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 |
Select appropriate tab below to view additional metadata details:
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 |
Subject:
| Subject ID: | SU001796 |
| Subject Type: | Human |
| Subject Species: | Homo sapiens |
| Taxonomy ID: | 9606 |
Factors:
Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)
| mb_sample_id | local_sample_id | Time to viral rebound (days) | Gender | Race |
|---|---|---|---|---|
| SA161913 | 19 | 119 | Male | African American |
| SA161914 | 12 | 14 | Male | Caucasian |
| SA161915 | 20 | 14 | Male | Caucasian |
| SA161916 | 1 | 14 | Male | Caucasian |
| SA161917 | 16 | 14 | Male | Caucasian |
| SA161918 | 18 | 14 | Male | Caucasian |
| SA161919 | 8 | 14 | Male | Caucasian |
| SA161920 | 4 | 14 | Male | Caucasian |
| SA161921 | 21 | 14 | Male | Caucasian |
| SA161922 | 11 | 15 | Female | African American |
| SA161923 | 14 | 21 | Male | Caucasian |
| SA161924 | 23 | 21 | Male | Caucasian |
| SA161925 | 9 | 27 | Male | Caucasian |
| SA161926 | 3 | 28 | Male | African American |
| SA161927 | 7 | 28 | Male | African American |
| SA161928 | 15 | 28 | Male | Caucasian |
| SA161929 | 17 | 28 | Male | Caucasian |
| SA161930 | 2 | 28 | Male | Caucasian |
| SA161931 | 6 | 28 | Male | Hispanic |
| SA161932 | 13 | 35 | Male | Caucasian |
| SA161933 | 10 | 35 | Male | Caucasian |
| SA161934 | 24 | 42 | Male | African American |
| SA161935 | 22 | 42 | Male | African American |
| SA161936 | 5 | 70 | Female | African American |
| SA161937 | QC-2 | NA | NA | NA |
| SA161938 | QC-5 | NA | NA | NA |
| SA161939 | QC-4 | NA | NA | NA |
| SA161940 | QC-3 | NA | NA | NA |
| Showing results 1 to 28 of 28 |
Collection:
| Collection ID: | CO001789 |
| Collection Summary: | Analyses were performed from banked plasma samples of two different cohorts that underwent analytical treatment interruption (ATI): (1) Philadelphia Cohort and (2) ACTG cohort. In the Philadelphia cohort, HIV+ individuals on suppressive ART underwent an open-ended ATI without concurrent immunomodulatory agents. The ACTG cohort combined 74 HIV-infected ART-suppressed participants who underwent ATI from six ACTG ATI studies (ACTG 371,28 A5024,29 A5068,30 A5170,31 A5187,32 and A519733). 27 of these 74 individuals exhibited a PTC phenotype post-ATI, i.e. these individuals remained off ART for ≥24 weeks post-treatment interruption, sustained virologic control for at least 24 weeks, maintained viral load (VL) ≤400 copies for at least 2/3 of time points, had plasma drug level testing performed, and had no evidence of spontaneous control pre-ART. The remaining 47 cohort members were non-controllers (NCs) who exhibited virologic rebound before meeting PTC criteria. These two groups were matched for gender, age, % treated at the early stage of HIV infection, ART duration, pre-ATI CD4 count, and ethnicity. All analyses were performed on samples collected immediately before ATI in both cohorts. |
| Sample Type: | Blood (plasma) |
Treatment:
| Treatment ID: | TR001809 |
| Treatment Summary: | No treatment |
Sample Preparation:
| Sampleprep ID: | SP001802 |
| Sampleprep Summary: | Briefly, polar metabolites were extracted from 50 µl plasma samples with 500 µl ice-cold 80% methanol, and deproteinated supernatants were stored at -80 °C prior to analysis. A quality control (QC) sample was generated by pooling equal volumes of all samples after extraction. |
| Processing Storage Conditions: | On ice |
| Extract Storage: | -80℃ |
Combined analysis:
| Analysis ID | AN002802 |
|---|---|
| Analysis type | MS |
| Chromatography type | HILIC |
| Chromatography system | Thermo Vanquish |
| Column | SeQuant ZIC-pHILIC (150 x 2.1mm,5um) |
| MS Type | ESI |
| MS instrument type | Orbitrap |
| MS instrument name | Thermo Q Exactive HF-X Orbitrap |
| Ion Mode | UNSPECIFIED |
| Units | Peak Area |
Chromatography:
| Chromatography ID: | CH002070 |
| Chromatography Summary: | Hydrophilic interaction liquid chromatography (HILIC) was performed at 0.2 ml/min on a ZIC-pHILIC column (2.1 mm × 150 mm, EMD Millipore) at 45 °C. Solvent A was 20 mM ammonium carbonate, 0.1% ammonium hydroxide, pH 9.2, and solvent B was acetonitrile. The gradient was 85% B for 2 min, 85% B to 20% B over 15 min, 20% B to 85% B over 0.1 min, and 85% B for 8.9 min. The autosampler was held at 4 °C. For each analysis, 4 µl of sample was injected. |
