Current and emerging biomarkers for ulcerative colitis

Nowak, Jan K.; Kalla, Rahul; Satsangi, Jack

doi:10.1080/14737159.2023.2279611

Cited by 12 publications

(4 citation statements)

References 134 publications

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“…In particular, fecal calprotectin (FC) and CRP have been investigated in a large number of studies using antibody-based methods such as ELISA [68][69][70]. Although their use is often hindered by disadvantages such as a lack of specificity [71], we considered them as biomarkers in our cohort. Both show a significant decrease in patients with remission, but there is no significant difference between patients with and without remission at baseline to predict therapy success.…”

Section: Identification Of Disease-specific Biomarkersmentioning

confidence: 99%

Fecal metaproteomics enables functional characterization of remission in patients with inflammatory bowel disease

Wolf,

Lange,

Benndorf

et al. 2024

Preprint

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BackgroundThe gut microbiome is an important contributor to the development and the course of inflammatory bowel disease (IBD). While changes in the gut microbiome composition were observed in response to IBD therapy using biologics, studies elucidating human and microbial proteins and pathways in dependence on therapy success are sparse.MethodsFecal samples of a cohort of IBD patients were collected before and after 14 weeks of treatment with three different biologics. Clinical disease activity scores were used to determine the clinical response and remission. Fecal metaproteomes of remitting patients (n=12) and of non-remitting patients (n=12) were compared before treatment and changes within both groups were assessed over sampling time to identify functional changes and potential human and microbial biomarkers.ResultsThe abundance of proteins associated with the intestinal barrier, neutrophilic granulocytes, and immunoglobulins significantly decreased in remitting patients. In contrast, an increase of those proteins was observed in non-remitting patients. There were significant changes in pathways of microbial metabolism in samples from patients with remission after therapy. This included, for example, an increased abundance of proteins from butyrate fermentation. Finally, new potential biomarkers for the prediction and monitoring of therapy success could be identified, e.g. human lysosome-associated membrane glycoprotein 1, a cytotoxicity marker, or microbial anthranilate synthase component 2, a part of the tryptophan metabolism.ConclusionsDistinct changes of proteins related to gut inflammation and gut microbiome metabolism showed whether IBD remission was achieved or not. This suggests that metaproteomics could be a useful tool for monitoring remission in IBD therapies.

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Section: Identification Of Disease-specific Biomarkersmentioning

confidence: 99%

Fecal metaproteomics enables functional characterization of remission in patients with inflammatory bowel disease

Wolf,

Lange,

Benndorf

et al. 2024

Preprint

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“…IBD is a lifelong disease, with a peak onset in teenage and early adult years, associated with poor quality of life affecting the ability to work, and a need for recurrent surgeries 33 . There is a clear unmet need for IBD biomarkers that can diagnose, monitor disease activity, measure therapeutic effectiveness and predict recurrence 34,35 .…”

Section: Introductionmentioning

confidence: 99%

“…biomarkers that can diagnose, monitor disease activity, measure therapeutic effectiveness and predict recurrence 34,35 .…”

mentioning

confidence: 99%

Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery

Fu,

Vegesna,

Sundararaman

et al. 2024

Preprint

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Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package. This innovative tool uses the discovery cohort analysis to select precursors, peptides, and proteins that adhere to established targeted assay criteria. TEAQ was applied to Data-Independent Acquisition MS data from plasma samples acquired on an OrbitrapTM AstralTM MS. Identified precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation from 11-point loading curves under three throughputs, to develop a resource for clinical-grade targeted assays. From a clinical cohort of individuals with inflammatory bowel disease (n=492), TEAQ successfully identified 1116 signature peptides for 327 quantifiable proteins from 1180 identified proteins. Embedding stringent selection criteria adaptable to targeted assay development into the analysis of discovery data will streamline the transition to validation and clinical studies.

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“…This study explores high-throughput technologies and ML to identify molecular signatures associated with IBD, enhancing our understanding of IBD pathogenesis [ 10 , 11 , 12 , 13 , 14 , 15 , 16 ]. We aim to employ supervised feature selection (FS) methods to identify informative gene biomarkers for accurately classifying IBD patients and healthy controls, facilitating earlier diagnosis and personalized treatment.…”

Section: Introductionmentioning

confidence: 99%

Advances in Inflammatory Bowel Disease Diagnostics: Machine Learning and Genomic Profiling Reveal Key Biomarkers for Early Detection

Syed,

Abujabal,

Ahmad

et al. 2024

Diagnostics

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This study, utilizing high-throughput technologies and Machine Learning (ML), has identified gene biomarkers and molecular signatures in Inflammatory Bowel Disease (IBD). We could identify significant upregulated or downregulated genes in IBD patients by comparing gene expression levels in colonic specimens from 172 IBD patients and 22 healthy individuals using the GSE75214 microarray dataset. Our ML techniques and feature selection methods revealed six Differentially Expressed Gene (DEG) biomarkers (VWF, IL1RL1, DENND2B, MMP14, NAAA, and PANK1) with strong diagnostic potential for IBD. The Random Forest (RF) model demonstrated exceptional performance, with accuracy, F1-score, and AUC values exceeding 0.98. Our findings were rigorously validated with independent datasets (GSE36807 and GSE10616), further bolstering their credibility and showing favorable performance metrics (accuracy: 0.841, F1-score: 0.734, AUC: 0.887). Our functional annotation and pathway enrichment analysis provided insights into crucial pathways associated with these dysregulated genes. DENND2B and PANK1 were identified as novel IBD biomarkers, advancing our understanding of the disease. The validation in independent cohorts enhances the reliability of these findings and underscores their potential for early detection and personalized treatment of IBD. Further exploration of these genes is necessary to fully comprehend their roles in IBD pathogenesis and develop improved diagnostic tools and therapies. This study significantly contributes to IBD research with valuable insights, potentially greatly enhancing patient care.

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Current and emerging biomarkers for ulcerative colitis

Cited by 12 publications

References 134 publications

Fecal metaproteomics enables functional characterization of remission in patients with inflammatory bowel disease

Fecal metaproteomics enables functional characterization of remission in patients with inflammatory bowel disease

Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery

Advances in Inflammatory Bowel Disease Diagnostics: Machine Learning and Genomic Profiling Reveal Key Biomarkers for Early Detection

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