Clinical trial · Observational
Urine Metabolites in the Diagnosis of Disease
Observational Study of Urine Metabolites in the Diagnosis of Disease
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The goal of this observational study is to validate a non-invasive, urine-based diagnostic technology for the detection and differentiation of various gastrointestinal (GI) diseases. This research study intends to enroll participants across a range of demographics and GI disease states including colorectal cancer, small intestinal bacterial overgrowth (SIBO), Crohn\'s disease, and Celiac disease, collect urine samples and clinical data, and use artificial intelligence and machine learning to build disease-specific models which can identify and differentiate a participants' specific GI disease. The main questions it aims to answer are: 1. Does the platform identify a disease signal within each disease cohort, compared to normal controls? 2. How well does the test perform (e.g. sensitivity and specificity/false-positive rate)?
Conditions
Conditions (4)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Celiac Disease | — | UNRESOLVED | — |
| Colorectal Cancer | Malignant Colorectal Neoplasm | CURATED_BROADER | 0.80 |
| Crohn Disease | — | UNRESOLVED | — |
| Small Intestinal Bacterial Overgrowth Syndrome (SIBO) | — | UNRESOLVED | — |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (1)
- label
- Disease Cohort
Primary outcomes (2)
- measure
- Disease signal detection
- timeFrame
- From date of enrollment to the end of sample analysis, up to 100 weeks
- description
- Disease signal detection quantification within each disease cohort, compared to normal controls.
- measure
- Test performance measures
- timeFrame
- From date of enrollment to the end of sample analysis, up to 100 weeks
- description
- Sensitivity and specificity/false-positive rate
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Age ≥ 18 years of age at time of enrollment. * Able and willing to provide a one-time urine sample and comply with all study procedures for the study. * Able to understand the study procedures, able to provide consent to participate in the study, and willing to authorize release of relevant protected health information by consenting to a HIPAA medical release form. Exclusion Criteria: * Known to be pregnant. * A medical condition which, in the opinion of the Investigator and/or Sponsor, should preclude enrollment in the study.
References
Publications (5)
- BACKGROUNDPasikanti KK, Ho PC, Chan EC. Gas chromatography/mass spectrometry in metabolic profiling of biological fluids. J Chromatogr B Analyt Technol Biomed Life Sci. 2008 Aug 15;871(2):202-11. doi: 10.1016/j.jchromb.2008.04.033. Epub 2008 Apr 29. PMID 18479983
- BACKGROUNDDinges SS, Hohm A, Vandergrift LA, Nowak J, Habbel P, Kaltashov IA, Cheng LL. Cancer metabolomic markers in urine: evidence, techniques and recommendations. Nat Rev Urol. 2019 Jun;16(6):339-362. doi: 10.1038/s41585-019-0185-3. PMID 31092915
- BACKGROUNDWittmann BM, Stirdivant SM, Mitchell MW, Wulff JE, McDunn JE, Li Z, Dennis-Barrie A, Neri BP, Milburn MV, Lotan Y, Wolfert RL. Bladder cancer biomarker discovery using global metabolomic profiling of urine. PLoS One. 2014 Dec 26;9(12):e115870. doi: 10.1371/journal.pone.0115870. eCollection 2014. PMID 25541698
- BACKGROUNDFan J, Hong J, Hu JD, Chen JL. Ion chromatography based urine amino Acid profiling applied for diagnosis of gastric cancer. Gastroenterol Res Pract. 2012;2012:474907. doi: 10.1155/2012/474907. Epub 2012 Jul 25. PMID 22888338
- BACKGROUNDIssaq HJ, Nativ O, Waybright T, Luke B, Veenstra TD, Issaq EJ, Kravstov A, Mullerad M. Detection of bladder cancer in human urine by metabolomic profiling using high performance liquid chromatography/mass spectrometry. J Urol. 2008 Jun;179(6):2422-6. doi: 10.1016/j.juro.2008.01.084. Epub 2008 Apr 23. PMID 18433783