Summary of Study ST001719
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001053. The data can be accessed directly via it's Project DOI: 10.21228/M8KQ59 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
| Study ID | ST001719 |
| Study Title | Metabolomics Analysis of Philadelphia Cohort - Update (part-I) |
| Study Type | Metabolomics Analysis |
| Study Summary | Global metabolomics analysis of Philadelphia cohort |
| Institute | The Wistar Institute |
| Last Name | Abdel-Mohsen |
| First Name | Mohamed |
| Address | 3601 Spruce St, Philadelphia, PA 19104 |
| mmohsen@wistar.org | |
| Phone | 215-898-6008 |
| Submit Date | 2021-01-07 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2021-05-25 |
| Release Version | 1 |
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Project:
| Project ID: | PR001053 |
| Project DOI: | doi: 10.21228/M8KQ59 |
| Project Title: | Non-Invasive Plasma Glycomic and Metabolic Biomarkers of Post-treatment Control of HIV |
| Project Summary: | 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 rare population demonstrating sustained virologic suppression after ART-cessation. The signatures remained significant after adjusting for key demographic and clinical confounders. We also confirmed a mechanistic link between biomarkers and HIV latency reactivation and myeloid inflammation in vitro. Finally, machine learning algorithms selected sets of biomarkers that predict time-to-viral-rebound with 74-76% capacity and probability-of-viral-rebound with 97.5% capacity. In summary, we fill a major gap in HIV cure research by identifying non-invasive biomarkers, with potential functional significance, that predict duration and probability of viral remission after treatment interruption. |
| Institute: | The Wistar Institute |
| Last Name: | Abdel-Mohsen |
| First Name: | Mohamed |
| Address: | 3601 Spruce St, Philadelphia, PA 19104 |
| Email: | mmohsen@wistar.org |
| Phone: | 215-898-6008 |
