ArticlePloS one2016
Plasma Metabolomics Biosignature According to HIV Stage of Infection, Pace of Disease Progression, Viremia Level and Immunological Response to Treatment.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 30 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it, 50 citations in OpenAlex.
- Pooled it
- Integrative Multi-Omics Reveals Serum Markers of Tuberculosis in Advanced HIV.Frontiers in immunology · 2021Trial
- Immune non-response despite effective antiretroviral therapy in people living with HIV: A review of potential mechanisms, biomarkers and therapeutic approaches.HIV medicine · 2026Review
- Diagnostic value of miR-155, miR-29a and lncRNAs (NEAT1, GAS5 and COX2) in HIV, tuberculosis, and HIV/TB co-infection.Scientific reports · 2026Article
- Mechanisms of HIV-immunologic non-responses and research trends based on gut microbiota.Frontiers in immunology · 2024Review
- The metabolic consequences of HIV/TB co-infection.BMC infectious diseases · 2023Article
- Elevated glutamate impedes anti-HIV-1 CD8 + T cell responses in HIV-1-infected individuals on antiretroviral therapy.Communications biology · 2023Article
- Biological Aging in People Living with HIV on Successful Antiretroviral Therapy: Do They Age Faster?Current HIV/AIDS reports · 2023Review
- Multi-omics in HIV: searching insights to understand immunological non-response in PLHIV.Frontiers in immunology · 2023Review
- Altered lipid metabolites accelerate early dysfunction of T cells in HIV-infected rapid progressors by impairing mitochondrial function.Frontiers in immunology · 2023Article
- Altered plasma metabolites and inflammatory networks in HIV-1 infected patients with different immunological responses after long-term antiretroviral therapy.Frontiers in immunology · 2023Article
- Gut dysbiosis and inflammatory blood markers precede HIV with limited changes after early seroconversion.EBioMedicine · 2022Article
- Altered Expression of ACE2 and Co-receptors of SARS-CoV-2 in the Gut Mucosa of the SIV Model of HIV/AIDS.Frontiers in microbiology · 2022Article
- HLA-B*13, B*35 and B*39 Alleles Are Closely Associated With the Lack of Response to ART in HIV Infection: A Cohort Study in a Population of Northern Brazil.Frontiers in immunology · 2022Article
- Latency-associated DNA methylation patterns among HIV-1 infected individuals with distinct disease progression courses or antiretroviral virologic response.Scientific reports · 2021Article
- Article
- Metabolomics as a Tool to Investigate HIV/TB Co-Infection.Frontiers in molecular biosciences · 2021Review
- Altered Gut Microbiota and Host Metabolite Profiles in Women With Human Immunodeficiency Virus.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2020Article
- Integrative Metabolomics to Identify Molecular Signatures of Responses to Vaccines and Infections.Metabolites · 2020Review
- Bioenergetic adaptations to HIV infection. Could modulation of energy substrate utilization improve brain health in people living with HIV-1?Experimental neurology · 2020Review
Corrections and comments
- Erratum issuedCorrection: Plasma Metabolomics Biosignature According to HIV Stage of Infection, Pace of Disease Progression, Viremia Level and Immunological Response to Treatment.2017 · Scarpelini, Bruno [corrected to Scapellini, Bruno]
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe evaluated plasma samples HIV-infected individuals with different phenotypic profile among five HIV-infected elite controllers and five rapid progressors after recent HIV infection and one year later and from 10 individuals subjected to antiretroviral therapy, five of whom were immunological non-responders (INR), before and after one year of antiretroviral treatment compared to 175 samples from HIV-negative patients. A targeted quantitative tandem mass spectrometry metabolomics approach was used in order to determine plasma metabolomics biosignature that may relate to HIV infection, pace of HIV disease progression, and immunological response to treatment.
resultsTwenty-five unique metabolites were identified, including five metabolites that could distinguish rapid progressors and INRs at baseline. Severe deregulation in acylcarnitine and sphingomyelin metabolism compatible with mitochondrial deficiencies was observed. β-oxidation and sphingosine-1-phosphate-phosphatase-1 activity were down-regulated, whereas acyl-alkyl-containing phosphatidylcholines and alkylglyceronephosphate synthase levels were elevated in INRs. Evidence that elite controllers harbor an inborn error of metabolism (late-onset multiple acyl-coenzyme A dehydrogenase deficiency [MADD]) was detected.
conclusionsBlood-based markers from metabolomics show a very high accuracy of discriminating HIV infection between varieties of controls and have the ability to predict rapid disease progression or poor antiretroviral immunological response. These metabolites can be used as biomarkers of HIV natural evolution or treatment response and provide insight into the mechanisms of the disease.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.