. The median MoCA score was 24 (21, 27). The plasma cfmtDNA level was higher in those with cognitive impairment (MoCA <23) ( P = 0.02 by the t test) and remained significantly associated with cognitive impairment in a multivariable logistic regression model controlling for age, sex, race, CD4 T-cell nadir, HIV-1 viremia, and depression. Two-thirds of participants met the criteria for a prefrail or frail state; higher plasma cfmtDNA was associated with slow walk and exhaustion but not overall frailty state. Cognitive dysfunction was not associated with C-reactive protein, IL-6, interferon gamma, or tumor necrosis factor alpha, and frailty state was only associated with IL-6. CONCLUSIONS: Plasma cfmtDNA may have a role as a novel biomarker of cognitive dysfunction and key components of frailty. Longitudinal investigation of cfmtDNA is warranted to assess its utility as a biomarker of geriatric syndromes in older people with HIV.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".