| Instrument Name: | Thermo Vanquish |
| Column Name: | SeQuant ZIC-pHILIC (150 x 2.1mm,5um) |
| Flow Gradient: | 85% B for 2 min, 85% B to 20% B over 15 min, 20% B to 85% B over 0.1 min, and 85% B for 8.9 min. |
| Solvent A: | 100% water; 20 mM ammonium carbonate; 0.1% ammonium hydroxide, pH 9.2 |
| Solvent B: | 100% acetonitrile |
| Chromatography Type: | HILIC |
MS:
| MS ID: | MS002597 |
| Analysis ID: | AN002802 |
| Instrument Name: | Thermo Q Exactive HF-X Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | The following parameters were used for the MS analysis: sheath gas flow rate, 40; auxiliary gas flow rate, 10; sweep gas flow rate, 1; auxiliary gas heater temperature, 350 °C; spray voltage, 3.5 kV for positive mode and 3.2 kV for negative mode; capillary temperature, 325 °C; and funnel RF level, 40. All samples were analyzed by full MS with polarity switching. The QC sample was analyzed at the start of the sample sequence and after every 8-14 samples. The QC sample was also analyzed by data-dependent MS/MS with separate runs for positive and negative ion modes. Full MS scans were acquired at 120,000 resolution with a scan range of 65 -975 m/z. Data-dependent MS/MS scans were acquired for the top 10 highest intensity ions at 15,000 resolution with an isolation width of 1.0 m/z and stepped normalized collision energy of 20-40-60. Data analysis was performed using Compound Discoverer 3.1 (ThermoFisher Scientific) with separate analyses for positive and negative polarities. Retention time alignment used the adaptative curve model with 0.3 min maximum shift, 5 ppm mass tolerance, and 3 S/N threshold. Peak detection required less than 5 ppm mass error for extracted ion chromatograms with a 50,000 minimum peak intensity. [M+H]+1 and [M-H]-1 were set as base ions with consideration for other adducts. Peaks were required to have a width at half height less than 0.5 min and a minimum of 5 scans. Components that had only a monoisotopic peak and no further isotopes were not considered. The maximum element count for isotope pattern modeling was C90H190N10Na2O15P3S5. Compounds were grouped across samples with 5 ppm mass error and 0.3 min retention time shift. Peaks not detected initially in a given sample were determined using the fill gaps algorithm with 5 ppm mass error and 1.5 S/N threshold with real peak detection. The gap function uses a priority system to determine missing values: 1) matching detected ions based on expected m/z and retention time regardless of adduct assignment, 2) re-detecting peaks at lower thresholds, 3) simulating peaks based on expected m/z, and 4) imputing spectrum noise based on detection limit values. Compound quantifications were corrected for instrument drift by QC areas using the cubic spline regression model. Each compound was required to be detected in at least 40% of QC runs with an RSD less than 50%. Metabolites were identified by accurate mass (5 ppm mass error) and retention time (0.5 min shift) using a database generated from pure standards or by accurate mass and MS2 spectra using the mzCloud spectral database (mzCloud.org), specifically the ‘Endogenous Metabolites’ and ‘Steroids/Vitamins/Hormones’ compound classes, and selecting the best matches with HighChem HighRes identity search match factors of 50 or greater. Results were manually processed to remove entries with apparent peak mis-integrations and correct commonly misannotated metabolites. Positive and negative data sets of identified compounds were merged, and the preferred polarity was selected for compounds identified in both polarities. Compound quantifications were normalized per volume plasma injected, which was equivalent for all samples. Values from the ACTG study were further normalized to the summed area of identified metabolites in each sample. For compounds identified multiple times at different retention times, a single entry was selected with priority given to standards database matches followed by greater mzCloud match factors and peak areas. |
| Ion Mode: | UNSPECIFIED |
