Summary of Study ST002557
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 PR001649. The data can be accessed directly via it's Project DOI: 10.21228/M8JQ50 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 | ST002557 |
| Study Title | Untargeted Metabolomics Identifies Biomarkers for MCADD Neonates in Dried Blood Spots |
| Study Type | Newborn screening |
| Study Summary | Medium-chain acyl-CoA dehydrogenase deficiency (MCADD) is the most common inherited mitochondrial metabolic disease of fatty acid β-oxidation, especially in newborns. MCADD is clinically diagnosed using Newborn Bloodspot Screening (NBS) and genetic testing. Still, these methods have limitations, such as false negatives or positives in NBS and variants of uncertain significance in genetic testing. Thus, complementary diagnostic approaches for MCADD are needed. Recently, untargeted metabolomics has been proposed as a diagnostic approach for inherited metabolic diseases (IMDs) due to its ability to detect a wide range of metabolic alterations. We performed untargeted metabolic profiling of dried blood spots (DBS) from MCADD newborns (n=14) and healthy controls (n=14) to discover potential metabolic biomarkers/pathways associated with MCADD. Extracted metabolites from DBS samples were analyzed using UPLC-QToF-MS for untargeted metabolomics analyses. Multivariate and univariate analyses were used to analyze the metabolomics data, and pathway and biomarker analyses were also performed on the significantly endogenous identified metabolites. MCADD newborns had 1034 significantly dysregulated metabolites compared to healthy newborns (Moderated t-test, no correction, p-value ≤ 0.05, FC 1.5). 23 endogenous metabolites were upregulated, while 84 endogenous metabolites were downregulated. Pathway analyses showed phenylalanine, tyrosine, and tryptophan biosynthesis as the most affected pathway. Potential metabolic biomarkers for MCADD were PGP (a21:0/PG/F1alpha) and glutathione with an area under the curve (AUC) of 0.949 and 0.898, respectively. PGP (a21:0/PG/F1alpha) was the only oxidized lipid in the top-15 biomarker list with the highest p-value and FC. Also, glutathione was chosen to indicate oxidative stress events that could happen during fatty acid oxidation defects. Our findings suggest that MCADD newborns may have oxidative stress events as signs of the disease. However, further validations of these biomarkers are needed in future studies to ensure their accuracy and reliability as complementary markers with established MCADD markers for clinical diagnosis. |
| Institute | King Faisal Specialist Hospital and Research Centre (KFSHRC) |
| Last Name | AlMalki |
| First Name | Reem |
| Address | Zahrawi Street, Al Maather, Riyadh 11211, Saudi Arabia |
| 439203044@student.ksu.edu.sa | |
| Phone | 0534045397 |
| Submit Date | 2023-04-11 |
| Num Groups | 2 |
| Total Subjects | 28 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Waters) |
| Analysis Type Detail | LC-MS |
| Release Date | 2023-04-28 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
| Project ID: | PR001649 |
| Project DOI: | doi: 10.21228/M8JQ50 |
| Project Title: | Untargeted Metabolomics Identifies Biomarkers for MCADD Neonates in Dried Blood Spots |
| Project Type: | newborn screening |
| Project Summary: | Medium-chain acyl-CoA dehydrogenase deficiency (MCADD) is the most common inherited mitochondrial metabolic disease of fatty acid β-oxidation, especially in newborns. MCADD is clinically diagnosed using Newborn Bloodspot Screening (NBS) and genetic testing. Still, these methods have limitations, such as false negatives or positives in NBS and variants of uncertain significance in genetic testing. Thus, complementary diagnostic approaches for MCADD are needed. Recently, untargeted metabolomics has been proposed as a diagnostic approach for inherited metabolic diseases (IMDs) due to its ability to detect a wide range of metabolic alterations. We performed untargeted metabolic profiling of dried blood spots (DBS) from MCADD newborns (n=14) and healthy controls (n=14) to discover potential metabolic biomarkers/pathways associated with MCADD. Extracted metabolites from DBS samples were analyzed using UPLC-QToF-MS for untargeted metabolomics analyses. Multivariate and univariate analyses were used to analyze the metabolomics data, and pathway and biomarker analyses were also performed on the significantly endogenous identified metabolites. MCADD newborns had 1034 significantly dysregulated metabolites compared to healthy newborns (Moderated t-test, no correction, p-value ≤ 0.05, FC 1.5). 