Elevated Cell-Free Mitochondrial DNA in Filtered Plasma Is Associated With HIV Infection and Inflammation
Bibliographic record
Abstract
BACKGROUND: Increased cell-free DNA levels are associated with poor health outcomes, and cell-free mitochondrial DNA (cf-mtDNA) has proinflammatory properties. Given that HIV infection is associated with chronic inflammation, we investigated the relationship between cf-mtDNA and proinflammatory cytokine interleukin-6 (IL-6) in the context of HIV infection. We also optimized separation of cell-free plasma from blood. SETTING: In this retrospective cross-sectional study, we collected blood, demographic information, and clinical data from 99 HIV-infected and 103 HIV-uninfected adults and children enrolled in the Children and Women: AntiRetrovirals and Markers of Aging pan-Canadian (CARMA) cohort. METHODS: Plasma was separated from blood by 14,000g centrifugation followed by 0.45-μm filtration to remove cells and platelets. Cf-mtDNA and cell-free nuclear DNA were quantified simultaneously via monochrome, multiplex, quantitative polymerase chain reaction. IL-6 was measured using enzyme-linked immunosorbent assay. RESULTS: Higher speed centrifugation and filtration was necessary to isolate truly cell-free plasma. Higher cf-mtDNA levels were univariately associated with HIV infection, elevated IL-6 levels, younger age, higher white blood cell count, and higher cell-free nuclear DNA levels but not blood mtDNA content or HIV viral load. In a multivariable model, HIV infection (P < 0.001), elevated IL-6 (P = 0.021), younger age (P < 0.001), and higher blood nDNA levels (P = 0.007) were independently associated with higher cf-mtDNA. CONCLUSIONS: People living with HIV have higher levels of circulating cf-mtDNA than their uninfected peers. Increased levels of inflammatory marker IL-6 are associated with elevated cf-mtDNA, independent of the effect of HIV infection. Higher cf-mtDNA levels and white blood cell count in younger people may reflect higher cell turnover in that population.
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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 | 0.002 |
| 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".