Host iron redistribution as a risk factor for incident tuberculosis in HIV infection: an 11-year retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Identifying people at higher risk of developing tuberculosis with human immunodeficiency virus (HIV) infection may improve clinical management of co-infections. Iron influences tuberculosis (TB) pathogenesis, but understanding the exact mechanisms of how and timing of when iron is involved remains challenging since biological samples are rarely available from the disease susceptibility period due to the difficulty in predicting in who and when, if ever, TB will develop. The objective of this research was to determine how host iron status measured at HIV diagnosis and genotypes related to host iron metabolism were associated with incident TB. METHODS: Archived clinical data, plasma and DNA were analyzed from 1139 adult participants in a large HIV-1, HIV-2 and dual seroprevalent cohort based at the Medical Research Council Laboratories in The Gambia. Incident pulmonary and/or extrapulmonary TB diagnoses a minimum of 28 days after HIV diagnosis were independently re-confirmed using available evidence (n=152). Multiple host iron status biomarkers, Haptoglobin and solute carrier family 11, member 1 (SLC11A1) genotypes were modeled to characterize how indicators of host iron metabolism were associated with TB susceptibility. RESULTS: Hemoglobin (incidence rate ratio, IRR=0.88, 95% CI=0.79-0.98), plasma transferrin (IRR=0.53, 0.33-0.84) and ferritin (IRR=1.26, 1.05-1.51) were significantly associated with TB after adjusting for TB susceptibility factors. While genotype associations were not statistically significant, SLC11A1 associations replicated similar directions as reported in HIV-seronegative meta-analyses. CONCLUSIONS: Evidence of host iron redistribution at HIV diagnosis was associated with incident TB, and genetic influences on iron homeostasis may be involved. Low hemoglobin was associated with subsequent diagnosis of TB, but when considered in combination with additional iron status biomarkers, the collective findings point to a mechanism whereby anemia and iron redistribution are likely due to viral and/or bacteria-driven processes and the host immune response to infection. As a result, iron supplementation may not be efficacious or safe under these circumstances. Clinical and nutritional management of HIV and Mycobacterium tuberculosis co-infected individuals, especially in regions where food insecurity and malnutrition co-exist, may be further improved when the iron-related TB risk factors identified here are better understood and managed to favor host rather than pathogen outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".