Advances in non-invasive biomarkers for pediatric inflammatory bowel disease diagnosis

Abstract

Pediatric inflammatory bowel disease (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), presents significant diagnostic challenges due to its heterogeneous clinical presentation and reliance on invasive procedures such as endoscopy. Recent studies highlight the potential of non-invasive biomarkers, particularly serum cytokines, for distinguishing pediatric IBD from non-IBD conditions. CXCL9, interleukin 8, and interleukin 22 have shown strong discriminatory ability, correlating with disease activity and aiding in the differentiation between CD and UC. These biomarkers may also inform disease progression and treatment needs, including the identification of patients likely to require biologic therapy. However, important gaps remain in translating biomarker findings into routine clinical practice, especially for predicting long-term treatment response. This editorial summarizes recent advances in non-invasive biomarkers for pediatric IBD, focusing on serum, fecal, and genetic markers, and discusses their integration with conventional diagnostic approaches. Ongoing validation in large pediatric cohorts is required to support clinical implementation and optimize biomarker-guided management strategies.

Key Words: Pediatric inflammatory bowel disease; Non-invasive biomarkers; Crohn’s disease; Ulcerative colitis; Precision medicine

Core Tip: Biomarkers and genetic testing are transforming the diagnosis and management of pediatric inflammatory bowel disease (IBD), offering non-invasive alternatives to traditional invasive diagnostic methods. Fecal calprotectin and genetic markers show promise in accurately distinguishing Crohn’s disease from ulcerative colitis, while multi-omic approaches and machine learning models enhance predictive capabilities for disease progression and therapy responses, supporting precision medicine in pediatric IBD.

INTRODUCTION

Pediatric inflammatory bowel disease (IBD), comprising Crohn’s disease (CD) and ulcerative colitis, has shown a steadily increasing incidence and prevalence worldwide over recent decades, with pediatric-onset cases now accounting for a substantial proportion of the overall IBD population, and presents significant diagnostic challenges due to its heterogeneous clinical presentation and the need for invasive diagnostic methods like endoscopy[1,2]. Pediatric-onset IBD often follows an unpredictable and potentially aggressive disease course, making early and accurate diagnosis particularly critical for optimizing long-term outcomes and minimizing cumulative disease burden. Over the last decade, the understanding of IBD in children has expanded due to the application of novel molecular diagnostics, including biomarkers from blood, feces, and genetic testing, offering non-invasive and personalized diagnostic approaches[3,4]. Recent studies have highlighted the diagnostic relevance of serum cytokine profiles, with specific markers such as CXCL9, interleukin 8, and interleukin 22 demonstrating strong discriminatory potential for pediatric IBD and its subtypes[5]. With the increasing prevalence of very early-onset IBD (VEO-IBD) and its complex pathogenesis, particularly related to genetic factors, the integration of biomarkers and genetic tests holds substantial potential in improving diagnostic precision and therapeutic strategies[6,7].

While these advances are promising, many challenges remain in accurately diagnosing and differentiating IBD subtypes, as traditional clinical methods often fail to provide definitive diagnoses, especially in cases of overlapping or atypical disease manifestations[8]. Therefore, exploring biomarkers such as fecal calprotectin, serum inflammatory markers, and genetic profiles is crucial in enhancing early diagnosis, predicting disease course, and guiding treatment decisions[9,10]. In this editorial, we discuss and contextualize recent advances in non-invasive biomarkers for pediatric IBD, with a focus on their current clinical relevance, practical limitations, and future implications rather than providing a systematic review of the literature (Figure 1 and Table 1).

Figure 1 Overview of non-invasive biomarkers and genetic testing for pediatric inflammatory bowel disease diagnosis. IBD: Inflammatory bowel disease; CRP: C-reactive protein; LRG: Leucine-rich alpha-2 glycoprotein.

Table 1 Key biomarkers for diagnosing pediatric inflammatory bowel disease.