23 endogenous metabolites were upregulated, while 84 endogenous metabolites were downregulated. Pathway analyses showed phenylalanine, tyrosine, and tryptophan biosynthesis as the most affected pathway. Potential metabolic biomarkers for MCADD were PGP (a21:0/PG/F1alpha) and glutathione with an area under the curve (AUC) of 0.949 and 0.898, respectively. PGP (a21:0/PG/F1alpha) was the only oxidized lipid in the top-15 biomarker list with the highest p-value and FC. Also, glutathione was chosen to indicate oxidative stress events that could happen during fatty acid oxidation defects. Our findings suggest that MCADD newborns may have oxidative stress events as signs of the disease. However, further validations of these biomarkers are needed in future studies to ensure their accuracy and reliability as complementary markers with established MCADD markers for clinical diagnosis. |
| Institute: | King Faisal Specialist Hospital and Research Centre (KFSHRC) |
| Last Name: | AlMalki |
| First Name: | Reem |
| Address: | King Fahad road, Riyadh 11211, Saudi Arabia |
| Email: | 439203044@student.ksu.edu.sa |
| Phone: | +966534045397 |
Subject:
| Subject ID: | SU002658 |
| Subject Type: | Human |
| Subject Species: | Homo sapiens |
| Taxonomy ID: | 9606 |
| Gender: | Male and female |
Factors:
Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)
| mb_sample_id | local_sample_id | Genotype |
|---|---|---|
| SA257210 | DR_Rajaa_MCAD_19031569 | Ctrl |
| SA257211 | DR_Rajaa_MCAD_20427551 | Ctrl |
| SA257212 | DR_Rajaa_MCAD_21747425 | Ctrl |
| SA257213 | DR_Rajaa_MCAD_20845942 | Ctrl |
| SA257214 | DR_Rajaa_MCAD_20802600 | Ctrl |
| SA257215 | DR_Rajaa_MCAD_20845951 | Ctrl |
| SA257216 | DR_Rajaa_MCAD_21379950 | Ctrl |
| SA257217 | DR_Rajaa_MCAD_21766545 | Ctrl |
| SA257218 | DR_Rajaa_MCAD_21780952 | Ctrl |
| SA257219 | DR_Rajaa_MCAD_21753499 | Ctrl |
| SA257220 | DR_Rajaa_MCAD_21730638 | Ctrl |
| SA257221 | DR_Rajaa_MCAD_21753806 | Ctrl |
| SA257222 | DR_Rajaa_MCAD_21027862 | Ctrl |
| SA257223 | DR_Rajaa_MCAD_21741306 | Ctrl |
| SA257224 | DR_Rajaa_MCAD_21805686 | MCADD |
| SA257225 | DR_Rajaa_MCAD_19031293 | MCADD |
| SA257226 | DR_Rajaa_MCAD_20736112 | MCADD |
| SA257227 | DR_Rajaa_MCAD_20325183 | MCADD |
| SA257228 | DR_Rajaa_MCAD_19505374 | MCADD |
| SA257229 | DR_Rajaa_MCAD_21241125 | MCADD |
| SA257230 | DR_Rajaa_MCAD_20296632 | MCADD |
| SA257231 | DR_Rajaa_MCAD_20400509 | MCADD |
| SA257232 | DR_Rajaa_MCAD_21905959 | MCADD |
| SA257233 | DR_Rajaa_MCAD_183489111 | MCADD |
| SA257234 | DR_Rajaa_MCAD_21245015 | MCADD |
| SA257235 | DR_Rajaa_MCAD_21112823 | MCADD |
| SA257236 | DR_Rajaa_MCAD_20725912 | MCADD |
| SA257237 | DR_Rajaa_MCAD_21241295 | MCADD |
| Showing results 1 to 28 of 28 |
Collection:
| Collection ID: | CO002651 |
| Collection Summary: | DBS samples were obtained from the metabolomics section in the Center for Genomic Medicine at King Faisal Specialist Hospital and Research Center (KFSHRC). The samples were collected from MCADD newborns (n=14) and healthy newborns (controls) (n=14). These newborns were age- and gender-matched. The inclusion criteria for the patient group included newborns positively diagnosed with only MCADD through the newborn screening program’s platform. For the control group, the inclusion criteria were healthy, gender-and age-match newborns. Also, newborns with less than a month were included as the average age of MCADD newborns was 15.3 days, and healthy newborns were 11 days. Any DBS samples collected from newborns diagnosed with other IMD or older than a month were excluded. |
| Collection Protocol Filename: | MCAD_biological_samples.docx |
| Sample Type: | Blood (plasma) |
| Storage Conditions: | -20℃ |
Treatment:
