Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Crowdsourced study of children with autism and their typically developing siblings identifies differences in taxonomic and predicted function for stool-associated microbes using exact sequence variant analysis

Maude M David, Christine Tataru, Jena Daniels, Jessey Schwartz, Jessica Keating, Jarrad Hampton-Marcell, Neil Gottel, Jack A. Gilbert, Dennis P. Wall
doi: https://doi.org/10.1101/319236
Maude M David
1Department of Pediatrics, Division of Systems Medicine, Stanford University, Stanford, CA, USA
2Department of Microbiology, Oregon State University, Corvallis, OR, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christine Tataru
1Department of Pediatrics, Division of Systems Medicine, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jena Daniels
1Department of Pediatrics, Division of Systems Medicine, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jessey Schwartz
1Department of Pediatrics, Division of Systems Medicine, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jessica Keating
1Department of Pediatrics, Division of Systems Medicine, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jarrad Hampton-Marcell
3Bioscience Division, The Microbiome Center, Argonne National Laboratory, Argonne, Illinois, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Neil Gottel
4Department of Surgery, The Microbiome Center, University of Chicago, Chicago, Illinois, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jack A. Gilbert
3Bioscience Division, The Microbiome Center, Argonne National Laboratory, Argonne, Illinois, USA
4Department of Surgery, The Microbiome Center, University of Chicago, Chicago, Illinois, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dennis P. Wall
1Department of Pediatrics, Division of Systems Medicine, Stanford University, Stanford, CA, USA
5Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: dpwall@stanford.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

ABSTRACT

Background The existence of a link between the gut microbiome and autism spectrum disorder (ASD) is well established in mice, but in human populations efforts to identify microbial biomarkers have been limited due to problems stratifying participants within the broad phenotype of ASD and a lack of appropriately matched controls. To overcome these limitations and investigate the relationship between ASD and the gut microbiome, we ran a crowdsourced study of families 2-7 year old sibling pairs, where one child of the pair had a diagnosis of ASD and the other child did not.

Methods Parents of age-matched sibling pairs electronically consented and completed study procedures via a secure web portal (microbiome.stanford.edu). Parents collected stool samples from each child, responded to behavioral questionnaires about the ASD child’s typical behavior, and whenever possible provided a home video of their ASD child’s natural social behavior. We performed DNA extraction and 16S rRNA amplicon sequencing on 117 stool samples (60 ASD and 57 NT) that met all study design eligibility criteria,. Using DADA2, Exact Sequence Variants (ESVs) were identified as taxonomic units, and three statistical tests were performed on ESV abundance counts: (1) permutation test to determine differences between sibling pairs, (2) differential abundance test using a zero-inflated gaussian mixture model to account for the sparse abundance matrix, and (3) differential abundance test after modeling under a negative binomial distribution. The potential functional gene abundance for each sample was also inferred from the 16S rRNA data, providing KEGG Ortholog (KO), which were analyzed for differential abundance.

Results In total, 21 ESVs had significantly differentially proportions in stool of children with ASD and their neurotypical siblings. Of these 21 ESVs, 11 were enriched in neurotypical children and ten were enriched in children with ASD. ESVs enriched in the ASD cohort were predominantly associated with Ruminococcaceae and Bacteroidaceae; while those enriched in controls were more diverse including taxa associated with Bifidobacterium, Porphyromonas, Slackia, Desulfovibrio, Acinetobacter johnsonii, and Lachnospiraceae. Exact Variant Analysis suggested that Lachnospiraceae was specific to the control cohort, while Ruminococcaceae, Tissierellaceae and Bacteroidaceae were significantly enriched in children with ASD. Metabolic gene predictions determined that while both cohorts harbor the butyrogenic pathway, the ASD cohort was more likely to use the 4-aminobutanoate (4Ab) pathway, while the control cohort was more likely to use the pyruvate pathway. The 4Ab pathway releases harmful by-products like ammonia and can shunt glutamate, affecting its availability as an excitatory neurotransmitter. Finally, we observed differences in the carbohydrate uptake capabilities of various ESVs identified between the two cohorts.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted May 25, 2018.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Crowdsourced study of children with autism and their typically developing siblings identifies differences in taxonomic and predicted function for stool-associated microbes using exact sequence variant analysis
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Crowdsourced study of children with autism and their typically developing siblings identifies differences in taxonomic and predicted function for stool-associated microbes using exact sequence variant analysis
Maude M David, Christine Tataru, Jena Daniels, Jessey Schwartz, Jessica Keating, Jarrad Hampton-Marcell, Neil Gottel, Jack A. Gilbert, Dennis P. Wall
bioRxiv 319236; doi: https://doi.org/10.1101/319236
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Crowdsourced study of children with autism and their typically developing siblings identifies differences in taxonomic and predicted function for stool-associated microbes using exact sequence variant analysis
Maude M David, Christine Tataru, Jena Daniels, Jessey Schwartz, Jessica Keating, Jarrad Hampton-Marcell, Neil Gottel, Jack A. Gilbert, Dennis P. Wall
bioRxiv 319236; doi: https://doi.org/10.1101/319236

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Microbiology
Subject Areas
All Articles
  • Animal Behavior and Cognition (3513)
  • Biochemistry (7359)
  • Bioengineering (5338)
  • Bioinformatics (20306)
  • Biophysics (10034)
  • Cancer Biology (7763)
  • Cell Biology (11331)
  • Clinical Trials (138)
  • Developmental Biology (6444)
  • Ecology (9968)
  • Epidemiology (2065)
  • Evolutionary Biology (13346)
  • Genetics (9365)
  • Genomics (12598)
  • Immunology (7718)
  • Microbiology (19059)
  • Molecular Biology (7452)
  • Neuroscience (41106)
  • Paleontology (300)
  • Pathology (1233)
  • Pharmacology and Toxicology (2141)
  • Physiology (3171)
  • Plant Biology (6869)
  • Scientific Communication and Education (1275)
  • Synthetic Biology (1899)
  • Systems Biology (5320)
  • Zoology (1090)