Biomarker	Type	Role in diagnosis	Disease subtypes	Diagnostic performance	Notes
Fecal calprotectin	Fecal marker	Detects intestinal inflammation; differentiates IBD from non-IBD conditions	Crohn’s disease, ulcerative colitis	High sensitivity and specificity (commonly > 80%-90%)	Widely used for screening, monitoring disease activity, and relapse prediction
S100A12	Fecal marker	Inflammatory marker for pediatric IBD diagnosis	Crohn’s disease, ulcerative colitis	Sensitivity approximately 95%, specificity approximately 97%	Higher specificity for intestinal inflammation compared with CRP
Leucine-rich alpha-2 glycoprotein	Serum marker	Reflects intestinal inflammatory activity	Crohn’s disease, ulcerative colitis	Moderate to high diagnostic accuracy; superior to CRP	Useful adjunct marker when fecal testing is limited
CRP	Serum marker	Acute-phase reactant for systemic inflammation	Crohn’s disease, ulcerative colitis	Moderate sensitivity; low disease specificity	Non-specific marker; influenced by infections and extraintestinal inflammation
Proteomic markers	Serum/plasma proteins	Identifies protein signatures distinguishing IBD subtypes	Crohn’s disease, ulcerative colitis	AUC > 0.90 in selected pediatric studies	Promising for disease stratification; limited routine availability
ASCA	Serological marker	Supports differentiation of Crohn’s disease	Crohn’s disease	Moderate sensitivity and specificity	Limited diagnostic utility as a standalone test
Perinuclear anti-neutrophil cytoplasmic antibodies	Serological marker	Supports differentiation of ulcerative colitis	Ulcerative colitis	Moderate sensitivity and specificity	Often interpreted in combination with ASCA
DNA methylation markers	Epigenetic marker	Provides diagnostic and prognostic information	Crohn’s disease, ulcerative colitis	AUC approximately 0.90-0.94 (IBD vs controls)	Emerging tools; currently research-based
MicroRNA signatures	Serum/plasma marker	Predicts disease activity and relapse risk	Crohn’s disease, ulcerative colitis	High sensitivity; AUC up to approximately 0.90	Potential role in treatment response prediction
Gut microbiome profiles	Microbiome marker	Differentiates IBD subtypes based on microbial alterations	Crohn’s disease, ulcerative colitis	AUC approximately 0.95 in selected cohorts	High inter-cohort variability; limited standardization

ASCA: Anti-saccharomyces cerevisiae antibodies; IBD: Inflammatory bowel disease; CRP: C-reactive protein; AUC: Area under the curve.

BIOMARKERS IN PEDIATRIC IBD

Non-invasive biomarkers have emerged as pivotal tools for diagnosing IBD and monitoring disease activity. Fecal calprotectin has shown the highest diagnostic accuracy, with reported sensitivities and specificities commonly exceeding 80%-90% in pediatric cohorts, outperforming traditional markers like C-reactive protein (CRP) and offering a reliable alternative to endoscopy[11,12]. CRP is a non-specific marker of systemic inflammation and may be elevated in a wide range of infectious or inflammatory conditions, whereas calprotectin levels correlate strongly with intestinal disease activity, and its routine use in clinical practice allows for non-invasive assessment of mucosal inflammation, relapse prediction, and treatment response monitoring, particularly in children with suspected IBD or during follow-up to guide decisions on treatment escalation or de-escalation, making it an essential marker for predicting relapse and guiding treatment adjustments[13].

Proteomic analyses are also gaining traction in pediatric IBD, identifying unique protein signatures that differentiate between CD and ulcerative colitis, with several recent studies reporting area under the curve (AUC) values greater than 0.90 for disease subtype discrimination, thereby enhancing disease subtype stratification[14,15], including recent pediatric proteomic studies demonstrating the potential of serum-based protein panels to support early diagnosis and treatment stratification[16]. Additionally, biomarkers such as S100A12 and leucine-rich alpha-2 glycoprotein (LRG) demonstrate high discriminatory power, with S100A12 showing reported sensitivity and specificity up to approximately 95% and 97%, respectively, and greater specificity for intestinal inflammation compared with CRP, and LRG outperforming CRP in reflecting intestinal inflammatory activity, which may be particularly useful in pediatric patients with atypical gastrointestinal symptoms where differentiation between IBD and other inflammatory enteropathies is clinically challenging, supporting their potential utility in distinguishing IBD from other non-IBD causes of pediatric enteropathy, further supporting their role in non-invasive diagnosis[3,17].

