Summary of Study ST001000
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 PR000677. The data can be accessed directly via it's Project DOI: 10.21228/M85H44 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 | ST001000 |
Study Title | Gut microbiome structure and metabolic activity in inflammatory bowel disease |
Study Summary | The inflammatory bowel diseases (IBD), which include Crohn’s disease (CD) and ulcerative colitis (UC), are multifactorial, chronic conditions of the gastrointestinal tract. While IBD has been associated with dramatic changes in the gut microbiota, changes in the gut metabolome -- the molecular interface between host and microbiota -- are less-well understood. To address this gap, we performed untargeted LC-MS metabolomic and shotgun metagenomic profiling of cross-sectional stool samples from discovery (n=155) and validation (n=65) cohorts of CD, UC, and non-IBD control subjects. Metabolomic and metagenomic profiles were broadly correlated with fecal calprotectin levels (a measure of gut inflammation). Across >8,000 measured metabolite features, we identified chemicals and chemical classes that were differentially abundant (DA) in IBD, including enrichments for sphingolipids and bile acids, and depletions for triacylglycerols and tetrapyrroles. While >50% of DA metabolite features were uncharacterized, many could be assigned putative roles through metabolomic “guilt-by-association” (covariation with known metabolites). DA species and functions from the metagenomic profiles reflected adaptation to oxidative stress in the IBD gut, and were individually consistent with previous findings. Integrating these data, however, we identified 122 robust associations between DA species and well-characterized DA metabolites, indicating possible mechanistic relationships that are perturbed in IBD. Finally, we found that metabolome- and metagenome-based classifiers of IBD status were highly accurate and, like the vast majority of individual trends, generalized well to the independent validation cohort. Our findings thus provide an improved understanding of perturbations of the microbiome-metabolome interface in IBD, including identification of many potential diagnostic and therapeutic targets. |
Institute | Broad Institute of MIT and Harvard |
Department | Metabolomics Platform |
Last Name | Avila-Pacheco |
First Name | Julian |
Address | 415 Main Street |
jravilap@broadinstitute.org | |
Phone | 617-714-8264 |
Submit Date | 2018-07-09 |
Num Groups | 3 |
Total Subjects | 220 |
Raw Data Available | Yes |
Raw Data File Type(s) | raw(Thermo) |
Analysis Type Detail | LC-MS |
Release Date | 2019-04-17 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR000677 |
Project DOI: | doi: 10.21228/M85H44 |
Project Title: | Gut microbiome structure and metabolic activity in inflammatory bowel disease |
Project Summary: | The inflammatory bowel diseases (IBD), which include Crohn’s disease (CD) and ulcerative colitis (UC), are multifactorial, chronic conditions of the gastrointestinal tract. While IBD has been associated with dramatic changes in the gut microbiota, changes in the gut metabolome -- the molecular interface between host and microbiota -- are less-well understood. To address this gap, we performed untargeted LC-MS metabolomic and shotgun metagenomic profiling of cross-sectional stool samples from discovery (n=155) and validation (n=65) cohorts of CD, UC, and non-IBD control subjects. Metabolomic and metagenomic profiles were broadly correlated with fecal calprotectin levels (a measure of gut inflammation). Across >8,000 measured metabolite features, we identified chemicals and chemical classes that were differentially abundant (DA) in IBD, including enrichments for sphingolipids and bile acids, and depletions for triacylglycerols and tetrapyrroles. While >50% of DA metabolite features were uncharacterized, many could be assigned putative roles through metabolomic “guilt-by-association” (covariation with known