Plasma metabolomics identifies lipid abnormalities linked to markers of inflammation, microbial translocation, and hepatic function in HIV patients receiving protease inhibitors
Bibliographic record
Abstract
BACKGROUND: Metabolic abnormalities are common in HIV-infected individuals on antiretroviral therapy (ART), but the biochemical details and underlying mechanisms of these disorders have not been defined. METHODS: Untargeted metabolomic profiling of plasma was performed for 32 HIV patients with low nadir CD4 counts (<300 cells/ul) on protease inhibitor (PI)-based ART and 20 healthy controls using liquid or gas chromatography and mass spectrometry. Effects of Hepatitis C (HCV) co-infection and relationships between altered lipid metabolites and markers of inflammation, microbial translocation, and hepatic function were examined. Unsupervised hierarchical clustering, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), Random forest, pathway mapping, and metabolite set enrichment analysis (MSEA) were performed using dChip, Metaboanalyst, and MSEA software. RESULTS: A 35-metabolite signature mapping to lipid, amino acid, and nucleotide metabolism distinguished HIV patients with advanced disease on PI-based ART from controls regardless of HCV serostatus (p<0.05, false discovery rate (FDR)<0.1). Many altered lipids, including bile acids, sulfated steroids, polyunsaturated fatty acids, and eicosanoids, were ligands of nuclear receptors that regulate metabolism and inflammation. Distinct clusters of altered lipids correlated with markers of inflammation (interferon-α and interleukin-6), microbial translocation (lipopolysaccharide (LPS) and LPS-binding protein), and hepatic function (bilirubin) (p<0.05). Lipid alterations showed substantial overlap with those reported in non-alcoholic fatty liver disease (NALFD). Increased bile acids were associated with noninvasive markers of hepatic fibrosis (FIB-4, APRI, and YKL-40) and correlated with acylcarnitines, a marker of mitochondrial dysfunction. CONCLUSIONS: Lipid alterations in HIV patients receiving PI-based ART are linked to markers of inflammation, microbial translocation, and hepatic function, suggesting that therapeutic strategies attenuating dysregulated innate immune activation and hepatic dysfunction may be beneficial for prevention and treatment of metabolic disorders in HIV patients.
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 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 | 0.001 |
| 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 | 0.001 | 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".