From a comparative perspective, currently available non-invasive biomarkers differ substantially in diagnostic accuracy, clinical practicality, and readiness for routine use in pediatric IBD. Fecal calprotectin remains the most widely adopted marker in daily practice due to its high sensitivity for intestinal inflammation, non-invasiveness, and broad availability, making it particularly suitable for initial screening and disease monitoring. Serum markers such as CRP are easily accessible but limited by low disease specificity, whereas newer serum-based candidates, including S100A12 and LRG, offer improved specificity for intestinal inflammation but are less universally available. Proteomic and epigenetic biomarkers demonstrate strong discriminatory performance in research settings and hold promise for refined disease stratification; however, their clinical implementation is currently constrained by cost, technical complexity, and the lack of standardized testing platforms. These differences highlight that no single biomarker is sufficient across all clinical scenarios, and that a complementary, context-dependent approach is likely required to optimize diagnostic and monitoring strategies in pediatric IBD, such as in VEO-IBD or cases with suspected monogenic disease where early stratification is critical.

Moreover, emerging epigenetic markers, particularly DNA methylation profiles, provide valuable insights into IBD pathogenesis. Methylation changes in genes like transforming growth factor-β1 and interleukin-6 have shown promise as diagnostic and prognostic markers, with reported diagnostic performance reaching AUC values of approximately 0.90-0.94 in pediatric studies, primarily in differentiating pediatric IBD from healthy controls, and predicting disease progression and relapse[18,19]. These markers may eventually complement existing tools by offering additional layers of diagnostic precision, especially in complex cases. Although these epigenetic biomarkers are not yet part of routine clinical workflows, they may complement established fecal and serum markers by improving diagnostic precision and risk stratification in clinically complex pediatric scenarios such as VEO-IBD or treatment-refractory disease.

GENETIC TESTING: A KEY TOOL IN DIAGNOSIS AND TREATMENT

Genetic testing, particularly next-generation sequencing, is revolutionizing the diagnosis of pediatric IBD, especially for cases of VEO-IBD. Monogenic forms of IBD, linked to specific genetic mutations like NOD2, IL23R, and CTLA4, are increasingly recognized for their role in disease onset and progression[20,21]. Early identification of these mutations allows for tailored therapeutic interventions, including hematopoietic stem cell transplantation, which differs significantly from the standard IBD treatment regimen[22].

For example, in VEO-IBD, genetic testing can directly inform personalized clinical decision-making. In a pediatric patient presenting with severe, treatment-refractory colitis at an early age, identification of a monogenic defect affecting immune regulation (such as mutations involving interleukin-10 signaling or CTLA4-related pathways) may fundamentally alter the therapeutic strategy. Rather than following conventional step-up therapy used in polygenic IBD, such patients may benefit from targeted immunomodulatory approaches or early consideration of hematopoietic stem cell transplantation. This genotype-driven stratification illustrates how genetic biomarkers move beyond diagnostic classification to actively guide individualized treatment selection, risk assessment, and long-term management in pediatric IBD.

In addition to identifying monogenic causes, genetic tests can predict the response to biologic therapies, particularly anti-tumor necrosis factor agents, which are commonly used in pediatric IBD treatment[23,24]. The integration of genetic data with other omics approaches, such as transcriptomics and proteomics, further refines treatment strategies and improves outcomes[25,26].

However, the widespread clinical adoption of genetic testing faces several barriers, including high costs, limited accessibility, and interpretation challenges[27]. These factors hinder the routine implementation of genetic screening in pediatric IBD care, despite its clear potential in guiding treatment decisions and personalized management.

