2020
DOI: 10.21203/rs.3.rs-102034/v1
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Non-Invasive Plasma Glycomic and Metabolic Biomarkers of Post-treatment Control of HIV

Abstract: Non-invasive biomarkers that predict HIV remission after antiretroviral therapy (ART) interruption are urgently needed. Such biomarkers can improve the safety of analytic treatment interruption (ATI) and provide mechanistic insights into the pathways involved in post-ART HIV control. We identified plasma glycomic and metabolic signatures of time-to-viral-rebound and probability-of-viral-rebound using samples from two independent cohorts. These samples include a large number of post-treatment controllers, a rar… Show more

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Cited by 8 publications
(14 citation statements)
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“…Untargeted measurement of Plasma metabolites. Metabolomics analysis was performed as described previously (145,146). Briefly, polar metabolites were extracted with 80% methanol.…”
Section: Measurement Of Plasma Markers Of Inflammationmentioning
confidence: 99%
“…Untargeted measurement of Plasma metabolites. Metabolomics analysis was performed as described previously (145,146). Briefly, polar metabolites were extracted with 80% methanol.…”
Section: Measurement Of Plasma Markers Of Inflammationmentioning
confidence: 99%
“…This correlation suggests that many US transcripts originate from defective HIV genomes, which in theory might raise concerns as to the significance of US RNA as a predictive marker for viral rebound. However, a number of studies have demonstrated this marker to be a powerful predictor of viral rebound, suggesting its value as surrogate for the active replication-competent HIV reservoir [49 ▪▪ ,53–54,55 ▪▪ ,60 ▪ ]. We demonstrated that US RNA was predictive not only of the time to viral rebound to both >50 and >400 copies/ml but also of the magnitude of the viral rebound, independently of pre-ART virological biomarkers [55 ▪▪ ].…”
Section: Viral Biomarkers Of Virological Remission and Posttreatment ...mentioning
confidence: 66%
“…This concept is based on the assumption that such a composite molecular profile is expected to outperform each of the individual component biomarkers by the predictive power for viral rebound. Interestingly, a similar concept was recently followed by Giron et al , who used a machine-learning algorithm to identify a set of plasma biomarkers that predicts the viral rebound and distinguishes PTCs from noncontrollers better than any of the single component biomarkers [49 ▪▪ ].…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Untargeted measurement of Plasma metabolites. Metabolomics analysis was performed as described previously (133,134). Briefly, polar metabolites were extracted with 80% methanol.…”
Section: Measurement Of Plasma Markers Of Inflammationmentioning
confidence: 99%