metabolites). DA species and functions from the metagenomic profiles reflected adaptation to oxidative stress in the IBD gut, and were individually consistent with previous findings. Integrating these data, however, we identified 122 robust associations between DA species and well-characterized DA metabolites, indicating possible mechanistic relationships that are perturbed in IBD. Finally, we found that metabolome- and metagenome-based classifiers of IBD status were highly accurate and, like the vast majority of individual trends, generalized well to the independent validation cohort. Our findings thus provide an improved understanding of perturbations of the microbiome-metabolome interface in IBD, including identification of many potential diagnostic and therapeutic targets. |
Institute: | Broad Institute of MIT and Harvard |
Department: | Metabolomics Platform |
Last Name: | Avila-Pacheco |
First Name: | Julian |
Address: | 415 Main Street, Cambridge MA |
Email: | jravilap@broadinstitute.org |
Phone: | 617-714-8264 |
Contributors: | Eric A. Franzosa, Alexandra Sirota-Madi, Julian Avila-Pacheco, Nadine Fornelos, Henry J. Haiser, Stefan Reinker, Tommi Vatanen, A. Brantley Hall, Himel Mallick, Lauren J. McIver, Jenny S. Sauk, Robin G. Wilson, Betsy W. Stevens, Justin M. Scott, Kerry Pierce, Amy A. Deik, Kevin Bullock, Floris Imhann, Jeffrey Porter, Alexandra Zhernakova, Jingyuan Fu,7, Rinse K. Weersma, Cisca Wijmenga, Clary B. Clish, Hera Vlamakis, Curtis Huttenhower, Ramnik J. Xavier |
Subject:
Subject ID: | SU001207 |
Subject Type: | Human |
Subject Species: | Homo sapiens |
Taxonomy ID: | 9606 |
Species Group: | Mammals |
Factors:
Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)
mb_sample_id | local_sample_id | Diagnosis |
---|---|---|
SA079280 | 8374 | CD |
SA079281 | 8361 | CD |
SA079282 | 8336 | CD |
SA079283 | 8802 | CD |
SA079284 | 8377 | CD |
SA079285 | 8406 | CD |
SA079286 | 8452 | CD |
SA079287 | 8841 | CD |
SA079288 | 8807 | CD |
SA079289 | 8806 | CD |
SA079290 | 8800 | CD |
SA079291 | 8843 | CD |
SA079292 | 8753 | CD |
SA079293 | 7122 | CD |
SA079294 | 8758 | CD |
SA079295 | 8095 | CD |
SA079296 | 8749 | CD |
SA079297 | 8226 | CD |
SA079298 | 8783 | CD |
SA079299 | 8264 | CD |
SA079300 | 8746 | CD |
SA079301 | 7989 | CD |
SA079302 | 8675 | CD |
SA079303 | 8534 | CD |
SA079304 | 8523 | CD |
SA079305 | 8592 | CD |
SA079306 | 8892 | CD |
SA079307 | 8537 | CD |
SA079308 | 8550 | CD |
SA079309 | 8577 | CD |
SA079310 | 8573 | CD |
SA079311 | 8565 | CD |
SA079312 | 8564 | CD |
SA079313 | 8624 | CD |
SA079314 | 8878 | CD |
SA079315 | 8475 | CD |
SA079316 | 8467 | CD |
SA079317 | 8466 | CD |
SA079318 | 7971 | CD |
SA079319 | 8847 | CD |
SA079320 | 8483 | CD |
SA079321 | 8629 | CD |
SA079322 | 8496 | CD |
SA079323 | 8485 | CD |
SA079324 | 8462 | CD |
SA079325 | 7948 | CD |
SA079326 | 7744 | CD |
SA079327 | UMCGIBD00027 | CD |
SA079328 | 7658 | CD |
SA079329 | 7547 | CD |
SA079330 | 7759 | CD |
SA079331 | UMCGIBD00238 | CD |
SA079332 | UMCGIBD00254 | CD |
SA079333 | 7843 | CD |
SA079334 | 7791 | CD |
SA079335 | UMCGIBD00233 | CD |
SA079336 | UMCGIBD00064 | CD |
SA079337 | 7486 | CD |
SA079338 | 7184 | CD |
SA079339 | 7153 | CD |
SA079340 | 7150 | CD |
SA079341 | 7147 | CD |
SA079342 | 7238 | CD |
SA079343 | 7406 | CD |
SA079344 | 7445 | CD |
SA079345 | 7421 | CD |
SA079346 | 7408 | CD |
SA079347 | UMCGIBD00458 | CD |
SA079348 | UMCGIBD00106 | CD |
SA079349 | UMCGIBD00030 | CD |
SA079350 | UMCGIBD00032 | CD |
SA079351 | UMCGIBD00145 | CD |
SA079352 | UMCGIBD00072 | CD |
SA079353 | 7938 | CD |
SA079354 | 8591 | CD |
SA079355 | 7947 | CD |
SA079356 | 7941 | CD |
SA079357 | 8794 | CD |
SA079358 | UMCGIBD00485 | CD |
SA079359 | UMCGIBD00508 | CD |
SA079360 | UMCGIBD00112 | CD |
SA079361 | UMCGIBD00077 | CD |
SA079362 | UMCGIBD00041 | CD |
SA079363 | UMCGIBD00442 | CD |
SA079364 | UMCGIBD00126 | CD |
SA079365 | 7875 | CD |
SA079366 | UMCGIBD00082 | CD |
SA079367 | UMCGIBD00141 | CD |
SA079368 | 8784 | Control |
SA079369 | 8788 | Control |