MULTI-OMIC APPROACHES AND MACHINE LEARNING

The future of pediatric IBD diagnosis lies in the integration of multi-omic data, which combines genomics, proteomics, transcriptomics, and microbiome profiling to provide a comprehensive understanding of disease mechanisms and individual patient profiles[26]. Multi-omic approaches have demonstrated superior diagnostic accuracy in differentiating between IBD subtypes and predicting therapy responses when compared to traditional diagnostic tools[28,29], with several recent pediatric studies reporting improved classification performance when multiple omic layers are jointly analyzed rather than evaluated in isolation, including subtype discrimination and treatment-response prediction with validated performance metrics, particularly in studies integrating host transcriptomic and microbiome data in pediatric IBD cohorts[30,31].

Machine learning models applied to multi-omic data further enhance the ability to predict disease progression and response to therapy. Commonly used model types in pediatric IBD studies include supervised learning approaches such as random forest classifiers, support vector machines, and neural network-based models, which are trained to integrate high-dimensional omic features. Current applications in pediatric IBD include the prediction of response to biologic therapies prior to treatment initiation, identification of patients at higher risk for developing complicated disease phenotypes (such as structuring or penetrating CD), and stratification of relapse risk during maintenance therapy, thereby supporting earlier and more individualized clinical decision-making. By leveraging large datasets, machine learning can identify novel biomarkers and gene expression signatures associated with specific disease phenotypes, typically derived from cohorts ranging from several dozen to a few hundred pediatric patients, with reported model performance in selected pediatric cohorts achieving AUC values approaching or exceeding 0.85-0.90, with sensitivities and specificities generally in the range of 75%-90% in internal validation settings, enabling more precise stratification and personalized treatment plans[25,32].

Despite the promise of multi-omics and machine learning, challenges remain in standardizing these approaches for clinical use. The complexity of data integration, technical demands, and the need for large-scale validation studies limit their current application in routine pediatric care[27]. Additional barriers include limited pediatric sample sizes, heterogeneity across cohorts, and the lack of external validation in independent populations, as many existing models rely predominantly on internal cross-validation rather than prospective or multicenter external validation, which collectively hinder the immediate translation of machine learning-based models into everyday clinical practice, as highlighted by prior pediatric studies emphasizing the need for prospective and multicenter validation before clinical adoption[33].

CHALLENGES AND OPPORTUNITIES IN CLINICAL IMPLEMENTATION

While the integration of biomarkers and genetic testing into pediatric IBD diagnosis holds considerable promise, several challenges must be addressed before they can be routinely applied in clinical practice. The primary obstacles include cost, accessibility, and the need for robust, standardized protocols to ensure the accuracy and reliability of these tests across diverse healthcare settings[18,20,34]. Emerging strategies to address these barriers include the development of cost-effective targeted biomarker or genetic panels, the expansion of point-of-care testing models for key markers, and international collaborative efforts aimed at harmonizing testing standards and validation frameworks across pediatric populations.

Additionally, ethical and counseling challenges surrounding genetic testing in pediatric populations must be carefully considered. Parents and caregivers need appropriate guidance regarding the implications of genetic results, particularly when these results could influence long-term management decisions or suggest monogenic causes of the disease[22]. Specific ethical considerations include the management of incidental or secondary findings, potential implications for family members, and data privacy concerns related to genomic information, underscoring the need for structured genetic counseling and clear consent processes in pediatric IBD care.

CONCLUSION

Advancements in non-invasive biomarkers and genetic testing are transforming the diagnosis and management of pediatric IBD, offering reported high diagnostic performance across recent pediatric studies and aiding in the differentiation of disease subtypes, disease course prediction, and treatment response. Multi-omic approaches and machine learning models further enable personalized treatment strategies. However, challenges such as cost, accessibility, and clinical integration remain. Future efforts should focus on large-scale pediatric validation, standardization of biomarker thresholds, and the translation of biomarker-guided strategies into clinically applicable pathways. Overcoming these barriers through continued research and standardization in large pediatric cohorts will unlock the full potential of these technologies, ultimately improving patient outcomes and supporting targeted therapies in pediatric IBD care.