| Treatment ID: | TR002670 |
| Treatment Summary: | no treatment |
Sample Preparation:
| Sampleprep ID: | SP002664 |
| Sampleprep Summary: | Metabolites Extraction The metabolites were extracted as reported before with modification (43). In detail, one punch, a size of 3.2 mm, was collected from each DBS sample and transferred into a 96-well plate for metabolite extraction. Metabolite extraction was performed by adding 250 ul extraction solvent (20:40:40) (H2O: ACN: MeOH) to each well with agitation for 2 hours at room temperature. Subsequently, sample extracts were dried using SpeedVac (Thermo Fischer, Christ, Germany). The dried samples were reconstituted in 100 ul of 50% A: B mobile phase. (A: 0.1% Formic acid in H2O, B: 0.1% FA in 50% ACN: MeOH). Additional punches were taken for quality control (QC) from the project samples to maintain the instrument performance. |
| Sampleprep Protocol Filename: | Metabolites_Extraction.docx |
Combined analysis:
| Analysis ID | AN004212 | AN004213 |
|---|---|---|
| Analysis type | MS | MS |
| Chromatography type | Reversed phase | Reversed phase |
| Chromatography system | Waters Acquity | Waters Acquity |
| Column | Waters Acquity UPLC XSelect HSS C18 (100 × 2.1mm, 2.5um) | Waters Acquity UPLC XSelect HSS C18 (100 × 2.1mm, 2.5um) |
| MS Type | ESI | ESI |
| MS instrument type | QTOF | QTOF |
| MS instrument name | Waters Xevo-G2-S | Waters Xevo-G2-S |
| Ion Mode | POSITIVE | NEGATIVE |
| Units | peak area | peak area |
Chromatography:
| Chromatography ID: | CH003123 |
| Chromatography Summary: | Metabolomics analysis was explored using the Waters Acquity UPLC system coupled with a Xevo G2-S QTOF mass spectrometer equipped with an electrospray ionization source (ESI) (43,44). In detail, the extracted metabolites were chromatographed using an ACQUITY UPLC using XSelect (100×2.1mm 2.5 μm) column (Waters Ltd., Elstree, UK), the mobile phase composed of 0.1% formic acid in dH2O as solvent A and solvent B consists of 0.1% formic acid in 50% ACN: MeOH. A gradient elution schedule was run as follows: 0-16 min 95- 5% A, 16-19 min 5% A, 19-20 min 5-95% A, 20-22 min 95- 95% A, at 300 μL/min flow rate. MS spectra were acquired under positive and negative electrospray ionization modes (ESI+, ESI-). MS conditions were as follows: source temperature was 150◦C, the desolvation temperature was 500◦C (ESI+) or 140 (ESI−), the capillary voltage was 3.20 kV (ESI+) or 3 kV (ESI−), cone voltage was 40 V, desolvation gas flow was 800.0 L/h, cone gas flow was 50 L/h. The collision energies of low and high functions were set at 0 and 10-50 V, respectively, in MSE mode. The mass spectrometer was calibrated with sodium formate in 100–1200 Da. Data were collected in continuum mode with Masslynx™ V4.1 (Waters Technologies, Milford, MA., USA) workstation. |
| Methods Filename: | LC-MS_Metabolomics_MCAD.docx |
| Instrument Name: | Waters Acquity |
| Column Name: | Waters Acquity UPLC XSelect HSS C18 (100 × 2.1mm, 2.5um) |
| Column Temperature: | 55 |
| Flow Gradient: | 0–16 min 95%–5% A, 16–19 min 5% A, 19–20 min 5%–95% A, and 20–22 min, 95%– 95% A |
| Flow Rate: | 300 μl/min. |
| Solvent A: | 0.1% formic acid in dH2O |
| Solvent B: | 0.1% formic acid in 50% MeOH and ACN |
| Chromatography Type: | Reversed phase |
MS:
| MS ID: | MS003959 |
| Analysis ID: | AN004212 |
| Instrument Name: | Waters Xevo-G2-S |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | The DIA data were collected with a Masslynx™ V4.1 workstation in continuum mode (Waters Inc., Milford, MA, USA). The raw MS data were processed following a standard pipeline using the Progenesis QI v.3.0 software. |
| Ion Mode: | POSITIVE |
| Analysis Protocol File: | LC-MS_Metabolomics_MCAD.docx |
| MS ID: | MS003960 |
| Analysis ID: | AN004213 |
| Instrument Name: | Waters Xevo-G2-S |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | The DIA data were collected with a Masslynx™ V4.1 workstation in continuum mode (Waters Inc., Milford, MA, USA). The raw MS data were processed following a standard pipeline using the Progenesis QI v.3.0 software. |
| Ion Mode: | NEGATIVE |
| Analysis Protocol File: | LC-MS_Metabolomics_MCAD.docx |
