Immune activation and chronic inflammation
Bibliographic record
Abstract
ABSTRACT: HIV infection has become a chronic disease, with a lower mortality, but a consequent increase in age-related noninfectious comorbidities. Metabolic disorders have been linked to the effect of cART as well to the effects of immune activation and chronic inflammation. Whereas it is known that aging is intrinsically associated with hyperinflammation and immune system deterioration, the relative impact of chronic HIV infection on such inflammatory and immune activation has not yet been studied focusing on an elderly HIV-infected population.The objectives of the study were to assess 29 blood markers of immune activation and inflammation using an ultrasensitive technique, in HIV-infected patients aged ≥75 years with no or 1 comorbidity (among hypertension, renal disease, neoplasia, diabetes mellitus, cardiovascular disease, stroke, dyslipidemia, and osteoporosis), in comparison with age-adjusted HIV-uninfected individuals to identify whether biomarkers were associated with comorbidities. Wilcoxon nonparametric tests were used to compare the levels of each marker between control and HIV groups; logistic regression to identify biomarkers associated to comorbidity in the HIV group and principal component analysis (PCA) to determine clusters associated with a group or a specific comorbidity.A total of 111 HIV-infected subjects were included from the Dat'AIDS cohort and compared to 63 HIV-uninfected controls. In the HIV-infected group, 4 biomarkers were associated with the risk of developing a comorbidity: monocyte chemoattractant protein-1 (MCP-1), neurofilament light chain (NF-L), neopterin, and soluble CD14. Six biomarkers (interleukin [IL]-1B, IL-7, IL-18, neopterin, sCD14, and fatty acid-binding protein) were significantly higher in the HIV-infected group compared to the control group, 11 biomarkers (myeloperoxydase, interleukin-1 receptor antagonist, tumor necrosis factor receptor 1, interferon-gamma, MCP-1, tumor necrosis factor receptor 2, IL-22, ultra sensitivity C-reactive protein, fibrinogen, IL-6, and NF-L) were lower. Despite those differences, PCA to determine clusters associated with a group or a specific comorbidity did not reveal clustering nor between healthy control and HIV-infected patients neither between the presence of comorbidity within HIV-infected group.In this highly selected geriatric HIV population, HIV infection does not seem to have an additional impact on age-related inflammation and immune disorder. Close monitoring could have led to optimize prevention and treatment of comorbidities, and have limited both immune activation and inflammation in the aging HIV population.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".