ArticleJournal of proteome research2015
Exploring Metabolic Profile Differences between Colorectal Polyp Patients and Controls Using Seemingly Unrelated Regression.
Article in Journal of proteome research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Modeling blood metabolite homeostatic levels reduces sample heterogeneity across cohorts.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Current status of serum metabolites biomarkers for polyps and colorectal cancer: a systematic review.Gastroenterology report · 2024Review
- Demographic, Health and Lifestyle Factors Associated with the Metabolome in Older Women.Metabolites · 2023Article
- NMR Metabolomics Methods for Investigating Disease.Analytical chemistry · 2023Review
- Article
- Study of Differential Serum Metabolites in Patients with Adenomatous Polyps of Colon and Yang-Deficiency Constitution Based on Ultra-Performance Liquid Chromatography-Mass Spectrometry.Chinese journal of integrative medicine · 2022Article
- Serum Colorectal Cancer Biomarkers Unraveled by NMR Metabolomics: Past, Present, and Future.Analytical chemistry · 2022Article
- Integrative analysis of time course metabolic data and biomarker discovery.BMC bioinformatics · 2020Article
- Metabolomics Analysis in Serum from Patients with Colorectal Polyp and Colorectal Cancer byDisease markers · 2019Article
- Article
- Multivariate Analysis of the Cotton Seed Ionome Reveals a Shared Genetic Architecture.G3 (Bethesda, Md.) · 2018Article
- Altered metabolite levels and correlations in patients with colorectal cancer and polyps detected using seemingly unrelated regression analysis.Metabolomics : Official journal of the Metabolomic Society · 2017Article
- Article
- The future of NMR-based metabolomics.Current opinion in biotechnology · 2017Review
- Recent Advances in NMR-Based Metabolomics.Analytical chemistry · 2017Review
- Combining NMR and LC/MS Using Backward Variable Elimination: Metabolomics Analysis of Colorectal Cancer, Polyps, and Healthy Controls.Analytical chemistry · 2016Article
- Applications of NMR spectroscopy to systems biochemistry.Progress in nuclear magnetic resonance spectroscopy · 2016Review
- Globally Optimized Targeted Mass Spectrometry: Reliable Metabolomics Analysis with Broad Coverage.Analytical chemistry · 2015Article
- Metabolomic Approaches in Cancer Epidemiology.Diseases (Basel, Switzerland) · 2015Review
- NMR-based metabolomics: Where are we now and where are we going?Progress in nuclear magnetic resonance spectroscopyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Despite the fact that colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world, the development of improved and robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC continues to be evasive. In particular, patients with colon polyps are at higher risk of developing colon cancer; however, noninvasive methods to identify these patients suffer from poor performance. In consideration of the challenges involved in identifying metabolite biomarkers in individuals with high risk for colon cancer, we have investigated NMR-based metabolite profiling in combination with numerous demographic parameters to investigate the ability of serum metabolites to differentiate polyp patients from healthy subjects. We also investigated the effect of disease risk on different groups of biologically related metabolites. A powerful statistical approach, seemingly unrelated regression (SUR), was used to model the correlated levels of metabolites in the same biological group. The metabolites were found to be significantly affected by demographic covariates such as gender, BMI, BMI(2), and smoking status. After accounting for the effects of the confounding factors, we then investigated potential of metabolites from serum to differentiate patients with polyps and age matched healthy controls. Our results showed that while only valine was slightly associated, individually, with polyp patients, a number of biologically related groups of metabolites were significantly associated with polyps. These results may explain some of the challenges and promise a novel avenue for future metabolite profiling methodologies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.