Summary of Study ST002332
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 PR001496. The data can be accessed directly via it's Project DOI: 10.21228/M8BX3F 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 | ST002332 |
| Study Title | Plasma metabolomic profiling of individuals with autism spectrum disorder and their family members. |
| Study Summary | Autism spectrum disorder (ASD) is a common neurodevelopmental condition affecting 2.3% of 8-year-old children and is attributable to polygenic risks in most cases. Gene discovery studies catalogued >1000 genes with de novo, rare and common genetic variants that are likely associated with ASD; however, the candidate genes are rarely translated to diagnostic and treatment biomarkers. As such no pharmacological treatment option is available for targeting core symptoms. Neural circuits involved in verbal/nonverbal communications and social interaction are likely changed, which may be caused by an excitatory-inhibitory (E-I) imbalance in individuals with ASD. To date, clinical trials targeting excitatory glutamatergic or inhibitory GABAergic receptors showed mixed results. These early clinical trials highlight the unmet need of biomarkers for target populations and outcome indicators. We investigated whether plasma biomarkers would be associated with genetic risk factors and core symptoms of ASD. Plasma samples were collected for metabolomics profiling from the Autism Genetics Resource Exchange (AGRE). Detailed phenotype information is available at NIMH Data Archive (Collection ID: 4214) and can be accessed using NDAR GUID for the individuals. |
| Institute | Boston Childrens Hospital |
| Department | Computational Health informatics Program |
| Laboratory | Kong Lab |
| Last Name | Kong |
| First Name | Sek Won |
| Address | 401 Park Drive, LM5528.4 |
| sekwon.kong@childrens.harvard.edu | |
| Phone | 6179192689 |
| Submit Date | 2022-10-14 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzXML |
| Analysis Type Detail | LC-MS |
| Release Date | 2023-10-14 |
| Release Version | 1 |
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Collection:
| Collection ID: | CO002412 |
| Collection Summary: | The Autism Genetic Resource Exchange (AGRE) Consortium has the collection of WGS, biospecimen and phenotype data of families containing at least one individual diagnosed with Autism Spectrum Disorder (ASD) by the Autism Diagnostic Interview-Revised (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS). For identifying ASD patients, we used AGRE’s “derived affected status” information marked with “Autism”, “Not Quite Autism (NQA)“, or “ASD”. Patients with known genetic causes of ASD (e.g., Fragile X, Trisomy 21, 15q deletion, and 22q duplication) or syndromes with overlapping ASD-features (e.g., Sotos syndrome) were excluded. We used plasma samples from individuals with both WGS and detailed phenotype information were available. |
| Sample Type: | Blood (plasma) |