SA079370 | 8789 | Control |
SA079371 | LLDeep_0028 | Control |
SA079372 | LLDeep_0033 | Control |
SA079373 | LLDeep_0030 | Control |
SA079374 | LLDeep_0029 | Control |
SA079375 | LLDeep_0027 | Control |
SA079376 | LLDeep_0034 | Control |
SA079377 | LLDeep_0037 | Control |
SA079378 | LLDeep_0052 | Control |
SA079379 | LLDeep_0047 | Control |
Collection:
Collection ID: | CO001201 |
Collection Summary: | PRISM subject stool samples were collected at the MGH gastroenterology clinic and stored at -80°C prior to DNA extraction. For the Netherlands validation cohort subjects enrolled collected stool at home and then froze it within 15 min in a conventional freezer. A research nurse visited all participants at home to collect home-frozen stool samples, which were then transported and stored at -80°C. The stool samples were kept frozen at -80°C prior to DNA extraction or metabolomic profiling. |
Sample Type: | Stool |
Storage Conditions: | Described in summary |
Treatment:
Treatment ID: | TR001222 |
Treatment Summary: | NA |
Sample Preparation:
Sampleprep ID: | SP001215 |
Sampleprep Summary: | Stool samples (weight range 50-5167.8 mg) were homogenized in 4 µL of water per milligram stool sample weight using a bead mill (TissueLyser II; Qiagen) and the aqueous homogenates were aliquoted for metabolite profiling analyses. |
Combined analysis:
Analysis ID | AN001878 | AN001879 | AN001880 | AN001881 |
---|---|---|---|---|
Analysis type | MS | MS | MS | MS |
Chromatography type | HILIC | HILIC | Reversed phase | Reversed phase |
Chromatography system | Shimadzu Nexera X2 | Shimadzu Nexera X2 | Shimadzu Nexera X2 | Shimadzu Nexera X2 |
Column | Waters 150 x 2 mm Atlantis HILIC | Phenomenex Luna NH2 (150 x 2.1mm,3um) | Waters 150 x 2 mm ACQUITY T3 | Waters Acquity BEH C8 (100 x 2.1mm,1.7um) |
MS Type | ESI | ESI | ESI | ESI |
MS instrument type | Orbitrap | Orbitrap | Orbitrap | Orbitrap |
MS instrument name | Thermo Q Exactive Orbitrap | Thermo Q Exactive Orbitrap | Thermo Q Exactive Orbitrap | Thermo Exactive Plus Orbitrap |
Ion Mode | POSITIVE | NEGATIVE | NEGATIVE | POSITIVE |
Units | abundance | abundance | abundance | abundance |
Chromatography:
Chromatography ID: | CH001359 |
Instrument Name: | Shimadzu Nexera X2 |
Column Name: | Waters 150 x 2 mm Atlantis HILIC |
Chromatography Type: | HILIC |
Chromatography ID: | CH001360 |
Instrument Name: | Shimadzu Nexera X2 |
Column Name: | Phenomenex Luna NH2 (150 x 2.1mm,3um) |
Chromatography Type: | HILIC |
Chromatography ID: | CH001361 |
Instrument Name: | Shimadzu Nexera X2 |
Column Name: | Waters 150 x 2 mm ACQUITY T3 |
Chromatography Type: | Reversed phase |
Chromatography ID: | CH001362 |
Instrument Name: | Shimadzu Nexera X2 |
Column Name: | Waters Acquity BEH C8 (100 x 2.1mm,1.7um) |
Chromatography Type: | Reversed phase |
MS:
MS ID: | MS001734 |
Analysis ID: | AN001878 |
Instrument Name: | Thermo Q Exactive Orbitrap |
Instrument Type: | Orbitrap |
MS Type: | ESI |
MS Comments: | Detailed acquisition and data processing methods available in Fransoza et al. (2019) DOI 10.1038/s41564-018-0306-4 |
Ion Mode: | POSITIVE |
MS ID: | MS001735 |
Analysis ID: | AN001879 |
Instrument Name: | Thermo Q Exactive Orbitrap |
Instrument Type: | Orbitrap |
MS Type: | ESI |
MS Comments: | Detailed acquisition and data processing methods available in Fransoza et al. (2019) DOI 10.1038/s41564-018-0306-4 |
Ion Mode: | NEGATIVE |
MS ID: | MS001736 |
Analysis ID: | AN001880 |
Instrument Name: | Thermo Q Exactive Orbitrap |
Instrument Type: | Orbitrap |
MS Type: | ESI |
MS Comments: | Detailed acquisition and data processing methods available in Fransoza et al. (2019) DOI 10.1038/s41564-018-0306-4 |
Ion Mode: | NEGATIVE |
MS ID: | MS001737 |
Analysis ID: | AN001881 |
Instrument Name: | Thermo Exactive Plus Orbitrap |
Instrument Type: | Orbitrap |
MS Type: | ESI |
MS Comments: | Detailed acquisition and data processing methods available in Fransoza et al. (2019) DOI 10.1038/s41564-018-0306-4 |
Ion Mode: | POSITIVE |