Evidence map›Paper›PMID 41690702›Full record

ReviewGut2026

Rise of prediagnostic molecular profiling in inflammatory bowel disease-can we close the door before the horse has bolted?

Nick Powell

Abstract readReview
PubMed Publisher
In one paragraph

Review in Gut, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Nick PowellDivision of Digestive Diseases, Imperial College London, London, UK npowell@ic.ac.uk.ORCID http://orcid.org/0000-0003-3231-6950

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inflammatory bowel disease (IBD) is typically diagnosed after the onset of symptoms in the context of established, characteristic patterns of intestinal inflammation. However, there is now substantial evidence pointing to a prolonged, biologically active preclinical phase of disease. Analysis of archived biological samples from large-scale longitudinal cohort studies of healthy individuals, some of whom develop incident IBD, has identified different molecular features that can be detected many years before clinical presentation. These include increased titres of antimicrobial and autoreactive antibodies and perturbations in a complex network of circulating, immunologically active proteins. As well as affording 'diagnostic' opportunities to identify individuals destined to develop IBD, an integrated view of these multiple different molecular features enables speculation of potential proximal drivers of preclinical IBD. Consistently recognised associations include dysregulated mononuclear phagocyte-lymphocyte interactions, augmented chemotaxis, frequently relating to interferon-γ-driven chemokine programmes and evidence of early tissue injury, such as increased circulating extracellular matrix components and metalloproteinases. Increased levels of circulating antibacterial and antiviral antibody responses hint towards disordered host-microbe interactions as potential prime triggers for the transition between health and early disease, although it is possible that these serological responses are an epiphenomenon linked to early mucosal damage and microbial translocation. There is now a timely opportunity to develop these different molecular features into scalable and clinically tractable biomarker panels to detect preclinical disease and enable strategies to proactively intercept IBD before it even develops.

Indexed as

Inflammatory Bowel DiseasesAnimalsBiomarkersHumansBiomarkersIBDIBD BASIC RESEARCHIBD CLINICAL

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.